Abstract
The vehicle routing problem with time windows and simultaneous pick-ups and deliveries (VRPTWSPD) is one of the main distribution planning problems. VRPTWSPD aims to find the best distribution plan that minimizes the number of vehicle used and the total travelled distance. Due to the NP-Hard nature of the VRPTWSPD, practical large-scale instances cannot be solved to optimality within acceptable computational times. Therefore, it is necessary to develop approximation algorithms to tackle the VRPTWSPD as effectively as possible, as we try to do within the context of this study. Accordingly, a Grey Wolf Optimizer (GWO) algorithm is designed to solve the VRPTWSPD. The designed algorithm starts its search with a group of solutions constructed through the K-means algorithm. Additionally, the algorithm has been enhanced by incorporating the Variable Neighbourhood Search (VNS) algorithm as a local search algorithm. The performance evaluation tests of the developed GWO algorithm was done on the standard benchmark sets which is taken from the related literature. Computational results indicate that the proposed GWO algorithm has a satisfactory performance in solving VRPTWSPD instances.
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