A Robust Multi-Critia Decision-Making Procedure for Outsourcing Decisions in Reverse Logistics

Abstract

Product return processes are managed by Reverse Logistics (RL) which is a systematic way of putting recovery activities into action successfully. One of the research topics in the RL field is “outsourcing” that has a strategic role in achievement of profitability and compatibility. It mainly includes three decisions: (1) make all operations by the firm itself, (2) all reverse logistics operations are outsourced by the firm, and (3) operations are partially outsourced. This paper proposes a multi phased new approach that combines cloud based design optimization (CBDO) with Analytical Hierarchy Process (AHP) in order to select the best outsourcing alternative under uncertainties. As a novel approach, CBDO is good at dealing with high uncertainty, in computationally satisfactory way. Because the perceptions and ideas of managers can change across time, traditional multi criteria decision making (MCDM) techniques such as AHP is strengthened by a robust technique such as CBDO in our study. In order to verify the performance of the proposed model, an illustrative study is conducted.