Foundations Of Genetic Algorithms

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An Introduction to Genetic Algorithms

Author : Melanie Mitchell
Publisher : MIT Press
ISBN 13 : 9780262631853
Total Pages : 226 pages
Book Rating : 4.6/5 (318 download)

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Book Synopsis An Introduction to Genetic Algorithms by : Melanie Mitchell

Download or read book An Introduction to Genetic Algorithms written by Melanie Mitchell and published by MIT Press. This book was released on 1998-03-02 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics—particularly in machine learning, scientific modeling, and artificial life—and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.

The Simple Genetic Algorithm

Author : Michael D. Vose
Publisher : MIT Press
ISBN 13 : 9780262220583
Total Pages : 650 pages
Book Rating : 4.2/5 (25 download)

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Book Synopsis The Simple Genetic Algorithm by : Michael D. Vose

Download or read book The Simple Genetic Algorithm written by Michael D. Vose and published by MIT Press. This book was released on 1999 with total page 650 pages. Available in PDF, EPUB and Kindle. Book excerpt: Content Description #"A Bradford book."#Includes bibliographical references (p.) and index.

Foundations of Global Genetic Optimization

Author : Robert Schaefer
Publisher : Springer
ISBN 13 : 354073192X
Total Pages : 222 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Foundations of Global Genetic Optimization by : Robert Schaefer

Download or read book Foundations of Global Genetic Optimization written by Robert Schaefer and published by Springer. This book was released on 2007-07-07 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic algorithms today constitute a family of e?ective global optimization methods used to solve di?cult real-life problems which arise in science and technology. Despite their computational complexity, they have the ability to explore huge data sets and allow us to study exceptionally problematic cases in which the objective functions are irregular and multimodal, and where information about the extrema location is unobtainable in other ways. Theybelongtotheclassofiterativestochasticoptimizationstrategiesthat, during each step, produce and evaluate the set of admissible points from the search domain, called the random sample or population. As opposed to the Monte Carlo strategies, in which the population is sampled according to the uniform probability distribution over the search domain, genetic algorithms modify the probability distribution at each step. Mechanisms which adopt sampling probability distribution are transposed from biology. They are based mainly on genetic code mutation and crossover, as well as on selection among living individuals. Such mechanisms have been testedbysolvingmultimodalproblemsinnature,whichiscon?rmedinpart- ular by the many species of animals and plants that are well ?tted to di?erent ecological niches. They direct the search process, making it more e?ective than a completely random one (search with a uniform sampling distribution). Moreover,well-tunedgenetic-basedoperationsdonotdecreasetheexploration ability of the whole admissible set, which is vital in the global optimization process. The features described above allow us to regard genetic algorithms as a new class of arti?cial intelligence methods which introduce heuristics, well tested in other ?elds, to the classical scheme of stochastic global search.

Genetic Algorithms and Engineering Optimization

Author : Mitsuo Gen
Publisher : John Wiley & Sons
ISBN 13 : 9780471315315
Total Pages : 520 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Genetic Algorithms and Engineering Optimization by : Mitsuo Gen

Download or read book Genetic Algorithms and Engineering Optimization written by Mitsuo Gen and published by John Wiley & Sons. This book was released on 1999-12-28 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Im Mittelpunkt dieses Buches steht eines der wichtigsten Optimierungsverfahren der industriellen Ingenieurtechnik: Mit Hilfe genetischer Algorithmen lassen sich Qualität, Design und Zuverlässigkeit von Produkten entscheidend verbessern. Das Verfahren beruht auf der Wahrscheinlichkeitstheorie und lehnt sich an die Prinzipien der biologischen Vererbung an: Die Eigenschaften des Produkts werden, unter Beachtung der äußeren Randbedingungen, schrittweise optimiert. Ein hochaktueller Band international anerkannter Autoren. (03/00)

Genetic Algorithms and Engineering Design

Author : Mitsuo Gen
Publisher : John Wiley & Sons
ISBN 13 : 9780471127413
Total Pages : 436 pages
Book Rating : 4.1/5 (274 download)

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Book Synopsis Genetic Algorithms and Engineering Design by : Mitsuo Gen

