DocumentCode :
292087
Title :
Constrained clustering and parallel genetic algorithm on a multiprocessor system FIN
Author :
Myung-Mook Jian ; Tatsumi, Shoji ; Kitamura, Yasuhiko ; Okumoto, Takaaki
Author_Institution :
Dept. of Inf. & Comput. Sci., Osaka City Univ., Japan
Volume :
2
fYear :
1994
fDate :
2-5 Oct 1994
Firstpage :
1920
Abstract :
Genetic algorithms (GA) are typically regarded as the unconstrained search procedure within the given representation space. But many actual problems hold one or more constraints that must be satisfied. In this paper, we consider the incorporation of constraints into fitness function and solve the constrained clustering problem using the GA through a multiprocessor system (FIN) which has a self-similarity network
Keywords :
constraint theory; genetic algorithms; operations research; parallel algorithms; travelling salesman problems; constrained clustering; fitness function; multiprocessor system FIN; parallel genetic algorithm; self-similarity network; travelling salesman problem; Annealing; Biological system modeling; Cities and towns; Clustering algorithms; Computer science; Cost function; Genetic algorithms; Multiprocessing systems; Search methods; Traveling salesman problems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-2129-4
Type :
conf
DOI :
10.1109/ICSMC.1994.400132
Filename :
400132
Link To Document :
بازگشت