Title :
A new fitness function for discovering a lot of satisfiable solutions in constraint satisfaction problems
Author :
Handa, Hisashi ; Katai, Osamu ; Konishi, Tadataka ; Baba, Mitsuru
Author_Institution :
Dept. of Inf. Technol., Okayama Univ., Japan
Abstract :
In this paper, we discuss how many satisfiable solutions a genetic algorithm can find in a problem instance of a constraint satisfaction problems in a single execution. Hence, we propose a framework for a new fitness function which can be applied to traditional fitness functions. However, the mechanism of the proposed fitness function is quite simple, and several experimental results on a variety of instances of general constraint satisfaction problems demonstrate the effectiveness of the proposed fitness function
Keywords :
constraint theory; functions; genetic algorithms; operations research; constraint satisfaction problems; fitness function; genetic algorithm; problem instances; satisfiable solutions discovery; Artificial intelligence; Books; Computer simulation; Genetic algorithms; Genetic engineering; Informatics; Information technology;
Conference_Titel :
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location :
La Jolla, CA
Print_ISBN :
0-7803-6375-2
DOI :
10.1109/CEC.2000.870783
