关键词: 动力电池回收；选址优化；机会约束规划；Fermat-Weber 问题；随机模拟遗传算法

Abstract: Considering the uncertainties in battery life distribution, new energy vehicle sales scale, and spatial distribution of recycling demand that affect the location selection of power battery recycling centers, this paper adopts the Weibull life model to depict the battery retirement process and introduces the spatial gravity model to describe the allocation relationship from regions to terminal recycling stations. With the objective of minimizing total transportation costs, a stochastic chance-constrained location model under regional constraints is constructed, and the model is equivalently transformed into a weighted Fermat-Weber problem with regional constraints. The analytical benchmark of the model is obtained through an analytical algorithm, and the optimal solution of the model is obtained through a stochastic simulated genetic algorithm. The case analysis validates the effectiveness of the proposed model, evaluates the convergence behavior and solution accuracy of the stochastic simulated genetic algorithm, and further investigates the effects of confidence level, number of candidate sites, and regional distribution on the location results.

Key words: power battery recycling; site selection optimization; chance-constrained programming; Fermat-Weber problem; stochastic simulated genetic algorithm