resource allocation using multi objective evolutionary algorithms



Hanan Luss Equitable Resource Allocation. Models, Algorithms and Applications Hanan Luss Equitable Resource Allocation. Models, Algorithms and Applications Новинка

Hanan Luss Equitable Resource Allocation. Models, Algorithms and Applications

9700.9 руб.
A unique book that specifically addresses equitable resource allocation problems with applications in communication networks, manufacturing, emergency services, and more Resource allocation problems focus on assigning limited resources in an economically beneficial way among competing activities. Solutions to such problems affect people and everyday activities with significant impact on the private and public sectors and on society at large. Using diverse application areas as examples, Equitable Resource Allocation: Models, Algorithms, and Applications provides readers with great insight into a topic that is not widely known in the field. Starting with an overview of the topics covered, the book presents a large variety of resource allocation models with special mathematical structures and provides elegant, efficient algorithms that compute optimal solutions to these models. Authored by one of the leading researchers in the field, Equitable Resource Allocation: Is the only book that provides a comprehensive exposition of equitable resource allocation problems Presents a collection of resource allocation models with applications in communication networks, transportation, content distribution, manufacturing, emergency services, and more Exhibits practical algorithms for solving a variety of resource allocation models Uses real-world applications and examples to explain important concepts Includes end-of-chapter exercises Bringing together much of the equitable resource allocation research from the past thirty years, this book is a valuable reference for anyone interested in solving diverse optimization problems.
Hanan Luss Equitable Resource Allocation. Models, Algorithms and Applications Hanan Luss Equitable Resource Allocation. Models, Algorithms and Applications Новинка

Hanan Luss Equitable Resource Allocation. Models, Algorithms and Applications

9451.22 руб.
A unique book that specifically addresses equitable resource allocation problems with applications in communication networks, manufacturing, emergency services, and more Resource allocation problems focus on assigning limited resources in an economically beneficial way among competing activities. Solutions to such problems affect people and everyday activities with significant impact on the private and public sectors and on society at large. Using diverse application areas as examples, Equitable Resource Allocation: Models, Algorithms, and Applications provides readers with great insight into a topic that is not widely known in the field. Starting with an overview of the topics covered, the book presents a large variety of resource allocation models with special mathematical structures and provides elegant, efficient algorithms that compute optimal solutions to these models. Authored by one of the leading researchers in the field, Equitable Resource Allocation: Is the only book that provides a comprehensive exposition of equitable resource allocation problems Presents a collection of resource allocation models with applications in communication networks, transportation, content distribution, manufacturing, emergency services, and more Exhibits practical algorithms for solving a variety of resource allocation models Uses real-world applications and examples to explain important concepts Includes end-of-chapter exercises Bringing together much of the equitable resource allocation research from the past thirty years, this book is a valuable reference for anyone interested in solving diverse optimization problems.
Igor Ushakov A. Optimal Resource Allocation. With Practical Statistical Applications and Theory Igor Ushakov A. Optimal Resource Allocation. With Practical Statistical Applications and Theory Новинка

Igor Ushakov A. Optimal Resource Allocation. With Practical Statistical Applications and Theory

7823.96 руб.
A UNIQUE ENGINEERING AND STATISTICAL APPROACH TO OPTIMAL RESOURCE ALLOCATION Optimal Resource Allocation: With Practical Statistical Applications and Theory features the application of probabilistic and statistical methods used in reliability engineering during the different phases of life cycles of technical systems. Bridging the gap between reliability engineering and applied mathematics, the book outlines different approaches to optimal resource allocation and various applications of models and algorithms for solving real-world problems. In addition, the fundamental background on optimization theory and various illustrative numerical examples are provided. The book also features: An overview of various approaches to optimal resource allocation, from classical Lagrange methods to modern algorithms based on ideas of evolution in biology Numerous exercises and case studies from a variety of areas, including communications, transportation, energy transmission, and counterterrorism protection The applied methods of optimization with various methods of optimal redundancy problem solutions as well as the numerical examples and statistical methods needed to solve the problems Practical thoughts, opinions, and judgments on real-world applications of reliability theory and solves practical problems using mathematical models and algorithms Optimal Resource Allocation is a must-have guide for electrical, mechanical, and reliability engineers dealing with engineering design and optimal reliability problems. In addition, the book is excellent for graduate and PhD-level courses in reliability theory and optimization.
Yaacoub Elias Resource Allocation in Uplink OFDMA Wireless Systems. Optimal Solutions and Practical Implementations Yaacoub Elias Resource Allocation in Uplink OFDMA Wireless Systems. Optimal Solutions and Practical Implementations Новинка

Yaacoub Elias Resource Allocation in Uplink OFDMA Wireless Systems. Optimal Solutions and Practical Implementations

9219.83 руб.
Tackling problems from the least complicated to the most, Resource Allocation in Uplink OFDMA Wireless Systems provides readers with a comprehensive look at resource allocation and scheduling techniques (for both single and multi-cell deployments) in uplink OFDMA wireless networks—relying on convex optimization and game theory to thoroughly analyze performance. Inside, readers will find topics and discussions on: Formulating and solving the uplink ergodic sum-rate maximization problem Proposing suboptimal algorithms that achieve a close performance to the optimal case at a considerably reduced complexity and lead to fairness when the appropriate utility is used Investigating the performance and extensions of the proposed suboptimal algorithms in a distributed base station scenario Studying distributed resource allocation where users take part in the scheduling process, and considering scenarios with and without user collaboration Formulating the sum-rate maximization problem in a multi-cell scenario, and proposing efficient centralized and distributed algorithms for intercell interference mitigation Discussing the applicability of the proposed techniques to state-of-the-art wireless technologies, LTE and WiMAX, and proposing relevant extensions Along with schematics and figures featuring simulation results, Resource Allocation in Uplink OFDMA Wireless Systems is a valuable book for?wireless communications and cellular systems professionals and students.
Bujar Krasniqi Long Term Evolution Bujar Krasniqi Long Term Evolution Новинка

Bujar Krasniqi Long Term Evolution

10002 руб.
In this book is given an introduction to Partial Frequency Reuse as Inter-Cell Interference Mitigation scheme for downlink of Long Term Evolution. Furthermore, a short explanation of optimization techniques: Dual Decomposition and Geometric Programming for Radio Resource Allocation is given. Applying the optimization techniques in the next chapters of the book, are presented the optimization algorithms for Radio Resource Allocation. This book is aimed to serve for young and experienced researchers as well as telecommunication experts, who want to understand how to develop and analyze the radio resource allocation algorithms in Partial Frequency Reuse. The optimization algorithms are followed by a considerable number of simulation in order to understand them easily.
Jacob Sunil Wireless Technology First Edition Jacob Sunil Wireless Technology First Edition Новинка

Jacob Sunil Wireless Technology First Edition

9214 руб.
The book, focuses on the following research problem: Given a suburban/urban relay enhanced wireless cellular network, how can we design resource allocation algorithms and protocols that explicitly consider the impact of interference and mobility so as to provide users with service availability, QoS assurance, and fair spectrum utilization.In this book, the various issues involved in interference aware resource allocation are addressed. The various resource allocation problems through the prism of SINR induced interference and its impact on network performance are studied. The system model used in this book is presented in chapter 2. Random access OFDMA network with dynamic resource allocation and dynamic Source quick route rebuilding is discussed in chapter 3. Random access OFDMA network with resource allocation for suboptimal relay using partial channel knowledge is discussed in chapter 4 Random access OFDMA Network with joint resource allocation for unpredictable channels presented in chapter 5. Finally, conclusions and future work are given in chapter 6. This book is targeted to student who are researching in the resource allocation in wireless technology
Patricia Ruiz Evolutionary Algorithms for Mobile Ad Hoc Networks Patricia Ruiz Evolutionary Algorithms for Mobile Ad Hoc Networks Новинка

Patricia Ruiz Evolutionary Algorithms for Mobile Ad Hoc Networks

8521.46 руб.
Describes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers in optimization and mobile networking Mobile ad hoc networks (MANETs), vehicular networks (VANETs), sensor networks (SNs), and hybrid networks—each of these require a designer’s keen sense and knowledge of evolutionary algorithms in order to help with the common issues that plague professionals involved in optimization and mobile networking. This book introduces readers to both mobile ad hoc networks and evolutionary algorithms, presenting basic concepts as well as detailed descriptions of each. It demonstrates how metaheuristics and evolutionary algorithms (EAs) can be used to help provide low-cost operations in the optimization process—allowing designers to put some “intelligence” or sophistication into the design. It also offers efficient and accurate information on dissemination algorithms, topology management, and mobility models to address challenges in the field. Evolutionary Algorithms for Mobile Ad Hoc Networks: Instructs on how to identify, model, and optimize solutions to problems that arise in daily research Presents complete and up-to-date surveys on topics like network and mobility simulators Provides sample problems along with solutions/descriptions used to solve each, with performance comparisons Covers current, relevant issues in mobile networks, like energy use, broadcasting performance, device mobility, and more Evolutionary Algorithms for Mobile Ad Hoc Networks is an ideal book for researchers and students involved in mobile networks, optimization, advanced search techniques, and multi-objective optimization.
Fegade Madhav, Muley Aniket, Jadhav Vinayak Multi-Objective Transportation Problem Fegade Madhav, Muley Aniket, Jadhav Vinayak Multi-Objective Transportation Problem Новинка

