电商冷链配送：时间窗约束下的联合路径优化

E-Commerce Cold Chain Distribution: Joint Path Optimization under Time-Window Constraints

摘要: 随着电商行业的蓬勃发展，生鲜电商等细分领域逐渐兴起，冷链物流配送需求不断增加，成本控制与效率优化成为关键问题。针对带时间窗的电商冷链物流联合配送车辆路径问题展开研究，构建融合制冷成本和损坏成本等在内的多维度成本优化模型，并采用遗传算法与变邻域搜索算法相结合的混合算法进行求解。通过仿真实验得出：联合配送在多方面均优于独立配送；综合考虑全部成本可使配送总成本达到最优，实现经济与环境效益的平衡；电商企业在不同需求场景下可选择不同车型，为电商冷链物流企业降本增效，实现转型升级提供理论依据和决策支持。

Abstract: With the booming development of the e-commerce industry, fresh e-commerce and other subdivisions are gradually emerging, and the demand for cold chain logistics distribution is increasing. Cost control and efficiency optimization have become key issues. This study focuses on the joint distribution vehicle routing problem in e-commerce cold chain logistics with time windows. A multi-dimensional cost optimization model incorporating refrigeration costs and damage costs was constructed. A hybrid algorithm combining genetic algorithm and variable neighborhood search algorithm is used to solve the model. The simulation results showed that joint distribution outperforms independent distribution in many aspects. Considering all costs comprehensively can optimize the total distribution cost, achieving a balance between economic and environmental benefits. E-commerce enterprises can choose different vehicle types under different demand scenarios. This study provided theoretical basis and decision-making support for e-commerce cold chain logistics enterprises to reduce costs and improve efficiency, and to achieve transformation and upgrading.