Evacuation planning for disaster responses: A stochastic programming framework

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

Research output: Contribution to journalArticlepeer-review

37 Scopus citations


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
StatePublished - Aug 1 2016


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

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Management Science and Operations Research


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