Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Paat Rusmevichientong"'
Publikováno v:
Operations Research. 71:603-625
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 le
Publikováno v:
Operations Research.
In “Estimating Large-Scale Tree Logit Models,” S. Jagabathula, P. Rusmevichientong, A. Venkataraman, and X. Zhao tackle the demand estimation problem under the tree logit model, also known as the nested logit or d-level nested logit model. The mo
Autor:
Yicheng Bai, Omar El Housni, Billy Jin, Paat Rusmevichientong, Huseyin Topaloglu, David P. Williamson
Publikováno v:
Management Science.
One of the most prevalent demand models in the revenue management literature is based on dividing the selling horizon into a number of time periods such that there is at most one customer arrival at each time period. This demand model is equivalent t
Publikováno v:
Operations Research.
There are a variety of revenue management systems that require making pricing or availability decisions for unique resources. For example, lodging marketplaces, boutique hotels, and bed-and-breakfasts offer unique rooms, apartments, or houses. Matchi
Autor:
Yuhang Ma, Ningyuan Chen, Paat Rusmevichientong, Pin Gao, Anran Li, Huseyin Topaloglu, Guillermo Gallego
Publikováno v:
Operations Research. 69:1509-1532
Sequential Recommendation Under the Multinomial Logit Model with Impatient Customers In many applications, customers incrementally view a subset of offered products and make purchasing decisions before observing all the offered products. In this case
Publikováno v:
Management Science. 67:2845-2869
We examine the revenue–utility assortment optimization problem with the goal of finding an assortment that maximizes a linear combination of the expected revenue of the firm and the expected utility of the customer. This criterion captures the trad
Autor:
Vishal Gupta, Paat Rusmevichientong
Publikováno v:
Management Science. 67:220-241
Optimization applications often depend on a huge number of uncertain parameters. In many contexts, however, the amount of relevant data per parameter is small, and hence, we may only have imprecise estimates. We term this setting—in which the numbe
Publikováno v:
Management Science. 66:2820-2844
We consider dynamic assortment problems with reusable products, in which each arriving customer chooses a product within an offered assortment, uses the product for a random duration of time, and returns the product back to the firm to be used by oth
Publikováno v:
Operations Research. 68:741-761
We consider uncapacitated and capacitated assortment problems under the paired combinatorial logit model, where the goal is to fi nd a set of products to maximize the expected revenue obtained from each customer. In the uncapacitated setting, we can
Publikováno v:
Operations Research. 68:834-855
Many revenue management problems require making capacity control and pricing decisions for multiple products. The decisions for the different products interact because either the products use a common pool of resources or the customers choose and sub