An Efficient Variable Neighborhood Search with Tabu Shaking for a Class of Multi-Depot Vehicle Routing Problems
(Published in Computers & Operations)
We present a Variable Tabu Neighborhood Search (VTNS) algorithm for solving a class of Multi-Depot Vehicle Routing Problems including MDVRP, MDVRP with Time Windows (MDVRPTW), and Multi-Depot Open Vehicle Routing Problem (MDOVRP). Our computational tests on these three problems show that VTNS provides promising results competitive with state-of-the-art algorithms from the literature in terms of both solution quality and run time. Overall, we achieve six new best-known solutions in the MDVRP, one in the MDVRPTW, and four in the MDOVRP benchmark data sets.
The following Tables present the new best solution found by VTNS for six instances of MDVRP. one instance of MDVRPTW, and four instances of MDOVRP.