Genetic Algorithm in search, optimization and Machine Learning

By:

David Edward Goldberg

Material type: Text

TextPublication details: Delhi Pearson Education 1989Description: 412 pagesISBN:

817808130-x

Subject(s):

Genetic algorithms. Machine learning

DDC classification:

006.3'1 GOL-G

Summary: The text introduces the theory, operation, and application of genetic algorithms----search algorithms based on the mechanics of natural selection and genetics. This book, suitable for both course work and self-study, brings together for the first time, in an informal, tutorial fashion, the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields: programmers, scientists, engineers, mathematicians, statisticians and management scientists will all find interesting possibilities here. Major concepts are illustrated with running examples, and major algorithms are illustrated by Pascal computer programs. Chapter concludes with exercises and computer assignments. No prior knowledge of Gas or genetics is assumed.

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Holdings
Item type	Current library	Home library	Call number	Status	Date due	Barcode
Book	Dept. of Computational Biology and Bioinformatics Processing Center	Dept. of Computational Biology and Bioinformatics	006.3'1 GOL-G (Browse shelf(Opens below))	Available		DCB172

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The text introduces the theory, operation, and application of genetic algorithms----search algorithms based on the mechanics of natural selection and genetics. This book, suitable for both course work and self-study, brings together for the first time, in an informal, tutorial fashion, the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields: programmers, scientists, engineers, mathematicians, statisticians and management scientists will all find interesting possibilities here. Major concepts are illustrated with running examples, and major algorithms are illustrated by Pascal computer programs. Chapter concludes with exercises and computer assignments. No prior knowledge of Gas or genetics is assumed.

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