A multi-center joint distribution optimization model considering carbon emissions and customer satisfaction

Logistics enterprises are searching for a sustainable solution between the economy and the environment under the concept of green logistics development. Given that, this study integrates carbon emission as one of the costs into the vehicle routing problem with time window (VRPTW) and establishes a multi-center joint distribution optimization model taking into account distribution cost, carbon emission, and customer satisfaction. In the study of carbon emissions, this paper selected the vehicle load rate and vehicle distance as the main indicators. An improved ant colony algorithm is designed to solve the model by introducing the elite strategy, the saving strategy, vehicle service rules, and customer selection rules. Simulation results show that compared with the traditional ant colony optimization and genetic algorithm, the improved ant colony algorithm can effectively reduce the distribution cost and carbon emission and, improve customer satisfaction.

Automated summary

This study incorporates carbon emission as a cost into the vehicle routing problem and establishes a multi-center joint distribution optimization model that considers the distribution cost, carbon emission, and customer satisfaction. The improved ant colony algorithm effectively reduces costs and carbon emissions while improving customer satisfaction.