Supplier selection and order allocation in closed-loop supply chain systems using hybrid Monte Carlo simulation and goal programming

Abstract

Supplier selection is an important strategic design decision in closed-loop supply chain systems. In addition, and after identifying the candidate suppliers, optimal order allocations are also considered as crucial tactical decisions. This research presents a multi-objective optimisation model to select the best suppliers and configure manufacturing and refurbishing facilities with the optimal number of parts and products in a closed-loop supply chain network. The objective functions in this research are formulated as total profit, total defective parts, total late delivered parts and economic risk factors of the candidate suppliers. The proposed multi-objective model is solved by hybrid Monte Carlo simulation integrated with three different variants of goal programming method. The effectiveness of the mathematical model and the proposed solution algorithms in obtaining Pareto-optimal solutions is demonstrated in a numerical example adopted from a real case study.