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A Conic Integer Programming Approach to Constrained Assortment Optimization under the Mixed Multinomial Logit Model (1705.09040v2)

Published 25 May 2017 in math.OC

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.

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