Markov Chain Analysis Of Evolutionary Algorithms
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| Author | : William M. Spears |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 244 |
| Release | : 2000-06-15 |
| Genre | : Computers |
| ISBN | : 9783540669500 |
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 | : Thomas Jansen |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 264 |
| Release | : 2013-01-24 |
| Genre | : Computers |
| ISBN | : 364217339X |
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 | : Michael D. Vose |
| Publisher | : MIT Press |
| Total Pages | : 650 |
| Release | : 1999 |
| Genre | : Computers |
| ISBN | : 9780262220583 |
Content Description #"A Bradford book."#Includes bibliographical references (p.) and index.
| Author | : Luigi Fortuna |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 275 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1447103572 |
The book presents a clear understanding of a new type of computation system, the Cellular Neural Network (CNN), which has been successfully applied to the solution of many heavy computation problems, mainly in the fields of image processing and complex partial differential equations. The text describes how CNN will improve the soft-computation toolbox, and examines the many applications of soft computing to complex systems.
| Author | : Thomas Back |
| Publisher | : Oxford University Press |
| Total Pages | : 329 |
| Release | : 1996-01-11 |
| Genre | : Computers |
| ISBN | : 0195356705 |
This book presents a unified view of evolutionary algorithms: the exciting new probabilistic search tools inspired by biological models that have immense potential as practical problem-solvers in a wide variety of settings, academic, commercial, and industrial. In this work, the author compares the three most prominent representatives of evolutionary algorithms: genetic algorithms, evolution strategies, and evolutionary programming. The algorithms are presented within a unified framework, thereby clarifying the similarities and differences of these methods. The author also presents new results regarding the role of mutation and selection in genetic algorithms, showing how mutation seems to be much more important for the performance of genetic algorithms than usually assumed. The interaction of selection and mutation, and the impact of the binary code are further topics of interest. Some of the theoretical results are also confirmed by performing an experiment in meta-evolution on a parallel computer. The meta-algorithm used in this experiment combines components from evolution strategies and genetic algorithms to yield a hybrid capable of handling mixed integer optimization problems. As a detailed description of the algorithms, with practical guidelines for usage and implementation, this work will interest a wide range of researchers in computer science and engineering disciplines, as well as graduate students in these fields.
| Author | : Wai-Ki Ching |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 212 |
| Release | : 2006-06-05 |
| Genre | : Mathematics |
| ISBN | : 038729337X |
Markov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems over time. This monograph will present a series of Markov models, starting from the basic models and then building up to higher-order models. Included in the higher-order discussions are multivariate models, higher-order multivariate models, and higher-order hidden models. In each case, the focus is on the important kinds of applications that can be made with the class of models being considered in the current chapter. Special attention is given to numerical algorithms that can efficiently solve the models. Therefore, Markov Chains: Models, Algorithms and Applications outlines recent developments of Markov chain models for modeling queueing sequences, Internet, re-manufacturing systems, reverse logistics, inventory systems, bio-informatics, DNA sequences, genetic networks, data mining, and many other practical systems.
| Author | : Jin-Kao Hao |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 372 |
| Release | : 1998-02-18 |
| Genre | : Computers |
| ISBN | : 9783540641698 |
The volume presents a survey of the state-of-the-art in artificial evolution, covering theoretical issues, methodologies, and applications in various areas, including genetic-algorithm operators and evolvable hardware and robotics.
| Author | : William M. Spears |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 224 |
| Release | : 2013-03-09 |
| Genre | : Computers |
| ISBN | : 3662041995 |
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 | : Ruhul Sarker |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 416 |
| Release | : 2006-04-11 |
| Genre | : Business & Economics |
| ISBN | : 0306480417 |
Evolutionary computation techniques have attracted increasing att- tions in recent years for solving complex optimization problems. They are more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS problems. E- lutionary computation techniques can deal with complex optimization problems better than traditional optimization techniques. However, most papers on the application of evolutionary computation techniques to Operations Research /Management Science (OR/MS) problems have scattered around in different journals and conference proceedings. They also tend to focus on a very special and narrow topic. It is the right time that an archival book series publishes a special volume which - cludes critical reviews of the state-of-art of those evolutionary com- tation techniques which have been found particularly useful for OR/MS problems, and a collection of papers which represent the latest devel- ment in tackling various OR/MS problems by evolutionary computation techniques. This special volume of the book series on Evolutionary - timization aims at filling in this gap in the current literature. The special volume consists of invited papers written by leading - searchers in the field. All papers were peer reviewed by at least two recognised reviewers. The book covers the foundation as well as the practical side of evolutionary optimization.
| Author | : Xin Yao |
| Publisher | : World Scientific |
| Total Pages | : 384 |
| Release | : 1999 |
| Genre | : Science |
| ISBN | : 9789810223069 |
Evolutionary computation is the study of computational systems which use ideas and get inspiration from natural evolution and adaptation. This book is devoted to the theory and application of evolutionary computation. It is a self-contained volume which covers both introductory material and selected advanced topics. The book can roughly be divided into two major parts: the introductory one and the one on selected advanced topics. Each part consists of several chapters which present an in-depth discussion of selected topics. A strong connection is established between evolutionary algorithms and traditional search algorithms. This connection enables us to incorporate ideas in more established fields into evolutionary algorithms. The book is aimed at a wide range of readers. It does not require previous exposure to the field since introductory material is included. It will be of interest to anyone who is interested in adaptive optimization and learning. People in computer science, artificial intelligence, operations research, and various engineering fields will find it particularly interesting.
