Reverse Logistics Location Based on Energy Consumption: Modeling and Multi-Objective Optimization Method

The low-carbon economy, as a major trend of global economic development, has been a widespread concern, which is a rare opportunity to realize the transformation of the economic way in China. The realization of a low-carbon economy requires improved resource utilization efficiency and reduced carbon emissions. The reasonable location of logistics nodes is of great significance in the optimization of a logistics network. This study formulates a double objective function optimization model of reverse logistics facility location considering the balance between the functional objectives of the carbon emissions and the benefits. A hybrid multi-objective optimization algorithm that combines a gravitation algorithm and a particle swarm optimization algorithm is proposed to solve this reverse logistics facility location model. The mobile phone recycling logistics network in Jilin Province is applied as the case study to verify the feasibility of the proposed reverse logistics facility location model and solution method. Analysis and discussion are conducted to monitor the robustness of the results. The results prove that this approach provides an effective tool to solve the multi-objective optimization problem of reverse logistics location