The Double Routing Vehicle Problem with Multiple Stacks (DVRPMS) consists in a Double Traveling Salesman Problem with Multiple Stacks (DTSPMS) with multiple vehicles. Both problems appeared for the urgent need of optimizing intermodal transportation in the european context. Consolidated economies call for logistics studies, particularly on intermodal transportation, which consists of using different transport modes between a start point and an end point. In DVRPMS, the collecting region is usually connected to the delivery region by sea, and the cities that make up each of these regions are interconnected by land routes. In this paper, we propose three heuristics for the DVRPMS based on the Iterated Local Search (ILS), Simulated Annealing (SA) and Variable Neighborhood Descent (VND). The objective is to provide a route with near optimum cost in a timeframe that complies with the customer's needs. The heuristics were applied in known instances and compared to the exact method. Both ILS and SA algorithms showed to be satisfactory for small instances and open to improvement for large instances. The SA algorithm managed to find solutions better than the best known upperbound. The VND algorithm served more as a guide to the quality of the initial solution than as a provider of a good final solution.