路径-脆弱点最短距离最大化的危险品运输网络设计
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摘要
为了实现危险品运输网络的有效设计,进而降低危险品运输风险。将分布于公路两侧的医院、学校、居民区、购物中心等人口集聚场所定义为"脆弱点",并通过计算运输路径和脆弱点间的加权距离来评估路段风险;结合双层理论构建模型,上层规划为政府的网络设计问题,通过关闭部分路段来最大化危险品车辆行驶路径与各脆弱点间的最小加权距离,下层规划则为承运商的车辆路径选择问题;为求解模型,设计1类启发式算法,并对算法的计算时间复杂性进行证明,最后根据算例分析发现,该算法经过有限数量的迭代即可得到风险最小的、次小的、…、第k小的运输路径及对应的路段关闭方案,为寻求兼顾运输风险和运输成本的最优方案提供决策支持。
In order to carry out the effective design of dangerous goods transportation network,thus reduce the risk of dangerous goods transportation,the population aggregation places such as hospital,school,residential area,shopping center laying beside the roads were defined as the "vulnerable points",and the risk of road section was assessed through calculating the weighted distance between the transportation path and the vulnerable points. A model was constructed by using the bi-level theory,the upper level programming was the network design problem of government,and the minimum weighted distance between the path of dangerous goods vehicles and each vulnerable point was maximized by closing some road sections,while the lower level programming was the vehicle path selection problem of carrier. A heuristic algorithm was proposed to solve the model,and the complexity of calculation time of the algorithm was proved. Through the case analysis,it showed that the algorithm could obtain the transportation paths with the smallest risk,the second-smallest risk,up to the kth-smallest risk and their corresponding schemes of road section closing through the finite iteration. It provides the decision support for the government to seek the optimal scheme giving consideration to both transport risk and transport cost.
In order to carry out the effective design of dangerous goods transportation network,thus reduce the risk of dangerous goods transportation,the population aggregation places such as hospital,school,residential area,shopping center laying beside the roads were defined as the "vulnerable points",and the risk of road section was assessed through calculating the weighted distance between the transportation path and the vulnerable points. A model was constructed by using the bi-level theory,the upper level programming was the network design problem of government,and the minimum weighted distance between the path of dangerous goods vehicles and each vulnerable point was maximized by closing some road sections,while the lower level programming was the vehicle path selection problem of carrier. A heuristic algorithm was proposed to solve the model,and the complexity of calculation time of the algorithm was proved. Through the case analysis,it showed that the algorithm could obtain the transportation paths with the smallest risk,the second-smallest risk,up to the kth-smallest risk and their corresponding schemes of road section closing through the finite iteration. It provides the decision support for the government to seek the optimal scheme giving consideration to both transport risk and transport cost.
引文
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[11]魏航,钟智龙,陈静.有害物品运输网络设计与运输路径优化研究[J].管理工程学报,2016,30(2):233-242.WEI Hang,ZHONG Zhilong,CHEN Jing. Network design for route control of hazardous materials transportation[J]. Journal of Industrial Engineering/Engineering Management, 2016, 30(2):233-242.
[12] SUN L,KARWAN M H,KWON C. Robust hazmat network design problems considering risk uncertainty[J]. Transportation Science,2016,50(4):1188-1203.
[13] ESFANDEHh T,KWON C,BATTA R. Time-dependent hazardous-materials network design problem[J]. Transportation Science,2017,52(2):454-473.
[14] MARCOTTE P,MERCIER A,SAVARD G. Toll policies for mitigating hazardous materials transport risk[J]. Transportation Science,2009,43(2):228-243.
[15] BIANCO L,CARAMIA M,GIORDANI S. A game-theoretic approach for regulating hazmat transportation[J]. Transportation Science,2015,50(2):424-438.
[16] ASSADIPOUR G,KE G Y,VERMA M. A toll-based bi-level programming approach to managing hazardous materials shipments over an intermodal transportation network[J]. Transportation Research Part D,2016,47:208-221.
[17] ABKOWITZ M,LEPOFSKY M,CHENG P. Selecting criteria for designating hazardous materials highway routes[J]. Transportation Research Record,1992,1333:30-35.
[18] BRONFMAN A,MARIANOV V,BELMAR G P,et al. The maximin hazmat routing problem[J]. European Journal of Operational Research,2015,241(1):15-27.
[2] ALP E. Risk-based transportation planning practice:overall methodology and a case example[J]. Infor Information Systems&Operational Research,1995,33(1):4-19.
[3] SIVAKUMAR R A,BATTA R,KARWAN M H. A network-based model for transporting extremely hazardous materials[J]. Operation Research Letters,1993,13(2):86-93.
[4] TOUMAZIS I,KWON C. Routing hazardous materials on time-dependent networks using conditional value-at-risk[J]. Transportation Research Part C,2013,37(3):73-92.
[5]辛春林,孟佳,张建文,等.危险品运输路径优化问题研究综述[J].中国安全科学学报,2018,28(3):102-107.XIN Chunlin,MENG Jia,ZHANG Jianwen,et al. A review of researches on optimization of hazardous materials transportation route[J].China Safety Science Journal,2018,28(3):102-107.
[6] KARA B Y,VERTER V. Designing a road network for hazardous materials transportation[J]. Transportation Science,2004,38(2):188-196.
[7] ERKUT E,GZARA F. Solving the hazmat transport network design problem[J]. Computers&Operations Research,2008,35(7):2234-2247.
[8] VERTER V,KARA B Y. A path-based approach for hazmat transport network design[J]. Management Science,2008,54(1):29-40.
[9] BERMAN O,VERTER V,KARA B Y. Designing emergency response networks for hazardous materials transportation[J]. Computers&Operations Research,2007,34(5):1374-1388.
[10]种鹏云,帅斌.连环恐怖袭击下危险品运输网络级联失效建模[J].系统工程理论与实践,2014,34(4):1059-1065.ZHONG Pengyun,SHUAI Bin. Model of cascading failure in hazardous material transportation network under series of terrorist attacks[J]. System-Engineering-Theory&Practice,2014,34(4):1059-1065.
[11]魏航,钟智龙,陈静.有害物品运输网络设计与运输路径优化研究[J].管理工程学报,2016,30(2):233-242.WEI Hang,ZHONG Zhilong,CHEN Jing. Network design for route control of hazardous materials transportation[J]. Journal of Industrial Engineering/Engineering Management, 2016, 30(2):233-242.
[12] SUN L,KARWAN M H,KWON C. Robust hazmat network design problems considering risk uncertainty[J]. Transportation Science,2016,50(4):1188-1203.
[13] ESFANDEHh T,KWON C,BATTA R. Time-dependent hazardous-materials network design problem[J]. Transportation Science,2017,52(2):454-473.
[14] MARCOTTE P,MERCIER A,SAVARD G. Toll policies for mitigating hazardous materials transport risk[J]. Transportation Science,2009,43(2):228-243.
[15] BIANCO L,CARAMIA M,GIORDANI S. A game-theoretic approach for regulating hazmat transportation[J]. Transportation Science,2015,50(2):424-438.
[16] ASSADIPOUR G,KE G Y,VERMA M. A toll-based bi-level programming approach to managing hazardous materials shipments over an intermodal transportation network[J]. Transportation Research Part D,2016,47:208-221.
[17] ABKOWITZ M,LEPOFSKY M,CHENG P. Selecting criteria for designating hazardous materials highway routes[J]. Transportation Research Record,1992,1333:30-35.
[18] BRONFMAN A,MARIANOV V,BELMAR G P,et al. The maximin hazmat routing problem[J]. European Journal of Operational Research,2015,241(1):15-27.