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Main Title Genetic algorithms + data structures = evolution programs /
Author Michalewicz, Zbigniew.
Publisher Springer-Verlag,
Year Published 1996
OCLC Number 33897934
ISBN 3540606769 (hardcover); 9783540606765 (hardcover)
Subjects Evolutionary programming (Computer science) ; Genetic algorithms ; Data structures (Computer science) ; Algoritmen ; Evolutie ; Computadores (software) ; Programmation âevolutionnaire ; Programmation (mathâematiques) ; Algorithmes gâenâetiques ; Structures de donnâees (informatique) ; Datenstruktur ; Evolutionèarer Algorithmus ; Genetischer Algorithmus
Internet Access
Description Access URL
Publisher description
Library Call Number Additional Info Location Last
EKDM  QA76.618.M53 1996 CEMM/EPD Library/Athens,GA 10/22/2012 STATUS
Edition 3rd rev. and extended ed.
Collation xx, 387 p. : ill. ; 24 cm.
Includes bibliographical references (p. [363]-382) and index.
Contents Notes
"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.