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Hybrid metaheuristic solutions to inventory location routing problem
Institution:1. Research Group of Technology Applied to Optimization (GTAO), Federal University of Paraná (UFPR), Curitiba, Brazil;2. Canada Research Chair in Integrated Logistics and CIRRELT, Université Laval, Québec, Canada
Abstract: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.
Keywords:Supply chain  Inventory location routing  Inventory-routing problem  Location-routing problem  Metaheuristic  Simulated annealing
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