摘要Risk and cost are the basic characteristics of the road transportation of dangerous goods. The characteristics in the programming of the road transportation network of dangerous goods were considered in this study. The influencing factors were divided into seven parts, namely, transportation distance, accident possibility, on-road population exposure, off-road population exposure, property damage, environmental pollution, and efficiency of emergency response. These factors were quantitatively evaluated by using the analytic hierarchy process. The relative weight was calculated. A bi-level model of the road transportation network of dangerous goods was formulated with the minimum risk that governments demand as the upper objective function and the minimum cost that enterprises demand as the lower objective function. The model was calculated by using the genetic algorithm (GA). The case study indicated that solving the bi-level programming model by using GA could rapidly identify a route that meets the minimum risk and cost simultaneously in the road transportation network of dangerous goods, complete the synthetical optimization of the road transportation network of dangerous goods, and find the optimal point of balance between risk and cost.
Abstract:Risk and cost are the basic characteristics of the road transportation of dangerous goods. The characteristics in the programming of the road transportation network of dangerous goods were considered in this study. The influencing factors were divided into seven parts, namely, transportation distance, accident possibility, on-road population exposure, off-road population exposure, property damage, environmental pollution, and efficiency of emergency response. These factors were quantitatively evaluated by using the analytic hierarchy process. The relative weight was calculated. A bi-level model of the road transportation network of dangerous goods was formulated with the minimum risk that governments demand as the upper objective function and the minimum cost that enterprises demand as the lower objective function. The model was calculated by using the genetic algorithm (GA). The case study indicated that solving the bi-level programming model by using GA could rapidly identify a route that meets the minimum risk and cost simultaneously in the road transportation network of dangerous goods, complete the synthetical optimization of the road transportation network of dangerous goods, and find the optimal point of balance between risk and cost.
基金资助:Supported by the Fundamental Research Funds for the Central Universities(No.3122014C001)
通讯作者:
LI Ying-hong,E-mail address: songyang_tju@163.com
E-mail: songyang_tju@163.com
引用本文:
宋洋, 王若愚. 危险品道路运输网络风险——成本综合优化研究[J]. Journal of Highway and Transportation Research and Development, 2016, 10(2): 92-97.
SONG Yang, WANG Ruo-yu. Route Optimization of the Road Transportation of Dangerous Goods Based on Bi-level Programming. Journal of Highway and Transportation Research and Development, 2016, 10(2): 92-97.
[1] REN Chang-xing. Study on Transportation Routing Optimal Method of Dangerous Goods Based on Risk Analysis[D].Tianjin:Nankai University, 2007. (in Chinese)
[2] SACCOMANNO F F, CHAN A Y W. Economic Evaluation of Routing Strategies for Hazardous Road Shipments[J]. Transportation Research Record, 1985,10(20):12-18.
[3] LIST G F, MIRCHANDANI P B, TURNUIST M A, et al. Modeling and Analysis for Hazardous Materials Transportation:Risk Analysis, Routing/Scheduling and Facility Location[J]. Transportation Science, 1991, 25(2):100-114.
[4] SHOBRYS D. A Model for the Selection of Shipping Routes and Storage Locations for a Hazardous Substance[D]. Baltimore:Johns Hopkins University, 1981.
[5] ROBBINS J. Routing Hazardous Materials Shipments[D]. Bloomington, Indiana University, 1981.
[6] KARA B Y, VERTER V. Designing a Road Network for Hazardous Materials Transportation[J]. Transportation Science, 2004, 38(2):188-196.
[7] CHU Qing-zhong, ZHANG Jia-ying, XIE Zhi-quan. Road Network Design for Hazardous Materials Transportation Based on Bi-level Programming[J]. Journal of Chongqing Jiaotong University:Natural Science Edition, 2010, 29(4):597-603.(in Chinese)
[8] SONG Wei-cheng, SHUAI Bin, CHEN Gang-tie. Dangerous Goods Transport Path Optimization Based on Point of Hazard[J]. China Safety Science Journal,2012,22(2):116-121. (in Chinese)
[9] WU Feng,WANG Xiao-yan. A Safety Evaluation Model for Dangerous Goods Transportation Based on Fuzzy Petri Nets and Its Application[J]. China Safety Science Journal,2011,21(1):93-98.(in Chinese)
[10] MA Chang-xi, GUANG Xiao-ping, WU Fang, et al. Highway Transportation Route Decision-making of Hazardous Material in Developed Transportation Network[J]. Journal of Transportation System Engineering and Information Technology, 2009, 9(4):134-139. (in Chinese)
[11] SONG Yang, XU Zhen, WANG Yan-qing. Route Optimization for Dangerous Goods Transportation Based on Ant Colony Algorithm[J]. Safety and Environmental Engineering, 2014, 21(1):148-152. (in Chinese)
[12] FENG Shu-min, YIN Guo-qiang. Transport Route Optimization Model of Dangerous Goods at Planning Level[J]. Journal of Harbin Institute of Technology, 2012, 44(8):53-56. (in Chinese)
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