Title :
On solving fuzzy constraint satisfaction problems with genetic algorithms
Author :
Kowalczyk, Ryszard
Author_Institution :
CSIRO, Carlton, Vic., Australia
Abstract :
An attempt to solve fuzzy constraint satisfaction problems (FCSPs) with the use of genetic algorithms (GAs) is presented in the paper. A fuzzy relation that represents the degrees of satisfaction of fuzzy constraints in a given FCSP is considered as an objective function of the respective unconstrained optimization problem. A solution of a FCSP such that all constraints are satisfied to the maximal degree is searched for with a GA using the objective function to evaluate the prospective solutions with respect to fuzzy constraint satisfaction. The presented approach is illustrated with an example of a FCSP taking into account different levels of fuzzy granulation influencing GA´s performance
Keywords :
constraint handling; fuzzy logic; genetic algorithms; fuzzy constraint satisfaction; fuzzy constraint satisfaction problems; fuzzy granulation; fuzzy relation; genetic algorithms; maximal degree; objective function; prospective solutions; respective unconstrained optimization problem; Aging; Australia; Constraint optimization; Design optimization; Filtering; Genetic algorithms; NP-complete problem; Open wireless architecture; Problem-solving; Resource management;
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.1998.700147
