Trends In Developing Metaheuristics Algorithms And Optimization Approaches
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Trends In Developing Metaheuristics Algorithms And Optimization Approaches
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Author : Yin, Peng-Yeng
language : en
Publisher: IGI Global
Release Date : 2012-10-31
Trends In Developing Metaheuristics Algorithms And Optimization Approaches written by Yin, Peng-Yeng and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-31 with Computers categories.
Developments in metaheuristics continue to advance computation beyond its traditional methods. With groundwork built on multidisciplinary research findings; metaheuristics, algorithms, and optimization approaches uses memory manipulations in order to take full advantage of strategic level problem solving. Trends in Developing Metaheuristics, Algorithms, and Optimization Approaches provides insight on the latest advances and analysis of technologies in metaheuristics computing. Offering widespread coverage on topics such as genetic algorithms, differential evolution, and ant colony optimization, this book aims to be a forum researchers, practitioners, and students who wish to learn and apply metaheuristic computing.
Metaheuristics For Finding Multiple Solutions
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Author : Mike Preuss
language : en
Publisher: Springer Nature
Release Date : 2021-10-22
Metaheuristics For Finding Multiple Solutions written by Mike Preuss and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-22 with Computers categories.
This book presents the latest trends and developments in multimodal optimization and niching techniques. Most existing optimization methods are designed for locating a single global solution. However, in real-world settings, many problems are “multimodal” by nature, i.e., multiple satisfactory solutions exist. It may be desirable to locate several such solutions before deciding which one to use. Multimodal optimization has been the subject of intense study in the field of population-based meta-heuristic algorithms, e.g., evolutionary algorithms (EAs), for the past few decades. These multimodal optimization techniques are commonly referred to as “niching” methods, because of the nature-inspired “niching” effect that is induced to the solution population targeting at multiple optima. Many niching methods have been developed in the EA community. Some classic examples include crowding, fitness sharing, clearing, derating, restricted tournament selection, speciation, etc. Nevertheless, applying these niching methods to real-world multimodal problems often encounters significant challenges. To facilitate the advance of niching methods in facing these challenges, this edited book highlights the latest developments in niching methods. The included chapters touch on algorithmic improvements and developments, representation, and visualization issues, as well as new research directions, such as preference incorporation in decision making and new application areas. This edited book is a first of this kind specifically on the topic of niching techniques. This book will serve as a valuable reference book both for researchers and practitioners. Although chapters are written in a mutually independent way, Chapter 1 will help novice readers get an overview of the field. It describes the development of the field and its current state and provides a comparative analysis of the IEEE CEC and ACM GECCO niching competitions of recent years, followed by a collection of open research questions and possible research directions that may be tackled in the future.
Recent Developments In Metaheuristics
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Author : Lionel Amodeo
language : en
Publisher: Springer
Release Date : 2017-09-18
Recent Developments In Metaheuristics written by Lionel Amodeo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-18 with Business & Economics categories.
This book highlights state-of-the-art developments in metaheuristics research. It examines all aspects of metaheuristic research including new algorithmic developments, applications, new research challenges, theoretical developments, implementation issues, in-depth experimental studies. The book is divided into two sections. Part I is focused on new optimization and modeling techniques based on metaheuristics. The chapters in this section cover topics from multi-objective problems with fuzzy data with triangular-valued objective functions, to hyper-heuristics optimization methodology, designing genetic algorithms, and also the cuckoo search algorithm. The techniques described help to enhance the usability and increase the potential of metaheuristic algorithms. Part II showcases advanced metaheuristic approaches to solve real-life applications issues. This includes an examination of scheduling, the vehicle routing problem, multimedia sensor network, supplier selection, bin packing, objects tracking, and radio frequency identification. In the fields covered in the chapters are of high-impact applications of metaheuristics. The chapters offer innovative applications of metaheuristics that have a potential of widening research frontiers. Altogether, this book offers a comprehensive look at how researchers are currently using metaheuristics in different domains of design and application.
Advances In Metaheuristics For Hard Optimization
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Author : Patrick Siarry
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-12-06
Advances In Metaheuristics For Hard Optimization written by Patrick Siarry 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 2007-12-06 with Mathematics categories.
Many advances have recently been made in metaheuristic methods, from theory to applications. The editors, both leading experts in this field, have assembled a team of researchers to contribute 21 chapters organized into parts on simulated annealing, tabu search, ant colony algorithms, general purpose studies of evolutionary algorithms, applications of evolutionary algorithms, and metaheuristics.
Advances In Metaheuristics Algorithms Methods And Applications
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Author : Erik Cuevas
language : en
Publisher: Springer
Release Date : 2018-04-10
Advances In Metaheuristics Algorithms Methods And Applications written by Erik Cuevas and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-10 with Technology & Engineering categories.
This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems. Though most of the new metaheuristic algorithms considered offer promising results, they are nevertheless still in their infancy. To grow and attain their full potential, new metaheuristic methods must be applied in a great variety of problems and contexts, so that they not only perform well in their reported sets of optimization problems, but also in new complex formulations. The only way to accomplish this is to disseminate these methods in various technical areas as optimization tools. In general, once a scientist, engineer or practitioner recognizes a problem as a particular instance of a more generic class, he/she can select one of several metaheuristic algorithms that guarantee an expected optimization performance. Unfortunately, the set of options are concentrated on algorithms whose popularity and high proliferation outstrip those of the new developments. This structure is important, because the authors recognize this methodology as the best way to help researchers, lecturers, engineers and practitioners solve their own optimization problems.
