A new method for computing a Pareto optimal solution of fuzzy multi-objective linear programming problems

Consider the multi-objective linear programming (MOLP) problems of maximizing given linear objective functions with common constraints for the feasible space. There are various methods for solving the MOLP problems. Zimmermann [1], using the notions of fuzzy set theory, introduced certain membership functions for the objectives and used a maxmin approach.The maxmin approach for solving the MOLP problems has two shortcomings: (1) It needs to solve two problems to find a Pareto optimal solution, and (2) it determines the value of an alternative by its minimal attribute, disregarding all the others regardless of their values [2].We present a new ordering scheme of the alternatives to avoid the maxmin's shortcomings, while preserving its merits. The following definition, characterizing preferred solutions, are used for ordering