Evacuation planning for disaster responses: A stochastic programming framework. (August 2016) - Wang, Li; Yang, Lixing; Gao, Ziyou; Li, Shukai; Zhou, Xuesong
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.