Fegade Madhav, Muley Aniket, Jadhav Vinayak Multi-Objective Transportation Problem

4389 руб.
In this book some methods of Multi-objective Transportation Problem are discussed.This book contains seven chapters. Here,fuzzy approach is used to get the optimal solutions of Multi-objective Transportation problem. Also, the number of solved problems based on proposed algorithms has been discussed. The real life application is also used to check the feasibility of the propsed algorithms in this book.
Alain Petrowski Evolutionary Algorithms Alain Petrowski Evolutionary Algorithms Новинка

Alain Petrowski Evolutionary Algorithms

7359.44 руб.
Evolutionary algorithms are bio-inspired algorithms based on Darwin’s theory of evolution. They are expected to provide non-optimal but good quality solutions to problems whose resolution is impracticable by exact methods. In six chapters, this book presents the essential knowledge required to efficiently implement evolutionary algorithms. Chapter 1 describes a generic evolutionary algorithm as well as the basic operators that compose it. Chapter 2 is devoted to the solving of continuous optimization problems, without constraint. Three leading approaches are described and compared on a set of test functions. Chapter 3 considers continuous optimization problems with constraints. Various approaches suitable for evolutionary methods are presented. Chapter 4 is related to combinatorial optimization. It provides a catalog of variation operators to deal with order-based problems. Chapter 5 introduces the basic notions required to understand the issue of multi-objective optimization and a variety of approaches for its application. Finally, Chapter 6 describes different approaches of genetic programming able to evolve computer programs in the context of machine learning.
Dan Simon Evolutionary Optimization Algorithms Dan Simon Evolutionary Optimization Algorithms Новинка

Dan Simon Evolutionary Optimization Algorithms

10303.08 руб.
A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies. This book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others. Evolutionary Optimization Algorithms: Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear—but theoretically rigorous—understanding of evolutionary algorithms, with an emphasis on implementation Gives a careful treatment of recently developed EAs—including opposition-based learning, artificial fish swarms, bacterial foraging, and many others— and discusses their similarities and differences from more well-established EAs Includes chapter-end problems plus a solutions manual available online for instructors Offers simple examples that provide the reader with an intuitive understanding of the theory Features source code for the examples available on the author's website Provides advanced mathematical techniques for analyzing EAs, including Markov modeling and dynamic system modeling Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science.
Ayhan IRCI On Optimal Resource Allocation in Phased Array Radar Systems Ayhan IRCI On Optimal Resource Allocation in Phased Array Radar Systems Новинка

Ayhan IRCI On Optimal Resource Allocation in Phased Array Radar Systems

10127 руб.
In this study, the problem of optimal resource allocation in real-time systems is studied. A recently proposed resource allocation approach called Q-RAM (Quality of Service based Resource Allocation Model) is investigated in detail. The goal of the Q-RAM based approaches is to minimize the execution speed in real-time systems while meeting resource constraints and maximizing total utility. Phased array radar system is an example of a system. In this system, multiple targets are tracked by the radar system simultaneously requiring processor and energy resources of the radar system. In the present study, first, the Q-RAM solution approach to the radar resource allocation problem with single resource type is extended to give a global optimal solution in all possible termination cases. For the case of multiple resource types, the Q-RAM approach can only generate near-optimal results. In this study, for the formulated radar resource allocation problem with multiple resource types, the Methods of Feasible Directions are considered as an alternative solution approach.
Ekram Hossain Radio Resource Management in Multi-Tier Cellular Wireless Networks Ekram Hossain Radio Resource Management in Multi-Tier Cellular Wireless Networks Новинка

Ekram Hossain Radio Resource Management in Multi-Tier Cellular Wireless Networks

9529.13 руб.
Providing an extensive overview of the radio resource management problem in femtocell networks, this invaluable book considers both code division multiple access femtocells and orthogonal frequency-division multiple access femtocells. In addition to incorporating current research on this topic, the book also covers technical challenges in femtocell deployment, provides readers with a variety of approaches to resource allocation and a comparison of their effectiveness, explains how to model various networks using Stochastic geometry and shot noise theory, and much more.
Omid Bozorg-Haddad Meta-heuristic and Evolutionary Algorithms for Engineering Optimization Omid Bozorg-Haddad Meta-heuristic and Evolutionary Algorithms for Engineering Optimization Новинка

Omid Bozorg-Haddad Meta-heuristic and Evolutionary Algorithms for Engineering Optimization

10458.89 руб.
A detailed review of a wide range of meta-heuristic and evolutionary algorithms in a systematic manner and how they relate to engineering optimization problems This book introduces the main metaheuristic algorithms and their applications in optimization. It describes 20 leading meta-heuristic and evolutionary algorithms and presents discussions and assessments of their performance in solving optimization problems from several fields of engineering. The book features clear and concise principles and presents detailed descriptions of leading methods such as the pattern search (PS) algorithm, the genetic algorithm (GA), the simulated annealing (SA) algorithm, the Tabu search (TS) algorithm, the ant colony optimization (ACO), and the particle swarm optimization (PSO) technique. Chapter 1 of Meta-heuristic and Evolutionary Algorithms for Engineering Optimization provides an overview of optimization and defines it by presenting examples of optimization problems in different engineering domains. Chapter 2 presents an introduction to meta-heuristic and evolutionary algorithms and links them to engineering problems. Chapters 3 to 22 are each devoted to a separate algorithm— and they each start with a brief literature review of the development of the algorithm, and its applications to engineering problems. The principles, steps, and execution of the algorithms are described in detail, and a pseudo code of the algorithm is presented, which serves as a guideline for coding the algorithm to solve specific applications. This book: Introduces state-of-the-art metaheuristic algorithms and their applications to engineering optimization; Fills a gap in the current literature by compiling and explaining the various meta-heuristic and evolutionary algorithms in a clear and systematic manner; Provides a step-by-step presentation of each algorithm and guidelines for practical implementation and coding of algorithms; Discusses and assesses the performance of metaheuristic algorithms in multiple problems from many fields of engineering; Relates optimization algorithms to engineering problems employing a unifying approach. Meta-heuristic and Evolutionary Algorithms for Engineering Optimization is a reference intended for students, engineers, researchers, and instructors in the fields of industrial engineering, operations research, optimization/mathematics, engineering optimization, and computer science. OMID BOZORG-HADDAD, PhD, is Professor in the Department of Irrigation and Reclamation Engineering at the University of Tehran, Iran. MOHAMMAD SOLGI, M.Sc., is Teacher Assistant for M.Sc. courses at the University of Tehran, Iran. HUGO A. LOÁICIGA, PhD, is Professor in the Department of Geography at the University of California, Santa Barbara, United States of America.
Ling-Feng Wang, Kay Chen Tan, Chee-Meng Chew EVOLUTIONARY ROBOTICS. FROM ALGORITHMS TO IMPLEMENTATIONS Ling-Feng Wang, Kay Chen Tan, Chee-Meng Chew EVOLUTIONARY ROBOTICS. FROM ALGORITHMS TO IMPLEMENTATIONS Новинка

Ling-Feng Wang, Kay Chen Tan, Chee-Meng Chew EVOLUTIONARY ROBOTICS. FROM ALGORITHMS TO IMPLEMENTATIONS

7552 руб.
This invaluable book comprehensively describes evolutionary robotics and computational intelligence, and how different computational intelligence techniques are applied to robotic system design. It embraces the most widely used evolutionary approaches with their merits and drawbacks, presents some related experiments for robotic behavior evolution and the results achieved, and shows promising future research directions. Clarity of explanation is emphasized such that a modest knowledge of basic evolutionary computation, digital circuits and engineering design will suffice for a thorough understanding of the material.The book is ideally suited to computer scientists, practitioners and researchers keen on computational intelligence techniques, especially the evolutionary algorithms in autonomous robotics at both the hardware and software levels.
Scott Sudhoff D. Power Magnetic Devices. A Multi-Objective Design Approach Scott Sudhoff D. Power Magnetic Devices. A Multi-Objective Design Approach Новинка

