Analyzing Evolutionary Algorithms

Author : Thomas Jansen
Publisher : Springer Science & Business Media
Page : 264 pages
File Size : 52,7 Mb
Release : 2013-01-24
Category : Computers
ISBN : 9783642173394

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Analyzing Evolutionary Algorithms by Thomas Jansen Pdf

Evolutionary algorithms is a class of randomized heuristics inspired by natural evolution. They are applied in many different contexts, in particular in optimization, and analysis of such algorithms has seen tremendous advances in recent years. In this book the author provides an introduction to the methods used to analyze evolutionary algorithms and other randomized search heuristics. He starts with an algorithmic and modular perspective and gives guidelines for the design of evolutionary algorithms. He then places the approach in the broader research context with a chapter on theoretical perspectives. By adopting a complexity-theoretical perspective, he derives general limitations for black-box optimization, yielding lower bounds on the performance of evolutionary algorithms, and then develops general methods for deriving upper and lower bounds step by step. This main part is followed by a chapter covering practical applications of these methods. The notational and mathematical basics are covered in an appendix, the results presented are derived in detail, and each chapter ends with detailed comments and pointers to further reading. So the book is a useful reference for both graduate students and researchers engaged with the theoretical analysis of such algorithms.

Author : William M. Spears
Publisher : Springer Science & Business Media
Page : 224 pages
File Size : 41,9 Mb
Release : 2013-03-09
Category : Computers
ISBN : 9783662041994

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Evolutionary Algorithms by William M. Spears Pdf

Despite decades of work in evolutionary algorithms, there remains an uncertainty as to the relative benefits and detriments of using recombination or mutation. This book provides a characterization of the roles that recombination and mutation play in evolutionary algorithms. It integrates important prior work and introduces new theoretical techniques for studying evolutionary algorithms. Consequences of the theory are explored and a novel method for comparing search and optimization algorithms is introduced. The focus allows the book to bridge multiple communities, including evolutionary biologists and population geneticists.

Author : Stefano Cagnoni
Publisher : Hindawi Publishing Corporation
Page : 473 pages
File Size : 43,7 Mb
Release : 2008
Category : Computer vision
ISBN : 9789774540011

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Genetic and Evolutionary Computation for Image Processing and Analysis by Stefano Cagnoni Pdf

Author : Benjamin Doerr,Frank Neumann
Publisher : Springer Nature
Page : 506 pages
File Size : 47,9 Mb
Release : 2019-11-20
Category : Computers
ISBN : 9783030294144

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Theory of Evolutionary Computation by Benjamin Doerr,Frank Neumann Pdf

This edited book reports on recent developments in the theory of evolutionary computation, or more generally the domain of randomized search heuristics. It starts with two chapters on mathematical methods that are often used in the analysis of randomized search heuristics, followed by three chapters on how to measure the complexity of a search heuristic: black-box complexity, a counterpart of classical complexity theory in black-box optimization; parameterized complexity, aimed at a more fine-grained view of the difficulty of problems; and the fixed-budget perspective, which answers the question of how good a solution will be after investing a certain computational budget. The book then describes theoretical results on three important questions in evolutionary computation: how to profit from changing the parameters during the run of an algorithm; how evolutionary algorithms cope with dynamically changing or stochastic environments; and how population diversity influences performance. Finally, the book looks at three algorithm classes that have only recently become the focus of theoretical work: estimation-of-distribution algorithms; artificial immune systems; and genetic programming. Throughout the book the contributing authors try to develop an understanding for how these methods work, and why they are so successful in many applications. The book will be useful for students and researchers in theoretical computer science and evolutionary computing.

Author : Thomas Bartz-Beielstein,Marco Chiarandini,Luís Paquete,Mike Preuss
Publisher : Springer Science & Business Media
Page : 469 pages
File Size : 53,5 Mb
Release : 2010-11-02
Category : Computers
ISBN : 9783642025389

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Experimental Methods for the Analysis of Optimization Algorithms by Thomas Bartz-Beielstein,Marco Chiarandini,Luís Paquete,Mike Preuss Pdf

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.

