摘要
针对生鲜农产品集货中点多量散、车载限制、货物易腐等特点,研究需求可拆分下生鲜农产品集货的路径优化。通过网点布局与网络需求、车辆路径与载量要求、产品特征与成本消耗等描述生鲜农产品集货基本问题,从制冷、货损、油耗三个方面构造总的集货成本,考虑需求拆分、流量均衡、车辆起始与服务等约束,建立集货路径优化模型;基于遗传算法,以序号排序标定适应度函数,改进轮盘赌选择,用精英策略进行算子分析与遗传操作,设计问题求解模式;最后,以湖南省某乡镇脐橙集货为例进行实证分析。案例分析结果表明:优化后,总集货成本下降19.34%,货损成本减少最多,达1550.86元;集货路径总数减少1条,拆分点由5个变为3个,且按需求进行深度拆分;总行驶里程与时间分别减少72.4 km、2.06 h,整体优化效果明显。研究结果对生鲜农产品集货管理的效率提升有借鉴意义。
The characteristics of gathering fresh agricultural products,such as multiple nodes,scattered demands,cargo restrictions,and product perishability,are considered in studying split delivery route optimization.The basic problem of the gather of fresh agricultural products are described through node layout,network demand,vehicle routing and load requirements,product characteristics,and cost factors.The total gathering cost is modeled based on three aspects:refrigeration,cargo damage,and fuel consumption.Constraints are designed around split delivery,flow balancing,and vehicle scheduling to construct an optimized gathering route model.Using a genetic algorithm,the fitness function is calibrated by serial number sorting,and roulette wheel selection is improved.An elite strategy is employed for operator analysis and genetic operations,leading to a proposed solution method.An empirical analysis of orange gathering in a township in Hunan Province demonstrates the results:the optimized total gathering cost decreases by 19.34%,with the cargo damage cost reducing the most,by 1550.86 yuan.The total number of gathering routes is reduced by 1,and the number of splitting nodes decreases from 5 to 3,reflecting a deeper split by demand.The total driving distance and time are reduced by 72.4 km and 2.06 hours,respectively,showing a significant overall optimization effect.The research provides valuable insights for improving the efficiency of fresh agricultural product collection.
作者
李利华
夏春平
普国东
冯谦
LI Lihua;XIA Chunping;PU Guodong;FENG Qian(School of Traffic and Transport Engineering,Changsha University of Science and Technology,Changsha 410114,China;Hunan Key Laboratory of Smart Roadway and Cooperative Vehicle-Infrastructure Systems,Changsha University of Science and Technology,Changsha 410114,China)
出处
《交通科学与工程》
2024年第4期136-144,共9页
Journal of Transport Science and Engineering
基金
湖南省哲学社会科学基金项目(22WTC12)
长沙理工大学智能道路与车路协同湖南省重点实验室开放基金资助项目(KFJ210702)
长沙理工大学研究生科研创新项目(CX2021SS03)。
关键词
需求可拆分
生鲜农产品
集货路径优化
遗传算法
split delivery
fresh agricultural product
gathered route optimization
genetic algorithm
