Title :
RasID-GA with Simplex Crossover(SPX) for Optimization problems
Author :
Sohn, Dongkyu ; Mabu, Shingo ; Hirasawa, Kotaro ; Hu, Jinglu
Author_Institution :
Waseda Univ., Fukuoka
Abstract :
In this paper, we propose RasID-GA (an abbreviation of adaptive random search with intensification and diversification combined with genetic algorithm) which improves the ability of diversification searching with Simplex Crossover (SPX). SPX generates the offspring based on uniform probability distribution and uses the M + 1 number of parent vectors, where M is the dimension of the vector. The RasID-GA with simplex crossover is compared with parallel RasIDs and GA with simplex crossover using 23 different objective functions having no local minima, a small number of local minima and a large number of local minima.
Keywords :
genetic algorithms; probability; random processes; search problems; adaptive random search; genetic algorithm; objective function; optimization problem; simplex crossover; uniform probability distribution; Evolution (biology); Evolutionary computation; Genetic algorithms; Mathematics; Optimization methods; Probability density function; Probability distribution; Production systems; Search methods;
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9487-9
DOI :
10.1109/CEC.2006.1688690