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A Stochastic, Multi-Commodity Multi-Period Inventory-Location Problem: Modeling and Solving an Industrial Application

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Computational Logistics (ICCL 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11756))

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Abstract

This paper addresses the real-world supply chain network design problem with a strategic multi-commodity and multi-period inventory-location problem with stochastic demands. The proposed methodology involves a complex non-linear, non-convex, mixed integer programming model, which allows for the optimization of warehouse location, demand zone’s assignment, and manufacturing settings while minimizing the fixed costs of a distribution center (DC), along with the transportation and inventory costs in a multi-commodity, multi-period scenario. In addition, a genetic algorithm is implemented to obtain near-optimal solutions at competitive times. We applied the model to a real-world industrial case of a Colombian rolled steel manufacturing company, where a new, optimized supply chain distribution network is required to serve customers at a national level. The proposed approach provides a practical solution to optimize their distribution network, achieving significant cost reductions for the company.

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Author information

Authors and Affiliations

  1. Department of Civil Engineering, Universidad Militar Nueva Granada, Carrera, 58#55-66, Bogotá, Colombia

    Mauricio Orozco-Fontalvo

  2. Department of Civil and Environmental Engineering, Universidad del Norte, Km 5 Vía Puerto Colombia, Barranquilla, Colombia

    Víctor Cantillo

  3. Department of Engineering Sciences, Faculty of Engineering, Universidad Andres Bello, Campus Viña Del Mar, Santiago, Chile

    Pablo A. Miranda

Authors
  1. Mauricio Orozco-Fontalvo
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  2. Víctor Cantillo
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  3. Pablo A. Miranda
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Corresponding author

Correspondence to Mauricio Orozco-Fontalvo .

Editor information

Editors and Affiliations

  1. Universidad del Norte, Barranquilla, Colombia

    Carlos Paternina-Arboleda

  2. Universität Hamburg, Hamburg, Germany

    Stefan Voß

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Orozco-Fontalvo, M., Cantillo, V., Miranda, P.A. (2019). A Stochastic, Multi-Commodity Multi-Period Inventory-Location Problem: Modeling and Solving an Industrial Application. In: Paternina-Arboleda, C., Voß, S. (eds) Computational Logistics. ICCL 2019. Lecture Notes in Computer Science(), vol 11756. Springer, Cham. https://doi.org/10.1007/978-3-030-31140-7_20

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  • DOI: https://doi.org/10.1007/978-3-030-31140-7_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-31139-1

  • Online ISBN: 978-3-030-31140-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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