A combined fuzzy AHP and fuzzy goal programming approach for effective six-sigma project selection

This paper presents a combined fuzzy analytic hierarchy process (AHP) and fuzzy goal programming (GP) approach to determine the preferred compromise solution for six-sigma project selection problem with multiple objectives, in which the parameters are fuzzy in nature. Goal programming is an important technique for solving many decision/management problems. Fuzzy GP involves applying the fuzzy set theory to GP, thus allowing the model to take into account the vague aspirations of a decision-maker. In fact, the effective six-sigma project selection problem has been formulated as a fuzzy GP problem that includes six primary goals: maximize financial benefits, maximize process capability, maximize customer satisfaction, minimize cost, minimize project completion time and minimize risk. Fuzzy AHP is then used to specify judgments about the relative importance of each goal in terms of its contribution to the achievement of the overall goal. An illustration with a data set from a realistic situation is included to demonstrate the effectiveness of the proposed model.