MODEL AND METHOD BASED ON GA FOR NONLINEAR-PROGRAMMING PROBLEMS WITH FUZZY OBJECTIVE AND RESOURCES

As an extension of our previous paper (Tang and Wang 1997) for solving nonlinear programming problems, this paper focuses on a symmetric mod el for a kind of fuzzy nonlinear programming problems (FO/RNP) by way of a special Genetic Algorithm (GA) with mutation along the weighted g radient direction. It uses an r-power type of membership function to f ormulate a kind of fuzzy objective and two kinds of fuzzy resource con straints which are commonly used in actual production problems. Th sol ution to FO/RNP may be transformed into the solution to three kinds of model according to different kinds of criteria preferred by the decis ion maker (DM). This paper develops an inexact approach to solve this type of model of nonlinear programming problems. Instead of finding an exact optimal solution, this approach uses a GA with mutation along t he weighted gradient direction to find a family of solutions with acce ptable membership degrees. Then by means of the human-computer interac tion, the solutions preferred by the (DM) under different criteria can be achieved. The overall procedure for FO/RNP is also developed in th is paper, it may supply a preliminary framework for practical applicat ion of the FO/RNP model.