Modeling road vulnerability to snow using mixed integer optimization

Tony Rodriguez; Olufemi A. Omitaomu; Jim Ostrowski; Budhendra L. Bhaduri

Modeling road vulnerability to snow using mixed integer optimization

Tony Rodriguez, Olufemi A. Omitaomu, Jim Ostrowski, Budhendra L. Bhaduri

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

As the number and severity of snowfall events continue to grow, the need to intelligently direct road maintenance during these snowfall events will also grow. In several locations, local governments lack the resources to completely treat all roadways during snow events. Furthermore, some governments utilize only traffic data to determine which roads should be treated. As a result, many schools, businesses, and government offices must be unnecessarily closed, which directly impacts the social, educational, and economic well-being of citizens and institutions. In this work, we propose a mixed integer programming formulation to optimally allocate resources to manage snowfall on roads using meteorological, geographical, and environmental parameters. Additionally, we evaluate the impacts of an increase in budget for winter road maintenance on snow control resources.

Original language	English
Title of host publication	67th Annual Conference and Expo of the Institute of Industrial Engineers 2017
Editors	Harriet B. Nembhard, Katie Coperich, Elizabeth Cudney
Publisher	Institute of Industrial Engineers
Pages	1326-1331
Number of pages	6
ISBN (Electronic)	9780983762461
State	Published - 2017
Event	67th Annual Conference and Expo of the Institute of Industrial Engineers 2017 - Pittsburgh, United States Duration: May 20 2017 → May 23 2017

Publication series

Name	67th Annual Conference and Expo of the Institute of Industrial Engineers 2017

Conference

Conference	67th Annual Conference and Expo of the Institute of Industrial Engineers 2017
Country/Territory	United States
City	Pittsburgh
Period	05/20/17 → 05/23/17

Funding

Research sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U. S. Department of Energy. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Funders	Funder number
U. S. Department of Energy
Oak Ridge National Laboratory

Keywords

Mixed integer optimization
Network flow
Operations research
Snow removal

Cite this

Rodriguez, T., Omitaomu, O. A., Ostrowski, J., & Bhaduri, B. L. (2017). Modeling road vulnerability to snow using mixed integer optimization. In H. B. Nembhard, K. Coperich, & E. Cudney (Eds.), 67th Annual Conference and Expo of the Institute of Industrial Engineers 2017 (pp. 1326-1331). (67th Annual Conference and Expo of the Institute of Industrial Engineers 2017). Institute of Industrial Engineers.

Rodriguez, Tony ; Omitaomu, Olufemi A. ; Ostrowski, Jim et al. / Modeling road vulnerability to snow using mixed integer optimization. 67th Annual Conference and Expo of the Institute of Industrial Engineers 2017. editor / Harriet B. Nembhard ; Katie Coperich ; Elizabeth Cudney. Institute of Industrial Engineers, 2017. pp. 1326-1331 (67th Annual Conference and Expo of the Institute of Industrial Engineers 2017).

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title = "Modeling road vulnerability to snow using mixed integer optimization",

abstract = "As the number and severity of snowfall events continue to grow, the need to intelligently direct road maintenance during these snowfall events will also grow. In several locations, local governments lack the resources to completely treat all roadways during snow events. Furthermore, some governments utilize only traffic data to determine which roads should be treated. As a result, many schools, businesses, and government offices must be unnecessarily closed, which directly impacts the social, educational, and economic well-being of citizens and institutions. In this work, we propose a mixed integer programming formulation to optimally allocate resources to manage snowfall on roads using meteorological, geographical, and environmental parameters. Additionally, we evaluate the impacts of an increase in budget for winter road maintenance on snow control resources.",

keywords = "Mixed integer optimization, Network flow, Operations research, Snow removal",

author = "Tony Rodriguez and Omitaomu, {Olufemi A.} and Jim Ostrowski and Bhaduri, {Budhendra L.}",

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series = "67th Annual Conference and Expo of the Institute of Industrial Engineers 2017",

publisher = "Institute of Industrial Engineers",

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editor = "Nembhard, {Harriet B.} and Katie Coperich and Elizabeth Cudney",

booktitle = "67th Annual Conference and Expo of the Institute of Industrial Engineers 2017",

note = "67th Annual Conference and Expo of the Institute of Industrial Engineers 2017 ; Conference date: 20-05-2017 Through 23-05-2017",

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Rodriguez, T, Omitaomu, OA, Ostrowski, J & Bhaduri, BL 2017, Modeling road vulnerability to snow using mixed integer optimization. in HB Nembhard, K Coperich & E Cudney (eds), 67th Annual Conference and Expo of the Institute of Industrial Engineers 2017. 67th Annual Conference and Expo of the Institute of Industrial Engineers 2017, Institute of Industrial Engineers, pp. 1326-1331, 67th Annual Conference and Expo of the Institute of Industrial Engineers 2017, Pittsburgh, United States, 05/20/17.

Modeling road vulnerability to snow using mixed integer optimization. / Rodriguez, Tony; Omitaomu, Olufemi A.; Ostrowski, Jim et al.
67th Annual Conference and Expo of the Institute of Industrial Engineers 2017. ed. / Harriet B. Nembhard; Katie Coperich; Elizabeth Cudney. Institute of Industrial Engineers, 2017. p. 1326-1331 (67th Annual Conference and Expo of the Institute of Industrial Engineers 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - As the number and severity of snowfall events continue to grow, the need to intelligently direct road maintenance during these snowfall events will also grow. In several locations, local governments lack the resources to completely treat all roadways during snow events. Furthermore, some governments utilize only traffic data to determine which roads should be treated. As a result, many schools, businesses, and government offices must be unnecessarily closed, which directly impacts the social, educational, and economic well-being of citizens and institutions. In this work, we propose a mixed integer programming formulation to optimally allocate resources to manage snowfall on roads using meteorological, geographical, and environmental parameters. Additionally, we evaluate the impacts of an increase in budget for winter road maintenance on snow control resources.

AB - As the number and severity of snowfall events continue to grow, the need to intelligently direct road maintenance during these snowfall events will also grow. In several locations, local governments lack the resources to completely treat all roadways during snow events. Furthermore, some governments utilize only traffic data to determine which roads should be treated. As a result, many schools, businesses, and government offices must be unnecessarily closed, which directly impacts the social, educational, and economic well-being of citizens and institutions. In this work, we propose a mixed integer programming formulation to optimally allocate resources to manage snowfall on roads using meteorological, geographical, and environmental parameters. Additionally, we evaluate the impacts of an increase in budget for winter road maintenance on snow control resources.

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KW - Network flow

KW - Operations research

KW - Snow removal

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Y2 - 20 May 2017 through 23 May 2017

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Rodriguez T, Omitaomu OA, Ostrowski J, Bhaduri BL. Modeling road vulnerability to snow using mixed integer optimization. In Nembhard HB, Coperich K, Cudney E, editors, 67th Annual Conference and Expo of the Institute of Industrial Engineers 2017. Institute of Industrial Engineers. 2017. p. 1326-1331. (67th Annual Conference and Expo of the Institute of Industrial Engineers 2017).

Modeling road vulnerability to snow using mixed integer optimization

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Keywords

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