DocumentCode
2325434
Title
Solving constraint satisfaction problems using genetic algorithms
Author
Eiben, A.E. ; Raué, P.E. ; Ruttkay, Zs
Author_Institution
Dept. of Math. & Comput. Sci., Vrije Univ., Amsterdam, Netherlands
fYear
1994
fDate
27-29 Jun 1994
Firstpage
542
Abstract
This article discusses the applicability of genetic algorithms (GAs) to solve constraint satisfaction problems (CSPs). We discuss the requirements and possibilities of defining so-called heuristic GAs (HGAs), which can be expected to be effective and efficient methods to solve CSPs since they adopt heuristics used in classical CSP solving search techniques. We present and analyse experimental results gained by testing different heuristic GAs on the N-queens problem and on the graph 3-colouring problem
Keywords
constraint handling; game theory; genetic algorithms; graph colouring; N-queens problem; constraint satisfaction problems; genetic algorithms; graph 3-colouring problem; heuristic GAs; Artificial intelligence; Computer science; Constraint optimization; Genetic algorithms; Mathematics; Search methods; Space exploration; Testing;
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.1994.350002
Filename
350002
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