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Dynamic conditional value-at-risk model for routing and scheduling of hazardous material transportation networks

Author

Listed:
  • Shahrzad Faghih-Roohi

    (Nanyang Technological University)

  • Yew-Soon Ong

    (Nanyang Technological University)

  • Sobhan Asian

    (Nanyang Technological University)

  • Allan N. Zhang

    (Nanyang Technological University)

Abstract

This paper illustrates a dynamic model of conditional value-at-risk (CVaR) measure for risk assessment and mitigation of hazardous material transportation in supply chain networks. The well-established market risk measure, CVaR, which is commonly used by financial institutions for portfolio optimizations, is investigated. In contrast to previous works, we consider CVaR as the main objective in the optimization of hazardous material (hazmat) transportation network. In addition to CVaR minimization and route planning of a supply chain network, the time scheduling of hazmat shipments is imposed and considered in the present study. Pertaining to the general dynamic risk model, we analyzed several scenarios involving a variety of hazmats and time schedules with respect to optimal route selection and CVaR minimization. A solution algorithm is then proposed for solving the model, with verifications made using numerical examples and sensitivity analysis.

Suggested Citation

  • Shahrzad Faghih-Roohi & Yew-Soon Ong & Sobhan Asian & Allan N. Zhang, 2016. "Dynamic conditional value-at-risk model for routing and scheduling of hazardous material transportation networks," Annals of Operations Research, Springer, vol. 247(2), pages 715-734, December.
    • Handle: RePEc:spr:annopr:v:247:y:2016:i:2:d:10.1007_s10479-015-1909-2
    DOI: 10.1007/s10479-015-1909-2
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    References listed on IDEAS

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    Cited by:

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    2. Cunrui Ma & Baohua Mao & Qi Xu & Guodong Hua & Sijia Zhang & Tong Zhang, 2018. "Multi-Depot Vehicle Routing Optimization Considering Energy Consumption for Hazardous Materials Transportation," Sustainability, MDPI, vol. 10(10), pages 1-21, September.
    3. Ali Jamshidi & Shahrzad Faghih‐Roohi & Siamak Hajizadeh & Alfredo Núñez & Robert Babuska & Rolf Dollevoet & Zili Li & Bart De Schutter, 2017. "A Big Data Analysis Approach for Rail Failure Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1495-1507, August.
    4. Lam, C.Y. & Cruz, A.M., 2019. "Risk analysis for consumer-level utility gas and liquefied petroleum gas incidents using probabilistic network modeling: A case study of gas incidents in Japan," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 198-212.
    5. Huang, Wencheng & Zhou, Bowen & Yu, Yaocheng & Yin, Dezhi, 2021. "Vulnerability analysis of road network for dangerous goods transportation considering intentional attack: Based on Cellular Automata," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    6. Sanjoy Kumar Paul & Sobhan Asian & Mark Goh & S. Ali Torabi, 2019. "Managing sudden transportation disruptions in supply chains under delivery delay and quantity loss," Annals of Operations Research, Springer, vol. 273(1), pages 783-814, February.
    7. Mohri, Seyed Sina & Asgari, Nasrin & Zanjirani Farahani, Reza & Bourlakis, Michael & Laker, Benjamin, 2020. "Fairness in hazmat routing-scheduling: A bi-objective Stackelberg game," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    8. Mohri, Seyed Sina & Mohammadi, Mehrdad & Gendreau, Michel & Pirayesh, Amir & Ghasemaghaei, Ali & Salehi, Vahid, 2022. "Hazardous material transportation problems: A comprehensive overview of models and solution approaches," European Journal of Operational Research, Elsevier, vol. 302(1), pages 1-38.
    9. Dawei Lu & Yi Ding & Sobhan Asian & Sanjoy Kumar Paul, 2018. "From Supply Chain Integration to Operational Performance: The Moderating Effect of Market Uncertainty," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 19(1), pages 3-20, March.
    10. Li, Jiang-Cheng & Leng, Na & Zhong, Guang-Yan & Wei, Yu & Peng, Jia-Sheng, 2020. "Safe marginal time of crude oil price via escape problem of econophysics," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
    11. Xifei Huang & Xinhao Wang & Jingjing Pei & Ming Xu & Xiaowu Huang & Yun Luo, 2018. "Risk assessment of the areas along the highway due to hazardous material transportation accidents," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(3), pages 1181-1202, September.
    12. Zhong, Shaopeng & Cheng, Rong & Jiang, Yu & Wang, Zhong & Larsen, Allan & Nielsen, Otto Anker, 2020. "Risk-averse optimization of disaster relief facility location and vehicle routing under stochastic demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    13. Chen Wei & Sobhan Asian & Gurdal Ertek & Zhi-Hua Hu, 2020. "Location-based pricing and channel selection in a supply chain: a case study from the food retail industry," Annals of Operations Research, Springer, vol. 291(1), pages 959-984, August.
    14. Mina Rahimi & Ashkan Hafezalkotob & Sobhan Asian & Luis Martínez, 2021. "Environmental Policy Making in Supply Chains under Ambiguity and Competition: A Fuzzy Stackelberg Game Approach," Sustainability, MDPI, vol. 13(4), pages 1-24, February.
    15. Hasti Seraji & Reza Tavakkoli-Moghaddam & Sobhan Asian & Harpreet Kaur, 2022. "An integrative location-allocation model for humanitarian logistics with distributive injustice and dissatisfaction under uncertainty," Annals of Operations Research, Springer, vol. 319(1), pages 211-257, December.

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