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Identifying geographically diverse routes for the transportation of hazardous materials

Author

Listed:
  • Dadkar, Yashoda
  • Jones, Dean
  • Nozick, Linda

Abstract

Often, the carrier/shipper of hazardous materials is interested in a collection of routes with approximately the same performance so that they can switch between different routes to avoid exposing the same population and potentially as a security measure. We develop a K shortest path algorithm for which the performance of each highway facility, with respect to each objective, can be stochastic and can vary over time. We also devise a mixed integer program to identify a subset of paths, which represents an acceptable trade-off between geographic diversity and performance. These models are then applied to a realistic case study.

Suggested Citation

  • Dadkar, Yashoda & Jones, Dean & Nozick, Linda, 2008. "Identifying geographically diverse routes for the transportation of hazardous materials," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(3), pages 333-349, May.
    • Handle: RePEc:eee:transe:v:44:y:2008:i:3:p:333-349
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    Citations

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    Cited by:

    1. Zajac, Sandra & Huber, Sandra, 2021. "Objectives and methods in multi-objective routing problems: a survey and classification scheme," European Journal of Operational Research, Elsevier, vol. 290(1), pages 1-25.
    2. Mahmoudabadi, Abbas & Seyedhosseini, Seyed Mohammad, 2014. "Solving Hazmat Routing Problem in chaotic damage severity network under emergency environment," Transport Policy, Elsevier, vol. 36(C), pages 34-45.
    3. Miranda, Pablo A. & Blazquez, Carola A. & Vergara, Rodrigo & Weitzler, Sebastian, 2015. "A novel methodology for designing a household waste collection system for insular zones," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 227-247.
    4. Dadkar, Yashoda & Nozick, Linda & Jones, Dean, 2010. "Optimizing facility use restrictions for the movement of hazardous materials," Transportation Research Part B: Methodological, Elsevier, vol. 44(2), pages 267-281, February.
    5. 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.
    6. Reilly, Allison & Nozick, Linda & Xu, Ningxiong & Jones, Dean, 2012. "Game theory-based identification of facility use restrictions for the movement of hazardous materials under terrorist threat," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 115-131.
    7. Dinler, Esra & Güngör, Zülal, 2017. "Planning decisions for recycling products containing hazardous and explosive substances: A fuzzy multi-objective model," Resources, Conservation & Recycling, Elsevier, vol. 117(PB), pages 93-101.
    8. Romero, Natalia & Nozick, Linda K. & Xu, Ningxiong, 2016. "Hazmat facility location and routing analysis with explicit consideration of equity using the Gini coefficient," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 165-181.
    9. Ditta, A. & Figueroa, O. & Galindo, G. & Yie-Pinedo, R., 2019. "A review on research in transportation of hazardous materials," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    10. Mohammadi, Mehrdad & Jula, Payman & Tavakkoli-Moghaddam, Reza, 2017. "Design of a reliable multi-modal multi-commodity model for hazardous materials transportation under uncertainty," European Journal of Operational Research, Elsevier, vol. 257(3), pages 792-809.
    11. 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.
    12. Changxi Ma & Wei Hao & Fuquan Pan & Wang Xiang, 2018. "Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-22, June.

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