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Retail shelf space allocation considering inventory replenishment

Author

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  • Hasmukh K. Gajjar
  • Gajendra Kumar Adil

Abstract

Shelf space allocation to products greatly impacts the profitability in a retail store. This paper makes two contributions to existing retail shelf space allocation problem. First, a nonlinear shelf space allocation model (NLSSAMINV) is developed incorporating inventory replenishment into an existing nonlinear shelf space allocation model (NLSSAM). Second, existing solution methods [dynamic programming algorithm (DPA) and local search heuristic (LSH)] developed to solve NLSSAM are suitably adapted for solving NLSSAMINV. A pre-processing routine is also developed to reduce the search space in DPA and LSH. It is found from experimental studies that due to pre-processing routine, DPA and LSH took less CPU time to solve NLSSAMINV than that required for solving NLSSAM.

Suggested Citation

  • Hasmukh K. Gajjar & Gajendra Kumar Adil, 2015. "Retail shelf space allocation considering inventory replenishment," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 22(2), pages 221-234.
    • Handle: RePEc:ids:ijsoma:v:22:y:2015:i:2:p:221-234
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    Cited by:

    1. Bianchi-Aguiar, Teresa & Hübner, Alexander & Carravilla, Maria Antónia & Oliveira, José Fernando, 2021. "Retail shelf space planning problems: A comprehensive review and classification framework," European Journal of Operational Research, Elsevier, vol. 289(1), pages 1-16.

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