Evacuation transportation planning under uncertainty: A robust optimization approach

Tao Yao; Supreet Reddy Mandala; Byung Do Chung

doi:10.1007/s11067-009-9103-1

Evacuation transportation planning under uncertainty: A robust optimization approach

Tao Yao, Supreet Reddy Mandala, Byung Do Chung

Department of Industrial Engineering

Research output: Contribution to journal › Article › peer-review

98 Citations (Scopus)

Abstract

This paper considers evacuation via surface transportation networks in an uncertain environment. We focus on demand uncertainty which can lead to significant infeasibility cost during evacuation, where loss of life or property may appear. We develop a robust linear programming model based on a robust optimization approach where hard constraints are guaranteed within an appropriate uncertainty set. The robust counterpart solutions have been shown tractable. We show that the robustness in evacuation is important and a robust solution outperforms a nominal deterministic solution in both quality and feasibility.

Original language	English
Pages (from-to)	171-189
Number of pages	19
Journal	Networks and Spatial Economics
Volume	9
Issue number	2
DOIs	https://doi.org/10.1007/s11067-009-9103-1
Publication status	Published - 2009

Bibliographical note

Funding Information:
Acknowledgment The authors greatly acknowledge the discussions with Aharon Ben-Tal, Faculty of Industrial Engineering and Management, Technion — Israel Institute of Technology. This research is based on work supported in part by the NSF grant CMMI-0824640 and Marcus Fund.

All Science Journal Classification (ASJC) codes

Software
Computer Networks and Communications
Artificial Intelligence

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author = "Tao Yao and Mandala, {Supreet Reddy} and Chung, {Byung Do}",

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N2 - This paper considers evacuation via surface transportation networks in an uncertain environment. We focus on demand uncertainty which can lead to significant infeasibility cost during evacuation, where loss of life or property may appear. We develop a robust linear programming model based on a robust optimization approach where hard constraints are guaranteed within an appropriate uncertainty set. The robust counterpart solutions have been shown tractable. We show that the robustness in evacuation is important and a robust solution outperforms a nominal deterministic solution in both quality and feasibility.

AB - This paper considers evacuation via surface transportation networks in an uncertain environment. We focus on demand uncertainty which can lead to significant infeasibility cost during evacuation, where loss of life or property may appear. We develop a robust linear programming model based on a robust optimization approach where hard constraints are guaranteed within an appropriate uncertainty set. The robust counterpart solutions have been shown tractable. We show that the robustness in evacuation is important and a robust solution outperforms a nominal deterministic solution in both quality and feasibility.

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Evacuation transportation planning under uncertainty: A robust optimization approach

Abstract

Bibliographical note

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