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Practical Handbook of Genetic Algorithms (Record no. 10570)

MARC details
000 -LEADER
fixed length control field 01532 a2200253 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250526161932.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250430041995xx 4 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780849325298
Qualifying information BB
037 ## - SOURCE OF ACQUISITION
Source of stock number/acquisition Taylor & Francis
Terms of availability GBP 160.00
Form of issue BB
040 ## - CATALOGING SOURCE
Original cataloging agency 01
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
072 7# - SUBJECT CATEGORY CODE
Subject category code UY
Source thema
072 7# - SUBJECT CATEGORY CODE
Subject category code UB
Source thema
072 7# - SUBJECT CATEGORY CODE
Subject category code UY
Source bic
072 7# - SUBJECT CATEGORY CODE
Subject category code UB
Source bic
072 7# - SUBJECT CATEGORY CODE
Subject category code MAT000000
Source bisac
072 7# - SUBJECT CATEGORY CODE
Subject category code MAT021000
Source bisac
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Lance D. Chambers
9 (RLIN) 904
245 10 - TITLE STATEMENT
Title Practical Handbook of Genetic Algorithms
Remainder of title New Frontiers, Volume II
250 ## - EDITION STATEMENT
Edition statement 1
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Name of publisher, distributor, etc. CRC Press
Date of publication, distribution, etc. 19950815
300 ## - PHYSICAL DESCRIPTION
Extent 448 p
520 ## - SUMMARY, ETC.
Expansion of summary note The mathematics employed by genetic algorithms (GAs)are among the most exciting discoveries of the last few decades. But what exactly is a genetic algorithm? A genetic algorithm is a problem-solving method that uses genetics as its model of problem solving. It applies the rules of reproduction, gene crossover, and mutation to pseudo-organisms so those "organisms" can pass beneficial and survival-enhancing traits to new generations. GAs are useful in the selection of parameters to optimize a system's performance. A second potential use lies in testing and fitting quantitative models. Unlike any other book available, this interesting new text/reference takes you from the construction of a simple GA to advanced implementations. As you come to understand GAs and their processes, you will begin to understand the power of the genetic-based problem-solving paradigms that lie behind them.

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