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
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