Linear programming with fuzzy objectives

This paper presents a new method for solving linear programming problems with fuzzy parameters in the objective function. To determine a compromise solution the authors do not reduce the set of infinitely many objective functions to a single ‘compromise objective function’ as done in classical deterministic or stochastic procedures. Here the problem is only reduced to a few extreme objective functions. The information contained in the membership functions can be used to any extent by a method called ‘α-level related pair formation’. Moreover, if different level sets are considered the stability of the optimal solution can be tested.