基于改进细菌觅食算法的两阶段选址-路径规划  

Two-stage location-path planning based on improved bacterial foraging algorithm

作　　者：刘巍巍[1] 姜珊 祁朔 王迎春[1] LIU Weiwei;JIANG Shan;QI Shuo;WANG Yingchun(School of Mechanical Engineering,Shenyang University of Technology,Shenyang 110870,Liaoning,China)

机构地区：[1]沈阳工业大学机械工程学院,辽宁沈阳110870

出　　处：《沈阳工业大学学报》2025年第2期238-249,共12页Journal of Shenyang University of Technology

基　　金：辽宁省科技计划联合计划技术攻关项目(2024JH2/102600216)。

摘　　要：【目的】诸如名贵药材、有机水果等高值农产品往往具有高品质把控和高保鲜要求,通常需要经过初加工才能进入市场流通,故初加工中心的选址对平衡生产端分散的农村采购物流和配送点密集的城市配送物流起到重要的协调作用。鉴于高值农产品存在的农村采购物流与城市配送物流协调性差、运输成本占比过大的共性特征,如何在保证客户满意度的同时降本增效是高值农产品选址-路径规划中亟待解决的关键问题。【方法】提出了以总成本最小、客户满意度值最大为目标的两阶段物流选址-路径优化模型。第1阶段聚焦烘干中心选址,考虑建设成本、运输便利性、服务辐射范围等构建选址模型,优选出与中草药产区及用户地理位置相匹配的初加工中心;第2阶段基于筛选的初加工中心位置规划物流运输路径,以车辆容量、速度、时间窗为约束,综合运输、惩罚、货损成本与客户满意度构建多目标路径规划模型。为求解上述模型,将粒子群算法、差分进化理念及种群进化因子融入细菌觅食算法中,提出了混合多目标优化的MOBFO-NMOPSO算法,所设计算法通过引入基于小生境的多目标粒子群算法以提高求解精度;通过在复制操作中引入差分进化思想以保留种群的多样性;通过将种群进化因子引入迁徙操作以提高算法收敛速度。为验证模型及算法的有效性,首先将所提出的MOBFO-NMOPSO算法与NSGA-II、MOPSO、NMOPSO、GWOEDA、GA等算法对比,验证了算法在求解性能及求解速度上的优势。其次以S企业中草药供应链的实际数据为支撑,综合考虑烘干中心建设成本、车辆运输成本、时间惩罚成本及货损成本,全面求解两阶段选址-路径规划问题。【结果】仿真结果表明,优化后的企业运输成本降低了10.26%,客户满意度提升了44.84%,验证了模型在求解高值农产品物流规划问题上的有效性。�[Objective]High-value agricultural products such as precious medicinal materials and organic fruits generally have requirements for high-quality control and preservation and usually require initial processing before entering the market circulation.Therefore,the location of the initial processing center plays an important coordinating role in balancing the dispersed rural procurement logistics on the production end and the urban distribution logistics with dense distribution points.Given the common characteristics of poor coordination between rural procurement logistics and urban distribution logistics and a high proportion of transportation costs for high-value agricultural products,how to reduce costs and increase efficiency while ensuring customer satisfaction is a key issue that urgently needs to be addressed in the location-path planning of high-value agricultural products.[Methods]A two-stage logistics location-path planning model was proposed with the goals of minimizing total cost and maximizing customer satisfaction.The first stage focused on the location of the drying center,considering construction costs,transportation convenience,service radiation range,etc.,to construct a location model and optimize the initial processing center location that matches the Chinese herbal medicine production area and users′locations.In the second stage,logistics transportation paths were planned depending on the selected initial processing center location,with vehicle capacity,speed,and time windows taken as constraints.A multi-objective path planning model was constructed by integrating transportation,penalties,cargo damage costs,and customer satisfaction.To solve the above model,particle swarm algorithm,differential evolution concept,and population evolution factors were integrated into the bacterial foraging algorithm,and a hybrid multi-objective bacterial foraging optimization-niche multi-objective particle swarm optimization(MOBFO-NMOPSO)algorithm was proposed for multi-objective optimization.The designed algorith

关 键 词：选址路径 双目标模型 两阶段物流 细菌觅食算法 粒子群算法 差分进化 种群进化 车辆运输 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]