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。
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.
作者
吴暖
谭力旗
杜剑
WU Nuan;TAN Liqi;DU Jian(College of Transportation Engineering,Dalian Jiaotong University,Dalian,Liaoning 116028,China)
出处
《计算机工程与应用》
北大核心
2025年第18期336-346,共11页
Computer Engineering and Applications
基金
国家自然科学基金(72174034)
辽宁省属本科高校基本科研业务费专项资金(LJ212410150001)
辽宁省教育厅基本科研青年项目(JYTQN2023008)。
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
pre-cooling facilities
genetic algorithm
adaptive large-scale neighborhood search algorithm
location-route optimization
uncertain demand
