Genetic algorithms + data structures = evolution programs / Zbigniew Michalewicz.

By: Michalewicz, Zbigniew Material type: Text

TextLanguage: English Publication details: Berlin ; New York : Springer-Verlag, c1996. Edition: 3rd rev. and extended edDescription: xx, 387 p. : ill. ; 24 cmISBN: 3540606769 (hardcover); 9783540606765Other title: Genetic algorithms plus data structures equals evolution programsSubject(s): Evolutionary programming (Computer science) | Genetic algorithms | Data structures (Computer science)DDC classification: 005.1 LOC classification: QA76.618 | .M53 1996Online resources: Publisher description | Table of contents only | WorldCat details

Contents:

TOC Introduction.- Part I. Genetic Algorithms. GAs: What Are They? - GAs: How Do They Work? - GAs: Why Do They Work? - GAs: Selected Topics.- Part II. Numerical Optimization. Binary or Float? - Fine Local Tuning.- Handling Constraints.- Evolution Strategies and Other Methods.- Part III. Evolution Programs. The Transportation Problem.- The Traveling Salesman Problem.- Machine Learning.- Evolutionary Programming and Genetic Programming.- A Hierarchy of Evolution Programs.- Evolution Programs and Heuristics.- Conclusions.- Appendices.- References.- Index.

Summary: "Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control. The importance of these techniques is still growing, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science." "The aim of this book is to talk about the field of evolutionary computation in simple terms, and discuss the simplicity and elegance of its methods on many interesting test cases. The book may serve as a guide to writing an evolution program, and to making this an enjoyable experience. It is self-contained and the only prerequisite is basic undergraduate mathematics. Aimed at researchers, practitioners, and graduate students, it may serve as a text for advanced courses in computer science and artificial intelligence, operations research, and engineering." "This third edition has been substantially revised and extended. Three new chapters discuss the recent paradigm of genetic programming, heuristic methods and constraint handling, and current directions of research. Additional appendices contain test functions for experiments with evolutionary techniques and discuss possible projects for use in a project-oriented course."--BOOK JACKET.

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Item type	Current library	Collection	Call number	Copy number	Status	Barcode
Text	Dr. S. R. Lasker Library, EWU Reserve Section	Non-fiction	005.1 MIG 1996 (Browse shelf(Opens below))	C-1	Not For Loan	16323
Text	Dr. S. R. Lasker Library, EWU Reserve Section	Non-fiction	005.1 MIG 1996 (Browse shelf(Opens below))	C-2	Not For Loan	16324
Text	Dr. S. R. Lasker Library, EWU Circulation Section	Non-fiction	005.1 MIG 1996 (Browse shelf(Opens below))	C-4	Available	16326
Text	Dr. S. R. Lasker Library, EWU Circulation Section	Non-fiction	005.1 MIG 1996 (Browse shelf(Opens below))	C-5	Available	16327
Text	Dr. S. R. Lasker Library, EWU Circulation Section	Non-fiction	005.1 MIG 1996 (Browse shelf(Opens below))	C-6	Available	21833
Text	Dr. S. R. Lasker Library, EWU Circulation Section	Non-fiction	005.1 MIG 1996 (Browse shelf(Opens below))	C-7	Available	21834
Text	Dr. S. R. Lasker Library, EWU Circulation Section	Non-fiction	005.1 MIG 1996 (Browse shelf(Opens below))	C-8	Available	21835

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Includes bibliographical references (p. [363]-382) and index.

"Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control. The importance of these techniques is still growing, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science." "The aim of this book is to talk about the field of evolutionary computation in simple terms, and discuss the simplicity and elegance of its methods on many interesting test cases. The book may serve as a guide to writing an evolution program, and to making this an enjoyable experience. It is self-contained and the only prerequisite is basic undergraduate mathematics. Aimed at researchers, practitioners, and graduate students, it may serve as a text for advanced courses in computer science and artificial intelligence, operations research, and engineering." "This third edition has been substantially revised and extended. Three new chapters discuss the recent paradigm of genetic programming, heuristic methods and constraint handling, and current directions of research. Additional appendices contain test functions for experiments with evolutionary techniques and discuss possible projects for use in a project-oriented course."--BOOK JACKET.

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Tahur Ahmed

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