Sustainable shelters and hub locations for flood disasters: A multimodal transportation approach

This paper proposes a two-phase sustainable optimization framework for flood relief distribution. The first phase solves a multi-objective problem to optimize shelter-hub locations and response team allocation, considering economic, social, and environmental factors, using a hybrid genetic algorithm and exact method. The second phase evaluates first-phase solutions through a model that incorporates multimodal transportation (truck, drone, and heterogeneous boats) with response team arrival time-window, solved by combining variable neighborhood search, exact method, and dynamic threshold-based procedure. The solution methods are tested on generated instances and case study in Jakarta, Indonesia, a region highly prone to flood disasters characterized by deep flood depths, extensive flooded area, long rainfall duration, and a high potential risk of death. The results demonstrate promising solutions and provide useful managerial insights.