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Inventory planning for low demand items in online retailing
(Massachusetts Institute of Technology, 2007)
A large online retailer strategically stocks inventory for SKUs with low demand. The motivations are to provide a wide range of selections and faster customer fulfillment service. We assume the online retailer has the ...
A sequential approach of estimating two-factor interactions
(Cambridge, Mass. : Alfred P. Sloan School of Management, Massachusetts Institute of Technology, 1993)
Multiple part type decomposition method in manufacturing processing line
(Massachusetts Institute of Technology, 2001)
An approach to solving constraint satisfaction problems using asynchronous teams of autonomous agents
(Massachusetts Institute of Technology, 1994)
Network value concept in airline revenue management
(Massachusetts Institute of Technology, 1998)
Performance of multiple cabin optimization methods in airline revenue management
(Massachusetts Institute of Technology, 2013)
Although many airlines offer seats in multiple cabins (economy vs. premium classes) with different service quality, previous work on airline revenue management has focused on treating the cabins separately. In this thesis, ...
Multi-modal, multi-period, multi-commodity transportation : models and algorithms
(Massachusetts Institute of Technology, 2014)
In this paper we present a mixed integer optimization framework for modeling the shipment of goods between origin destination (O-D) pairs by vehicles of different types over a time-space network. The output of the model ...
Winning the competitive edge in the DRAM market : a system dynamics analysis
(Massachusetts Institute of Technology, 1998)
Price incentives for online retailers using social media
(Massachusetts Institute of Technology, 2015)
In the era of Big Data, online retailers have access to a large amount of data about their customers. This data can include demographic information, shopping carts, transactions and browsing history. In the last decade, ...
Revenue optimization for a hotel property with different market segments : demand prediction, price selection and capacity allocation
(Massachusetts Institute of Technology, 2017)
We present our work with a hotel company as an example of how machine learning techniques can be used to improve the demand predictions of a hotel property, as well as its pricing and capacity allocation decisions. First, ...