Title :
Evolutionary diffusion optimization. II. Performance assessment
Author :
Tsui, Kwok Ching ; Liu, Jiming
Author_Institution :
Dept. of Comput. Sci., Hong Kong Baptist Univ., Kowloon, China
fDate :
6/24/1905 12:00:00 AM
Abstract :
A new population-based stochastic search algorithm called evolutionary diffusion optimization (EDO) inspired by diffusion in nature has been proposed. This article compares the performance of EDO with simulated annealing and fast evolutionary programming. Experimental results show that EDO performs better than SA and FEP in some cases
Keywords :
diffusion; evolutionary computation; optimisation; search problems; stochastic processes; evolutionary diffusion optimization; performance assessment; population-based stochastic search algorithm; Ant colony optimization; Computational modeling; Computer science; Cultural differences; Data structures; Evolutionary computation; Genetic programming; Particle swarm optimization; Simulated annealing; 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.2002.1004428
