Solving an Emergency Resource Planning Problem with Deprivation Time by a Hybrid MetaHeuristic Algorithm

Every year, natural disasters (e.g., floods and earthquakes) threaten people's lives and finances. To cope with the damage of natural disasters, emergency resources (e.g., rescue teams) must be planned efficiently. Therefore, designing a decision support model to allocate and schedule rescue teams is necessary for the response phase of disaster management. The literature review shows that social aspects of disaster management have less been addressed by researchers, whereas this phenomenon must be incorporated into decision-making processes. The lack of timely relief implies a loss in people's welfare, which leads to social costs called deprivation cost or time. This study proposes a multi-objective mixed-integer programming model to assign and schedule the rescue teams considering different rescuers' capabilities, fatigue effects, and deprivation time. Due to the NP-Hardness of the proposed model, a hybrid approach based on the Lpmetric method and meta-heuristic algorithms are applied to solve the given problem. The results show that the developed algorithm can obtain high-quality solutions in a reasonable time.