Practical Handbook of Genetic Algorithms

Regular price €198.40
Boltzmann Selection
Category=UYAM
Chunk Size
Cosmid Clone
Dynamic Scheduling Algorithms
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_non-fiction
evolutionary computation
Execution Times
Fitness Function
Fragment Matches
GA
genetic algorithm coding
Genetic Sectoring
KDEL Sequence
Linear Ranking
Local Post-optimization
MT
multi-niche crowding
Parallel GAs
PBIL
Proportional Selection
Scheduling Algorithms
Scheduling Overhead
Scheduling Steps
Search Algorithm
SSE
structured genetic algorithm
Tabu Search Heuristic
VRP.

Product details

  • ISBN 9780849325298
  • Weight: 826g
  • Dimensions: 156 x 234mm
  • Publication Date: 15 Aug 1995
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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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.

Chambers, Lance D.