Download or read book Genetic Algorithms and Engineering Design written by Mitsuo Gen and published by John Wiley & Sons. This book was released on 1997-01-21 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: The last few years have seen important advances in the use ofgenetic algorithms to address challenging optimization problems inindustrial engineering. Genetic Algorithms and Engineering Designis the only book to cover the most recent technologies and theirapplication to manufacturing, presenting a comprehensive and fullyup-to-date treatment of genetic algorithms in industrialengineering and operations research. Beginning with a tutorial on genetic algorithm fundamentals andtheir use in solving constrained and combinatorial optimizationproblems, the book applies these techniques to problems in specificareas--sequencing, scheduling and production plans, transportationand vehicle routing, facility layout, location-allocation, andmore. Each topic features a clearly written problem description,mathematical model, and summary of conventional heuristicalgorithms. All algorithms are explained in intuitive, rather thanhighly-technical, language and are reinforced with illustrativefigures and numerical examples. Written by two internationally acknowledged experts in the field,Genetic Algorithms and Engineering Design features originalmaterial on the foundation and application of genetic algorithms,and also standardizes the terms and symbols used in othersources--making this complex subject truly accessible to thebeginner as well as to the more advanced reader. Ideal for both self-study and classroom use, this self-containedreference provides indispensable state-of-the-art guidance toprofessionals and students working in industrial engineering,management science, operations research, computer science, andartificial intelligence. The only comprehensive, state-of-the-arttreatment available on the use of genetic algorithms in industrialengineering and operations research . . . Written by internationally recognized experts in the field ofgenetic algorithms and artificial intelligence, Genetic Algorithmsand Engineering Design provides total coverage of currenttechnologies and their application to manufacturing systems.Incorporating original material on the foundation and applicationof genetic algorithms, this unique resource also standardizes theterms and symbols used in other sources--making this complexsubject truly accessible to students as well as experiencedprofessionals. Designed for clarity and ease of use, thisself-contained reference: * Provides a comprehensive survey of selection strategies, penaltytechniques, and genetic operators used for constrained andcombinatorial optimization problems * Shows how to use genetic algorithms to make production schedules,solve facility/location problems, make transportation/vehiclerouting plans, enhance system reliability, and much more * Contains detailed numerical examples, plus more than 160auxiliary figures to make solution procedures transparent andunderstandable

Foundations of Genetic Algorithms 1993 (FOGA 2)

Author : FOGA
Publisher : Morgan Kaufmann
ISBN 13 : 0080948324
Total Pages : 322 pages
Book Rating : 4.0/5 (89 download)

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Book Synopsis Foundations of Genetic Algorithms 1993 (FOGA 2) by : FOGA

Download or read book Foundations of Genetic Algorithms 1993 (FOGA 2) written by FOGA and published by Morgan Kaufmann. This book was released on 2014-06-28 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Genetic Algorithms, Volume 2 provides insight of theoretical work in genetic algorithms. This book provides a general understanding of a canonical genetic algorithm. Organized into six parts encompassing 19 chapters, this volume begins with an overview of genetic algorithms in the broader adaptive systems context. This text then reviews some results in mathematical genetics that use probability distributions to characterize the effects of recombination on multiple loci in the absence of selection. Other chapters examine the static building block hypothesis (SBBH), which is the underlying assumption used to define deception. This book discusses as well the effect of noise on the quality of convergence of genetic algorithms. The final chapter deals with the primary goal in machine learning and artificial intelligence, which is to dynamically and automatically decompose problems into simpler problems to facilitate their solution. This book is a valuable resource for theorists and genetic algorithm researchers.

Foundations of Genetic Algorithms

Author : Alden H. Wright
Publisher : Springer
ISBN 13 : 9783540272373
Total Pages : 0 pages
Book Rating : 4.2/5 (723 download)

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Book Synopsis Foundations of Genetic Algorithms by : Alden H. Wright

Download or read book Foundations of Genetic Algorithms written by Alden H. Wright and published by Springer. This book was released on 2005-07-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The8thWorkshopontheFoundationsofGeneticAlgorithms,FOGA-8,washeld at the University of Aizu in Aizu-Wakamatsu City, Japan, January 5–9, 2005. This series of workshops was initiated in 1990 to encourage further research on the theoretical aspects of genetic algorithms, and the workshops have been held biennially ever since. The papers presented at these workshops are revised, edited and published as volumes during the year following each workshop. This series of (now eight) volumes provides an outstanding source of reference for the theoretical work in this ?eld. At the same time this series of volumes provides a clear picture of how the theoretical research has grown and matured along with the ?eld to encompass many evolutionary computation paradigms including evolution strategies (ES), evolutionary programming (EP), and genetic programming (GP), as well as the continuing growthininteractionswith other ?elds suchas mathematics,physics, and biology. Atraditionoftheseworkshopsisorganizetheminsuchawayastoencourage lots of interaction and discussion by restricting the number of papers presented and the number of attendees, and by holding the workshop in a relaxed and informal setting. This year’s workshop was no exception. Thirty-two researchers met for 3 days to present and discuss 16 papers. The local organizer was Lothar Schmitt who, together with help and support from his university, provided the workshop facilities. Aftertheworkshopwasover,theauthorsweregiventheopportunitytorevise their papers based on the feedback they received from the other participants.

