Constrained Assortment Optimization Problem under the Multilevel Nested Logit Model
研究了多层嵌套Logit模型下，每个选择阶段都有不购买选项的约束性分类优化问题，目标是满足基数约束下最大化每位顾客的期望利润，并给出了多项式时间算法。
We study the choice‐based constrained assortment optimization problem under the multilevel nested logit model with a no‐purchase option in every choice stage. For this problem, each candidate product is associated with a fixed profit. The goal is to identify the optimal assortment satisfying a cardinality constraint to maximize the expected profit per customer. There is a cardinality limitation imposed on nodes in the second lowest level. A polynomial‐time algorithm with computational complexity O( nmax{ m, k}) is provided to locate the optimal assortment for the m‐level nested logit model with n products, where k is the maximum number of products within any node in level m − 1.