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An optimization based approach for deployment of roadway incident response vehicles with reliability constraints

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  • Pal, Raktim
  • Bose, Indranil
Abstract
In recent years transportation agencies have introduced patrol based response programs to remove roadway incidents rapidly. With the evolution of technology incident detection and notification from remote traffic operation centers is possible and patrols to detect incidents are not necessary. Instead, the response units can be placed at various depots in urban areas and dispatched to incident sites upon notification. In this paper, we propose a reliability based mixed integer programming model to find best locations of incidence response depots and assign response vehicles to these depots so that incidents can be cleared efficiently at a minimum cost. The approach is unique as it considers fixed and variable costs of vehicles and depots, occurrences of major and minor incidents, and reliability of response service in the same model. Numerical results are generated for an example problem and sensitivity analysis is conducted to explore the relationships between parameters of the problem.

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  • Pal, Raktim & Bose, Indranil, 2009. "An optimization based approach for deployment of roadway incident response vehicles with reliability constraints," European Journal of Operational Research, Elsevier, vol. 198(2), pages 452-463, October.
    • Handle: RePEc:eee:ejores:v:198:y:2009:i:2:p:452-463
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    References listed on IDEAS

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    Cited by:

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    3. Camacho-Collados, M. & Liberatore, F. & Angulo, J.M., 2015. "A multi-criteria Police Districting Problem for the efficient and effective design of patrol sector," European Journal of Operational Research, Elsevier, vol. 246(2), pages 674-684.
    4. 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.
    5. 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.

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