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Scenario-based approach for the ambulance location problem with stochastic call arrivals under a dispatching policy

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  • Inkyung Sung

    (KAIST)

  • Taesik Lee

    (KAIST)

Abstract

This paper proposes a scenario-based ambulance location model which explicitly computes the availability of ambulances with stochastic call arrivals under a dispatching policy. The model utilizes two-stage stochastic programming to represent the temporal variations in call arrivals as a set of call arrival sequences. Constraints are embedded in the model to ensure that available ambulances are assigned to incoming calls following a dispatching policy. A logic-based Benders decomposition algorithm is presented to solve the model. The advantage of using our algorithm is demonstrated by comparing its performance with those of other location models.

Suggested Citation

  • Inkyung Sung & Taesik Lee, 2018. "Scenario-based approach for the ambulance location problem with stochastic call arrivals under a dispatching policy," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 153-170, June.
    • Handle: RePEc:spr:flsman:v:30:y:2018:i:1:d:10.1007_s10696-016-9271-5
    DOI: 10.1007/s10696-016-9271-5
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    Cited by:

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    2. Hyunjin Lee & Taesik Lee, 2021. "Demand modelling for emergency medical service system with multiple casualties cases: k-inflated mixture regression model," Flexible Services and Manufacturing Journal, Springer, vol. 33(4), pages 1090-1115, December.
    3. Soovin Yoon & Laura A. Albert & Veronica M. White, 2021. "A Stochastic Programming Approach for Locating and Dispatching Two Types of Ambulances," Transportation Science, INFORMS, vol. 55(2), pages 275-296, March.
    4. Wang, Wei & Wu, Shining & Wang, Shuaian & Zhen, Lu & Qu, Xiaobo, 2021. "Emergency facility location problems in logistics: Status and perspectives," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).

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