Multi Objective Optimization Problems
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Evolutionary Algorithms For Solving Multi Objective Problems
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Author : Carlos Coello Coello
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-09-18
Evolutionary Algorithms For Solving Multi Objective Problems written by Carlos Coello Coello and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-18 with Computers categories.
This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems. It contains exhaustive appendices, index and bibliography and links to a complete set of teaching tutorials, exercises and solutions.
Multi Objective Combinatorial Optimization Problems And Solution Methods
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Author : Mehdi Toloo
language : en
Publisher: Academic Press
Release Date : 2022-02-09
Multi Objective Combinatorial Optimization Problems And Solution Methods written by Mehdi Toloo and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-09 with Science categories.
Multi-Objective Combinatorial Optimization Problems and Solution Methods discusses the results of a recent multi-objective combinatorial optimization achievement that considered metaheuristic, mathematical programming, heuristic, hyper heuristic and hybrid approaches. In other words, the book presents various multi-objective combinatorial optimization issues that may benefit from different methods in theory and practice. Combinatorial optimization problems appear in a wide range of applications in operations research, engineering, biological sciences and computer science, hence many optimization approaches have been developed that link the discrete universe to the continuous universe through geometric, analytic and algebraic techniques. This book covers this important topic as computational optimization has become increasingly popular as design optimization and its applications in engineering and industry have become ever more important due to more stringent design requirements in modern engineering practice. - Presents a collection of the most up-to-date research, providing a complete overview of multi-objective combinatorial optimization problems and applications - Introduces new approaches to handle different engineering and science problems, providing the field with a collection of related research not already covered in the primary literature - Demonstrates the efficiency and power of the various algorithms, problems and solutions, including numerous examples that illustrate concepts and algorithms
Evolutionary Multi Objective Optimization In Uncertain Environments
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Author : Chi-Keong Goh
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-03-09
Evolutionary Multi Objective Optimization In Uncertain Environments written by Chi-Keong Goh and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-03-09 with Computers categories.
Evolutionary algorithms are sophisticated search methods that have been found to be very efficient and effective in solving complex real-world multi-objective problems where conventional optimization tools fail to work well. Despite the tremendous amount of work done in the development of these algorithms in the past decade, many researchers assume that the optimization problems are deterministic and uncertainties are rarely examined. The primary motivation of this book is to provide a comprehensive introduction on the design and application of evolutionary algorithms for multi-objective optimization in the presence of uncertainties. In this book, we hope to expose the readers to a range of optimization issues and concepts, and to encourage a greater degree of appreciation of evolutionary computation techniques and the exploration of new ideas that can better handle uncertainties. "Evolutionary Multi-Objective Optimization in Uncertain Environments: Issues and Algorithms" is intended for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of evolutionary multi-objective optimization and uncertainties.
Multi Objective Optimization Using Evolutionary Algorithms
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Author : Kalyanmoy Deb
language : en
Publisher: John Wiley & Sons
Release Date : 2001-07-05
Multi Objective Optimization Using Evolutionary Algorithms written by Kalyanmoy Deb and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-07-05 with Mathematics categories.
Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many real-world search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run. Comprehensive coverage of this growing area of research Carefully introduces each algorithm with examples and in-depth discussion Includes many applications to real-world problems, including engineering design and scheduling Includes discussion of advanced topics and future research Can be used as a course text or for self-study Accessible to those with limited knowledge of classical multi-objective optimization and evolutionary algorithms The integrated presentation of theory, algorithms and examples will benefit those working and researching in the areas of optimization, optimal design and evolutionary computing. This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.
Non Convex Multi Objective Optimization
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Author : Panos M. Pardalos
language : en
Publisher: Springer
Release Date : 2017-07-27
Non Convex Multi Objective Optimization written by Panos M. Pardalos and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-27 with Mathematics categories.
Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions. Multi-objective optimization methods facilitate designers, engineers, and researchers to make decisions on appropriate trade-offs between various conflicting goals. A variety of deterministic and stochastic multi-objective optimization methods are developed in this book. Beginning with basic concepts and a review of non-convex single-objective optimization problems; this book moves on to cover multi-objective branch and bound algorithms, worst-case optimal algorithms (for Lipschitz functions and bi-objective problems), statistical models based algorithms, and probabilistic branch and bound approach. Detailed descriptions of new algorithms for non-convex multi-objective optimization, their theoretical substantiation, and examples for practical applications to the cell formation problem in manufacturing engineering, the process design in chemical engineering, and business process management are included to aide researchers and graduate students in mathematics, computer science, engineering, economics, and business management.
Multi Objective Optimization Problems
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Author : Fran Sérgio Lobato
language : en
Publisher: Springer
Release Date : 2017-07-03
Multi Objective Optimization Problems written by Fran Sérgio Lobato and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-03 with Mathematics categories.
