The challenge in last-mile supply chains deliveries is to maintain and improve the operational costeffectiveness by the implementation of efficient procedures while facing increased levels of congestion in cities. One competitive alternative is Horizontal Cooperation (HC). City distribution problems under HC conditions can be modeled as multi-depot vehicle routing problems, which are NP-hard problems meaning that exact methods provide optimal solutions only for small datasets. This complexity increases when considering stochastic demand. Therefore, real-life situations must be solved using heuristic algorithms. This paper proposes the implementation of a simheuristic (i.e., an algorithm combining heuristics with simulation). Experiments are carried out using realistic data from the city of Bogotá, Colombia, regarding the distribution of goods to the whole network of the three major chains of convenience stores currently operating in the city. Results show the power of the proposed simheuristic in comparison with traditional solution approaches based on mathematical programming.