Robust design for a multi-echelon regional construction and demolition waste reverse logistics network based on decision Maker’s conservative attitude

Abstract

Improving the robustness of a reverse logistics network for construction and demolition waste (C&DW) can increase the ability of the network to mitigate supply uncertainty. However, a very conservative network may entail a higher price for its increased robustness. Thus, to maximize the robustness decision utility, decision-makers need to make a trade-off between relative robustness against uncertain situations and the price of such robustness. In this paper, we argue that facility capacity acquisition can improve the robustness of the network. We use a robust optimization method to establish the decision-making model for this problem, and propose a way to prove the model’s effectiveness in providing a lower bound of network robustness. Then the study takes on a real case in the Chongming district of Shanghai, China, and conducts a Monte Carlo simulation to investigate the trade-off performance. The results show that based on the decision-maker’s conservative attitude toward uncertain situations, the proposed model can adjust the robustness of the reverse logistics network. They also show that accepting a lower degree of robustness will result in substantial savings, due to the high “price” of robustness. This study provides a decision tool to help design a robust reverse logistics network under uncertain situations.