A new hybrid algorithm for multi-depot vehicle routing problem with time windows and split delivery

Effective coordination of distribution operations of a manufacturing organisation is paramount since it represents the major cost component of the logistic supply chain. To deal with high demand of orders with shorter lead time, distributed warehouse concept is introduced, and this is currently being practised. Furthermore, due to inherent deficiencies in vehicle routing problem (VRP), rules have been extended to accommodate large-scale orders by splitting the delivery. Time-constrained routing is relevant in an application where timely scheduled productions occur. Artificial intelligences based approaches are widely used in the literature to solve VRP problems with extensions. In this research, hybrid algorithm (SATS) is developed based on simulated annealing (SA) and Tabu search (TS) techniques to improve the solution quality of the complex multi-depot VRP with time windows and split delivery. The simulation results reveal that SATS outperforms in solution quality when it is compared with the result of Cordeau et al. (2001). Results reveal SATS gives best results for more than 50% instances.