Optimization for online platforms

In the last decade, there has been a surge in online platforms for providing a wide variety of services. These platforms face an array of challenges that can be mitigated with appropriate modeling and the use of optimization tools. In this thesis, we examine, model, and provide solutions to some of the key challenges. First, we focus on the problem of intelligent SMS routing faced by several online platforms today. In a dynamically changing environment, platforms need to carefully choose SMS aggregators to have a high number of text messages being delivered to users at a low cost. To model this problem, we consider a novel variant of the multi-armed bandit (MAB) problem, MAB with cost subsidy, which models many real-life applications where the learning agent has to pay to select an arm and is concerned about optimizing cumulative costs and rewards.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Operations Research Center

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2021

Author dc:creator

• Sinha, Deeksha.

Advisor dc:contributor.advisor

• Vivek. F. Farias.

• Operations Research Center.

Statement dc:rights

• MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/130723

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/130723