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A conic optimization approach for SKU rationalization

Author

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  • KEGELART, Tanguy

    (Universitécatholique de Louvain, Louvain School of Management, Belgium)

  • VAN VYVE, Mathieu

    (Université catholique de Louvain, CORE, Belgium)

Abstract

Expanding variety and the number of offered products is attractive for a firm to fit customer needs. Nevertheless, the greater complexity and the proliferation of stock-keeping units (SKUs) without substantial differentiation may not substantially improve customer satisfaction while raising costs. Based on the principle that the product-line size involves operational implications and particularly manufacturing and holding costs, this paper develops a mixed-integer nonlinear mathematical program (MINLP) to support efficient product portfolio reductions. Basically, the fixed costs elimination and the risk-pooling effects must balance the demand contraction due to customer dissatisfaction. Off-the-shelve Mixed-Integer Quadratic Problem (MIQP) solver provides optimal solution to the proposed conic quadratic reformulation, and a real-life industrial case illustrates the program and the algorithm efficiency. Findings show that our mathematical programming subject to various assumptions and estimations is efficient to rationalize portfolios up to at least 400 SKUs.

Suggested Citation

  • KEGELART, Tanguy & VAN VYVE, Mathieu, 2014. "A conic optimization approach for SKU rationalization," LIDAM Discussion Papers CORE 2014034, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvco:2014034
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    References listed on IDEAS

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    1. Zuo-Jun Max Shen & Mark S. Daskin, 2005. "Trade-offs Between Customer Service and Cost in Integrated Supply Chain Design," Manufacturing & Service Operations Management, INFORMS, vol. 7(3), pages 188-207, September.
    2. Snyder, Lawrence V. & Daskin, Mark S. & Teo, Chung-Piaw, 2007. "The stochastic location model with risk pooling," European Journal of Operational Research, Elsevier, vol. 179(3), pages 1221-1238, June.
    3. Charles J. Corbett & Kumar Rajaram, 2006. "A Generalization of the Inventory Pooling Effect to Nonnormal Dependent Demand," Manufacturing & Service Operations Management, INFORMS, vol. 8(4), pages 351-358, August.
    4. Gregory Dobson & Shlomo Kalish, 1988. "Positioning and Pricing a Product Line," Marketing Science, INFORMS, vol. 7(2), pages 107-125.
    5. Mark Daskin & Collette Coullard & Zuo-Jun Shen, 2002. "An Inventory-Location Model: Formulation, Solution Algorithm and Computational Results," Annals of Operations Research, Springer, vol. 110(1), pages 83-106, February.
    6. Marshall Fisher, 2009. "OR FORUM--Rocket Science Retailing: The 2006 Philip McCord Morse Lecture," Operations Research, INFORMS, vol. 57(3), pages 527-540, June.
    7. Alper Atamtürk & Gemma Berenguer & Zuo-Jun (Max) Shen, 2012. "A Conic Integer Programming Approach to Stochastic Joint Location-Inventory Problems," Operations Research, INFORMS, vol. 60(2), pages 366-381, April.
    8. Gregory Dobson & Shlomo Kalish, 1993. "Heuristics for Pricing and Positioning a Product-Line Using Conjoint and Cost Data," Management Science, INFORMS, vol. 39(2), pages 160-175, February.
    9. Richard D. McBride & Fred S. Zufryden, 1988. "An Integer Programming Approach to the Optimal Product Line Selection Problem," Marketing Science, INFORMS, vol. 7(2), pages 126-140.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    supply chain management; efficient portfolio reduction; joint product portfolio-inventory model; conic quadratic mixed-integer program;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management

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