An inexact approach based on Genetic Algorithm for fuzzy programming problems

In this paper, an inexact approach is proposed for the fuzzy nonlinear programming problems. Instead of finding an exact optimal solution, we use a Genetic Algorithm (GA) with mutation along the weighted total forces direction to find a family of solutions with acceptable membership degree under different criteria preferred by the decision maker (DM). The total forces are given based on the idea that is to mimic the physics of electromagnetism by considering each individual as electrical charge. The method is applied to actual production problems. We achieved a family of solution under different criteria. The numerical results illustrate the accuracy and efficiency of the algorithm.