AN INTEGRATED RELIEF NETWORK DESIGN MODEL FOR LOGISTICS PLANNING UNDER UNCERTAINTY

Locating facilities in candidate nodes and allocating relief items to these facilities for emergency response before a disaster occurs, is a common approach to increasing the eectiveness of relief logistics. In this study, humanitarian logistics networks and network restoration are presented in the form of an integrated network, so that the damaged routes are repaired by crews using restoration equipment to distribute relief items. In this paper, a two-stage stochastic programming model is proposed in order to locate relief facilities and restoration equipment and distribute relief items to demand nodes as soon as possible.
The objective function minimizes the social costs of the problem such as deprivation cost (i.e., the cost imposed on survivors by the lack of access to critical supplies) and logistics costs under each scenario. Also, the ow of trucks carrying relief items and repair equipment on the routes is specied. In order to adapt the model to the real world, according to the nature of the eective parameters of the model, two types of structural and functional uncertainties have been considered. The rst source is that some uncertain parameters may be based on future scenarios which are considered according to the probability of their occurrence. The second source is that the values of these parameters in each scenario are usually imprecise and can be specied by possibility distributions. In this regard, a robust fuzzy stochastic programming approach has been used to solve the model. Possibility theory is used to choose a solution to such a problem and a robust fuzzy stochastic programming approach is proposed that has signicant advantages. The proposed model has been implemented for a case study of 39 districts of Istanbul and the computational results show the eective eciency of this model in reducing the social costs of the humanitarian logistics problem.