Author : Günter Rudolph,Thomas Jansen,Simon M. Lucas,Carlo Poloni,Nicola Beume
Publisher : Springer
Page : 1183 pages
File Size : 48,5 Mb
Release : 2008-09-16
Category : Computers
ISBN : 9783540877004

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Parallel Problem Solving from Nature - PPSN X by Günter Rudolph,Thomas Jansen,Simon M. Lucas,Carlo Poloni,Nicola Beume Pdf

This book constitutes the refereed proceedings of the 10th International Conference on Parallel Problem Solving from Nature, PPSN 2008, held in Dortmund, Germany, in September 2008. The 114 revised full papers presented were carefully reviewed and selected from 206 submissions. The conference covers a wide range of topics, such as evolutionary computation, quantum computation, molecular computation, neural computation, artificial life, swarm intelligence, artificial ant systems, artificial immune systems, self-organizing systems, emergent behaviors, and applications to real-world problems. The paper are organized in topical sections on formal theory, new techniques, experimental analysis, multiobjective optimization, hybrid methods, and applications.

Author : Jörg Biethahn,Volker Nissen
Publisher : Springer Science & Business Media
Page : 384 pages
File Size : 50,9 Mb
Release : 2012-12-06
Category : Business & Economics
ISBN : 9783642612176

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Evolutionary Algorithms in Management Applications by Jörg Biethahn,Volker Nissen Pdf

Evolutionary Algorithms (EA) are powerful search and optimisation techniques inspired by the mechanisms of natural evolution. They imitate, on an abstract level, biological principles such as a population based approach, the inheritance of information, the variation of information via crossover/mutation, and the selection of individuals based on fitness. The most well-known class of EA are Genetic Algorithms (GA), which have received much attention not only in the scientific community lately. Other variants of EA, in particular Genetic Programming, Evolution Strategies, and Evolutionary Programming are less popular, though very powerful too. Traditionally, most practical applications of EA have appeared in the technical sector. Management problems, for a long time, have been a rather neglected field of EA-research. This is surprising, since the great potential of evolutionary approaches for the business and economics domain was recognised in pioneering publications quite a while ago. John Holland, for instance, in his seminal book Adaptation in Natural and Artificial Systems (The University of Michigan Press, 1975) identified economics as one of the prime targets for a theory of adaptation, as formalised in his reproductive plans (later called Genetic Algorithms).

Author : Jing Liu,Hussein A. Abbass,Kay Chen Tan
Publisher : Springer
Page : 148 pages
File Size : 46,7 Mb
Release : 2018-09-22
Category : Technology & Engineering
ISBN : 9783319600000

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Evolutionary Computation and Complex Networks by Jing Liu,Hussein A. Abbass,Kay Chen Tan Pdf

This book introduces the linkage between evolutionary computation and complex networks and the advantages of cross-fertilising ideas from both fields. Instead of introducing each field individually, the authors focus on the research that sits at the interface of both fields. The book is structured to address two questions: (1) how complex networks are used to analyze and improve the performance of evolutionary computation methods? (2) how evolutionary computation methods are used to solve problems in complex networks? The authors interweave complex networks and evolutionary computing, using evolutionary computation to discover community structure, while also using network analysis techniques to analyze the performance of evolutionary algorithms. The book is suitable for both beginners and senior researchers in the fields of evolutionary computation and complex networks.

Author : Franz Rothlauf
Publisher : Springer Science & Business Media
Page : 335 pages
File Size : 46,6 Mb
Release : 2006-03-14
Category : Technology & Engineering
ISBN : 9783540324447

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Representations for Genetic and Evolutionary Algorithms by Franz Rothlauf Pdf

In the field of genetic and evolutionary algorithms (GEAs), a large amount of theory and empirical study has been focused on operators and test problems, while problem representation has often been taken as given. This book breaks with this tradition and provides a comprehensive overview on the influence of problem representations on GEA performance. The book summarizes existing knowledge regarding problem representations and describes how basic properties of representations, such as redundancy, scaling, or locality, influence the performance of GEAs and other heuristic optimization methods. Using the developed theory, representations can be analyzed and designed in a theory-guided matter. The theoretical concepts are used for solving integer optimization problems and network design problems more efficiently. The book is written in an easy-readable style and is intended for researchers, practitioners, and students who want to learn about representations. This second edition extends the analysis of the basic properties of representations and introduces a new chapter on the analysis of direct representations.