Foundations of Genetic Algorithms 2001 (FOGA 6)

Author : Worth Martin
Publisher : Elsevier
ISBN 13 : 9780080506876
Total Pages : 342 pages
Book Rating : 4.5/5 (68 download)

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Book Synopsis Foundations of Genetic Algorithms 2001 (FOGA 6) by : Worth Martin

Download or read book Foundations of Genetic Algorithms 2001 (FOGA 6) written by Worth Martin and published by Elsevier. This book was released on 2001-07-18 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Genetic Algorithms, Volume 6 is the latest in a series of books that records the prestigious Foundations of Genetic Algorithms Workshops, sponsored and organised by the International Society of Genetic Algorithms specifically to address theoretical publications on genetic algorithms and classifier systems. Genetic algorithms are one of the more successful machine learning methods. Based on the metaphor of natural evolution, a genetic algorithm searches the available information in any given task and seeks the optimum solution by replacing weaker populations with stronger ones. Includes research from academia, government laboratories, and industry Contains high calibre papers which have been extensively reviewed Continues the tradition of presenting not only current theoretical work but also issues that could shape future research in the field Ideal for researchers in machine learning, specifically those involved with evolutionary computation

Foundations of Genetic Algorithms 1991 (FOGA 1)

Author : FOGA
Publisher : Elsevier
ISBN 13 : 0080506844
Total Pages : 341 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Foundations of Genetic Algorithms 1991 (FOGA 1) by : FOGA

Download or read book Foundations of Genetic Algorithms 1991 (FOGA 1) written by FOGA and published by Elsevier. This book was released on 2014-06-28 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Genetic Algorithms 1991 (FOGA 1) discusses the theoretical foundations of genetic algorithms (GA) and classifier systems. This book compiles research papers on selection and convergence, coding and representation, problem hardness, deception, classifier system design, variation and recombination, parallelization, and population divergence. Other topics include the non-uniform Walsh-schema transform; spurious correlations and premature convergence in genetic algorithms; and variable default hierarchy separation in a classifier system. The grammar-based genetic algorithm; conditions for implicit parallelism; and analysis of multi-point crossover are also elaborated. This text likewise covers the genetic algorithms for real parameter optimization and isomorphisms of genetic algorithms. This publication is a good reference for students and researchers interested in genetic algorithms.

Genetic Algorithms: Principles and Perspectives

Author : Colin R. Reeves
Publisher : Springer Science & Business Media
ISBN 13 : 0306480506
Total Pages : 332 pages
Book Rating : 4.3/5 (64 download)

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Book Synopsis Genetic Algorithms: Principles and Perspectives by : Colin R. Reeves

Download or read book Genetic Algorithms: Principles and Perspectives written by Colin R. Reeves and published by Springer Science & Business Media. This book was released on 2006-04-11 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory is a survey of some important theoretical contributions, many of which have been proposed and developed in the Foundations of Genetic Algorithms series of workshops. However, this theoretical work is still rather fragmented, and the authors believe that it is the right time to provide the field with a systematic presentation of the current state of theory in the form of a set of theoretical perspectives. The authors do this in the interest of providing students and researchers with a balanced foundational survey of some recent research on GAs. The scope of the book includes chapter-length discussions of Basic Principles, Schema Theory, "No Free Lunch", GAs and Markov Processes, Dynamical Systems Model, Statistical Mechanics Approximations, Predicting GA Performance, Landscapes and Test Problems.

Genetic Algorithm Essentials

Author : Oliver Kramer
Publisher : Springer
ISBN 13 : 331952156X
Total Pages : 92 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Genetic Algorithm Essentials by : Oliver Kramer

Download or read book Genetic Algorithm Essentials written by Oliver Kramer and published by Springer. This book was released on 2017-01-07 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces readers to genetic algorithms (GAs) with an emphasis on making the concepts, algorithms, and applications discussed as easy to understand as possible. Further, it avoids a great deal of formalisms and thus opens the subject to a broader audience in comparison to manuscripts overloaded by notations and equations. The book is divided into three parts, the first of which provides an introduction to GAs, starting with basic concepts like evolutionary operators and continuing with an overview of strategies for tuning and controlling parameters. In turn, the second part focuses on solution space variants like multimodal, constrained, and multi-objective solution spaces. Lastly, the third part briefly introduces theoretical tools for GAs, the intersections and hybridizations with machine learning, and highlights selected promising applications.

Genetic Algorithms and Genetic Programming in Computational Finance

Author : Shu-Heng Chen
Publisher : Springer Science & Business Media
ISBN 13 : 1461508355
Total Pages : 491 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Genetic Algorithms and Genetic Programming in Computational Finance by : Shu-Heng Chen

Download or read book Genetic Algorithms and Genetic Programming in Computational Finance written by Shu-Heng Chen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: After a decade of development, genetic algorithms and genetic programming have become a widely accepted toolkit for computational finance. Genetic Algorithms and Genetic Programming in Computational Finance is a pioneering volume devoted entirely to a systematic and comprehensive review of this subject. Chapters cover various areas of computational finance, including financial forecasting, trading strategies development, cash flow management, option pricing, portfolio management, volatility modeling, arbitraging, and agent-based simulations of artificial stock markets. Two tutorial chapters are also included to help readers quickly grasp the essence of these tools. Finally, a menu-driven software program, Simple GP, accompanies the volume, which will enable readers without a strong programming background to gain hands-on experience in dealing with much of the technical material introduced in this work.

