a robust possibilistic programming model for disaster relief routing under information and communication technology

In this paper, we investigate an integrated procurement and capacitated vehicle routing problem for the distribution of multiple relief goods after the disaster, to determine the best tour for vehicles as well as the best selection of multiple relief goods and their quantity to be loaded on vehicles. due to the uncertain nature of the parameters, the demand distribution and cost parameters are considered as fuzzy parameters. furthermore, this paper examines the impact of information and communication technology in the affected areas so that instant information, communicate between the affected areas and the disaster coordination center due to new events caused by the disaster. we have examined the impact of information and communication technology on reducing demand uncertainty such that with consideration of the cost of equipping gps in affected areas, as well as its impact on reducing demand uncertainty and the cost of dissatisfaction as a result; the best affected areas are selected to be equipped with gps. to have robust solutions, a robust possibilistic programming model is proposed. the results of the model are shown in a real case study in district 7 of tehran which acclaim that the proposed model achieves a better result than the traditional models without considering ict.