Scott Sudhoff D. Power Magnetic Devices. A Multi-Objective Design Approach

10257.51 руб.
Presents a multi-objective design approach to the many power magnetic devices in use today Power Magnetic Devices: A Multi-Objective Design Approach addresses the design of power magnetic devices—including inductors, transformers, electromagnets, and rotating electric machinery—using a structured design approach based on formal single- and multi-objective optimization. The book opens with a discussion of evolutionary-computing-based optimization. Magnetic analysis techniques useful to the design of all the devices considered in the book are then set forth. This material is then used for inductor design so readers can start the design process. Core loss is next considered; this material is used to support transformer design. A chapter on force and torque production feeds into a chapter on electromagnet design. This is followed by chapters on rotating machinery and the design of a permanent magnet AC machine. Finally, enhancements to the design process including thermal analysis and AC conductor losses due to skin and proximity effects are set forth. Power Magnetic Devices: Focuses on the design process as it relates to power magnetic devices such as inductors, transformers, electromagnets, and rotating machinery Offers a structured design approach based on single- and multi-objective optimization Helps experienced designers take advantage of new techniques which can yield superior designs with less engineering time Provides numerous case studies throughout the book to facilitate readers’ comprehension of the analysis and design process Includes Powerpoint-slide-based student and instructor lecture notes and MATLAB-based examples, toolboxes, and design codes Designed to support the educational needs of students, Power Magnetic Devices: A Multi-Objective Design Approach also serves as a valuable reference tool for practicing engineers and designers. MATLAB examples are available via the book support site.
Xin-She Yang Optimization Techniques and Applications with Examples Xin-She Yang Optimization Techniques and Applications with Examples Новинка

Xin-She Yang Optimization Techniques and Applications with Examples

8614.19 руб.
A guide to modern optimization applications and techniques in newly emerging areas spanning optimization, data science, machine intelligence, engineering, and computer sciences Optimization Techniques and Applications with Examples introduces the fundamentals of all the commonly used techniques in optimization that encompass the broadness and diversity of the methods (traditional and new) and algorithms. The author—a noted expert in the field—covers a wide range of topics including mathematical foundations, optimization formulation, optimality conditions, algorithmic complexity, linear programming, convex optimization, and integer programming. In addition, the book discusses artificial neural network, clustering and classifications, constraint-handling, queueing theory, support vector machine and multi-objective optimization, evolutionary computation, nature-inspired algorithms and many other topics. Designed as a practical resource, all topics are explained in detail with step-by-step examples to show how each method works. The book’s exercises test the acquired knowledge that can be potentially applied to real problem solving. By taking an informal approach to the subject, the author helps readers to rapidly acquire the basic knowledge in optimization, operational research, and applied data mining. This important resource: Offers an accessible and state-of-the-art introduction to the main optimization techniques Contains both traditional optimization techniques and the most current algorithms and swarm intelligence-based techniques Presents a balance of theory, algorithms, and implementation Includes more than 100 worked examples with step-by-step explanations Written for upper undergraduates and graduates in a standard course on optimization, operations research and data mining, Optimization Techniques and Applications with Examples is a highly accessible guide to understanding the fundamentals of all the commonly used techniques in optimization.
Shokoufeh Mirzaei Supply Chain Network Configuration: Dynamicity and Sustainability Shokoufeh Mirzaei Supply Chain Network Configuration: Dynamicity and Sustainability Новинка

Shokoufeh Mirzaei Supply Chain Network Configuration: Dynamicity and Sustainability

4749 руб.
Supply chain problems with respect to the area that they address can be classified into four major groups: location-allocation problem, transportation problem, manufacturing problem, and inventory problem. In this book, location-allocation and routing problems, also called LRPs, are studied with two approaches. In the first approach the objective is to minimize the total system cost by finding the best location-allocation and routing plan when demand and travel times are dynamic. The dynamic nature of demand/travel time is presented by functions obtained from historical data. In the second approach, the sustainability perspective of the LRP is considered. The objective is to minimize the total network cost. However,despite the traditional objective function of distance minimization, the total cost is presented in terms of energy cost.
Evelyne Lutton Evolutionary Algorithms for Food Science and Technology Evelyne Lutton Evolutionary Algorithms for Food Science and Technology Новинка

Evelyne Lutton Evolutionary Algorithms for Food Science and Technology

10458.89 руб.
Researchers and practitioners in food science and technology routinely face several challenges, related to sparseness and heterogeneity of data, as well as to the uncertainty in the measurements and the introduction of expert knowledge in the models. Evolutionary algorithms (EAs), stochastic optimization techniques loosely inspired by natural selection, can be effectively used to tackle these issues. In this book, we present a selection of case studies where EAs are adopted in real-world food applications, ranging from model learning to sensitivity analysis.
Bakhshi Ziaul Hassan Stochastic Programming Approach in Stratified Sampling Problems Bakhshi Ziaul Hassan Stochastic Programming Approach in Stratified Sampling Problems Новинка

Bakhshi Ziaul Hassan Stochastic Programming Approach in Stratified Sampling Problems

8189 руб.
This book is based on the application of Stochastic programming techniques in Stratified Sampling problems. Stochastic programming deals with a class of optimization models and algorithms in which some of the data may be considered as random. First chapter provides a brief historical sketch of mathematical programming, stochastic programming and its application to various fields including sampling are presented. Various methods namely E-model, modified E-model, Branch and Bound approach and chance constrained programming are used to solve Probabilistic objective function & constraint into an equivalent deterministic. Allocation problems arising in univariate sratified sampling have been considered in first four (II-V) chapters and multivariate case in the last chapter. The problems are solved by first deriving the deterministic equivalents and then by using a suitable convex programming algorithm or by using the Chance constrained technique. Allocation problem in two stage stratified sampling with random parameters in both objective and constraints is also discussed. A numerical example is presented in all chapters and the problems are solved by LINGO software.
Dang Xuan Tho Genetic Algorithms and Application in Examination Scheduling Dang Xuan Tho Genetic Algorithms and Application in Examination Scheduling Новинка

Dang Xuan Tho Genetic Algorithms and Application in Examination Scheduling

3989 руб.
Research Paper (undergraduate) from the year 2009 in the subject Computer Science - Applied, , language: English, abstract: AbstractIn this thesis, we present an introduction about genetic algorithms (GAs). Genetic algorithms are not too hard to program or understand, since they are biologically based. This thesis also shows scheduling problems, expecially examination scheduling problems. We provide a way that can be easily used to apply the evolutionary principle to the problem solutions. Furthermore, these are the program's applications in reality as well as in science.Keyword: Genetic Algorithms, Scheduling Problems, ExaminationScheduling Problems.
Pawel Cichosz Data Mining Algorithms. Explained Using R Pawel Cichosz Data Mining Algorithms. Explained Using R Новинка

Pawel Cichosz Data Mining Algorithms. Explained Using R

6197.43 руб.
Data Mining Algorithms is a practical, technically-oriented guide to data mining algorithms that covers the most important algorithms for building classification, regression, and clustering models, as well as techniques used for attribute selection and transformation, model quality evaluation, and creating model ensembles. The author presents many of the important topics and methodologies widely used in data mining, whilst demonstrating the internal operation and usage of data mining algorithms using examples in R.
Cyril Tomkins Corporate Resource Allocation. Financial, Strategic and Organizational Perspectives Cyril Tomkins Corporate Resource Allocation. Financial, Strategic and Organizational Perspectives Новинка

Cyril Tomkins Corporate Resource Allocation. Financial, Strategic and Organizational Perspectives

5039 руб.
Most books on allocating major corporate resources are written from just one viewpoint whether it be finance, strategy or behavioral science. Professor Tomkins argues that these important decisions obviously have multi-functional facets and implications. In this book he presents an integrated approach.
Harding Jenny A. Evolutionary Computing in Advanced Manufacturing Harding Jenny A. Evolutionary Computing in Advanced Manufacturing Новинка

Harding Jenny A. Evolutionary Computing in Advanced Manufacturing

15505.54 руб.
This cutting-edge book covers emerging, evolutionary and nature inspired optimization techniques in the field of advanced manufacturing. The complexity of real life advanced manufacturing problems often cannot be solved by traditional engineering or computational methods. Hence, in recent years researchers and practitioners have proposed and developed new strands of advanced, intelligent techniques and methodologies. Evolutionary computing approaches are introduced in the context of a wide range of manufacturing activities, and through the examination of practical problems and their solutions, readers will gain confidence to apply these powerful computing solutions. The initial chapters introduce and discuss the well established evolutionary algorithm, to help readers to understand the basic building blocks and steps required to successfully implement their own solutions to real life advanced manufacturing problems. In the later chapters, modified and improved versions of evolutionary algorithms are discussed. The book concludes with appendices which provide general descriptions of several evolutionary algorithms.
Marcos Gestal, Daniel Rivero, Alejandro Pazos Genetic Algorithms. Key Concepts and Examples Marcos Gestal, Daniel Rivero, Alejandro Pazos Genetic Algorithms. Key Concepts and Examples Новинка

Marcos Gestal, Daniel Rivero, Alejandro Pazos Genetic Algorithms. Key Concepts and Examples

