Title :
A fuzzy evolutionary approach to constrained optimisation problems
Author_Institution :
Fac. of Inf. Sci. & Eng, Univ. of Canberra, ACT, Australia
Abstract :
Non-linear constrained optimisation problems are fuzzified and a method of fuzzy evolutionary programming is introduced to solve the problems. In this method, the degrees of constraint satisfaction are used as weight factors for the potential solutions. The method is extended to stochastic programming problems and other analogous fuzzy optimisation problems
Keywords :
fuzzy logic; genetic algorithms; mathematical programming; nonlinear programming; operations research; stochastic programming; degrees of constraint satisfaction; fuzzy evolutionary approach; fuzzy evolutionary programming; fuzzy optimisation problems; nonlinear constrained optimisation problems; potential solutions; stochastic programming problems; weight factors; Australia; Constraint optimization; Evolutionary computation; Fuzzy sets; Genetic algorithms; Genetic programming; Operations research; Optimization methods; Shape control; Stochastic processes;
Conference_Titel :
Evolutionary Computation, 1996., Proceedings of IEEE International Conference on
Conference_Location :
Nagoya
Print_ISBN :
0-7803-2902-3
DOI :
10.1109/ICEC.1996.542374
