In–Out Algorithm for assortment planning under a ranking-based consumer choice model

Abstract

We consider a retailer’s assortment planning problem under a ranking-based consumer choice model. The retailer incurs a fixed carrying cost per product offered, a substitution penalty cost for each customer who does not purchase his first choice, and a penalty cost on lost sales. We develop an effective In–Out Algorithm to identify the optimal solution. The extensive numerical study shows that the algorithm performs well, and is more than 10,000 times faster than enumeration on problems with 20 products.