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A Solver-Free Heuristic for Store-Wide Shelf Space Allocation

In: Retail Space Analytics

Author

Listed:
  • Tulay Flamand

    (Department of Economics and Business, Colorado School of Mines)

  • Ahmed Ghoniem

    (University of Massachusetts Amherst)

  • Bacel Maddah

    (American University of Beirut)

Abstract

We investigate a store-wide shelf space allocation problem where the retailer seeks to maximize the expected impulse buying profit by allocating product categories to the store shelves. Based on the extant literature, in-store traffic is captured via a complex predictive model as a function of both allocation decisions and the store layout. We demonstrate that a solver-free heuristic yields promising solutions that can alternatively be obtained and validated by more computationally intensive mathematical programming-based approaches. The proposed approach is applied to a grocery store in Beirut, Lebanon, and more generally provides a practical tool that can be adapted for store-wide shelf space allocation in a variety of brick-and-mortar stores.

Suggested Citation

  • Tulay Flamand & Ahmed Ghoniem & Bacel Maddah, 2023. "A Solver-Free Heuristic for Store-Wide Shelf Space Allocation," International Series in Operations Research & Management Science, in: Ahmed Ghoniem & Bacel Maddah (ed.), Retail Space Analytics, pages 21-34, Springer.
    • Handle: RePEc:spr:isochp:978-3-031-27058-1_2
    DOI: 10.1007/978-3-031-27058-1_2
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