A weighted possibilistic programming approach for sustainable vendor selection and order allocation in fuzzy environment

Abstract

This paper focused on the analysis of imprecise information in terms of many critical parameters for a multi-objective multi-item vendor selection-order allocation problem with price-breaks. We used both quantitative and qualitative criteria taking into account the economic, technological, social, environmental factors, and the price-breaks that were offered on order quantity following ‘all-unit discount schedule.’ We developed an optimization model that integrated fuzzy multi-objective integer linear programming and analytic hierarchy process techniques. A weighted possibilistic programming approach was presented to solve the optimization model, which simultaneously minimized (maximized) the best scenario, the likeliest scenario, and the worst scenario for the imprecise objective functions thereby avoiding situations that may force the solution process to divert. The integrated model and the solution approach were tested on the data set of an industrial case study. A detailed performance analysis and comparisons were done to show superiority of the proposed methodology over the existing related fuzzy programming approaches.