| 随机需求应急物流多阶段定位-路径鲁棒优化研究 |
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| 引用本文： | 孙华丽,王循庆,薛耀锋.随机需求应急物流多阶段定位-路径鲁棒优化研究[J].运筹与管理,2013,22(6):45-51. |
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| 作者姓名： | 孙华丽 王循庆 薛耀锋 |
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| 作者单位： | 1.上海大学 管理学院,上海 200444;2.南开大学 商学院,天津 300071;3.华东师范大学上海数字化教育装备工程技术研究中心,上海 200062 |
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| 基金项目： | 国家自然科学基金资助项目(71203134);国家自然科学基金重大研究计划培育项目(91024002);教育部人文社会科学研究项目(10YJC630213) |
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| 摘 要： | 为提高应急物流系统的应急反应能力,论文针对需求随机变化的应急物流定位-路径问题,利用鲁棒优化的思想将灾区物资需求量表示为区间型数据,将应急救援过程划分为多个阶段,以总救援时间和系统总成本最小为目标,构建了多物资多运输车辆应急物流定位-路径优化模型,设计了改进的遗传算法对其进行求解。实例计算结果表明,该模型和算法可以有效地解决应急物流系统中需求随机变化的定位-路径问题,为政府机构应对重大突发事件提供科学的决策参考。
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| 关 键 词： | 应急物流 鲁棒优化 遗传算法 定位-路径问题 |
| 收稿时间： | 2012-06-18 |
Robust Optimization for Multi-Stage Location-Routing Problem with Stochastic Demand Under Emergency Logistics |
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| SUN Hua-li,WANG Xun-qing,XUE Yao-feng.Robust Optimization for Multi-Stage Location-Routing Problem with Stochastic Demand Under Emergency Logistics[J].Operations Research and Management Science,2013,22(6):45-51. |
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| Authors: | SUN Hua-li WANG Xun-qing XUE Yao-feng |
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| Institution: | 1. Management School, Shanghai University, Shanghai 200444, China;2. Business School ,Nankai University,Tianjin 300071, China;3. e-Education System Engineering Research Center, East China Normal University, Shanghai 200062, China |
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| Abstract: | To improve the response capability of emergency logistics system, a stochastic demand location-routing problem in emergency logistics system is studied. Relief commodities requirements of demand points are presented by intervals based on robust optimization and emergency relief procedures are divided into multi-stages, then the model of emergency location-routing problem with multi-materials multi-vehicles is developed to minimize the total system costs and total transportation time. An improved genetic algorithm is proposed to solve the model. The results show that the model and algorithm are effective for resolving the location-routing problem with stochastic demand in emergency logistics system, and it can provide scientific decision-making for government responding to major emergencies. |
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| Keywords: | emergency logistics robust optimization genetic algorithm location-routing problem |
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