This book is aimed at undergraduate and graduate students in applied mathematics or computer science, as a tool for solving real-world design problems. The present work covers fundamentals in multi-objective optimization and applications in mathematical and engineering system design using a new optimization strategy, namely the Self-Adaptive Multi-objective Optimization Differential Evolution (SA-MODE) algorithm. This strategy is proposed in order to reduce the number of evaluations of the objective function through dynamic update of canonical Differential Evolution parameters (population size, crossover probability and perturbation rate). The methodology is applied to solve mathematical functions considering test cases from the literature and various engineering systems design, such as cantilevered beam design, biochemical reactor, crystallization process, machine tool spindle design, rotary dryer design, among others.
Multi Objective Optimization In Theory And Practice Ii Metaheuristic Algorithms
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Author : André A. Keller
language : en
Publisher: Bentham Science Publishers
Release Date : 2019-03-28
Multi Objective Optimization In Theory And Practice Ii Metaheuristic Algorithms written by André A. Keller and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-28 with Mathematics categories.
Multi-Objective Optimization in Theory and Practice is a simplified two-part approach to multi-objective optimization (MOO) problems. This second part focuses on the use of metaheuristic algorithms in more challenging practical cases. The book includes ten chapters that cover several advanced MOO techniques. These include the determination of Pareto-optimal sets of solutions, metaheuristic algorithms, genetic search algorithms and evolution strategies, decomposition algorithms, hybridization of different metaheuristics, and many-objective (more than three objectives) optimization and parallel computation. The final section of the book presents information about the design and types of fifty test problems for which the Pareto-optimal front is approximated. For each of them, the package NSGA-II is used to approximate the Pareto-optimal front. It is an essential handbook for students and teachers involved in advanced optimization courses in engineering, information science and mathematics degree programs.
Multi Objective Optimization In Theory And Practice I Classical Methods
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Author : Andre A. Keller
language : en
Publisher: Bentham Science Publishers
Release Date : 2017-12-13
Multi Objective Optimization In Theory And Practice I Classical Methods written by Andre A. Keller and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-13 with Technology & Engineering categories.
Multi-Objective Optimization in Theory and Practice is a traditional two-part approach to solving multi-objective optimization (MOO) problems namely the use of classical methods and evolutionary algorithms. This first book is devoted to classical methods including the extended simplex method by Zeleny and preference-based techniques. This part covers three main topics through nine chapters. The first topic focuses on the design of such MOO problems, their complexities including nonlinearities and uncertainties, and optimality theory. The second topic introduces the founding solving methods including the extended simplex method to linear MOO problems and weighting objective methods. The third topic deals with particular structures of MOO problems, such as mixed-integer programming, hierarchical programming, fuzzy logic programming, and bimatrix games. Multi-Objective Optimization in Theory and Practice is a user-friendly book with detailed, illustrated calculations, examples, test functions, and small-size applications in Mathematica® (among other mathematical packages) and from scholarly literature. It is an essential handbook for students and teachers involved in advanced optimization courses in engineering, information science, and mathematics degree programs.
Solving Multi Objective Optimization Problems Through Unified Approach
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Author : H.A.Khalifa
language : en
Publisher: Infinite Study
Release Date :
Solving Multi Objective Optimization Problems Through Unified Approach written by H.A.Khalifa and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
In this paper, unified approach for solving multi- objective optimization problem is introduced. The approach is based on the Reference Direction (RD) method introduced by Narula et al. [14], and the Attainable Reference Point (ARP) method introduced by Wang et al. [19]. This approach improves the performance of the ARP method by using the initial weak efficient solution of the RD method that is to improve the weights in the Lexicographic weighted Techebycheff program. The weights in the unified approach are constructed through the ARP and the weak efficient solution. A numerical example is given in the sake of the paper to clarify the obtained results.
Multi Objective Optimization
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Author : Jyotsna K. Mandal
language : en
Publisher: Springer
Release Date : 2018-08-18
Multi Objective Optimization written by Jyotsna K. Mandal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-18 with Computers categories.
This book brings together the latest findings on efficient solutions of multi/many-objective optimization problems from the leading researchers in the field. The focus is on solving real-world optimization problems using strategies ranging from evolutionary to hybrid frameworks, and involving various computation platforms. The topics covered include solution frameworks using evolutionary to hybrid models in application areas like Analytics, Cancer Research, Traffic Management, Networks and Communications, E-Governance, Quantum Technology, Image Processing, etc. As such, the book offers a valuable resource for all postgraduate students and researchers interested in exploring solution frameworks for multi/many-objective optimization problems.