Title :
A comparison of stochastic local search and population based search
Author :
Mühlenbein, Heinz ; Mahnig, Thilo
Abstract :
For discrete optimization, the two basic search principles prevailing are stochastic local search and population based search. Local search has difficulties to get out of local optima. Here variable neighborhood search outperforms stochastic local search methods which accept worse points with a certain probability. Population based search performs best on problems with sharp gaps. It is outperformed by stochastic local search only when there are many paths to good local optima
Keywords :
genetic algorithms; probability; search problems; discrete optimization; genetic algorithms; local optima; population based search; probability; stochastic local search; univariate marginal distribution algorithm; variable neighborhood search; Bayesian methods; Couplings; Genetic algorithms; Genetic mutations; Maximum likelihood estimation; Optimization methods; Physics; Probability distribution; Search methods; Stochastic processes;
Conference_Titel :
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7282-4
DOI :
10.1109/CEC.2002.1006243
