In this paper, we studied the shelf-space allocation problem (SSAP). It is quite common recently to implement product design during a selling season and drastically change assortment decisions based on shelf-space allocation in response to up-to-date demand observations. While there are many literatures related to SSAP, However, existing literature assume that the demand is stationary. In this paper, we propose a dynamical framework to make shelf-space display decisions, in which space elasticity and potential demand are sequentially estimated using the latest data containing display space and sales for each product.

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@article{oscm-2019-240,
  title={Shelf-space Allocation Model with Demand Learning},
  author={},
  journal={Operations and Supply Chain Management: An International Journal},
  year={2019},
  volume={12},
  number={1},
  pages={0--0},
  doi={http://doi.org/10.31387/oscm0360219}
}

 (2019). Shelf-space Allocation Model with Demand Learning. Operations and Supply Chain Management: An International Journal, 12(1), 0-0. https://doi.org/http://doi.org/10.31387/oscm0360219