DocumentCode
2325083
Title
Extended forking genetic algorithm for order representation (o-fGA)
Author
Tsutsui, Shigeyoshi ; Fujimoto, Yoshiji ; Hayashi, Isao
Author_Institution
Dept. of Manage. & Inf. Sci., Hannan Univ., Osaka, Japan
fYear
1994
fDate
27-29 Jun 1994
Firstpage
639
Abstract
There are two types of GAs with difference of their representation of strings. They are the binary coded GA and the order-based GA. We´ve already proposed a new type of binary coded GA, called the forking GA (fGA), as a kind of multi-population GA and showed that the searching power of the fGA is superior to the standard GA. The distinguished feature of the fGA is that each population takes a different role in optimization. That is, each population is responsible for searching in a non-overlapping sub-area of the search space. In this paper, the extended forking GA for order representation, called the o-fGA, is proposed. The results of experiments for the blind traveling salesperson problem (TSP) show that the approach of fGA is also effective for the order representation
Keywords
combinatorial mathematics; genetic algorithms; optimisation; search problems; binary coded GA; blind traveling salesperson problem; extended forking genetic algorithm; forking genetic algorithm; order representation; order-based GA; searching power; Code standards; Convergence; Genetic algorithms; Informatics; Information management; Information science; Mathematics; Position measurement; Space exploration; Technology management;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the First IEEE Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1899-4
Type
conf
DOI
10.1109/ICEC.1994.349984
Filename
349984
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