Revenue Management Under a Mixture of Independent Demand and Multinomial Logit Models
研究了将独立需求模型与多项Logit模型混合，以在保持产品组合优化问题可解的同时，提升对顾客选择行为的建模灵活性。
Discrete choice models have recently attracted significant attention to model demand in revenue-management applications, as they can capture the fact that if a product is unavailable, then some customers substitute for this product, whereas others leave the system without a purchase. Although a more sophisticated choice model may capture the choice process of the customers more faithfully, a simpler choice model may result in tractable optimization problems when finding the optimal assortment of products to offer or prices to charge. One approach for coming up with sophisticated choice models is to mix existing ones, where the different segments of customers choose under the different choice models in the mixture. In “Revenue Management Under a Mixture of Independent Demand and Multinomial Logit Models,” Cao, Rusmevichientong, and Topaloglu demonstrate that mixing the independent demand and multinomial logit models can significantly increase the modeling flexibility of each of these choice models, while keeping the corresponding operational assortment optimization problems tractable.