%0 Journal Article
%T 考虑易腐品的越库中心车辆调度研究
Research on Truck Scheduling in Cross-Docking Centers for Perishable Goods
%A 范春阳
%A 潘飞
%J Modeling and Simulation
%P 52-65
%@ 2324-870X
%D 2025
%I Hans Publishing
%R 10.12677/mos.2025.143202
%X 随着物流行业竞争加剧，越库配送模式逐渐得到推广，尤其在易腐品物流中展现出明显优势。易腐品因其易变质特性，存储和运输难度大，多次搬运和长时间存储容易加速变质，增加损耗。越库模式通过减少商品的搬运次数和库存存储，提升了物流效率并减少了运输成本。本文提出将越库模式应用于易腐品转运过程的车辆调度，基于最小化总变质质量，构建混合整数数学规划模型，并设计基于车辆排序的遗传算法求解。通过数值分析对比最小化完工时间和最小化总变质质量模型，分析两种不同模型在易腐品越库转运过程中的优劣，为易腐品物流企业的越库实践提供指导，具有重要的现实意义。
With the intensification of competition in the logistics industry, the cross-docking distribution model has gradually been promoted and has shown obvious advantages especially in the logistics of perishable products. Perishable products are difficult to store and transport due to their perishable nature. Multiple handlings and long-term storage are likely to accelerate deterioration and increase losses. The cross-docking model improves logistics efficiency and reduces transportation costs by reducing the number of times goods are handled and inventory storage. This paper proposes to apply the cross-docking model to truck scheduling in the transshipment process of perishable products. Based on minimizing the total deteriorated quality, a mixed integer mathematical programming model is constructed, and a genetic algorithm based on truck sequencing is designed for solution. Through numerical analysis, the models of minimizing the makespan and minimizing the total deteriorated quality are compared, and the advantages and disadvantages of the two different models in the cross-docking transshipment process of perishable products are analyzed, which provides guidance for the cross-docking practice of perishable goods logistics enterprises and has important practical significance.
%K 易腐品，
%K 越库，
%K 车辆调度，
%K 遗传算法
Perishable Goods
%K Cross-Docking
%K Truck Scheduling
%K Genetic Algorithm
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=108941