Integrating fuzzy TOPSIS and goal programming for multiple objective integrated procurement-production planning

Abstract

In this paper, a four-phase approach for Integrated Procurement-Production (IPP) tactical planning in a multiechelon, multi-product and multi-period Supply Chain (SC) network is proposed. To account for ambiguity and vagueness in some real-world data and preferences, in the first phase of the approach, the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (fuzzy TOPSIS) method is used to obtain the overall performance and risk ratings of the suppliers with regard to a set of qualitative and quantitative criteria. In the second phase, we introduce a novel multi-objective possibilistic mixed integer linear programming model (MOPMILP) for solving an IPP planning considering conflicting goals simultaneously: maximization of the overall performance and minimization of the overall risk. Then, after converting this MOPMILP model into an equivalent crisp multi-objective mixed integer linear programming (MOMILP) model, we use the Goal Programming (GP) approach to solve this MOMILP model in order to find an efficient compromise solution (i.e. an efficient procurement production plan) for the whole SC. The proposed approach and solution methodology are validated through a numerical example.