Lead Battery Reverse Logistics Center Location Model and Simulation Analysis Based on Genetic Algorithm and Greedy Algorithm

Abstract

Lead acid batteries, as batteries with both cost and performance, are widely used in various fields such as transportation and communication. However, improper recycling can exacerbate environmental pollution. In response to this phenomenon, a hybrid lead-acid battery reverse logistics center location model based on genetic algorithm and greedy algorithm is proposed. Firstly, the basic mode of reverse logistics is introduced, and based on relevant location principles such as non-zero constraints and cost control conditions, a basic network model for reverse logistics center location for lead-acid batteries is established. Subsequently, genetic algorithm and greedy algorithm are introduced to solve and analyze the overall model. Through the performance of each algorithm, they are applied in different steps, and the running process of the hybrid algorithm is designed. Finally, the performance of the model is analyzed through experiments. The experimental results showed that the Gap value of the model used in the study was 51.02% lower on average than the other models, the total cost was reduced by 39.96% on average, and the sustainability score was 24.69% higher than the other models on average. Therefore, the research proposes a lead-acid battery reverse logistics center location model based on genetic greedy hybrid algorithm, which can achieve low-cost and short transportation route center point calculation.