Distribution planning is crucial for most companies since goods are rarely produced and consumed at the same place. Distribution costs, in addition, can be an important component of the final cost of the goods. In this paper , we study a VRP variant inspired on a real case of a large distribution company. In particular, we consider a VRP with a heterogeneous fleet of vehicles that are allowed to perform multiple trips. The problem also includes docking constraints in which some vehicles are unable to serve some particular customers. Given the combinatorial nature and the size of the problem, which discard the use of efficient exact methods for its resolution, a novel heuristic algorithm is proposed. The proposed algorithm, called GILS-VND, combines Iterated Local Search (ILS), Greedy Randomized Adaptive Search Procedure (GRASP) and Variable Neighborhood Descent (VND) procedures. Our method obtains better solutions than other approaches found in the related literature, and improves the solutions used by the company leading to