Abstract
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.
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Management
Date of Award
January 2016
Recommended Citation
Kim, Jinhak, "Cardinality Constrained Optimization Problems" (2016). Open Access Dissertations. 1388.
https://docs.lib.purdue.edu/open_access_dissertations/1388
First Advisor
Mohit Tawarmalani
Committee Member 1
Jean-Philippe P Richard
Committee Member 2
Yanjun Li
Committee Member 3
Thanh Nguyen