Hybrid metaheuristic solutions to inventory location routing problem

•The problem integrates location, allocation, inventory and routing decisions.•We present a novel and low complexity method to calculate inventory cost.•The problem is solved by decomposition into near exact subproblems.•The metaheuristic is competitive when solving LRP and IRP benchmark problems.•The metaheuristic can solve large-scale IRLP instances in reasonable time.

This paper considers a supply chain network with multiple depots and geographically dispersed customers, each of which faces non-constant demand over a discrete planning horizon. The goal is to determine a set of depots to open, the delivery quantities to customers per period and the sequence in which they are replenished by a vehicle fleet such that the total system-wide cost is minimized. To solve it, first we construct a mixed integer program, and then propose a hybrid metaheuristic consisting of initialization, intensification and post-optimization. Results show that the proposed heuristic is considerably efficient and effective for many classical instances.