8914 руб.
Evolutionary computation can be viewed as a set of techniques conceptually inspired by biological processes. Among that techniques, one of the most used are genetic algorithms. They follow the Darwin Law's to find the solution of a problem. The overall objective of this book is to provide a "roadmap" with which to find the way toward finding computational solutions to various problems. To this end, a general introduction is presented of the methods and techniques associated with genetic algorithms. In this context, this book ought not be viewed as an exhaustive or comprehensive analysis of the techniques presented herein. Instead, it should be considered as a reference that introduces the terminology, key concepts, and basic bibliography that can serve as a starting point such that the reader will be better equipped to subsequently pursue more deeply those topics that may be of special interest. In particular, this book is designed for those people who are interested in new approaches to problem solving as well for researchers who hope to initiate research directions along the lines of evolutionary computing or closely connected areas.
Dilbag Singh Gill, Amit Chhabra Integrated Multilevel Checkpointing Techniques and Greencloud Dilbag Singh Gill, Amit Chhabra Integrated Multilevel Checkpointing Techniques and Greencloud Новинка

Dilbag Singh Gill, Amit Chhabra Integrated Multilevel Checkpointing Techniques and Greencloud

8377 руб.
This book presents an approach for providing high availability to the requests of cloud's clients. To achieve this objective, fail-over strategies for cloud computing data centers using integrated multilevel checkpointing algorithms are proposed in this research work. Proposed strategy integrates checkpointing features with load balancing algorithms and also employs multilevel checkpointing to decrease checkpointing overheads. Additional objective of this research work is to improve the checkpointing efficiency and prevent checkpointing from becoming the bottleneck of cloud data centers. In this book, greencloud simulator is used for energy-aware cloud computing data centers. Along with the workload distribution, the simulator is used to capture details of the energy consumed by data center components (servers, switches, and links) as well as packet-level communication patterns in realistic setups.
Jie Liang Models and Algorithms for Biomolecules and Molecular Networks Jie Liang Models and Algorithms for Biomolecules and Molecular Networks Новинка

Jie Liang Models and Algorithms for Biomolecules and Molecular Networks

8908.8 руб.
By providing expositions to modeling principles, theories, computational solutions, and open problems, this reference presents a full scope on relevant biological phenomena, modeling frameworks, technical challenges, and algorithms. Up-to-date developments of structures of biomolecules, systems biology, advanced models, and algorithms Sampling techniques for estimating evolutionary rates and generating molecular structures Accurate computation of probability landscape of stochastic networks, solving discrete chemical master equations End-of-chapter exercises
Xin-She Yang Engineering Optimization. An Introduction with Metaheuristic Applications Xin-She Yang Engineering Optimization. An Introduction with Metaheuristic Applications Новинка

Xin-She Yang Engineering Optimization. An Introduction with Metaheuristic Applications

11847.82 руб.
An accessible introduction to metaheuristics and optimization, featuring powerful and modern algorithms for application across engineering and the sciences From engineering and computer science to economics and management science, optimization is a core component for problem solving. Highlighting the latest developments that have evolved in recent years, Engineering Optimization: An Introduction with Metaheuristic Applications outlines popular metaheuristic algorithms and equips readers with the skills needed to apply these techniques to their own optimization problems. With insightful examples from various fields of study, the author highlights key concepts and techniques for the successful application of commonly-used metaheuristc algorithms, including simulated annealing, particle swarm optimization, harmony search, and genetic algorithms. The author introduces all major metaheuristic algorithms and their applications in optimization through a presentation that is organized into three succinct parts: Foundations of Optimization and Algorithms provides a brief introduction to the underlying nature of optimization and the common approaches to optimization problems, random number generation, the Monte Carlo method, and the Markov chain Monte Carlo method Metaheuristic Algorithms presents common metaheuristic algorithms in detail, including genetic algorithms, simulated annealing, ant algorithms, bee algorithms, particle swarm optimization, firefly algorithms, and harmony search Applications outlines a wide range of applications that use metaheuristic algorithms to solve challenging optimization problems with detailed implementation while also introducing various modifications used for multi-objective optimization Throughout the book, the author presents worked-out examples and real-world applications that illustrate the modern relevance of the topic. A detailed appendix features important and popular algorithms using MATLAB® and Octave software packages, and a related FTP site houses MATLAB code and programs for easy implementation of the discussed techniques. In addition, references to the current literature enable readers to investigate individual algorithms and methods in greater detail. Engineering Optimization: An Introduction with Metaheuristic Applications is an excellent book for courses on optimization and computer simulation at the upper-undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners working in the fields of mathematics, engineering, computer science, operations research, and management science who use metaheuristic algorithms to solve problems in their everyday work.
William Kinlaw A Practitioner's Guide to Asset Allocation William Kinlaw A Practitioner's Guide to Asset Allocation Новинка

William Kinlaw A Practitioner's Guide to Asset Allocation

2647.21 руб.
Since the formalization of asset allocation in 1952 with the publication of Portfolio Selection by Harry Markowitz, there have been great strides made to enhance the application of this groundbreaking theory. However, progress has been uneven. It has been punctuated with instances of misleading research, which has contributed to the stubborn persistence of certain fallacies about asset allocation. A Practitioner's Guide to Asset Allocation fills a void in the literature by offering a hands-on resource that describes the many important innovations that address key challenges to asset allocation and dispels common fallacies about asset allocation. The authors cover the fundamentals of asset allocation, including a discussion of the attributes that qualify a group of securities as an asset class and a detailed description of the conventional application of mean-variance analysis to asset allocation.. The authors review a number of common fallacies about asset allocation and dispel these misconceptions with logic or hard evidence. The fallacies debunked include such notions as: asset allocation determines more than 90% of investment performance; time diversifies risk; optimization is hypersensitive to estimation error; factors provide greater diversification than assets and are more effective at reducing noise; and that equally weighted portfolios perform more reliably out of sample than optimized portfolios. A Practitioner's Guide to Asset Allocation also explores the innovations that address key challenges to asset allocation and presents an alternative optimization procedure to address the idea that some investors have complex preferences and returns may not be elliptically distributed. Among the challenges highlighted, the authors explain how to overcome inefficiencies that result from constraints by expanding the optimization objective function to incorporate absolute and relative goals simultaneously. The text also explores the challenge of currency risk, describes how to use shadow assets and liabilities to unify liquidity with expected return and risk, and shows how to evaluate alternative asset mixes by assessing exposure to loss throughout the investment horizon based on regime-dependent risk. This practical text contains an illustrative example of asset allocation which is used to demonstrate the impact of the innovations described throughout the book. In addition, the book includes supplemental material that summarizes the key takeaways and includes information on relevant statistical and theoretical concepts, as well as a comprehensive glossary of terms.
Tadeusz Sawik Scheduling in Supply Chains Using Mixed Integer Programming Tadeusz Sawik Scheduling in Supply Chains Using Mixed Integer Programming Новинка

Tadeusz Sawik Scheduling in Supply Chains Using Mixed Integer Programming

11529.76 руб.
A unified, systematic approach to applying mixed integer programming solutions to integrated scheduling in customer-driven supply chains Supply chain management is a rapidly developing field, and the recent improvements in modeling, preprocessing, solution algorithms, and mixed integer programming (MIP) software have made it possible to solve large-scale MIP models of scheduling problems, especially integrated scheduling in supply chains. Featuring a unified and systematic presentation, Scheduling in Supply Chains Using Mixed Integer Programming provides state-of-the-art MIP modeling and solutions approaches, equipping readers with the knowledge and tools to model and solve real-world supply chain scheduling problems in make-to-order manufacturing. Drawing upon the author's own research, the book explores MIP approaches and examples-which are modeled on actual supply chain scheduling problems in high-tech industries-in three comprehensive sections: Short-Term Scheduling in Supply Chains presents various MIP models and provides heuristic algorithms for scheduling flexible flow shops and surface mount technology lines, balancing and scheduling of Flexible Assembly Lines, and loading and scheduling of Flexible Assembly Systems Medium-Term Scheduling in Supply Chains outlines MIP models and MIP-based heuristic algorithms for supplier selection and order allocation, customer order acceptance and due date setting, material supply scheduling, and medium-term scheduling and rescheduling of customer orders in a make-to-order discrete manufacturing environment Coordinated Scheduling in Supply Chains explores coordinated scheduling of manufacturing and supply of parts as well as the assembly of products in supply chains with a single producer and single or multiple suppliers; MIP models for a single- or multiple-objective decision making are also provided Two main decision-making approaches are discussed and compared throughout. The integrated (simultaneous) approach, in which all required decisions are made simultaneously using complex, monolithic MIP models; and the hierarchical (sequential) approach, in which the required decisions are made successively using hierarchies of simpler and smaller-sized MIP models. Throughout the book, the author provides insight on the presented modeling tools using AMPL® modeling language and CPLEX solver. Scheduling in Supply Chains Using Mixed Integer Programming is a comprehensive resource for practitioners and researchers working in supply chain planning, scheduling, and management. The book is also appropriate for graduate- and PhD-level courses on supply chains for students majoring in management science, industrial engineering, operations research, applied mathematics, and computer science.
Yingtao Ren Vehicle Routing and Resource Allocation under Uncertainty Yingtao Ren Vehicle Routing and Resource Allocation under Uncertainty Новинка

