Search And Optimization By Metaheuristics

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Search and Optimization by Metaheuristics

Ke-Lin Du,M. N. S. Swamy
Search and Optimization by Metaheuristics Book PDF

Author : Ke-Lin Du,M. N. S. Swamy
Publisher : Birkhäuser
Page : 434 pages
File Size : 43,8 Mb
Release : 2016-07-20
Category : Computers
ISBN : 9783319411927

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Search and Optimization by Metaheuristics by Ke-Lin Du,M. N. S. Swamy Pdf

This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones. An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material. Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computing, quantum computing, and many others. General topics on dynamic, multimodal, constrained, and multiobjective optimizations are also described. Each chapter includes detailed flowcharts that illustrate specific algorithms and exercises that reinforce important topics. Introduced in the appendix are some benchmarks for the evaluation of metaheuristics. Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science. It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are interested in search and optimization methods.

Meta-Heuristics

Stefan Voß,Silvano Martello,Ibrahim H. Osman,Cathérine Roucairol
Meta Heuristics Book PDF

Author : Stefan Voß,Silvano Martello,Ibrahim H. Osman,Cathérine Roucairol
Publisher : Springer Science & Business Media
Page : 513 pages
File Size : 46,5 Mb
Release : 2012-12-06
Category : Business & Economics
ISBN : 9781461557753

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Meta-Heuristics by Stefan Voß,Silvano Martello,Ibrahim H. Osman,Cathérine Roucairol Pdf

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 Metaheuristics

Michel Gendreau,Jean-Yves Potvin
Handbook of Metaheuristics Book PDF

Author : Michel Gendreau,Jean-Yves Potvin
Publisher : Springer
Page : 611 pages
File Size : 47,5 Mb
Release : 2018-09-20
Category : Business & Economics
ISBN : 9783319910864

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Handbook of Metaheuristics by Michel Gendreau,Jean-Yves Potvin Pdf

The third edition of this handbook is designed to provide a broad coverage of the concepts, implementations, and applications in metaheuristics. The book’s chapters serve as stand-alone presentations giving both the necessary underpinnings as well as practical guides for implementation. The nature of metaheuristics invites an analyst to modify basic methods in response to problem characteristics, past experiences, and personal preferences, and the chapters in this handbook are designed to facilitate this process as well. This new edition has been fully revised and features new chapters on swarm intelligence and automated design of metaheuristics from flexible algorithm frameworks. The authors who have contributed to this volume represent leading figures from the metaheuristic community and are responsible for pioneering contributions to the fields they write about. Their collective work has significantly enriched the field of optimization in general and combinatorial optimization in particular.Metaheuristics are solution methods that orchestrate an interaction between local improvement procedures and higher level strategies to create a process capable of escaping from local optima and performing a robust search of a solution space. In addition, many new and exciting developments and extensions have been observed in the last few years. Hybrids of metaheuristics with other optimization techniques, like branch-and-bound, mathematical programming or constraint programming are also increasingly popular. On the front of applications, metaheuristics are now used to find high-quality solutions to an ever-growing number of complex, ill-defined real-world problems, in particular combinatorial ones. This handbook should continue to be a great reference for researchers, graduate students, as well as practitioners interested in metaheuristics.

Metaheuristics

Karl F. Doerner,Michel Gendreau,Peter Greistorfer,Walter Gutjahr,Richard F. Hartl,Marc Reimann
Metaheuristics Book PDF

Author : Karl F. Doerner,Michel Gendreau,Peter Greistorfer,Walter Gutjahr,Richard F. Hartl,Marc Reimann
Publisher : Springer Science & Business Media
Page : 409 pages
File Size : 45,9 Mb
Release : 2007-08-13
Category : Mathematics
ISBN : 9780387719214

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Metaheuristics by Karl F. Doerner,Michel Gendreau,Peter Greistorfer,Walter Gutjahr,Richard F. Hartl,Marc Reimann Pdf

This book’s aim is to provide several different kinds of information: a delineation of general metaheuristics methods, a number of state-of-the-art articles from a variety of well-known classical application areas as well as an outlook to modern computational methods in promising new areas. Therefore, this book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field.

