A variable neighborhood search for the multi-product inventory routing problem

We address a multi-product inventory routing problem, and propose a two-phase variable neighborhood search (VNS) metaheuristic to solve it. In the first phase, VNS is used to solve a capacitated vehicle routing problem, period by period, to find an initial solution without taking into account the inventory. In the second phase, VNS iteratively improves the initial solution while minimizing both the transportation and inventory costs. We propose an efficient heuristic to determine the amount of products to collect from each supplier at each time period. This heuristic is applied at each local search move, and during the exploration we use priority rules of suppliers and vehicles, based on the current delivery schedule over the planing horizon. Computational results show the efficiency of the two-phase approach proposed.