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The PrePack Optimization Problem

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8451))

Abstract

The goal of packing optimization is to provide a foundation for decisions related to inventory allocation as merchandise is brought to warehouses and then dispatched. Major retail chains must fulfill requests from hundreds of stores by dispatching items stored in their warehouses. The demand for clothing items may vary to a considerable extent from one store to the next. To take this into account, the warehouse must pack “boxes” containing different mixes of clothing items. The number of distinct box types has a major impact on the operating costs. Thus, the PrePack problem consists in determining the number and contents of the box types, as well as the allocation of boxes to stores. This paper introduces the PrePack problem and proposes CP and MIP models and a metaheuristic approach to address it.

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References

  1. Erie, C.W., Lee, J.S., Paske, R.T., Wilson, J.P.: Dynamic bulk packing and casing. International Business Machines Corporation, US20100049537 A1 (2010)

    Google Scholar 

  2. Vakhutinsky, A., Subramanian, S., Popkov, Y., Kushkuley, A.: Retail pre-pack optimizer. Oracle International Corporation, US20120284079 A1 (2012)

    Google Scholar 

  3. Pratt, R.W.: Computer-implemented systems and methods for pack optimization. SAS Institute, US20090271241 A1 (2009)

    Google Scholar 

  4. Chandra, A.K., Hirschberg, D.S., Wong, C.K.: Approximate algorithms for some generalized knapsack problems. Theoretical Computer Science 3(3), 293–304 (1976)

    Article  MathSciNet  Google Scholar 

  5. Mendoza, J.E., Medaglia, A.L., Velasco, N.: An evolutionary-based decision support system for vehicle routing: The case of a public utility. Decision Support Systems 46, 730–742 (2009)

    Article  Google Scholar 

  6. Medaglia, A.L., Gutérrez, E.J.: An object-oriented framework for rapid development of genetic algorithms. Handbook of Research on Nature Inspired Computing for Economics and Management. Idea Publishing Group (2006)

    Google Scholar 

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© 2014 Springer International Publishing Switzerland

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Hoskins, M., Masson, R., Gauthier Melançon, G., Mendoza, J.E., Meyer, C., Rousseau, LM. (2014). The PrePack Optimization Problem. In: Simonis, H. (eds) Integration of AI and OR Techniques in Constraint Programming. CPAIOR 2014. Lecture Notes in Computer Science, vol 8451. Springer, Cham. https://doi.org/10.1007/978-3-319-07046-9_10

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  • DOI: https://doi.org/10.1007/978-3-319-07046-9_10

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07045-2

  • Online ISBN: 978-3-319-07046-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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