Stochastic shelter site location under multi-hazard scenarios
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In some cases, natural disasters happen successively (e.g. a tsunami following an earthquake) in close proximity of each other, even if they are not correlated. This study locates shelter sites and allocates the a ected population to the established set of shelters by considering the aftershock(s) following the initial earthquake, via a three-stage stochastic mixed-integer programming model. In each stage, before the uncertainty, which is the number of a ected people, in the corresponding stage is resolved, shelters are established, and after the uncertainty is resolved, a ected population is allocated to the established set of shelters. To manage the inherent risk related to the uncertainty, conditional value-atrisk is utilized as a risk measure in allocation of victims to the established set of shelters. Computational results on the Istanbul dataset are presented to emphasize the necessity of considering secondary disaster(s), along with a heuristic method to improve the solution times and qualities. During these computational analyses, it is observed that the original single-objective model poses some obstacles in parameter selection. As in humanitarian operations, choosing parameters may cause con ict of interests and hence may be criticized, a multi-objective framework is developed with various formulations. Some generalizations regarding the performance and applicability of the developed formulations are discussed and nally, another heuristic for the multi-objective formulation is presented to tackle the curse of dimensionality and improve the solution times.
KeywordsShelter Site Location
Multi-Stage Stochastic Programming
Multi Objective Programming