Yingtao Ren Vehicle Routing and Resource Allocation under Uncertainty

9002 руб.
In this book, we study optimization models for health care under uncertainty and resource constraints. In particular, we study two problems. The first problem is the multi-shift Vehicle Routing Problem (MSVRP) with overtime to meet around-the-clock demand. We use insertion to create the initial routes and then use tabu search to improve the routes. We show that our algorithm can find high-quality solutions for very large problems. The second problem is a multi-city resource allocation model to distribute the medical supplies in order to minimize the total number of fatalities in an infectious disease outbreak. We consider the problem with uncertainty in the initial number of cases and transmission rate, and build a two-stage stochastic programming model. To solve instances of realistic size we use a heuristic based on Benders decomposition. Finally, we use sample average approximation (SAA) to get confidence intervals on the optimal solution. We illustrate the use of the model and the solution technique in planning an emergency response to a hypothetic national smallpox outbreak. Computations show that the algorithm is efficient and can obtain near-optimal solution.
Hossein Kazemi The New Science of Asset Allocation. Risk Management in a Multi-Asset World Hossein Kazemi The New Science of Asset Allocation. Risk Management in a Multi-Asset World Новинка

Hossein Kazemi The New Science of Asset Allocation. Risk Management in a Multi-Asset World

5301.04 руб.
A feasible asset allocation framework for the post 2008 financial world Asset allocation has long been a cornerstone of prudent investment management; however, traditional allocation plans failed investors miserably in 2008. Asset allocation still remains an essential part of the investment arena, and through a new approach, you'll discover how to make it work. In The New Science of Asset Allocation, authors Thomas Schneeweis, Garry Crowder, and Hossein Kazemi first explore the myths that plague this field then quickly move on to examine how the practice of asset allocation has failed in recent years. They then propose new allocation models that employ liquidity, transparency, and real risk controls across multiple asset classes. Outlines a new approach to asset allocation in a post-2008 world, where risk seems hidden The «great manager» problem is examined with solutions on how to capture manager alpha while limiting downside risk A complete case study is presented that allocates for beta and alpha Written by an experienced team of industry leaders and academic experts, The New Science of Asset Allocation explains how you can effectively apply this approach to a financial world that continues to change.
Nagaswaroopa Adapa Performance analysis of adaptive algorithms based on echo cancellation Nagaswaroopa Adapa Performance analysis of adaptive algorithms based on echo cancellation Новинка

Nagaswaroopa Adapa Performance analysis of adaptive algorithms based on echo cancellation

3212 руб.
In modern communication systems like hands-free and teleconferencing systems,the problem arise during conversation is creation of an acoustic echo.It degrads the quality of the information signal.Me and my professor magnusberggren has started research on this problem and obtained solution to this problem using adaptive algorithms NLMS,RLSand APA.The Acoustic echo cancellation with adaptive filtering technique will more accurately enhance the speech quality in hands free communication systems. The main aim of using adaptive algorithms for echo cancellation is to achieve higher ERLE at higher rate of convergence with low complexity. The adaptive algorithms NLMS, APA and RLS are implemented using MATLAB.
Samuel Blankson Asset Allocation. The Key to Financial Success Samuel Blankson Asset Allocation. The Key to Financial Success Новинка

Samuel Blankson Asset Allocation. The Key to Financial Success

527 руб.
Asset Allocation: The key to Financial Success is a book on the most critical factor in obtaining long-term financial success. Without a proper asset allocation plan in place, your financial security is in the hands of chance. A bad turn in economic cycles could wipe you out.This book shows you how to develop your own personal asset allocation plan to suit your particular needs. It covers the division of your investment capital across a broad range of asset classes and risk structures. A useful resource for everyone from homemakers to Wall Street fund managers.
Andrew Sage P. Risk Modeling, Assessment, and Management Andrew Sage P. Risk Modeling, Assessment, and Management Новинка

Andrew Sage P. Risk Modeling, Assessment, and Management

12782.93 руб.
Presents systems-based theory, methodology, and applications in risk modeling, assessment, and management This book examines risk analysis, focusing on quantifying risk and constructing probabilities for real-world decision-making, including engineering, design, technology, institutions, organizations, and policy. The author presents fundamental concepts (hierarchical holographic modeling; state space; decision analysis; multi-objective trade-off analysis) as well as advanced material (extreme events and the partitioned multi-objective risk method; multi-objective decision trees; multi-objective risk impact analysis method; guiding principles in risk analysis); avoids higher mathematics whenever possible; and reinforces the material with examples and case studies. The book will be used in systems engineering, enterprise risk management, engineering management, industrial engineering, civil engineering, and operations research. The fourth edition of Risk Modeling, Assessment, and Management features: Expanded chapters on systems-based guiding principles for risk modeling, planning, assessment, management, and communication; modeling interdependent and interconnected complex systems of systems with phantom system models; and hierarchical holographic modeling An expanded appendix including a Bayesian analysis for the prediction of chemical carcinogenicity, and the Farmer’s Dilemma formulated and solved using a deterministic linear model Updated case studies including a new case study on sequential Pareto-optimal decisions for emergent complex systems of systems A new companion website with over 200 solved exercises that feature risk analysis theories, methodologies, and application Risk Modeling, Assessment, and Management, Fourth Edition, is written for both undergraduate and graduate students in systems engineering and systems management courses. The text also serves as a resource for academic, industry, and government professionals in the fields of homeland and cyber security, healthcare, physical infrastructure systems, engineering, business, and more.
John Abbink B. Alternative Assets and Strategic Allocation. Rethinking the Institutional Approach John Abbink B. Alternative Assets and Strategic Allocation. Rethinking the Institutional Approach Новинка

John Abbink B. Alternative Assets and Strategic Allocation. Rethinking the Institutional Approach

5632.36 руб.
An insightful guide to making strategic investment allocation decisions that embraces both alternative and conventional assets In this much-needed resource, alternative and portfolio management expert John Abbink demonstrates new ways of analyzing and deploying alternative assets and explains the practical application of these techniques. Alternative Assets and Strategic Allocation clearly shows how alternative investments fit into portfolios and the role they play in an investment allocation that includes traditional investments as well. This book also describes innovative methods for valuation as applied to alternatives that previously have been difficult to analyze. Offers institutional investors, analysts, researchers, portfolio managers, and financial academics a down-to-earth method for measuring and analyzing alternative assets Reviews some of the latest alternatives that are increasing in popularity, such as high-frequency trading, direct lending, and long-term investment in real assets Outlines a strategic approach for including alternative investments into portfolios and shows the pivotal role they play in an investment allocation Using the information found in this book, you'll have a clearer sense of how to approach investment issues related to alternative assets and discover what it takes to make these products work for you.
Nabil Bin Hannan Gene Selection using MFSPSO Nabil Bin Hannan Gene Selection using MFSPSO Новинка

Nabil Bin Hannan Gene Selection using MFSPSO

3212 руб.
Minimized Featured Space Particle Swarm Optimization(MFSPSO) is a modified version of the evolutionary algorithm PSO. The main objective is to minimize the number of genes in case of detecting different kinds of cancerous diseases. The MFSPSO can be applied to any type of datasets and for various fields of studies such as: Pattern Recognition, Data Mining, Image Processing and so on. I hope this will take a great deal in modern medical science.
Erchin Serpedin Green Heterogeneous Wireless Networks Erchin Serpedin Green Heterogeneous Wireless Networks Новинка

Erchin Serpedin Green Heterogeneous Wireless Networks

8134.86 руб.
This book focuses on the emerging research topic «green (energy efficient) wireless networks» which has drawn huge attention recently from both academia and industry. This topic is highly motivated due to important environmental, financial, and quality-of-experience (QoE) considerations. Specifically, the high energy consumption of the wireless networks manifests in approximately 2% of all CO2 emissions worldwide. This book presents the authors’ visions and solutions for deployment of energy efficient (green) heterogeneous wireless communication networks. The book consists of three major parts. The first part provides an introduction to the «green networks» concept, the second part targets the green multi-homing resource allocation problem, and the third chapter presents a novel deployment of device-to-device (D2D) communications and its successful integration in Heterogeneous Networks (HetNets). The book is novel in that it specifically targets green networking in a heterogeneous wireless medium, which represents the current and future wireless communication medium faced by the existing and next generation communication networks. The book focuses on multi-homing resource allocation, exploiting network cooperation, and integrating different and new network technologies (radio frequency and VLC), expanding the network coverage and integrating new device centric communication paradigms such as D2D Communications. Whilst the book discusses a significant research topic supported with advanced mathematical analysis, the resulting algorithms and solutions are explained and summarized in a way that is easy to follow and grasp. This book is suitable for networking and telecommunications engineers, researchers in industry and academia, as well as students and instructors.
Stefan Seegert Portfoliooptimierung Mit Hilfe Der Asset-Allocation Stefan Seegert Portfoliooptimierung Mit Hilfe Der Asset-Allocation Новинка

