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Probabilistic programming models for traffic incident management operations planning

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  • Kaan Ozbay
  • Cem Iyigun
  • Melike Baykal-Gursoy
  • Weihua Xiao

Abstract

This paper proposes mathematical programming models with probabilistic constraints in order to address incident response and resource allocation problems for the planning of traffic incident management operations. For the incident response planning, we use the concept of quality of service during a potential incident to give the decision-maker the flexibility to determine the optimal policy in response to various possible situations. An integer programming model with probabilistic constraints is also proposed to address the incident response problem with stochastic resource requirements at the sites of incidents. For the resource allocation planning, we introduce a mathematical model to determine the number of service vehicles allocated to each depot to meet the resource requirements of the incidents by taking into account the stochastic nature of the resource requirement and incident occurrence probabilities. A detailed case study for the incident resource allocation problem is included to demonstrate the use of proposed model in a real-world context. The paper concludes with a summary of results and recommendations for future research. Copyright Springer Science+Business Media, LLC 2013

Suggested Citation

  • Kaan Ozbay & Cem Iyigun & Melike Baykal-Gursoy & Weihua Xiao, 2013. "Probabilistic programming models for traffic incident management operations planning," Annals of Operations Research, Springer, vol. 203(1), pages 389-406, March.
  • Handle: RePEc:spr:annopr:v:203:y:2013:i:1:p:389-406:10.1007/s10479-012-1174-6
    DOI: 10.1007/s10479-012-1174-6
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    References listed on IDEAS

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    Cited by:

    1. Zhen, Lu & Wu, Jingwen & Chen, Fengli & Wang, Shuaian, 2024. "Traffic emergency vehicle deployment and dispatch under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    2. 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.
    3. Marina Baltar & Victor Abreu & Glaydston Ribeiro & Laura Bahiense, 2021. "Multi-objective model for the problem of locating tows for incident servicing on expressways," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 58-77, April.

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