| 震后初期应急物资配送的模糊多目标选址-多式联运问题 |
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| 引用本文： | 李双琳,马祖军,郑斌,代颖.震后初期应急物资配送的模糊多目标选址-多式联运问题[J].中国管理科学,2013,0(2):144-151. |
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| 作者姓名： | 李双琳 马祖军 郑斌 代颖 |
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| 作者单位： | 1. 西南交通大学交通运输与物流学院, 四川 成都 610031;2. 西南交通大学经济管理学院物流与应急管理研究所, 四川 成都 610031 |
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| 基金项目： | 国家自然科学基金资助项目(90924012,71090402);教育部新世纪优秀人才支持计划项目(NCET-10-0706);教育部人文社会科学研究项目(08JC630067);四川省青年科技基金项目(09ZQ026-021);四川省哲学社会科学研究规划项目(SC11B049);四川省学术和技术带头人培养资金项目(川人社办发[2011]441号);中央高校基本科研业务费专项资金资助项目(SWJTU11CX152,2682013CX073);富士康科技集团项目(11F81210005) |
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| 摘 要： | 针对震后初期应急物资配送系统优化问题,考虑应急物资需求模糊情况下应急物资配送中心选址和应急物资多式联运安排的集成决策,以应急物资配送总时间最短和受灾点应急物资未满足的总损失最小为目标,建立了一个震后应急物资配送的多目标选址-多式联运问题优化模型,设计了一种采用二维编码的非支配排序多目标遗传算法,并对该算法进行了复杂性分析。算例分析结果表明:该算法可以在得到Pareto前沿的同时,根据决策者偏好在Pareto前沿面上给出各种优化决策方案。
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| 关 键 词： | 地震灾害 应急物资 选址 多式联运 多目标优化 遗传算法 |
| 收稿时间： | 2011-10-11; |
| 修稿时间： | 2012-05-22 |
Fuzzy Multi-Objective Location-Multimodal Transportation Problem for Relief Delivery during the Initial Post-earthquake Period |
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| LI Shuang-lin,MA Zu-jun,ZHENG Bin,DAI Ying.Fuzzy Multi-Objective Location-Multimodal Transportation Problem for Relief Delivery during the Initial Post-earthquake Period[J].Chinese Journal of Management Science,2013,0(2):144-151. |
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| Authors: | LI Shuang-lin MA Zu-jun ZHENG Bin DAI Ying |
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| Institution: | 1. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China;2. Institute for Logistics and Emergency Management, School of Economics and Management, Southwest Jiaotong University, Chengdu 610031, China |
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| Abstract: | To optimize emergency logistics system for relief delivery during the initial post-earthquake period, the joint decision of emergency facility location-allocation and multimodal transportation scheduling are investigated. A multi-objective location-multimodal transportation model is developed to minimize the total delivery time and total losses due to insufficient supplies. A no-dominate sort genetic algorithm based on bi-dimension encoding method is proposed and its algorithm complexity is analyzed. The results of a numerical example show that the algorithm can find the Pareto front and attain varied optimal solutions on the Pareto front according to the preferences of decision makers. |
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| Keywords: | earthquake disasters relief materials location multimodal transportation multi-objective optimization genetic algorithm |
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