Metaheuristic Search Concepts

Günther Zäpfel,Roland Braune,Michael Bögl
Metaheuristic Search Concepts Book PDF

Author : Günther Zäpfel,Roland Braune,Michael Bögl
Publisher : Springer Science & Business Media
Page : 316 pages
File Size : 43,6 Mb
Release : 2010-03-10
Category : Business & Economics
ISBN : 9783642113437

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Metaheuristic Search Concepts by Günther Zäpfel,Roland Braune,Michael Bögl Pdf

In many decision problems, e.g. from the area of production and logistics manage ment, the evaluation of alternatives and the determination of an optimal or at least suboptimal solution is an important but dif?cult task. For most such problems no ef?cient algorithm is known and classical approaches of Operations Research like Mixed Integer Linear Programming or Dynamic Pro gramming are often of limited use due to excessive computation time. Therefore, dedicated heuristic solution approaches have been developed which aim at providing good solutions in reasonable time for a given problem. However, such methods have two major drawbacks: First, they are tailored to a speci?c prob lem and their adaption to other problems is dif?cult and in many cases even impos sible. Second, they are typically designed to “build” one single solution in the most effective way, whereas most decision problems have a vast number of feasible solu tions. Hence usually the chances are high that there exist better ones. To overcome these limitations, problem independent search strategies, in particular metaheuris tics, have been proposed. This book provides an elementary step by step introduction to metaheuristics focusing on the search concepts they are based on. The ?rst part demonstrates un derlying concepts of search strategies using a simple example optimization problem.

An Introduction to Metaheuristics for Optimization

Bastien Chopard,Marco Tomassini
An Introduction to Metaheuristics for Optimization Book PDF

Author : Bastien Chopard,Marco Tomassini
Publisher : Springer
Page : 226 pages
File Size : 48,7 Mb
Release : 2018-11-02
Category : Computers
ISBN : 9783319930732

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An Introduction to Metaheuristics for Optimization by Bastien Chopard,Marco Tomassini Pdf

The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational concepts among the key methodologies. This textbook is a suitable introduction for undergraduate and graduate students, researchers, and professionals in computer science, engineering, and logistics.

Metaheuristics for Hard Optimization

Johann Dréo,Alain Pétrowski,Patrick Siarry,Eric Taillard
Metaheuristics for Hard Optimization Book PDF

Author : Johann Dréo,Alain Pétrowski,Patrick Siarry,Eric Taillard
Publisher : Springer Science & Business Media
Page : 372 pages
File Size : 51,8 Mb
Release : 2006-01-16
Category : Mathematics
ISBN : 9783540309666

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Metaheuristics for Hard Optimization by Johann Dréo,Alain Pétrowski,Patrick Siarry,Eric Taillard Pdf

Contains case studies from engineering and operations research Includes commented literature for each chapter

Metaheuristic Optimization via Memory and Evolution

Cesar Rego,Bahram Alidaee
Metaheuristic Optimization via Memory and Evolution Book PDF

Author : Cesar Rego,Bahram Alidaee
Publisher : Springer Science & Business Media
Page : 472 pages
File Size : 53,8 Mb
Release : 2006-03-30
Category : Business & Economics
ISBN : 9780387236674

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Metaheuristic Optimization via Memory and Evolution by Cesar Rego,Bahram Alidaee Pdf

Tabu Search (TS) and, more recently, Scatter Search (SS) have proved highly effective in solving a wide range of optimization problems, and have had a variety of applications in industry, science, and government. The goal of Metaheuristic Optimization via Memory and Evolution: Tabu Search and Scatter Search is to report original research on algorithms and applications of tabu search, scatter search or both, as well as variations and extensions having "adaptive memory programming" as a primary focus. Individual chapters identify useful new implementations or new ways to integrate and apply the principles of TS and SS, or that prove new theoretical results, or describe the successful application of these methods to real world problems.

