An introduction to genetic algorithms for numerical optimization

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Book, 64 p, March 2002
Contents
Optimization and hill climbing
The simplex method
Iterated simplex
A set of test problems
Performance of the simplex and iterated simplex methods
Evolution optimization and genetic algorithms
Biological evolution
The power of cumulative selection
A basic genetic algorithm
Information transfer in genetic algorithms
A genetic algorithm for numerical optimization
Overview and problem de nition
Minimal algorithmic components
Additional components
A case study
Hamming walls and creep mutation
Performance on test problems
A real application
Binary stars

Author(s): Charbonneau P.

Language: English
Commentary: 1368220
Tags: Информатика и вычислительная техника;Искусственный интеллект;Эволюционные алгоритмы