Probabilistic programming models for traffic incident management operations planning

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

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)389-406
Number of pages18
JournalAnnals of Operations Research
Volume203
Issue number1
DOIs
StatePublished - Mar 1 2013

Keywords

  • Incident management
  • Logistics
  • P-Efficient points
  • Probabilistic constraints
  • Quality of service
  • Stochastic programming
  • Transportation

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Management Science and Operations Research

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