A Conic Integer Programming Approach to Constrained Assortment Optimization under the Mixed Multinomial Logit Model
Optimization and Control
2017-08-15 v2
Abstract
We consider the constrained assortment optimization problem under the mixed multinomial logit model. Even moderately sized instances of this problem are challenging to solve directly using standard mixed-integer linear optimization formulations. This has motivated recent research exploring customized optimization strategies and approximation techniques. In contrast, we develop a novel conic quadratic mixed-integer formulation. This new formulation, together with McCormick inequalities exploiting the capacity constraints, enables the solution of large instances using commercial optimization software.
Cite
@article{arxiv.1705.09040,
title = {A Conic Integer Programming Approach to Constrained Assortment Optimization under the Mixed Multinomial Logit Model},
author = {Alper Sen and Alper Atamturk and Philip Kaminsky},
journal= {arXiv preprint arXiv:1705.09040},
year = {2017}
}