Metaheuristics For Dynamic Optimization

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Metaheuristics for Dynamic Optimization

Enrique Alba,Amir Nakib,Patrick Siarry
Metaheuristics for Dynamic Optimization Book PDF

Author : Enrique Alba,Amir Nakib,Patrick Siarry
Publisher : Springer
Page : 400 pages
File Size : 40,6 Mb
Release : 2012-08-11
Category : Technology & Engineering
ISBN : 9783642306655

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Metaheuristics for Dynamic Optimization by Enrique Alba,Amir Nakib,Patrick Siarry Pdf

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.

Metaheuristics for Dynamic Optimization

Anonim
Metaheuristics for Dynamic Optimization Book PDF

Author : Anonim
Publisher : Unknown
Page : 128 pages
File Size : 50,6 Mb
Release : 2013
Category : Combinatorial optimization
ISBN : 3642306667

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Metaheuristics for Dynamic Optimization by Anonim Pdf

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 becomingvery 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 bioinspiredtechniques. 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 bioinformaticsare 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.

Hybrid Metaheuristics

Christian Blum,Andrea Roli,Michael Sampels
Hybrid Metaheuristics Book PDF

Author : Christian Blum,Andrea Roli,Michael Sampels
Publisher : Springer
Page : 290 pages
File Size : 49,7 Mb
Release : 2008-06-24
Category : Technology & Engineering
ISBN : 9783540782957

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Hybrid Metaheuristics by Christian Blum,Andrea Roli,Michael Sampels Pdf

Optimization problems are of great importance across a broad range of fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. This book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments. The authors involved in this book are among the top researchers in their domain.

Hybrid Metaheuristics

Christian Blum,Günther R. Raidl
Hybrid Metaheuristics Book PDF

Author : Christian Blum,Günther R. Raidl
Publisher : Springer
Page : 172 pages
File Size : 50,7 Mb
Release : 2016-05-23
Category : Computers
ISBN : 9783319308838

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Hybrid Metaheuristics by Christian Blum,Günther R. Raidl Pdf

This book explains the most prominent and some promising new, general techniques that combine metaheuristics with other optimization methods. A first introductory chapter reviews the basic principles of local search, prominent metaheuristics, and tree search, dynamic programming, mixed integer linear programming, and constraint programming for combinatorial optimization purposes. The chapters that follow present five generally applicable hybridization strategies, with exemplary case studies on selected problems: incomplete solution representations and decoders; problem instance reduction; large neighborhood search; parallel non-independent construction of solutions within metaheuristics; and hybridization based on complete solution archives. The authors are among the leading researchers in the hybridization of metaheuristics with other techniques for optimization, and their work reflects the broad shift to problem-oriented rather than algorithm-oriented approaches, enabling faster and more effective implementation in real-life applications. This hybridization is not restricted to different variants of metaheuristics but includes, for example, the combination of mathematical programming, dynamic programming, or constraint programming with metaheuristics, reflecting cross-fertilization in fields such as optimization, algorithmics, mathematical modeling, operations research, statistics, and simulation. The book is a valuable introduction and reference for researchers and graduate students in these domains.

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 : 43,9 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.

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 : 707 pages
File Size : 40,9 Mb
Release : 2013-06-29
Category : Computers
ISBN : 9781475741377

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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.

Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization

Javier Del Ser Lorente,Eneko Osaba
Nature inspired Methods for Stochastic Robust and Dynamic Optimization Book PDF

Author : Javier Del Ser Lorente,Eneko Osaba
Publisher : BoD – Books on Demand
Page : 71 pages
File Size : 43,5 Mb
Release : 2018-07-18
Category : Mathematics
ISBN : 9781789233285

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Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization by Javier Del Ser Lorente,Eneko Osaba Pdf

Nature-inspired algorithms have a great popularity in the current scientific community, being the focused scope of many research contributions in the literature year by year. The rationale behind the acquired momentum by this broad family of methods lies on their outstanding performance evinced in hundreds of research fields and problem instances. This book gravitates on the development of nature-inspired methods and their application to stochastic, dynamic and robust optimization. Topics covered by this book include the design and development of evolutionary algorithms, bio-inspired metaheuristics, or memetic methods, with empirical, innovative findings when used in different subfields of mathematical optimization, such as stochastic, dynamic, multimodal and robust optimization, as well as noisy optimization and dynamic and constraint satisfaction problems.

