Evacuation planning for disaster responses: A stochastic programming framework. (August 2016)

• Record Type: Journal Article
• Authors: Wang, Li; Yang, Lixing; Gao, Ziyou; Li, Shukai; Zhou, Xuesong
• Is Part Of: Transportation research. Volume 69(2016)
• Page Start: 150
• Page End: 172
• Publication Date: 2016-08
• Subjects: Evacuation -- Stochastic programming -- Side constraint -- Relaxation-based heuristic; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2016.05.022
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: We formulate a stochastic evacuation planning framework with side constraints. Three evaluation criteria are introduced to formulate the objective function. A Lagrangian relaxation-based heuristic algorithm is designed. The algorithm can solve large-scale instances efficiently and effectively. 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.