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
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;
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
DOI :
10.1109/ICEC.1994.350002
