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Bi-Objective Modelling for Hazardous Materials Road–Rail Multimodal Routing Problem with Railway Schedule-Based Space–Time Constraints

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  • Yan Sun

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
    Ministry of Education Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China)

  • Maoxiang Lang

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
    Ministry of Education Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China)

  • Danzhu Wang

    (Transportation and Economics Research Institute, China Academy of Railway Sciences, Beijing 100081, China)

Abstract

The transportation of hazardous materials is always accompanied by considerable risk that will impact public and environment security. As an efficient and reliable transportation organization, a multimodal service should participate in the transportation of hazardous materials. In this study, we focus on transporting hazardous materials through the multimodal service network and explore the hazardous materials multimodal routing problem from the operational level of network planning. To formulate this problem more practicably, minimizing the total generalized costs of transporting the hazardous materials and the social risk along the planned routes are set as the optimization objectives. Meanwhile, the following formulation characteristics will be comprehensively modelled: (1) specific customer demands; (2) multiple hazardous material flows; (3) capacitated schedule-based rail service and uncapacitated time-flexible road service; and (4) environmental risk constraint. A bi-objective mixed integer nonlinear programming model is first built to formulate the routing problem that combines the formulation characteristics above. Then linear reformations are developed to linearize and improve the initial model so that it can be effectively solved by exact solution algorithms on standard mathematical programming software. By utilizing the normalized weighted sum method, we can generate the Pareto solutions to the bi-objective optimization problem for a specific case. Finally, a large-scale empirical case study from the Beijing–Tianjin–Hebei Region in China is presented to demonstrate the feasibility of the proposed methods in dealing with the practical problem. Various scenarios are also discussed in the case study.

Suggested Citation

  • Yan Sun & Maoxiang Lang & Danzhu Wang, 2016. "Bi-Objective Modelling for Hazardous Materials Road–Rail Multimodal Routing Problem with Railway Schedule-Based Space–Time Constraints," IJERPH, MDPI, vol. 13(8), pages 1-31, July.
    • Handle: RePEc:gam:jijerp:v:13:y:2016:i:8:p:762-:d:74856
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    References listed on IDEAS

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    1. Giannikos, Ioannis, 1998. "A multiobjective programming model for locating treatment sites and routing hazardous wastes," European Journal of Operational Research, Elsevier, vol. 104(2), pages 333-342, January.
    2. Yan Sun & Maoxiang Lang, 2015. "Modeling the Multicommodity Multimodal Routing Problem with Schedule-Based Services and Carbon Dioxide Emission Costs," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-21, December.
    3. Omid Boyer & Tang Sai Hong & Ali Pedram & Rosnah Bt Mohd Yusuff & Norzima Zulkifli, 2013. "A Mathematical Model for the Industrial Hazardous Waste Location-Routing Problem," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-10, December.
    4. George F. List & Pitu B. Mirchandani & Mark A. Turnquist & Konstantinos G. Zografos, 1991. "Modeling and Analysis for Hazardous Materials Transportation: Risk Analysis, Routing/Scheduling and Facility Location," Transportation Science, INFORMS, vol. 25(2), pages 100-114, May.
    5. Verma, Manish & Verter, Vedat & Zufferey, Nicolas, 2012. "A bi-objective model for planning and managing rail-truck intermodal transportation of hazardous materials," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 132-149.
    6. Zhao, Jun & Huang, Lixia & Lee, Der-Horng & Peng, Qiyuan, 2016. "Improved approaches to the network design problem in regional hazardous waste management systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 52-75.
    7. Mary E. Helander & Emanuel Melachrinoudis, 1997. "Facility Location and Reliable Route Planning in Hazardous Material Transportation," Transportation Science, INFORMS, vol. 31(3), pages 216-226, August.
    8. Samanlioglu, Funda, 2013. "A multi-objective mathematical model for the industrial hazardous waste location-routing problem," European Journal of Operational Research, Elsevier, vol. 226(2), pages 332-340.
    9. Verma, Manish & Verter, Vedat, 2010. "A lead-time based approach for planning rail-truck intermodal transportation of dangerous goods," European Journal of Operational Research, Elsevier, vol. 202(3), pages 696-706, May.
    10. Vedat Verter & Bahar Y. Kara, 2008. "A Path-Based Approach for Hazmat Transport Network Design," Management Science, INFORMS, vol. 54(1), pages 29-40, January.
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    Cited by:

    1. Zhen-Song Chen & Min Li & Wen-Tao Kong & Kwai-Sang Chin, 2019. "Evaluation and Selection of HazMat Transportation Alternatives: A PHFLTS- and TOPSIS-Integrated Multi-Perspective Approach," IJERPH, MDPI, vol. 16(21), pages 1-33, October.
    2. Apichit Maneengam, 2023. "Multi-Objective Optimization of the Multimodal Routing Problem Using the Adaptive ε-Constraint Method and Modified TOPSIS with the D-CRITIC Method," Sustainability, MDPI, vol. 15(15), pages 1-22, August.
    3. Shuxia Li & Yuedan Zu & Huimin Fang & Liping Liu & Tijun Fan, 2021. "Design Optimization of a HAZMAT Multimodal Hub-and-Spoke Network with Detour," IJERPH, MDPI, vol. 18(23), pages 1-18, November.

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