In this paper, we consider the distribution process of a manufacturing company that supplies products to the customers located in a service region. The company distributes its products partitioning the service region into delivery zones or districts that are served by a single deliveryman. Two objectives are considered when designing the delivery zones: balance the workload associated with each zone, and the minimization of the customers’ waiting times (latency). The former objective concerns a districting decision, and the latter objective is related to a routing decision. To support these planning decisions, an optimization framework based on a novel bi-objective optimization model is proposed. To approximate the frontier of non-dominated solutions of the bi-objective problem, an efficient heuristic algorithm inspired in the -constraint method is developed. The proposed algorithm exploits the characteristics of the problem, and it is used to solve a real case study. Obtained results are compared with the current solution employed by the company. Both objective function values are improved by any of the solutions in the approximated Pareto front. To show the efficiency and robustness of the proposed algorithm, an additional set of instances derived from the case study is tested. The results indicate that the algorithm is able to approximate the Pareto fronts despite their shape. Hence, interesting managerial insights to improve the current decisions of the company are provided derived from the computational experiments.
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