Stefan Seegert Portfoliooptimierung Mit Hilfe Der Asset-Allocation

2952 руб.
Die Asset-Allocation stellt innerhalb des Portfoliomanagements die Kernaufgabe dar. Grob kann man die Asset-Allocation als eine dreigliedrige Form der Vermögensstrukturierung sehen. Zunächst wird definiert, was unter einer Asset-Allocation zu verstehen ist, bevor der Autor auf die wesentlichen Bestandteile der Asset-Allocation eingeht. Die Asset-Allocation ist als ein Prinzip der strukturierten Portfolioaufteilung, welches die Reihenfolge der Vermögensanordnung vornimmt, zu verstehen. Als Kriterium dient die Performanceimplikation. Die Performance ist demzufolge das Zielkriterium des Portfoliomanagements, das als risikoadjustierte Rendite anzusehen ist. Asset-Allocation bezeichnet also einen Prozess einer strukturierten und zugleich zielgerichteten Aufteilung - Allocation - des Vermögens auf unterschiedliche Anlagemöglichkeiten, den Assets.Der Autor beleuchtet kritisch die Bedeutung der Asset-Allocation sowie die Einzelheiten des komplexen Prozesses.
Richard Weber Multi-armed Bandit Allocation Indices Richard Weber Multi-armed Bandit Allocation Indices Новинка

Richard Weber Multi-armed Bandit Allocation Indices

9838.56 руб.
In 1989 the first edition of this book set out Gittins' pioneering index solution to the multi-armed bandit problem and his subsequent investigation of a wide of sequential resource allocation and stochastic scheduling problems. Since then there has been a remarkable flowering of new insights, generalizations and applications, to which Glazebrook and Weber have made major contributions. This second edition brings the story up to date. There are new chapters on the achievable region approach to stochastic optimization problems, the construction of performance bounds for suboptimal policies, Whittle's restless bandits, and the use of Lagrangian relaxation in the construction and evaluation of index policies. Some of the many varied proofs of the index theorem are discussed along with the insights that they provide. Many contemporary applications are surveyed, and over 150 new references are included. Over the past 40 years the Gittins index has helped theoreticians and practitioners to address a huge variety of problems within chemometrics, economics, engineering, numerical analysis, operational research, probability, statistics and website design. This new edition will be an important resource for others wishing to use this approach.
Manuel Servin Fringe Pattern Analysis for Optical Metrology. Theory, Algorithms, and Applications Manuel Servin Fringe Pattern Analysis for Optical Metrology. Theory, Algorithms, and Applications Новинка

Manuel Servin Fringe Pattern Analysis for Optical Metrology. Theory, Algorithms, and Applications

14022.12 руб.
The main objective of this book is to present the basic theoretical principles and practical applications for the classical interferometric techniques and the most advanced methods in the field of modern fringe pattern analysis applied to optical metrology. A major novelty of this work is the presentation of a unified theoretical framework based on the Fourier description of phase shifting interferometry using the Frequency Transfer Function (FTF) along with the theory of Stochastic Process for the straightforward analysis and synthesis of phase shifting algorithms with desired properties such as spectral response, detuning and signal-to-noise robustness, harmonic rejection, etc.
Hitoshi Iba Evolutionary Computation in Gene Regulatory Network Research Hitoshi Iba Evolutionary Computation in Gene Regulatory Network Research Новинка

Hitoshi Iba Evolutionary Computation in Gene Regulatory Network Research

10845.5 руб.
Introducing a handbook for gene regulatory network research using evolutionary computation, with applications for computer scientists, computational and system biologists This book is a step-by-step guideline for research in gene regulatory networks (GRN) using evolutionary computation (EC). The book is organized into four parts that deliver materials in a way equally attractive for a reader with training in computation or biology. Each of these sections, authored by well-known researchers and experienced practitioners, provides the relevant materials for the interested readers. The first part of this book contains an introductory background to the field. The second part presents the EC approaches for analysis and reconstruction of GRN from gene expression data. The third part of this book covers the contemporary advancements in the automatic construction of gene regulatory and reaction networks and gives direction and guidelines for future research. Finally, the last part of this book focuses on applications of GRNs with EC in other fields, such as design, engineering and robotics. • Provides a reference for current and future research in gene regulatory networks (GRN) using evolutionary computation (EC) • Covers sub-domains of GRN research using EC, such as expression profile analysis, reverse engineering, GRN evolution, applications • Contains useful contents for courses in gene regulatory networks, systems biology, computational biology, and synthetic biology • Delivers state-of-the-art research in genetic algorithms, genetic programming, and swarm intelligence Evolutionary Computation in Gene Regulatory Network Research is a reference for researchers and professionals in computer science, systems biology, and bioinformatics, as well as upper undergraduate, graduate, and postgraduate students. Hitoshi Iba is a Professor in the Department of Information and Communication Engineering, Graduate School of Information Science and Technology, at the University of Tokyo, Toyko, Japan. He is an Associate Editor of the IEEE Transactions on Evolutionary Computation and the journal of Genetic Programming and Evolvable Machines. Nasimul Noman is a lecturer in the School of Electrical Engineering and Computer Science at the University of Newcastle, NSW, Australia. From 2002 to 2012 he was a faculty member at the University of Dhaka, Bangladesh. Noman is an Editor of the BioMed Research International journal. His research interests include computational biology, synthetic biology, and bioinformatics.
Rodriguez Miguel, Jabba Daladier Query Optimization Based on the Automata Theory Rodriguez Miguel, Jabba Daladier Query Optimization Based on the Automata Theory Новинка

Rodriguez Miguel, Jabba Daladier Query Optimization Based on the Automata Theory

8652 руб.
The query optimization problem has been widely addressed in Relational Database Management Systems (RDBMS). Many strategies have been implemented to solve this problem including deterministic algorithms, randomized algorithms, meta-heuristic algorithms and hybrid approaches. This book provides a literature review that includes solutions to the join-ordering problem using simulated annealing, genetic algorithms and ant colony optimization. Such methodologies deeply depend on the correct configuration of various input parameters. This book also introduces a new meta-heuristic approach based on the automata theory adapted to solve the join-ordering problem. The proposed method requires only a single input parameter that facilitates its usage respect to other methods. The algorithm was embedded into PostgreSQL and compared with the genetic competitor using random and star database schemas.
Kwang-Yong Kim Design Optimization of Fluid Machinery. Applying Computational Fluid Dynamics and Numerical Optimization Kwang-Yong Kim Design Optimization of Fluid Machinery. Applying Computational Fluid Dynamics and Numerical Optimization Новинка

Kwang-Yong Kim Design Optimization of Fluid Machinery. Applying Computational Fluid Dynamics and Numerical Optimization

14312.81 руб.
Design Optimization of Fluid Machinery: Applying Computational Fluid Dynamics and Numerical Optimization Drawing on extensive research and experience, this timely reference brings together numerical optimization methods for fluid machinery and its key industrial applications. It logically lays out the context required to understand computational fluid dynamics by introducing the basics of fluid mechanics, fluid machines and their components. Readers are then introduced to single and multi-objective optimization methods, automated optimization, surrogate models, and evolutionary algorithms. Finally, design approaches and applications in the areas of pumps, turbines, compressors, and other fluid machinery systems are clearly explained, with special emphasis on renewable energy systems. Written by an international team of leading experts in the field Brings together optimization methods using computational fluid dynamics for fluid machinery in one handy reference Features industrially important applications, with key sections on renewable energy systems Design Optimization of Fluid Machinery is an essential guide for graduate students, researchers, engineers working in fluid machinery and its optimization methods. It is a comprehensive reference text for advanced students in mechanical engineering and related fields of fluid dynamics and aerospace engineering.
Michael Bowles Machine Learning in Python. Essential Techniques for Predictive Analysis Michael Bowles Machine Learning in Python. Essential Techniques for Predictive Analysis Новинка

Michael Bowles Machine Learning in Python. Essential Techniques for Predictive Analysis

3873.39 руб.
Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions. Machine learning algorithms are at the core of data analytics and visualization. In the past, these methods required a deep background in math and statistics, often in combination with the specialized R programming language. This book demonstrates how machine learning can be implemented using the more widely used and accessible Python programming language. Predict outcomes using linear and ensemble algorithm families Build predictive models that solve a range of simple and complex problems Apply core machine learning algorithms using Python Use sample code directly to build custom solutions Machine learning doesn't have to be complex and highly specialized. Python makes this technology more accessible to a much wider audience, using methods that are simpler, effective, and well tested. Machine Learning in Python shows you how to do this, without requiring an extensive background in math or statistics.
Chen Z. Jeffrey Polyploid and Hybrid Genomics Chen Z. Jeffrey Polyploid and Hybrid Genomics Новинка

