Robust Shelter Locations for Evacuation Planning with Demand Uncertainty

Ashish Kulshrestha, Di Wu, Yingyan Lou, Yafeng Yin

Research output: Contribution to journalArticle

37 Scopus citations

Abstract

This article presents a robust approach for determining optimal locations of public shelters and their capacities, from a given set of potential sites during evacuation planning under demand uncertainty. Demand uncertainty in the article refers to the uncertainty associated with the number of people using the public shelters during evacuation. It is assumed that a planning authority determines the number of shelters, their locations, and capacities whereas evacuees choose a shelter to evacuate and the routes to access it. The proposed model is formulated as a mathematical program with complementarity constraints and is solved by a cutting-plane scheme. A numerical example on the Sioux Falls network demonstrates that robust plans are able to achieve nearly the same level of performance with a significant lower cost as compared to a conservative plan, which assumes the highest demand of each origin node.

Original languageEnglish (US)
Pages (from-to)272-288
Number of pages17
JournalJournal of Transportation Safety and Security
Volume3
Issue number4
DOIs
StatePublished - Dec 1 2011
Externally publishedYes

Keywords

  • demand uncertainty
  • evacuation planning
  • robust optimization
  • shelter location and capacity

ASJC Scopus subject areas

  • Transportation
  • Safety Research

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