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The assortment planning problem is a central piece in the revenue managementstrategy of any company in the retail industry. In this paper, we study arobust assortment optimization problem for substitutable products under asequential ranking-based choice model. Our modeling approach incorporates thecumulative effect of finding multiple unavailable products on the customers'purchase decisions. To model the highly uncertain order in which a customerexplores the products to buy, we present a bi-level optimization approach tomaximize the expected revenue under the worst-case order of products in thepreference lists of customers. We provide a polynomial-time algorithm thatoptimally solves a special case of the unconstrained assortment planningproblem under our choice model. For the general constrained version of theproblem, we devise a solution procedure that includes a single-levelreformulation and a cutting-plane approach to iteratively tighten the solutionspace. We also provide a greedy algorithm that can quickly solve largeinstances with small optimality gaps.

Robust Assortment Optimization under a Ranking-based Choice Model with Product Unavailability Effect