Essays and Surveys in Metaheuristics

Celso C. Ribeiro,Pierre Hansen
Essays and Surveys in Metaheuristics Book PDF

Author : Celso C. Ribeiro,Pierre Hansen
Publisher : Springer Science & Business Media
Page : 647 pages
File Size : 51,5 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461515074

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Essays and Surveys in Metaheuristics by Celso C. Ribeiro,Pierre Hansen Pdf

Finding exact solutions to many combinatorial optimization problems in busi ness, engineering, and science still poses a real challenge, despite the impact of recent advances in mathematical programming and computer technology. New fields of applications, such as computational biology, electronic commerce, and supply chain management, bring new challenges and needs for algorithms and optimization techniques. Metaheuristics are master procedures that guide and modify the operations of subordinate heuristics, to produce improved approx imate solutions to hard optimization problems with respect to more simple algorithms. They also provide fast and robust tools, producing high-quality solutions in reasonable computation times. The field of metaheuristics has been fast evolving in recent years. Tech niques such as simulated annealing, tabu search, genetic algorithms, scatter search, greedy randomized adaptive search, variable neighborhood search, ant systems, and their hybrids are currently among the most efficient and robust optimization strategies to find high-quality solutions to many real-life optimiza tion problems. A very large nmnber of successful applications of metaheuristics are reported in the literature and spread throughout many books, journals, and conference proceedings. A series of international conferences entirely devoted to the theory, applications, and computational developments in metaheuristics has been attracting an increasing number of participants, from universities and the industry.

Metaheuristics and Optimization in Computer and Electrical Engineering

Navid Razmjooy,Mohsen Ashourian,Zahra Foroozandeh
Metaheuristics and Optimization in Computer and Electrical Engineering Book PDF

Author : Navid Razmjooy,Mohsen Ashourian,Zahra Foroozandeh
Publisher : Springer Nature
Page : 311 pages
File Size : 44,8 Mb
Release : 2020-11-16
Category : Technology & Engineering
ISBN : 9783030566890

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Metaheuristics and Optimization in Computer and Electrical Engineering by Navid Razmjooy,Mohsen Ashourian,Zahra Foroozandeh Pdf

The use of artificial intelligence, especially in the field of optimization is increasing day by day. The purpose of this book is to explore the possibility of using different kinds of optimization algorithms to advance and enhance the tools used for computer and electrical engineering purposes.

Metaheuristics

Mauricio G.C. Resende,J. Pinho de Sousa
Metaheuristics Book PDF

Author : Mauricio G.C. Resende,J. Pinho de Sousa
Publisher : Springer Science & Business Media
Page : 744 pages
File Size : 44,6 Mb
Release : 2003-11-30
Category : Computers
ISBN : 1402076533

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Metaheuristics by Mauricio G.C. Resende,J. Pinho de Sousa Pdf

Combinatorial optimization is the process of finding the best, or optimal, so lution for problems with a discrete set of feasible solutions. Applications arise in numerous settings involving operations management and logistics, such as routing, scheduling, packing, inventory and production management, lo cation, logic, and assignment of resources. The economic impact of combi natorial optimization is profound, affecting sectors as diverse as transporta tion (airlines, trucking, rail, and shipping), forestry, manufacturing, logistics, aerospace, energy (electrical power, petroleum, and natural gas), telecommu nications, biotechnology, financial services, and agriculture. While much progress has been made in finding exact (provably optimal) so lutions to some combinatorial optimization problems, using techniques such as dynamic programming, cutting planes, and branch and cut methods, many hard combinatorial problems are still not solved exactly and require good heuristic methods. Moreover, reaching "optimal solutions" is in many cases meaningless, as in practice we are often dealing with models that are rough simplifications of reality. The aim of heuristic methods for combinatorial op timization is to quickly produce good-quality solutions, without necessarily providing any guarantee of solution quality. Metaheuristics are high level procedures that coordinate simple heuristics, such as local search, to find solu tions that are of better quality than those found by the simple heuristics alone: Modem metaheuristics include simulated annealing, genetic algorithms, tabu search, GRASP, scatter search, ant colony optimization, variable neighborhood search, and their hybrids.