Foundations of Genetic Algorithms

Author : Alden H. Wright
Publisher : Springer Science & Business Media
ISBN 13 : 3540272372
Total Pages : 325 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Foundations of Genetic Algorithms by : Alden H. Wright

Download or read book Foundations of Genetic Algorithms written by Alden H. Wright and published by Springer Science & Business Media. This book was released on 2005-07 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th workshop on the foundations of genetic algorithms, FOGA 2005, held in Aizu-Wakamatsu City, Japan, in January 2005. The 16 revised full papers presented provide an outstanding source of reference for the field of theoretical evolutionary computation including evolution strategies, evolutionary programming, and genetic programming, as well as the continuing growth in interactions with other fields such as mathematics, physics, and biology.

Foundations of Genetic Algorithms

Author : Colin R. Reeves
Publisher : Morgan Kaufmann
ISBN 13 : 9781558605596
Total Pages : 316 pages
Book Rating : 4.6/5 (55 download)

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Book Synopsis Foundations of Genetic Algorithms by : Colin R. Reeves

Download or read book Foundations of Genetic Algorithms written by Colin R. Reeves and published by Morgan Kaufmann. This book was released on 1999 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Consists of conference papers from the Foundations of Genetic Algorithms workshop.

Foundations of Genetic Algorithms

Author : Christopher R. Stephens
Publisher : Springer Science & Business Media
ISBN 13 : 3540734791
Total Pages : 220 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Foundations of Genetic Algorithms by : Christopher R. Stephens

Download or read book Foundations of Genetic Algorithms written by Christopher R. Stephens and published by Springer Science & Business Media. This book was released on 2007-06-29 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-proceedings of the 9th Workshop on the Foundations of Genetic Algorithms, FOGA 2007, held in Mexico City, Mexico in January 2007. The 11 revised full papers presented were carefully reviewed and selected during two rounds of reviewing and improvement from 22 submissions. The papers address all current topics in the field of theoretical evolutionary computation including evolution strategies, evolutionary programming, and genetic programming, and also depict the continuing growth in interactions with other fields such as mathematics, physics, and biology.

Genetic Algorithms in Search, Optimization, and Machine Learning

Author : David Edward Goldberg
Publisher : Addison-Wesley Professional
ISBN 13 :
Total Pages : 436 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Genetic Algorithms in Search, Optimization, and Machine Learning by : David Edward Goldberg

Download or read book Genetic Algorithms in Search, Optimization, and Machine Learning written by David Edward Goldberg and published by Addison-Wesley Professional. This book was released on 1989 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: A gentle introduction to genetic algorithms. Genetic algorithms revisited: mathematical foundations. Computer implementation of a genetic algorithm. Some applications of genetic algorithms. Advanced operators and techniques in genetic search. Introduction to genetics-based machine learning. Applications of genetics-based machine learning. A look back, a glance ahead. A review of combinatorics and elementary probability. Pascal with random number generation for fortran, basic, and cobol programmers. A simple genetic algorithm (SGA) in pascal. A simple classifier system(SCS) in pascal. Partition coefficient transforms for problem-coding analysis.

Foundations of Genetic Algorithms 6

Author : Worthy N. Martin
Publisher : Morgan Kaufmann Pub
ISBN 13 : 9781558607347
Total Pages : 342 pages
Book Rating : 4.6/5 (73 download)

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Book Synopsis Foundations of Genetic Algorithms 6 by : Worthy N. Martin

Download or read book Foundations of Genetic Algorithms 6 written by Worthy N. Martin and published by Morgan Kaufmann Pub. This book was released on 2001 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Genetic Algorithms, Volume 6 is the latest in a series of books that records the prestigious Foundations of Genetic Algorithms Workshops, sponsored and organised by the International Society of Genetic Algorithms specifically to address theoretical publications on genetic algorithms and classifier systems. Genetic algorithms are one of the more successful machine learning methods. Based on the metaphor of natural evolution, a genetic algorithm searches the available information in any given task and seeks the optimum solution by replacing weaker populations with stronger ones. Includes research from academia, government laboratories, and industry Contains high calibre papers which have been extensively reviewed Continues the tradition of presenting not only current theoretical work but also issues that could shape future research in the field Ideal for researchers in machine learning, specifically those involved with evolutionary computation