Chen Z. Jeffrey Polyploid and Hybrid Genomics

16932.85 руб.
Polyploidy plays an important role in biological diversity, trait improvement, and plant species survival. Understanding the evolutionary phenomenon of polyploidy is a key challenge for plant and crop scientists. This book is made up of contributions from leading researchers in the field from around the world, providing a truly global review of the subject. Providing broad-ranging coverage, and up-to-date information from some of the world’s leading researchers, this book is an invaluable resource for geneticists, plant and crop scientists, and evolutionary biologists.
Daniel Shain H. Annelids in Modern Biology Daniel Shain H. Annelids in Modern Biology Новинка

Daniel Shain H. Annelids in Modern Biology

13990.77 руб.
Annelids offer a diversity of experimentally accessible features making them a rich experimental subject across the biological sciences, including evolutionary development, neurosciences and stem cell research. This volume introduces the Annelids and their utility in evolutionary developmental biology, neurobiology, and environmental/ecological studies, including extreme environments. The book demonstrates the variety of fields in which Annelids are already proving to be a useful experimental system. Describing the utility of Annelids as a research model, this book is an invaluable resource for all researchers in the field.
Shivade Anand Multi-objective Optimization in WEDM of D3 Tool Steel Shivade Anand Multi-objective Optimization in WEDM of D3 Tool Steel Новинка

Shivade Anand Multi-objective Optimization in WEDM of D3 Tool Steel

8177 руб.
This book contains study of wire electrical discharge machining of D3 tool steel. Influence of different process parameters are investigated for MRR, dimensional deviation, gap current and machining time, during intricate machining of D3 tool steel. Taguchi method is used for single characteristics optimization and to optimize all four process parameters simultaneously, Grey relational analysis (GRA) is employed along with Taguchi method. Through GRA, grey relational grade is used as a performance index to determine the optimal setting of process parameters for multi-objective characteristics. Confirmatory results, proves the potential of GRA to optimize process parameters successfully for multi-objective characteristics.
Breno Miranda, Juliano Iyoda Recommender Systems for Manual Testing Breno Miranda, Juliano Iyoda Recommender Systems for Manual Testing Новинка

Breno Miranda, Juliano Iyoda Recommender Systems for Manual Testing

8514 руб.
Software testing is an arduous and expensive activity. In the context of manual testing, any effort to reduce the test execution time and to increase defect findings is welcome. One approach is to allocate test cases according to the testers profile in a way to maximise testing productivity. However, optimising the allocation of manual test cases is not a trivial task: in large companies, test managers are responsible for allocating hundreds of test cases among several testers. We implemented 2 assignment algorithms for test case allocation and defined 3 tester profiles based on recommender systems (the same kind of system that recommends, for example, a book at Amazon.com). Our allocation systems take into account the tester's effectiveness (valid defects found in the past) and expertise (ability to run tests with certain characteristics). We performed a controlled experiment in a real industrial setting in order to compare our allocation systems to the manager's allocation and to random allocations. The findings of this research are especially useful to software testing professionals, or anyone else who wants to better understand how the manual software testing process works.
Rehan Virender K. Evolutionary Biology. Cell-Cell Communication, and Complex Disease Rehan Virender K. Evolutionary Biology. Cell-Cell Communication, and Complex Disease Новинка

Rehan Virender K. Evolutionary Biology. Cell-Cell Communication, and Complex Disease

7470.49 руб.
An integrative view of the evolution of genetics and the natural world Even in this advanced age of genomics, the evolutionary process of unicellular and multicellular organisms is continually in debate. Evolutionary Biology, Cell–Cell Communication, and Complex Disease challenges current wisdom by using physiology to present an integrative view of the nature, origins, and evolution of fundamental biological systems. Providing a deeper understanding of the way genes relate to the traits of living organisms, this book offers useful information applying evolutionary biology, functional genomics, and cell communication studies to complex disease. Examining the 4.5 billion-year evolution process from environment adaptations to cell-cell communication to communication of genetic information for reproduction, Evolutionary Biology hones in on the «why and how» of evolution by uniquely focusing on the cell as the smallest unit of biologic structure and function. Based on empirically derived data rather than association studies, Evolutionary Biology covers: A model for forming testable hypotheses in complex disease studies The integrating role played by the evolution of metabolism, especially lipid metabolism The evolutionary continuum from development to homeostasis Regeneration and aging mediated by signaling molecules Ambitious and game-changing Evolutionary Biology suggests that biology began as a mechanism for reducing energy within the cell, defying the Second Law of Thermodynamics. An ideal text for those interested in forward thinking scientific study, the insights presented in Evolutionary Biology help practitioners effectively comprehend the evolutionary process.
Rashi Kohli and Manoj Kumar Cryptographic on System-Chip-Design Using VLSI Technique Rashi Kohli and Manoj Kumar Cryptographic on System-Chip-Design Using VLSI Technique Новинка

Rashi Kohli and Manoj Kumar Cryptographic on System-Chip-Design Using VLSI Technique

4419 руб.
In this book, research work in symmetric domain of cryptography is preferred over asymmetric cryptography domain at FPGA PLATFORM. To minimize the attacks like brute force attacks, linear and differential attacks over the system or the network, the approach adopted in this research work, verifies and conforms the increased level of security in comparison to previous approaches and also keeping in mind the resource consumption. The idea behind is to achieve "OPTIMIZATION" simultaneously increasing the security so that it can be used in different domains whether being at the network, ubiquitous computing, RFID Technology, Crypto-Cards, SIM cards etc. So this highlights the increased security in symmetric cryptography algorithms by proposed FPGA based MULTI-ENCRYPTION ALGORITHM whose results are compared to the previous approaches.
Apurba Das Bacterial Foraging Optimization for Digital Filter Synthesis Apurba Das Bacterial Foraging Optimization for Digital Filter Synthesis Новинка

Apurba Das Bacterial Foraging Optimization for Digital Filter Synthesis

6190 руб.
In any deterministic solution, the convergence is not at all guaranteed, whereas, the stochastic and random search algorithms are 1 shot optimization and it can hit the nearly optimized solution, with guarantee. Therefore the AI dependent evolutionary algorithms (GA, PSO, DE, BFOA) are prescribed for this type of optimization problems. Some selected evolutionary algorithms are presented for digital filter design. If the statistical characteristic of the input data varies with respect to time or the required knowledge about input data is not satisfactory, adaptive filters are needed. Adaptive filters (FIR and IIR) have attractive increasing attention due to their widespread use in many different applications such as system identification, noise cancellation, channel equalization, linear prediction, control, and modeling. In the present book, in order to achieve a global minimum solution to the fitness function related to filter transfer function, biologically inspired algorithm is used. Adaptation to classical Bacterial Foraging Optimization is employed to design stable and optimum digital filter design for signal processing and image processing applications.
Niclas Rüffer The Allocation of Innovation Promotion Programs Niclas Rüffer The Allocation of Innovation Promotion Programs Новинка

Niclas Rüffer The Allocation of Innovation Promotion Programs

9039 руб.
R&D and innovation policy is high on the political agenda in advanced economies. Market and system failures have been identified as reasons for private underinvestment in R&D and innovation and several policy instruments are in use to mitigate these failures. One central instrument of innovation policy are direct subsidies for firm R&D. By using direct project funding governments have the chance to target projects with high social returns and therefore, in theory, i. e. if policy makers can identify projects with high social returns, direct project funding can be an effective instrument to foster private sector R&D. However, there is no straightforward mechanism guaranteeing that subsidies are applied to projects which suffer from market or system failures. The allocation process of subsidies therefore appears to be central to the question of the effectiveness of subsidies.In spite of increasing scientific interest in innovation promotion policy, analysing allocation processes has been widely neglected in the mainstream literature. However, given the potential distortions which allocation processes can have it is worth addressing this issue in depth. This dissertation analyzes the allocation of R&D subsidies to firms theoretically and empirically using a unique data set from a special subsidy program from south-western Germany. Thereby this dissertation contributes to the growing literature on innovation promotion and is of interest for innovation research...
Robert Schober Wireless Information and Power Transfer. Theory and Practice Robert Schober Wireless Information and Power Transfer. Theory and Practice Новинка

Robert Schober Wireless Information and Power Transfer. Theory and Practice

12881.53 руб.
Wireless Information and Power Transfer offers an authoritative and comprehensive guide to the theory, models, techniques, implementation and application of wireless information and power transfer (WIPT) in energy-constrained wireless communication networks. With contributions from an international panel of experts, this important resource covers the various aspects of WIPT systems such as, system modeling, physical layer techniques, resource allocation and performance analysis. The contributors also explore targeted research problems typically encountered when designing WIPT systems.
Robert Schober Wireless Information and Power Transfer Robert Schober Wireless Information and Power Transfer Новинка

