Solving constraint satisfaction problems by using coevolutionary genetic algorithms

Author

Handa, Hisashi ; Katai, Osamu ; Baba, Norio ; Sawaragi, Tetsuo

Author_Institution

Dept. of Precision Eng., Kyoto Univ., Japan

fYear

1998

fDate

4-9 May 1998

Firstpage

21

Lastpage

26

Abstract

In this paper, Coevolutionary Genetic Algorithm for solving Constraint Satisfaction Problems (CSPs) is proposed. It consists of two Genetic Algorithms (GAs): a traditional GA and another GA to search for good schemata in the former GA. These GAs evolve in two levels, i.e., phenotype-level and schema-level, and affect with each other through genetic operations. To search for solutions effectively, we devise new genetic operator by utilizing search mechanism of solution synthesis approach used in CSP community. Computational results on general CSPs confirm the effectiveness of our approach

Keywords

constraint theory; genetic algorithms; search problems; coevolutionary genetic algorithms; constraint satisfaction problems; genetic operations; phenotype-level; schema-level; Cultural differences; Distributed processing; Evolutionary computation; Genetic algorithms; Genetic engineering; Genetic mutations; Information science; Precision engineering; Problem-solving; Search methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on

Conference_Location

Anchorage, AK

Print_ISBN

0-7803-4869-9

Type

conf

DOI

10.1109/ICEC.1998.699070

Filename

699070