Tractable Approximations for Assortment Planning with Product Costs
By Sumit Kunnumkal, Victor Martinez-de-Albeniz
Operations Research | March 2019
DOI
pubsonline.informs.org/doi/epdf/10.1287/opre.2018.1771
Citation
Kunnumkal, Sumit., Martinez-de-Albeniz, Victor. (2018). Tractable Approximations for Assortment Planning with Product Costs Operations Research pubsonline.informs.org/doi/epdf/10.1287/opre.2018.1771.
Copyright
Operations Research, 2018
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Abstract
Assortment planning under a logit demand model is a difficult problem when there are product specific costs associated with including products into the assortment. In this paper, we describe a tractable method to obtain an upper bound on the optimal expected profit. We provide performance guarantees on the upper bound obtained. Computational experiments reveal that our method can obtain significantly tighter bounds compared to benchmark methods. We describe how our method can be extended to incorporate additional constraints on the assortment or multiple customer segments.

Sumit Kunnumkal is a Professor and Area Leader of Operations Management at the Indian School of Business (ISB). He holds a PhD in Operations Research from Cornell University. He received his MS in Transportation from the Massachusetts Institute of Technology and a B.Tech in Civil Engineering from the Indian Institute of Technology, Madras.

Professor Kunnumkal has previously taught at the Smith School of Business, Queen’s University, and has held visiting positions at the Singapore University of Technology and Design and Universitat Pompeu Fabra. His research interests lie in the areas of pricing and revenue management, retail operations, assortment planning, and approximate dynamic programming.

At ISB, he has taught in the PGP programme, the Fellow programme, and various Advanced Management and Executive Education programmes.

Sumit Kunnumkal
Sumit Kunnumkal