Drug logistics network design based on the fleet routing by using the improved gray wolf optimizer algorithm

Transportation of pharmaceuticals as one of the most complex types of transportation has always been studied by researchers. This issue, which is a subset of a key issue called the transportation of hazardous substances, is one of the most integral and high-risk activities in the industrial activity cycle. Trying to find the optimal solution to this problem is one of the most useful topics in logistics. Accordingly, this study optimized the design of the drug logistics network. In this regard, the issue of vehicle routing (VRP) has been inspired. In this regard, the issue of vehicle routing (VRP) is inspired. To this end, first a conceptual model for this problem and a new mathematical model for routing drug transport vehicles with the role of path sensitivity and time window uncertainty are presented. In order to solve the problem, the Gray Wolf meta-heuristic algorithm has been used as a new and efficient algorithm. To evaluate the performance of the proposed algorithm, this algorithm is compared with the exact solution method and genetic algorithms and particle swarm and the results of the gray wolf algorithm show that this algorithm provides answers with the least possible error in a very short time.