Probabilistic programming models for traffic incident management operations planning
Kaan Ozbay (),
Cem Iyigun (),
Melike Baykal-Gursoy () and
Weihua Xiao ()
Annals of Operations Research, 2013, vol. 203, issue 1, 389-406
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
Keywords: Transportation; Incident management; Logistics; Quality of service; p-Efficient points; Stochastic programming; Probabilistic constraints (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (3)
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DOI: 10.1007/s10479-012-1174-6
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