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定位-路径问题综述

胡大伟 陈希琼 高扬

胡大伟,陈希琼,高扬.定位-路径问题综述[J].交通运输工程学报,2018,18(01):111-129.
引用本文: 胡大伟,陈希琼,高扬.定位-路径问题综述[J].交通运输工程学报,2018,18(01):111-129.
HU Da-wei,CHEN Xi-qiong,GAO Yang.Review on location-routing problem[J].Journal of Traffic and Transportation Engineering,2018,18(01):111-129.
Citation: HU Da-wei,CHEN Xi-qiong,GAO Yang.Review on location-routing problem[J].Journal of Traffic and Transportation Engineering,2018,18(01):111-129.

定位-路径问题综述

基金项目: 国家自然科学基金项目(61503043); 中央高校基本科研业务费专项资金项目(310822150020,300102228402)
详细信息
    作者简介:

    胡大伟(1963-),男,北京人,长安大学教授,工学博士,从事交通运输规划研究。

  • 中图分类号: U491.51

Review on location-routing problem

  • 摘要: 研究了定位-路径问题(LRP),总结了国内外LRP模型及其扩展模型,比较了LRP模型求解算法的适用性,分析了LRP测试算例的节点分布和数据规模,提出了LRP研究的主要方向。研究结果表明:LRP模型从基于基础网络的最简化问题(带容量约束的LRP, CLRP)向多方向模型进行扩展,包括基于网络复杂化的LRP扩展,如特定网络系统的多目标LRP(MOLRP)、同时取送货LRP(LRPSPD)、接驳转运中心LRP(CDCLRP)、两阶段LRP(2E-LRP)、选址-弧路径问题(LARP)、卡车和拖车路径问题(TTRP)与设施地点为二维连续的LRP(PLRP),基础网络参数不确定化的LRP,包括带模糊数据的LRP与多计划周期LRP(MPLRP),且正在向更切合实际的问题如高度集成、不确定与动态LRP发展; LRP算法方面,精确算法仅可用于求解小规模LRP,主要LRP求解算法由早期的智能算法逐渐转向元启发式算法、基于邻域搜索优化的算法与混合算法方向发展,这些改进算法均基于特定LRP设计,具有更好的求解性能,尤其是采用基于多种破坏和修复因子的自适应大邻域搜索算法求解大规模LRP取得了较好的解,且其改造性极强; 常用LRP测试算例的节点呈现均匀分布、堆分布及均匀与堆混合分布,且逐渐产生了适用于2E-LRP与LRPSPD等扩展LRP的测试算例; 根据物流市场环境变化和需求,提出LRP未来扩展研究的主要方向,包括多阶段LRP的扩展(如2E-LRPSPD、考虑库存的2E-LRP等)、节点二维连续的LRP、客户含优先级的带竞争或盈利LRP、混合不确定LRP等切合实际的问题; 提出了LRP求解算法未来方向,包括设计新型精确算法求解中、大规模LRP,设计更准确更高效的组合启发式算法与应用近似算法求解LRP及扩展LRP的最优解。

     

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  • 收稿日期:  2017-09-20
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