Essentials of Metaheuristics (Second Edition)

Sean Luke
Essentials of Metaheuristics Second Edition Book PDF

Author : Sean Luke
Publisher : Unknown
Page : 242 pages
File Size : 41,7 Mb
Release : 2012-12-20
Category : Algorithms
ISBN : 1300549629

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Essentials of Metaheuristics (Second Edition) by Sean Luke Pdf

Interested in the Genetic Algorithm? Simulated Annealing? Ant Colony Optimization? Essentials of Metaheuristics covers these and other metaheuristics algorithms, and is intended for undergraduate students, programmers, and non-experts. The book covers a wide range of algorithms, representations, selection and modification operators, and related topics, and includes 71 figures and 135 algorithms great and small. Algorithms include: Gradient Ascent techniques, Hill-Climbing variants, Simulated Annealing, Tabu Search variants, Iterated Local Search, Evolution Strategies, the Genetic Algorithm, the Steady-State Genetic Algorithm, Differential Evolution, Particle Swarm Optimization, Genetic Programming variants, One- and Two-Population Competitive Coevolution, N-Population Cooperative Coevolution, Implicit Fitness Sharing, Deterministic Crowding, NSGA-II, SPEA2, GRASP, Ant Colony Optimization variants, Guided Local Search, LEM, PBIL, UMDA, cGA, BOA, SAMUEL, ZCS, XCS, and XCSF.

Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications

Modestus O. Okwu,Lagouge K. Tartibu
Metaheuristic Optimization Nature Inspired Algorithms Swarm and Computational Intelligence Theory and Applications Book PDF

Author : Modestus O. Okwu,Lagouge K. Tartibu
Publisher : Springer Nature
Page : 192 pages
File Size : 49,9 Mb
Release : 2020-11-13
Category : Technology & Engineering
ISBN : 9783030611118

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Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications by Modestus O. Okwu,Lagouge K. Tartibu Pdf

This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examples included in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.

Meta-heuristic and Evolutionary Algorithms for Engineering Optimization

Omid Bozorg-Haddad,Mohammad Solgi,Hugo A. Loáiciga
Meta heuristic and Evolutionary Algorithms for Engineering Optimization Book PDF

Author : Omid Bozorg-Haddad,Mohammad Solgi,Hugo A. Loáiciga
Publisher : John Wiley & Sons
Page : 306 pages
File Size : 51,8 Mb
Release : 2017-10-09
Category : Mathematics
ISBN : 9781119386995

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Meta-heuristic and Evolutionary Algorithms for Engineering Optimization by Omid Bozorg-Haddad,Mohammad Solgi,Hugo A. Loáiciga Pdf

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.

Nature-Inspired Methods for Metaheuristics Optimization

Fouad Bennis,Rajib Kumar Bhattacharjya
Nature Inspired Methods for Metaheuristics Optimization Book PDF

Author : Fouad Bennis,Rajib Kumar Bhattacharjya
Publisher : Springer Nature
Page : 503 pages
File Size : 44,8 Mb
Release : 2020-01-17
Category : Business & Economics
ISBN : 9783030264581

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Nature-Inspired Methods for Metaheuristics Optimization by Fouad Bennis,Rajib Kumar Bhattacharjya Pdf

This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on advanced applications and case studies. They span different engineering fields, including mechanical, electrical and civil engineering, and earth/environmental science, and covers topics such as robotics, water management, process optimization, among others. The book covers both basic concepts and advanced issues, offering a timely introduction to nature-inspired optimization method for newcomers and students, and a source of inspiration as well as important practical insights to engineers and researchers.