Author : Agoston E. Eiben,J.E. Smith
Publisher : Springer Science & Business Media
Page : 307 pages
File Size : 54,5 Mb
Release : 2013-03-14
Category : Computers
ISBN : 9783662050941

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Introduction to Evolutionary Computing by Agoston E. Eiben,J.E. Smith Pdf

The first complete overview of evolutionary computing, the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. The text is aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to apply evolutionary computing to a particular problem or within a given application area. The book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.

Author : Thomas Bartz-Beielstein
Publisher : Springer Science & Business Media
Page : 221 pages
File Size : 53,9 Mb
Release : 2006-05-09
Category : Computers
ISBN : 9783540320272

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Experimental Research in Evolutionary Computation by Thomas Bartz-Beielstein Pdf

This book introduces the new experimentalism in evolutionary computation, providing tools to understand algorithms and programs and their interaction with optimization problems. It develops and applies statistical techniques to analyze and compare modern search heuristics such as evolutionary algorithms and particle swarm optimization. The book bridges the gap between theory and experiment by providing a self-contained experimental methodology and many examples.

Author : Zhi-Hua Zhou,Yang Yu,Chao Qian
Publisher : Springer
Page : 361 pages
File Size : 40,6 Mb
Release : 2019-05-22
Category : Computers
ISBN : 9789811359569

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Evolutionary Learning: Advances in Theories and Algorithms by Zhi-Hua Zhou,Yang Yu,Chao Qian Pdf

Many machine learning tasks involve solving complex optimization problems, such as working on non-differentiable, non-continuous, and non-unique objective functions; in some cases it can prove difficult to even define an explicit objective function. Evolutionary learning applies evolutionary algorithms to address optimization problems in machine learning, and has yielded encouraging outcomes in many applications. However, due to the heuristic nature of evolutionary optimization, most outcomes to date have been empirical and lack theoretical support. This shortcoming has kept evolutionary learning from being well received in the machine learning community, which favors solid theoretical approaches. Recently there have been considerable efforts to address this issue. This book presents a range of those efforts, divided into four parts. Part I briefly introduces readers to evolutionary learning and provides some preliminaries, while Part II presents general theoretical tools for the analysis of running time and approximation performance in evolutionary algorithms. Based on these general tools, Part III presents a number of theoretical findings on major factors in evolutionary optimization, such as recombination, representation, inaccurate fitness evaluation, and population. In closing, Part IV addresses the development of evolutionary learning algorithms with provable theoretical guarantees for several representative tasks, in which evolutionary learning offers excellent performance.

Author : Celso C. Ribeiro,Pierre Hansen
Publisher : Springer Science & Business Media
Page : 647 pages
File Size : 55,6 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.

Author : Dan Simon
Publisher : John Wiley & Sons
Page : 776 pages
File Size : 50,5 Mb
Release : 2013-06-13
Category : Mathematics
ISBN : 9781118659502

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Evolutionary Optimization Algorithms by Dan Simon Pdf

A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies. This book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others. Evolutionary Optimization Algorithms: Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear but theoretically rigorous understanding of evolutionary algorithms, with an emphasis on implementation Gives a careful treatment of recently developed EAs including opposition-based learning, artificial fish swarms, bacterial foraging, and many others and discusses their similarities and differences from more well-established EAs Includes chapter-end problems plus a solutions manual available online for instructors Offers simple examples that provide the reader with an intuitive understanding of the theory Features source code for the examples available on the author's website Provides advanced mathematical techniques for analyzing EAs, including Markov modeling and dynamic system modeling Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science.

Author : Anonim
Publisher : Unknown
Page : 128 pages
File Size : 53,5 Mb
Release : 2024-06-28
Category : Electronic
ISBN : 9789814466875

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Theory of Randomized Search Heuristics by Anonim Pdf