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Managing sudden transportation disruptions in supply chains under delivery delay and quantity loss

  • OR in Transportation
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Abstract

Transportation disruption, a common source of business interruptions, can cause significant economic loss to a lean supply chain. This paper studies a lean, two-stage supplier-manufacturer coordinated system where a sudden disruption interrupts the transportation network, creating delivery delays and product quantity losses. We develop a model to generate a recovery plan after a sudden disruption occurrence, helping supply chain managers minimize the negative impacts of the disruption. Given the computational intensity and problem complexity, we then propose three heuristic solutions based on the delivery delay and fractional quantity loss caused by a sudden disruption. Finally, We conduct a number of numerical experiments to validate our proposed solution methods, and a scenario-based analysis to test the model and analyse the impact of sudden transportation disruption under three disruption scenarios. The performance of presented heuristics against the generalized reduced gradient method is also compared. The results reveal that the proposed heuristics can generate a recovery plan accurately and consistently.

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Authors and Affiliations

  1. UTS Business School, University of Technology Sydney, Sydney, Australia

    Sanjoy Kumar Paul

  2. College of Business, RMIT University, Melbourne, Australia

    Sobhan Asian

  3. NUS Business School, The Logistics Institute Asia-Pacific, National University of Singapore, Singapore, Singapore

    Mark Goh

  4. School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

    S. Ali Torabi

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  1. Sanjoy Kumar Paul
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  2. Sobhan Asian
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  3. Mark Goh
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  4. S. Ali Torabi
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Correspondence to Sobhan Asian.

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Paul, S.K., Asian, S., Goh, M. et al. Managing sudden transportation disruptions in supply chains under delivery delay and quantity loss. Ann Oper Res 273, 783–814 (2019). https://doi.org/10.1007/s10479-017-2684-z

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