需求不确定下多周期农产品预冷设施选址-路径优化

doi:10.3778/j.issn.1002-8331.2407-0023

摘要/Abstract

摘要： 针对传统固定式冷库成本高、灵活性差等问题，结合农产品周期性变化和不确定需求的特点，提出了综合应用预冷车和移动冷库的协调预冷机制，构建了以预冷模式、车场选址、相关车辆的车型与数量及路径等因素为变量，以系统成本最低为目标的多周期农产品预冷设施选址-路径优化模型。求解时，利用k-means聚类算法完成了车场选址及客户群划分，并设计混合自适应大规模邻域搜索遗传算法（HALNS-GA）完成了路径优化。通过算例验证了模型和算法的有效性；通过不同预冷机制下的成本对比和重要参数的灵敏度分析，验证了提出的预冷机制的经济性。该研究可为我国农村预冷服务的布局规划和路径提供参考。

关键词: 预冷设施, 遗传算法, 自适应大规模邻域搜索算法, 选址-路径优化, 不确定需求

Abstract: In response to the problems of high cost and poor flexibility of traditional fixed cold storage, this paper proposes a coordinated pre-cooling mechanism that integrated pre-cooling vehicles and mobile cold storage, taking into account the characteristics of periodic changes and uncertain demand of agricultural products. A multi-cycle agricultural product pre-cooling facility site selection path optimization model is constructed with the objective of minimizing system cost, considering variables such as pre-cooling mode, yard location, relevant vehicle types and quantities, and paths. And the k-means clustering algorithm is used to complete the location problem and customer group division of the parking lot, and a hybrid adaptive large-scale neighborhood search genetic algorithm (HALNS-GA) is designed to complete routing optimization. Finally, the effectiveness of the model and algorithm is verified through numerical examples. By comparing the costs under different pre-cooling mechanisms and analyzing the sensitivity of important parameters, the economic feasibility of the pre-cooling mechanism has been verified. This study can provide reference for the layout planning and routing of pre-cooling services in rural areas of China.

Key words: pre-cooling facilities, genetic algorithm, adaptive large-scale neighborhood search algorithm, location-route optimization, uncertain demand

吴暖, 谭力旗, 杜剑. 需求不确定下多周期农产品预冷设施选址-路径优化[J]. 计算机工程与应用, 2025, 61(18): 336-346.

WU Nuan, TAN Liqi, DU Jian. Location-Routing Optimization of Multi-Cycle Precooling Facilities for Agricultural Products Under Uncertain Demand[J]. Computer Engineering and Applications, 2025, 61(18): 336-346.

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