000 01532 a2200253 4500
005 20250526161932.0
008 250430041995xx 4 eng
020 _a9780849325298
_qBB
037 _bTaylor & Francis
_cGBP 160.00
_fBB
040 _a01
041 _aeng
072 7 _aUY
_2thema
072 7 _aUB
_2thema
072 7 _aUY
_2bic
072 7 _aUB
_2bic
072 7 _aMAT000000
_2bisac
072 7 _aMAT021000
_2bisac
100 1 _aLance D. Chambers
_9904
245 1 0 _aPractical Handbook of Genetic Algorithms
_bNew Frontiers, Volume II
250 _a1
260 _bCRC Press
_c19950815
300 _a448 p
520 _bThe 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.
999 _c10570
_d10570