A Covering Tour Approach for Disaster Relief Locating and Routing with Fuzzy Demand

Optimizing the distribution and allocation of resources among individuals is one of the most important measures to be taken at the time of crisis. Time, as a vital factor, has a significant impact on the increase in the number of people rescued by relief activities. This paper presents an allocation and routing model for relief vehicles in the areas affected by a disaster. It uses a covering tour approach to reduce response time. Moreover, because determining the exact amount of demand for essential goods in the event of a disaster is very difficult and even impossible in some cases, the demand parameter is considered as a fuzzy parameter in this model. Accordingly, an optimization method is designed based on credibility theory, and a harmony search algorithm with random simulation is developed. Finally, the efficiency of the harmony search algorithm is analyzed by comparing the CPLEX solver and GRASP algorithm. The results show that the proposed algorithm performs well over a short operating time.