Abstract: Location-routing problem, as an important issue in supply chain management, has received a lot of attention. This paper develops a multi-period fuzzy chance-constrained optimization model for the reliable green location-routing problem under fuzzy demand, which minimizes total costs of logistics and fuel consumption with satisfying the transportation reliability constraint and the fuzzy chance constraints of facility capacity and vehicle capacity. To solve the model, a hybrid genetic algorithm（HGA） is designed. In order to verify the performance of the proposed algorithm and the rationality of the model, simulation experiments of different scales are carried out, and the results show the effectiveness of the algorithm and the rationality of the model. Finally, the influence of confidence level and reliability level on the final solution is analyzed by numerical experiments.

Key words: location-routing problem, fuzzy demand, reliability, genetic algorithm

摘要： 选址-路径问题作为供应链管理中的重要问题已经得到大量关注。针对模糊需求下的可靠性绿色选址-路径问题，建立多周期的模糊机会约束优化模型，在满足运输线路可靠性、设施能力和车辆能力模糊机会约束条件下最小化物流及燃油消耗成本。为了对模型进行求解，设计一种混合遗传算法（HGA）。为了验证所提出算法的性能和模型的合理性，进行了不同规模的仿真实验，结果表明了算法的有效性和模型的合理性。最后通过数值实验分析了置信水平和可靠性水平对最终解的影响。

关键词: 选址-路径问题, 模糊需求, 可靠性, 遗传算法