Multi-vehicle stochastic cyclic inventory routing with guaranteed replenishments

This paper studies the multi-vehicle cyclic inventory routing problem with stochastic demand. The objective is to provide cost-efficient buffering of the demand variability within a cyclic distribution plan using a combination of safety stock at the customers and expedited shipments from the depot to guarantee replenishments in cycles where cumulative demand exceeds the vehicle capacity. We present a powerful metaheuristic solution approach that integrates stochastic demand within the route and fleet design. Computational results show that the proposed method outperforms state-of-the-art solution approaches for the constant demand case and that it is able to adequately balance vehicle operating costs, cycle inventory and safety stock holding costs, with backlogging and expediting costs. The numerical results also confirm that important savings can be achieved by integrating demand variability in the route and fleet design, and that the cyclic approach can absorb demand variability with limited cost increases.