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A novel probabilistic formulation for locating and sizing emergency medical service stations

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  • Zhi-Hai Zhang
  • Kang Li

Abstract

The paper proposes a novel probabilistic model with chance constraints for locating and sizing emergency medical service stations. In this model, the chance constraints are approximated as second-order cone constraints to overcome computational difficulties for practical applications. The proposed approximations associated with different estimation accuracy of the stochastic nature are meaningful on a practical uncertainty environment. Then, the model is transformed into a conic quadratic mixed-integer program by employing a conic transformation. The resulting model can be efficiently addressed by a commercial optimization package. A special case is also considered and a class of valid inequalities is introduced to improve computational efficiency. Lastly, computational experiences on real data and randomly generated data are reported to illustrate the validity of the program. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Zhi-Hai Zhang & Kang Li, 2015. "A novel probabilistic formulation for locating and sizing emergency medical service stations," Annals of Operations Research, Springer, vol. 229(1), pages 813-835, June.
  • Handle: RePEc:spr:annopr:v:229:y:2015:i:1:p:813-835:10.1007/s10479-014-1758-4
    DOI: 10.1007/s10479-014-1758-4
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    Cited by:

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    2. Rania Boujemaa & Aida Jebali & Sondes Hammami & Angel Ruiz & Hanen Bouchriha, 2018. "A stochastic approach for designing two-tiered emergency medical service systems," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 123-152, June.
    3. Liu, Kanglin & Li, Qiaofeng & Zhang, Zhi-Hai, 2019. "Distributionally robust optimization of an emergency medical service station location and sizing problem with joint chance constraints," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 79-101.
    4. Soheyl Khalilpourazari & Alireza Arshadi Khamseh, 2019. "Bi-objective emergency blood supply chain network design in earthquake considering earthquake magnitude: a comprehensive study with real world application," Annals of Operations Research, Springer, vol. 283(1), pages 355-393, December.
    5. Liu, Kanglin & Zhang, Zhi-Hai, 2018. "Capacitated disassembly scheduling under stochastic yield and demand," European Journal of Operational Research, Elsevier, vol. 269(1), pages 244-257.
    6. 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).
    7. Kınay, Ömer Burak & Yetis Kara, Bahar & Saldanha-da-Gama, Francisco & Correia, Isabel, 2018. "Modeling the shelter site location problem using chance constraints: A case study for Istanbul," European Journal of Operational Research, Elsevier, vol. 270(1), pages 132-145.
    8. Luo, Weicong & Yao, Jing & Mitchell, Richard & Zhang, Xiaoxiang & Li, Wenqiang, 2022. "Locating emergency medical services to reduce urban-rural inequalities," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    9. Liu, Kanglin & Zhang, Hengliang & Zhang, Zhi-Hai, 2021. "The efficiency, equity and effectiveness of location strategies in humanitarian logistics: A robust chance-constrained approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    10. Liu, Kanglin & Liu, Changchun & Xiang, Xi & Tian, Zhili, 2023. "Testing facility location and dynamic capacity planning for pandemics with demand uncertainty," European Journal of Operational Research, Elsevier, vol. 304(1), pages 150-168.

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