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 language | English (US) |
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Pages (from-to) | 1-18 |
Number of pages | 18 |
Journal | Annals of Operations Research |
DOIs | |
State | Accepted/In press - 2012 |
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Keywords
- Incident management
- Logistics
- p-Efficient points
- Probabilistic constraints
- Quality of service
- Stochastic programming
- Transportation
ASJC Scopus subject areas
- Management Science and Operations Research
- Decision Sciences(all)
Cite this
Probabilistic programming models for traffic incident management operations planning. / Ozbay, Kaan; Iyigun, Cem; Baykal-Gursoy, Melike; Xiao, Weihua.
In: Annals of Operations Research, 2012, p. 1-18.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Probabilistic programming models for traffic incident management operations planning
AU - Ozbay, Kaan
AU - Iyigun, Cem
AU - Baykal-Gursoy, Melike
AU - Xiao, Weihua
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - Incident management
KW - Logistics
KW - p-Efficient points
KW - Probabilistic constraints
KW - Quality of service
KW - Stochastic programming
KW - Transportation
UR - http://www.scopus.com/inward/record.url?scp=84863083784&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863083784&partnerID=8YFLogxK
U2 - 10.1007/s10479-012-1174-6
DO - 10.1007/s10479-012-1174-6
M3 - Article
AN - SCOPUS:84863083784
SP - 1
EP - 18
JO - Annals of Operations Research
JF - Annals of Operations Research
SN - 0254-5330
ER -