Robert Schober Wireless Information and Power Transfer

10734.61 руб.
Wireless Information and Power Transfer offers an authoritative and comprehensive guide to the theory, models, techniques, implementation and application of wireless information and power transfer (WIPT) in energy-constrained wireless communication networks. With contributions from an international panel of experts, this important resource covers the various aspects of WIPT systems such as, system modeling, physical layer techniques, resource allocation and performance analysis. The contributors also explore targeted research problems typically encountered when designing WIPT systems.
Distributed Algorithms, Distributed Algorithms, Новинка

Distributed Algorithms,

10804 руб.
Distributed Algorithms,
Bernd Scheuermann FPGA Task Arrangement with Genetic Algorithms Bernd Scheuermann FPGA Task Arrangement with Genetic Algorithms Новинка

Bernd Scheuermann FPGA Task Arrangement with Genetic Algorithms

4677 руб.
Inhaltsangabe:Abstract: Two evolutionary approaches of allocating tasks onto a Field-Programmable Gate Array (FPGA) are presented. Offline task arrangement: whenever a set of tasks has to be arranged onto an FPGA in practice, one is interested in arranging a maximum number of tasks which efficiently utilize the FPGA area. A genetic algorithm is proposed searching for an arrangement of tasks offline, i.e. before the tasks are physically placed onto the FPGA. Online task arrangement: FPGAs that allow partial reconfiguration at run-time can be shared among multiple independent tasks. When the sequence of tasks to be performed is unpredictable the FPGA controller needs to make allocation decisions online. Since online allocation suffers from fragmentation, tasks can end up waiting despite there being sufficient, albeit non-contiguous resources available to service them. The time to complete tasks is consequently longer and the utilization of the FPGA is lower than it could be. A genetic algorithm is proposed rearranging a subset of the tasks executing on the FPGA when doing so allows the next pending task to be processed sooner. In comparison with other heuristic approaches a genetic algorithm is described and evaluated which overcomes the NP-hard problems of identifying feasible rearrangements and scheduling the rearrangements when moving tasks are reloaded from off-chip. Inhaltsverzeichnis:Table of Contents: 1.Introduction7 2.Field Programmable Gate Arrays9 2.1Architecture of F...
D. Dwight Davis The Giant Panda. A Morphological Study of Evolutionary Mechanisms D. Dwight Davis The Giant Panda. A Morphological Study of Evolutionary Mechanisms Новинка

D. Dwight Davis The Giant Panda. A Morphological Study of Evolutionary Mechanisms

1814 руб.
This ground-breaking work of evolutionary morphology, with its dozens of detailed and beautiful anatomical drawings, will make fascinating reading for students of evolutionary biology and panda enthusiasts everywhere.
Karsten Wendt Multi-Objective Optimization utilizing Cluster Analysis applied to Dimensional Transposed Problems Karsten Wendt Multi-Objective Optimization utilizing Cluster Analysis applied to Dimensional Transposed Problems Новинка

Karsten Wendt Multi-Objective Optimization utilizing Cluster Analysis applied to Dimensional Transposed Problems

6102 руб.
With respect to the importance of multi-objective optimization in the context of the today's information processing and analysis, as well as the limitation of current approaches to treat large and complex tasks in practical time and little adjustment costs, this work proposes a novel optimization concept, based on data domain transformations and subsequent cluster analyses to solve multi-objective optimization problems. The approach abstracts the transposition of large, high-dimensional and diverse data models to low-dimensional uniform equivalents within an independent framework, which is optimized regarding data similarity conservation, i.e. the semantic relations of the data items to each other are preserved, and low runtime complexity, i.e. linearly increasing model sizes also cause only linearly growing run­times in spite of the consideration of all data relations. The cluster analysis step is represented by an enhanced version of the k-Means algorithm, which is designed to group large numbers of data items to large numbers of clusters with also linear time complexity. Applying and adapting these both components to generic segmentation and pattern recognition tasks as two representative multi-objective optimization problems, illustrate and prove the usability of the proposed concept, by solving these tasks with high qualities of results and low runtimes with virtually linear time complexities. The abstracted components, as well as their application extensions are tes...
Aaron Saunders Building Cross-Platform Apps using Titanium, Alloy, and Appcelerator Cloud Services Aaron Saunders Building Cross-Platform Apps using Titanium, Alloy, and Appcelerator Cloud Services Новинка

Aaron Saunders Building Cross-Platform Apps using Titanium, Alloy, and Appcelerator Cloud Services

3312.49 руб.
Skip Objective-C and Java to get your app to market faster, using the skills you already have Building Cross-Platform Apps using Titanium, Alloy, and Appcelerator Cloud Services shows you how to build cross-platform iOS and Android apps without learning Objective-C or Java. With detailed guidance given toward using the Titanium Mobile Platform and Appcelerator Cloud Services, you will quickly develop the skills to build real, native apps— not web apps—using existing HTML, CSS, and JavaScript know-how. This guide takes you step-by-step through the creation of a photo-sharing app that leverages the power of Appcelerator's cloud platform, and establishes fundamental concepts before adding advanced techniques. Coverage extends beyond the development process to include expert advice for deployment on the App Store or Google Play, and more. The mobile app market is estimated at over $2.4 billion per year. These apps were traditionally built using Objective-C or Java, which can be complex and daunting to learn. Now you can use JavaScript on the Titanium framework to build amazing apps that run native on iOS and Android devices, and get your app to market faster with this guide. Integrate Cloud Services APIs into the app framework and UI Set up user accounts, and capture and store photos Work with location-based services and share via social media Deploy on the App Store, Google Play, and more When a great idea is in the works, no one wants to put it on hold to learn an entirely new skillset. Now there's an alternative. Get that app to market fast, using existing skills and powerful new tools, and grab a piece of that multi-billion-dollar market. Building Cross-Platform Apps using Titanium, Alloy, and Appcelerator Cloud Services is your ticket to the front of the line.
Gregory Parnell S. Decision Making in Systems Engineering and Management Gregory Parnell S. Decision Making in Systems Engineering and Management Новинка

Gregory Parnell S. Decision Making in Systems Engineering and Management

11387.92 руб.
Decision Making in Systems Engineering and Management is a comprehensive textbook that provides a logical process and analytical techniques for fact-based decision making for the most challenging systems problems. Grounded in systems thinking and based on sound systems engineering principles, the systems decisions process (SDP) leverages multiple objective decision analysis, multiple attribute value theory, and value-focused thinking to define the problem, measure stakeholder value, design creative solutions, explore the decision trade off space in the presence of uncertainty, and structure successful solution implementation. In addition to classical systems engineering problems, this approach has been successfully applied to a wide range of challenges including personnel recruiting, retention, and management; strategic policy analysis; facilities design and management; resource allocation; information assurance; security systems design; and other settings whose structure can be conceptualized as a system.

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A detailed review of a wide range of meta-heuristic and evolutionary algorithms in a systematic manner and how they relate to engineering optimization problems This book introduces the main metaheuristic algorithms and their applications in optimization. It describes 20 leading meta-heuristic and evolutionary algorithms and presents discussions and assessments of their performance in solving optimization problems from several fields of engineering. The book features clear and concise principles and presents detailed descriptions of leading methods such as the pattern search (PS) algorithm, the genetic algorithm (GA), the simulated annealing (SA) algorithm, the Tabu search (TS) algorithm, the ant colony optimization (ACO), and the particle swarm optimization (PSO) technique. Chapter 1 of Meta-heuristic and Evolutionary Algorithms for Engineering Optimization provides an overview of optimization and defines it by presenting examples of optimization problems in different engineering domains. Chapter 2 presents an introduction to meta-heuristic and evolutionary algorithms and links them to engineering problems. Chapters 3 to 22 are each devoted to a separate algorithm— and they each start with a brief literature review of the development of the algorithm, and its applications to engineering problems. The principles, steps, and execution of the algorithms are described in detail, and a pseudo code of the algorithm is presented, which serves as a guideline for coding the algorithm to solve specific applications. This book: Introduces state-of-the-art metaheuristic algorithms and their applications to engineering optimization; Fills a gap in the current literature by compiling and explaining the various meta-heuristic and evolutionary algorithms in a clear and systematic manner; Provides a step-by-step presentation of each algorithm and guidelines for practical implementation and coding of algorithms; Discusses and assesses the performance of metaheuristic algorithms in multiple problems from many fields of engineering; Relates optimization algorithms to engineering problems employing a unifying approach. Meta-heuristic and Evolutionary Algorithms for Engineering Optimization is a reference intended for students, engineers, researchers, and instructors in the fields of industrial engineering, operations research, optimization/mathematics, engineering optimization, and computer science. OMID BOZORG-HADDAD, PhD, is Professor in the Department of Irrigation and Reclamation Engineering at the University of Tehran, Iran. MOHAMMAD SOLGI, M.Sc., is Teacher Assistant for M.Sc. courses at the University of Tehran, Iran. HUGO A. LOÁICIGA, PhD, is Professor in the Department of Geography at the University of California, Santa Barbara, United States of America.
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