Cardinality Constrained Optimization Problems

In this thesis, we examine optimization problems with a constraint that allows for only a certain number of variables to be nonzero. This constraint, which is called a cardinality constraint, has received considerable attention in a number of areas such as machine learning, statistics, computational finance, and operations management. Despite their practical needs, most optimization problems with a cardinality constraints are hard to solve due to their nonconvexity. We focus on constructing tight convex relaxations to such problems.

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Management

Year

2016

Author dc:creator

• Kim, Jinhak

Contributors dc:contributor

• Mohit Tawarmalani
• Jean-Philippe P Richard
• Yanjun Li
• Thanh Nguyen

• Cardinality constraint
• Cutting planes
• Sparse principal component analysis

Repository record dc:identifier

https://docs.lib.purdue.edu/open_access_dissertations/1388

OAI identifier oai:identifier

oai:docs.lib.purdue.edu:open_access_dissertations-2604