FUZZY NONLINEAR GOAL PROGRAMMING USING GENETIC ALGORITHM

Goal programming(GP) is a powerful method which involves multiobjectiv es and is one of the excellent models in many real-world problems. The goal programming is to establish specific goals for each priorty leve l, formulate objective functions for each goal, and then seek a soluti on that minimize the deviations of these objective functions from thei r respective goals. Often, in real-world problems the objectives are i mprecise (or fuzzy). Recently, genetic algorithms are used to solve ma ny real-world problems and have received a great deal of attention abo ut their ability as optimization techniques for multiobjective optimiz ation problems. This paper is attempt to apply these genetic algorithm s to the goal programming problems which involve imprecise(or fuzzy) n onlinear information. Finally, we try to get some numerical experiment s which have multiobjectives, and imprecise nonlinear information, usi ng goal programming and genetic algorithm. (C) 1997 Elsevier Science L td.