Title :
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
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;
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
DOI :
10.1109/ICEC.1998.699070
