Title :
Asynchronous self-adjustable island genetic algorithm for multi-objective optimization problems
Author :
Zhu, Zhong-Yao ; Leung, Kwong-Sak
Author_Institution :
Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, China
Abstract :
In this paper, we present a new algorithm-asynchronous self-adjustable island genetic algorithm (aSAIGA) for multi-objective optimization problems. The proposed algorithm is built upon the coarse-grained architecture, which is divided into sub-processes and distributed amongst several island processors. In each sub-process, an asynchronous communication operation and a self-adjusting operation are adopted to enhance the algorithm in both speedup and global searching capabilities. Satisfactory results and significant speedup can be achieved by aSAIGA, as shown by simulation
Keywords :
genetic algorithms; search problems; self-adjusting systems; asynchronous communication operation; asynchronous self-adjustable island genetic algorithm; coarse-grained architecture; global searching; island processors; multi-objective optimization problems; self-adjusting operation; simulation; speedup; sub-processes; Asynchronous communication; Capacitive sensors; Computer architecture; Computer science; Decision making; Evolutionary computation; Genetic algorithms; Spine;
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.2002.1007034
