A bi-objective model for the design of daily routes over a planning period is analyzed. This model is proposed in response to a real problem encountered by a chemical analysis company located in Salamanca, (Spain). In order to improve its schedule for client visits, the company faced a two-level problem: first, to determine the days for client visits ("visit calendar") for each client during the planning period, and then to design the corresponding daily routes. To do so, two objectives were considered: minimization of transport costs and minimization of the number of changes to the existing calendar of visits. This model could be considered as a variant of the well-known periodic vehicle-routing problem (PVRP) with two objectives. A solution method that combines tabu search and MOAMP (Multiobjective Adaptive Memory Programming) strategies is proposed for this model. Also this method is compared with an adaptation of NSGA-II (Non-dominated Sorting Genetic Algorithm), a well-known strategy to multi-objective optimization. The computational results show that the MOAMP-Tabu Search method performs better.