Global Optimization Algorithms: Theory and Application
by Thomas Weise
Number of pages: 842
This book is about global optimization algorithms, which are methods to find optimal solutions for given problems. It especially focuses on evolutionary computation by discussing evolutionary algorithms, genetic algorithms, genetic programming, learning classifier systems, evolution strategy, differential evolution, particle swarm optimization, and ant colony optimization. The book also elaborates on other meta-heuristics, such as simulated annealing, hill climbing, tabu search, and random optimization.
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by R. Poli, W. B. Langdon, N. F. McPhee - Lulu.com
This book is an introduction to genetic programming GP is a systematic method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. GP has generated lots of results and applications.
by L. Spector, W.B. Langdon, U. O'Reilly, P.J. Angeline - The MIT Press
Genetic programming is a form of evolutionary computation that evolves programs and program-like executable structures for developing reliable applications. This volume highlights the recent technical advances in this increasingly popular field.
by Eisuke Kita - InTech
Evolutionary algorithms are successively applied to wide optimization problems in the engineering, marketing, operations research, and social science, such as include scheduling, genetics, material selection, structural design and so on.
by Adam Marczyk - The TalkOrigins Archive
Creationists argue that evolutionary processes cannot create new information, or that evolution has no practical benefits. This article disproves those claims by describing the explosive growth and widespread applications of genetic algorithms.