Çoklu afetlerin yönetimi: Rassal talep altında çadırkent yer seçimi problemi

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 affected 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 affected people, in the corresponding stage is resolved, shelters are established, and after the uncertainty is resolved, affected population is allocated to the established set of shelters. To manage the inherent risk related to the uncertainty, conditional value-at-risk 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 conflict 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 finally, another heuristic for the multi-objective formulation is presented to tackle the curse of dimensionality and improve the solution times.