Abstract
We address a milk run logistics problem in which goods must be transferred between facilities on a regular basis to support a company’s production. The resulting optimization problem is a form of cyclical, multi-commodity inventory routing problem with pick-ups and deliveries. This problem becomes particularly challenging when either all available cargo of a particular commodity must be picked up or none of it, so as to simplify internal logistics procedures. We model the problem mathematically and introduce a two-phase heuristic to solve the problem. The first phase consists of an adaptive large neighborhood search (ALNS), and the second phase uses a relaxed version of the mathematical model to improve the routes for the vehicles. We present experimental results on a dataset based on real-world data from a company in Germany and show that our two-phase procedure can find high quality solutions even to real-world sized problems in reasonable amounts of computation time.
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Notes
- 1.
Although the models are run on different machines, the mathematical model was run on a faster machine than the ALNS.
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Acknowledgments
We thank the Paderborn Center for Parallel Computation (PC\(^2\)) for the use of the OCuLUS cluster.
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Schulte, J., Römer, M., Tierney, K. (2020). Cyclical Inventory Routing with Unsplittable Pick-Up and Deliveries. In: Lalla-Ruiz, E., Mes, M., Voß, S. (eds) Computational Logistics. ICCL 2020. Lecture Notes in Computer Science(), vol 12433. Springer, Cham. https://doi.org/10.1007/978-3-030-59747-4_16
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