Metaheuristics for Combinatorial Optimization

Salvatore Greco,Mario F. Pavone,El-Ghazali Talbi,Daniele Vigo
Metaheuristics for Combinatorial Optimization Book PDF

Author : Salvatore Greco,Mario F. Pavone,El-Ghazali Talbi,Daniele Vigo
Publisher : Springer Nature
Page : 69 pages
File Size : 45,6 Mb
Release : 2021-02-13
Category : Technology & Engineering
ISBN : 9783030685201

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Metaheuristics for Combinatorial Optimization by Salvatore Greco,Mario F. Pavone,El-Ghazali Talbi,Daniele Vigo Pdf

This book presents novel and original metaheuristics developed to solve the cost-balanced traveling salesman problem. This problem was taken into account for the Metaheuristics Competition proposed in MESS 2018, Metaheuristics Summer School, and the top 4 methodologies ranked are included in the book, together with a brief introduction to the traveling salesman problem and all its variants. The book is aimed particularly at all researchers in metaheuristics and combinatorial optimization areas. Key uses are metaheuristics; complex problem solving; combinatorial optimization; traveling salesman problem.

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 : 48,8 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.

Applications of Metaheuristics in Process Engineering

Jayaraman Valadi,Patrick Siarry
Applications of Metaheuristics in Process Engineering Book PDF

Author : Jayaraman Valadi,Patrick Siarry
Publisher : Springer
Page : 451 pages
File Size : 49,7 Mb
Release : 2014-08-07
Category : Computers
ISBN : 9783319065083

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Applications of Metaheuristics in Process Engineering by Jayaraman Valadi,Patrick Siarry Pdf

Metaheuristics exhibit desirable properties like simplicity, easy parallelizability and ready applicability to different types of optimization problems such as real parameter optimization, combinatorial optimization and mixed integer optimization. They are thus beginning to play a key role in different industrially important process engineering applications, among them the synthesis of heat and mass exchange equipment, synthesis of distillation columns and static and dynamic optimization of chemical and bioreactors. This book explains cutting-edge research techniques in related computational intelligence domains and their applications in real-world process engineering. It will be of interest to industrial practitioners and research academics.

Advances in Metaheuristics for Hard Optimization

Patrick Siarry,Zbigniew Michalewicz
Advances in Metaheuristics for Hard Optimization Book PDF

Author : Patrick Siarry,Zbigniew Michalewicz
Publisher : Springer Science & Business Media
Page : 481 pages
File Size : 48,8 Mb
Release : 2007-12-06
Category : Mathematics
ISBN : 9783540729600

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Advances in Metaheuristics for Hard Optimization by Patrick Siarry,Zbigniew Michalewicz Pdf

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.

Hybrid Metaheuristics

Christian Blum,Andrea Roli,Michael Sampels
Hybrid Metaheuristics Book PDF

Author : Christian Blum,Andrea Roli,Michael Sampels
Publisher : Springer Science & Business Media
Page : 294 pages
File Size : 42,5 Mb
Release : 2008-04-11
Category : Mathematics
ISBN : 9783540782940

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Hybrid Metaheuristics by Christian Blum,Andrea Roli,Michael Sampels Pdf

Optimization problems are of great importance across a broad range of fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. This book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments. The authors involved in this book are among the top researchers in their domain.

Evolutionary Computation for Dynamic Optimization Problems

Shengxiang Yang,Xin Yao
Evolutionary Computation for Dynamic Optimization Problems Book PDF

Author : Shengxiang Yang,Xin Yao
Publisher : Springer
Page : 470 pages
File Size : 42,5 Mb
Release : 2013-11-18
Category : Technology & Engineering
ISBN : 9783642384165

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Evolutionary Computation for Dynamic Optimization Problems by Shengxiang Yang,Xin Yao Pdf

This book provides a compilation on the state-of-the-art and recent advances of evolutionary computation for dynamic optimization problems. The motivation for this book arises from the fact that many real-world optimization problems and engineering systems are subject to dynamic environments, where changes occur over time. Key issues for addressing dynamic optimization problems in evolutionary computation, including fundamentals, algorithm design, theoretical analysis, and real-world applications, are presented. "Evolutionary Computation for Dynamic Optimization Problems" is a valuable reference to scientists, researchers, professionals and students in the field of engineering and science, particularly in the areas of computational intelligence, nature- and bio-inspired computing, and evolutionary computation.

Hybrid Metaheuristics

El-ghazali Talbi
Hybrid Metaheuristics Book PDF

Author : El-ghazali Talbi
Publisher : Springer
Page : 458 pages
File Size : 46,8 Mb
Release : 2012-07-31
Category : Technology & Engineering
ISBN : 9783642306716

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Hybrid Metaheuristics by El-ghazali Talbi Pdf

The main goal of this book is to provide a state of the art of hybrid metaheuristics. The book provides a complete background that enables readers to design and implement hybrid metaheuristics to solve complex optimization problems (continuous/discrete, mono-objective/multi-objective, optimization under uncertainty) in a diverse range of application domains. Readers learn to solve large scale problems quickly and efficiently combining metaheuristics with complementary metaheuristics, mathematical programming, constraint programming and machine learning. Numerous real-world examples of problems and solutions demonstrate how hybrid metaheuristics are applied in such fields as networks, logistics and transportation, bio-medical, engineering design, scheduling.

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 : 53,8 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.