Optimizing Multi-Objective Reverse Logistics Network Structure through Analytical Hierarchical Process and Decision Tree Analysis

Reverse logistics is an important aspect of supply chain management, as it involves the return and disposal of products, materials, and equipment. To make strategic and cost-effective decisions about reverse logistics, companies need to have a systematic method for evaluating and comparing different options. In this study, we propose the use of the analytical hierarchical process (AHP) and decision tree analysis (DTA) as decisionmaking tools for configuring a reverse logistics network. The AHP allows the decision-makers to consider a wide range of factors when making decisions and to weigh the relative importance of each factor, while DTA provides a measure of the investment cost under uncertainty. We demonstrate the use of AHP and DTA through a case study of an electronics company that has multiple return channels and different disposition actions for returned products (i.e. refurbish or dispose off). Our results show that AHP and DTA can be used together to make informed, objective decisions about reverse logistics and to optimize the efficiency and cost of the reverse logistics network.