Measuring the satisfaction of constraints in fuzzy linear programming

The paper proposes a new kind of method for solving fuzzy linear programming problems based on the satisfaction (or fulfillment) degree of the constraints. Using a new ranking method of fuzzy numbers, the fulfillment of the constraints can be measured. Then the properties of the ranking index are discussed. With this ranking index, the decision maker can make the constraints tight or loose based on his optimistic or pessimistic attitude and get the optimal solution from the fuzzy constraint space. The corresponding value of objective distribution function can be obtained. A numerical example illustrates the merits of the approach. (C) 2001 Published by Elsevier Science B.V.