Robust improvement schemes for road networks under demand uncertainty

Yafeng Yin; Samer M. Madanat; Xiao Yun Lu

doi:10.1016/j.ejor.2008.09.008

Robust improvement schemes for road networks under demand uncertainty

Yafeng Yin, Samer M. Madanat, Xiao Yun Lu

Civil Engineering

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

Abstract

This paper is concerned with development of improvement schemes for road networks under future travel demand uncertainty. Three optimization models, sensitivity-based, scenario-based and min-max, are proposed for determining robust optimal improvement schemes that make system performance insensitive to realizations of uncertain demands or allow the system to perform better against the worst-case demand scenario. Numerical examples and simulation tests are presented to demonstrate and validate the proposed models.

Original language	English (US)
Pages (from-to)	470-479
Number of pages	10
Journal	European Journal of Operational Research
Volume	198
Issue number	2
DOIs	https://doi.org/10.1016/j.ejor.2008.09.008
State	Published - Oct 16 2009

Keywords

Network design
Robustness and sensitivity analysis
Transportation
Uncertainty modelling

ASJC Scopus subject areas

Computer Science(all)
Modeling and Simulation
Management Science and Operations Research
Information Systems and Management

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10.1016/j.ejor.2008.09.008

Cite this

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title = "Robust improvement schemes for road networks under demand uncertainty",

abstract = "This paper is concerned with development of improvement schemes for road networks under future travel demand uncertainty. Three optimization models, sensitivity-based, scenario-based and min-max, are proposed for determining robust optimal improvement schemes that make system performance insensitive to realizations of uncertain demands or allow the system to perform better against the worst-case demand scenario. Numerical examples and simulation tests are presented to demonstrate and validate the proposed models.",

keywords = "Network design, Robustness and sensitivity analysis, Transportation, Uncertainty modelling",

author = "Yafeng Yin and Madanat, {Samer M.} and Lu, {Xiao Yun}",

note = "Funding Information: This research was partly funded by the California Department of Transportation. The contents of this paper reflect the views of the authors, who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the State of California. The authors would like to thank three anonymous reviewers for constructive comments that helped to improve the paper.",

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AU - Yin, Yafeng

AU - Madanat, Samer M.

AU - Lu, Xiao Yun

N1 - Funding Information: This research was partly funded by the California Department of Transportation. The contents of this paper reflect the views of the authors, who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the State of California. The authors would like to thank three anonymous reviewers for constructive comments that helped to improve the paper.

PY - 2009/10/16

Y1 - 2009/10/16

N2 - This paper is concerned with development of improvement schemes for road networks under future travel demand uncertainty. Three optimization models, sensitivity-based, scenario-based and min-max, are proposed for determining robust optimal improvement schemes that make system performance insensitive to realizations of uncertain demands or allow the system to perform better against the worst-case demand scenario. Numerical examples and simulation tests are presented to demonstrate and validate the proposed models.

AB - This paper is concerned with development of improvement schemes for road networks under future travel demand uncertainty. Three optimization models, sensitivity-based, scenario-based and min-max, are proposed for determining robust optimal improvement schemes that make system performance insensitive to realizations of uncertain demands or allow the system to perform better against the worst-case demand scenario. Numerical examples and simulation tests are presented to demonstrate and validate the proposed models.

KW - Network design

KW - Robustness and sensitivity analysis

KW - Transportation

KW - Uncertainty modelling

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Robust improvement schemes for road networks under demand uncertainty

Abstract

Keywords

ASJC Scopus subject areas

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