Meta Heuristics
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Author : Stefan Voß
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Meta Heuristics written by Stefan Voß 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 2012-12-06 with Business & Economics categories.
Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimizations comprises a carefully refereed selection of extended versions of the best papers presented at the Second Meta-Heuristics Conference (MIC 97). The selected articles describe the most recent developments in theory and applications of meta-heuristics, heuristics for specific problems, and comparative case studies. The book is divided into six parts, grouped mainly by the techniques considered. The extensive first part with twelve papers covers tabu search and its application to a great variety of well-known combinatorial optimization problems (including the resource-constrained project scheduling problem and vehicle routing problems). In the second part we find one paper where tabu search and simulated annealing are investigated comparatively and two papers which consider hybrid methods combining tabu search with genetic algorithms. The third part has four papers on genetic and evolutionary algorithms. Part four arrives at a new paradigm within meta-heuristics. The fifth part studies the behavior of parallel local search algorithms mainly from a tabu search perspective. The final part examines a great variety of additional meta-heuristics topics, including neural networks and variable neighbourhood search as well as guided local search. Furthermore, the integration of meta-heuristics with the branch-and-bound paradigm is investigated.
Handbook Of Research On Modern Optimization Algorithms And Applications In Engineering And Economics
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Author : Vasant, Pandian
language : en
Publisher: IGI Global
Release Date : 2016-03-08
Handbook Of Research On Modern Optimization Algorithms And Applications In Engineering And Economics written by Vasant, Pandian and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-08 with Mathematics categories.
Modern optimization approaches have attracted many research scientists, decision makers and practicing researchers in recent years as powerful intelligent computational techniques for solving several complex real-world problems. The Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics highlights the latest research innovations and applications of algorithms designed for optimization applications within the fields of engineering, IT, and economics. Focusing on a variety of methods and systems as well as practical examples, this book is a significant resource for graduate-level students, decision makers, and researchers in both public and private sectors who are seeking research-based methods for modeling uncertain real-world problems. .
Meta Heuristics Optimization Algorithms In Engineering Business Economics And Finance
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Author : Vasant, Pandian M.
language : en
Publisher: IGI Global
Release Date : 2012-09-30
Meta Heuristics Optimization Algorithms In Engineering Business Economics And Finance written by Vasant, Pandian M. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-30 with Computers categories.
Optimization techniques have developed into a significant area concerning industrial, economics, business, and financial systems. With the development of engineering and financial systems, modern optimization has played an important role in service-centered operations and as such has attracted more attention to this field. Meta-heuristic hybrid optimization is a newly development mathematical framework based optimization technique. Designed by logicians, engineers, analysts, and many more, this technique aims to study the complexity of algorithms and problems. Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance explores the emerging study of meta-heuristics optimization algorithms and methods and their role in innovated real world practical applications. This book is a collection of research on the areas of meta-heuristics optimization algorithms in engineering, business, economics, and finance and aims to be a comprehensive reference for decision makers, managers, engineers, researchers, scientists, financiers, and economists as well as industrialists.
Experimental Methods For The Analysis Of Optimization Algorithms
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Author : Thomas Bartz-Beielstein
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-11-02
Experimental Methods For The Analysis Of Optimization Algorithms written by Thomas Bartz-Beielstein 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 2010-11-02 with Computers categories.
In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However, computational experiments differ from those in other sciences, and the last decade has seen considerable methodological research devoted to understanding the particular features of such experiments and assessing the related statistical methods. This book consists of methodological contributions on different scenarios of experimental analysis. The first part overviews the main issues in the experimental analysis of algorithms, and discusses the experimental cycle of algorithm development; the second part treats the characterization by means of statistical distributions of algorithm performance in terms of solution quality, runtime and other measures; and the third part collects advanced methods from experimental design for configuring and tuning algorithms on a specific class of instances with the goal of using the least amount of experimentation. The contributor list includes leading scientists in algorithm design, statistical design, optimization and heuristics, and most chapters provide theoretical background and are enriched with case studies. This book is written for researchers and practitioners in operations research and computer science who wish to improve the experimental assessment of optimization algorithms and, consequently, their design.
Optimization Using Evolutionary Algorithms And Metaheuristics
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Author : Kaushik Kumar
language : en
Publisher: CRC Press
Release Date : 2019-08-22
Optimization Using Evolutionary Algorithms And Metaheuristics written by Kaushik Kumar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-22 with Technology & Engineering categories.
Metaheuristic optimization is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem, especially with incomplete or imperfect information or limited computation capacity. This is usually applied when two or more objectives are to be optimized simultaneously. This book is presented with two major objectives. Firstly, it features chapters by eminent researchers in the field providing the readers about the current status of the subject. Secondly, algorithm-based optimization or advanced optimization techniques, which are applied to mostly non-engineering problems, are applied to engineering problems. This book will also serve as an aid to both research and industry. Usage of these methodologies would enable the improvement in engineering and manufacturing technology and support an organization in this era of low product life cycle. Features: Covers the application of recent and new algorithms Focuses on the development aspects such as including surrogate modeling, parallelization, game theory, and hybridization Presents the advances of engineering applications for both single-objective and multi-objective optimization problems Offers recent developments from a variety of engineering fields Discusses Optimization using Evolutionary Algorithms and Metaheuristics applications in engineering