Multi Objective Optimization In Theory And Practice Ii Metaheuristic Algorithms
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Multi Objective Optimization In Theory And Practice Ii
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Author : André A. Keller
language : en
Publisher:
Release Date : 2019
Multi Objective Optimization In Theory And Practice Ii written by André A. Keller and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Algorithms 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 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.
Metaheuristic Algorithms
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Author : Gai-Ge Wang
language : en
Publisher: CRC Press
Release Date : 2024-04-03
Metaheuristic Algorithms written by Gai-Ge Wang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-03 with Computers categories.
This book introduces the theory and applications of metaheuristic algorithms. It also provides methods for solving practical problems in such fields as software engineering, image recognition, video networks, and in the oceans. In the theoretical section, the book introduces the information feedback model, learning-based intelligent optimization, dynamic multi-objective optimization, and multi-model optimization. In the applications section, the book presents applications of optimization algorithms to neural architecture search, fuzz testing, oceans, and image processing. The neural architecture search chapter introduces the latest NAS method. The fuzz testing chapter uses multi-objective optimization and ant colony optimization to solve the seed selection and energy allocation problems in fuzz testing. In the ocean chapter, deep learning methods such as CNN, transformer, and attention-based methods are used to describe ENSO prediction and image processing for marine fish identification, and to provide an overview of traditional classification methods and deep learning methods. Rich in examples, this book will be a great resource for students, scholars, and those interested in metaheuristic algorithms, as well as professional practitioners and researchers working on related topics.
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
Metaheuristics For Dynamic Optimization
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Author : Enrique Alba
language : en
Publisher: Springer
Release Date : 2012-08-11
Metaheuristics For Dynamic Optimization written by Enrique Alba and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-11 with Technology & Engineering categories.
This book is an updated effort in summarizing the trending topics and new hot research lines in solving dynamic problems using metaheuristics. An analysis of the present state in solving complex problems quickly draws a clear picture: problems that change in time, having noise and uncertainties in their definition are becoming very important. The tools to face these problems are still to be built, since existing techniques are either slow or inefficient in tracking the many global optima that those problems are presenting to the solver technique. Thus, this book is devoted to include several of the most important advances in solving dynamic problems. Metaheuristics are the more popular tools to this end, and then we can find in the book how to best use genetic algorithms, particle swarm, ant colonies, immune systems, variable neighborhood search, and many other bioinspired techniques. Also, neural network solutions are considered in this book. Both, theory and practice have been addressed in the chapters of the book. Mathematical background and methodological tools in solving this new class of problems and applications are included. From the applications point of view, not just academic benchmarks are dealt with, but also real world applications in logistics and bioinformatics are discussed here. The book then covers theory and practice, as well as discrete versus continuous dynamic optimization, in the aim of creating a fresh and comprehensive volume. This book is targeted to either beginners and experienced practitioners in dynamic optimization, since we took care of devising the chapters in a way that a wide audience could profit from its contents. We hope to offer a single source for up-to-date information in dynamic optimization, an inspiring and attractive new research domain that appeared in these last years and is here to stay.
Discrete Diversity And Dispersion Maximization
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Author : Rafael Martí
language : en
Publisher: Springer Nature
Release Date : 2024-01-06
Discrete Diversity And Dispersion Maximization written by Rafael Martí and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-06 with Mathematics categories.
This book demonstrates the metaheuristic methodologies that apply to maximum diversity problems to solve them. Maximum diversity problems arise in many practical settings from facility location to social network analysis and constitute an important class of NP-hard problems in combinatorial optimization. In fact, this volume presents a “missing link” in the combinatorial optimization-related literature. In providing the basic principles and fundamental ideas of the most successful methodologies for discrete optimization, this book allows readers to create their own applications for other discrete optimization problems. Additionally, the book is designed to be useful and accessible to researchers and practitioners in management science, industrial engineering, economics, and computer science, while also extending value to non-experts in combinatorial optimization. Owed to the tutorials presented in each chapter, this book may be used in a master course, a doctoral seminar, or as supplementary to a primary text in upper undergraduate courses. The chapters are divided into three main sections. The first section describes a metaheuristic methodology in a tutorial style, offering generic descriptions that, when applied, create an implementation of the methodology for any optimization problem. The second section presents the customization of the methodology to a given diversity problem, showing how to go from theory to application in creating a heuristic. The final part of the chapters is devoted to experimentation, describing the results obtained with the heuristic when solving the diversity problem. Experiments in the book target the so-called MDPLIB set of instances as a benchmark to evaluate the performance of the methods.
Multi Objective Optimization In Computational Intelligence Theory And Practice
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Author : Thu Bui, Lam
language : en
Publisher: IGI Global
Release Date : 2008-05-31
Multi Objective Optimization In Computational Intelligence Theory And Practice written by Thu Bui, Lam and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-31 with Technology & Engineering categories.
Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.
Handbook Of Nature Inspired Optimization Algorithms The State Of The Art
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Author : Ali Wagdy Mohamed
language : en
Publisher: Springer Nature
Release Date : 2022-09-03
Handbook Of Nature Inspired Optimization Algorithms The State Of The Art written by Ali Wagdy Mohamed and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-03 with Technology & Engineering categories.
This book presents recent contributions and significant development, advanced issues, and challenges. In real-world problems and applications, most of the optimization problems involve different types of constraints. These problems are called constrained optimization problems (COPs). The optimization of the constrained optimization problems is considered a challenging task since the optimum solution(s) must be feasible. In their original design, evolutionary algorithms (EAs) are able to solve unconstrained optimization problems effectively. As a result, in the past decade, many researchers have developed a variety of constraint handling techniques, incorporated into (EAs) designs, to counter this deficiency. The main objective for this book is to make available a self-contained collection of modern research addressing the general constrained optimization problems in many real-world applications using nature-inspired optimization algorithms. This book is suitable for a graduate class on optimization, but will also be useful for interested senior students working on their research projects.
Multi Objective Optimization In Computer Networks Using Metaheuristics
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Author : Yezid Donoso
language : en
Publisher: CRC Press
Release Date : 2016-04-19
Multi Objective Optimization In Computer Networks Using Metaheuristics written by Yezid Donoso and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Computers categories.
Metaheuristics are widely used to solve important practical combinatorial optimization problems. Many new multicast applications emerging from the Internet-such as TV over the Internet, radio over the Internet, and multipoint video streaming-require reduced bandwidth consumption, end-to-end delay, and packet loss ratio. It is necessary to design an