Evacuation planning for disaster responses

A stochastic programming framework

Li Wang, Lixing Yang, Ziyou Gao, Shukai Li, Xuesong Zhou

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

Some disasters such as earthquakes, floods and hurricanes may result in evacuation for people in an affected area. This paper focuses on finding the a priori evacuation plans by considering side constraints and scenario-based stochastic link travel times and capacities. Hence a stochastic programming framework is developed so as to provide a reorganization of the traffic routing for a disaster response. Considering the different preferences of decision-makers, three evaluation criteria are introduced to formulate the objective function. Crisp linear equivalents for different evacuation strategies are further deduced to simplify solution methodologies. A heuristic algorithm combining the Lagrangian relaxation-based approach with K-shortest path techniques is designed to solve the expected disutility model. The experimental results indicate that the algorithm can solve large-scale instances for the problem of interest efficiently and effectively.

Original languageEnglish (US)
Pages (from-to)150-172
Number of pages23
JournalTransportation Research Part C: Emerging Technologies
Volume69
DOIs
StatePublished - Aug 1 2016

Fingerprint

Stochastic programming
Disasters
disaster
natural disaster
programming
Planning
planning
Hurricanes
Travel time
Heuristic algorithms
reorganization
decision maker
heuristics
Earthquakes
travel
traffic
scenario
methodology
evaluation
Disaster response

Keywords

  • Evacuation
  • Relaxation-based heuristic
  • Side constraint
  • Stochastic programming

ASJC Scopus subject areas

  • Computer Science Applications
  • Management Science and Operations Research
  • Automotive Engineering
  • Transportation

Cite this

Evacuation planning for disaster responses : A stochastic programming framework. / Wang, Li; Yang, Lixing; Gao, Ziyou; Li, Shukai; Zhou, Xuesong.

In: Transportation Research Part C: Emerging Technologies, Vol. 69, 01.08.2016, p. 150-172.

Research output: Contribution to journalArticle

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