Reducing the Carbon Emissions of the Decentralized Joint Distribution Alliance by Order Allocation: A 2-Stage Approach Based on Routing Optimization and Worst-Case Estimation

The primary cause of high carbon emissions due to inefficient transportation is the lack of cooperation among various logistics companies during distribution. Joint distribution mode represents an effective means to address this issue. However, research on the joint distribution mode primarily focuses on the centralized joint distribution mode. In the context of the decentralized joint distribution mode, logistics companies can autonomously choose their distribution routes based on the orders they are dispatched. If logistics companies unilaterally aim to reduce their own costs, it can easily lead to an increase in carbon emissions from the alliance, which can have adverse effects. This paper focuses on the decentralized joint distribution alliance and considers reducing carbon emissions through the allocation of the alliance’s order. A two-stage approach is proposed, based on routing optimization and worst-case estimation. The mathematical models for each stage are established and algorithms are designed. Subsequently, management recommendations are provided through numerical analysis. This paper aims to explore methods to address the challenges faced by decentralized joint distribution alliances.