Logistics network design is one of the principal parts of strategic decisions in the planning and control of production systems. It deals with determining the warehouses locations and the definition of product flow between facilities and clients. This work is focused in finding an approximation of the Pareto-optimal front for two conflicting objective functions in logistic networks design: minimize costs and maximize coverage. Since the establishing of which warehouses must be opened constitute a combinatorial optimization problem, two metaheuristic techniques, namely Improved Strength Pareto Evolutionary Algorithm - SPEA2 and a novel binary version of Bacterial Chemotaxis Multi-objective Optimization Algorithm - BCMOA, were applied. With the aim of finding the optimal flow between clients and warehouses, network flow algorithms were also used.