Modelling and optimization for a type of fuzzy nonlinear programming problems in manufacturing systems

A model for a type of fuzzy nonlinear programming problems (FNP) is proposed. This paper develops an inexact approach to solve this type model of nonlinear programming problems. Instead of finding an exact optimal solution. This approach uses a genetic algorithm (GA) with mutation along the weighted gradient direction to find a family of solutions with acceptable membership degrees. Then by means of human-computer interaction, the solution preferred by the decision maker (DM) under different criteria can be achieved.