An interactive algorithm for multi-objective flow shop scheduling with fuzzy processing time through resolution method and TOPSIS

Abstract

This paper develops a method for solving a multi-objective flow shop scheduling in a fuzzy environment where processing times are fuzzy numbers. The objective functions are designed to simultaneously minimize the makespan (completion time), the mean flow time, and the machine idle time. For each objective function, a fuzzy subset in the decision space whose membership function represents the balance between feasibility degree of constraints and satisfaction degree of the goal is defined. Then, technique for order preference by similarity to an ideal solution (TOPSIS) method finds the nondominated solution in a multiple objective state. The TOPSIS method and the interactive resolution method are integrated in the proposed method to solve the multi-objective flow shop scheduling problem. One of the new contributions of this research is combining these two methods in solving this problem. The proposed algorithm provides a way to find a crisp solution for the fuzzy flow shop scheduling in a multi-objective state. Also, the proposed method yields a reasonable solution that represents the balance between the feasibility of a decision vector and the optimality for an objective function by the interactive participation of the decision maker in all steps of decision process. Application of the proposed method to flow shop scheduling is shown with two numerical examples. The results show that the algorithm could be applied for determining the most preferable sequence by finding a nondominated solution for different degrees of satisfaction of constraints, and with regard to objective value, where processing time is fuzzy.