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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.

Authors:
 [1];  [1];  [1];  [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
1360076
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: Industrial and Systems Engineering Research Conference, Pittsburgh, PA, USA, 20170520, 20170523
Country of Publication:
United States
Language:
English
Subject:
Mixed integer optimization; network flow; operations research; snow removal

Citation Formats

Rodriguez, Tony K, Omitaomu, Olufemi A, Ostrowski, James A, and Bhaduri, Budhendra L. Modeling Road Vulnerability to Snow Using Mixed Integer Optimization. United States: N. p., 2017. Web.
Rodriguez, Tony K, Omitaomu, Olufemi A, Ostrowski, James A, & Bhaduri, Budhendra L. Modeling Road Vulnerability to Snow Using Mixed Integer Optimization. United States.
Rodriguez, Tony K, Omitaomu, Olufemi A, Ostrowski, James A, and Bhaduri, Budhendra L. Sun . "Modeling Road Vulnerability to Snow Using Mixed Integer Optimization". United States. doi:.
@article{osti_1360076,
title = {Modeling Road Vulnerability to Snow Using Mixed Integer Optimization},
author = {Rodriguez, Tony K and Omitaomu, Olufemi A and Ostrowski, James A and Bhaduri, Budhendra L},
abstractNote = {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.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Jan 01 00:00:00 EST 2017},
month = {Sun Jan 01 00:00:00 EST 2017}
}

Conference:
Other availability
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