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A relax-and-price heuristic for the inventory-location-routing problem

This paper considers the problem of designing a supply chain assuming routing decisions. The objective is to select a subset of depots to open from a set of candidates, the inventory policies for a two-echelon system, and the set of routes to perform distribution from the upper echelon to the next by a homogeneous fleet of vehicles over a finite planning horizon considering deterministic demand. To solve the problem, a partition is proposed using a Dantzig–Wolfe formulation on the routing variables. A hybridization between column generation, Lagrangian relaxation, and local search is presented within a heuristic procedure. Results demonstrate the capability of the algorithm to compute high quality solutions and empirically estimate the improvement in the cost function of the proposed model at up to 9% compared to the sequential approach. Furthermore, the suggested pricing problem is a new variant of the shortest path problem with applications in urban transportation and telecommunications.