Self-Adaptive Heuristics for Evolutionary Computation
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- Hardcover
- Taschenbuch ausgewählt
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Sprache:Englisch
Fr. 138.00
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
28.10.2010
Abbildungen
XII, 182 p. 39 illus.
Verlag
Springer BerlinSeitenzahl
182
Maße (L/B/H)
23.5/15.5/1.1 cm
Gewicht
306 g
Auflage
Softcover reprint of hardcover 1st edition 2008
Sprache
Englisch
ISBN
978-3-642-08878-0
Evolutionary algorithms are successful biologically inspired meta-heuristics. Their success depends on adequate parameter settings. The question arises: how can evolutionary algorithms learn parameters automatically during the optimization? Evolution strategies gave an answer decades ago: self-adaptation. Their self-adaptive mutation control turned out to be exceptionally successful. But nevertheless self-adaptation has not achieved the attention it deserves.
This book introduces various types of self-adaptive parameters for evolutionary computation. Biased mutation for evolution strategies is useful for constrained search spaces. Self-adaptive inversion mutation accelerates the search on combinatorial TSP-like problems. After the analysis of self-adaptive crossover operators the book concentrates on premature convergence of self-adaptive mutation control at the constraint boundary. Besides extensive experiments, statistical tests and some theoretical investigations enrich the analysis of the proposed concepts.
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