The inventory routing problem combines the issue of organizing product delivery or pick-up, and managing the inventory at each customer site. Our application deals with planning product pick-ups, customer inventory being emptied on each visit. We assume a deterministic production rate. The inventory costs are limited to those resulting from the transportation model. In this tactical model, the objective is to minimize the fleet size and to ensure that routes are geographically clustered. The planning must be repeated over the time horizon with constrained periodicity. We develop a truncated branch-and-price algorithm combined with rounding and local search heuristics that yield both primal solutions and dual bounds. On a large scale test problem coming from industry, we obtain a solution within 6.5\% deviation of the optimal. A rough comparison with the industrial practice shows a 10\% decrease in number of vehicles as well as in travel distance. The key to the success of the approach is the use of a state-space relaxation technique in formulating the master program to avoid the symmetry in time. The paper also includes a short review of column generation based heuristics.