Journal
MATHEMATICAL PROGRAMMING
Volume 95, Issue 2, Pages 189-217Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s10107-002-0347-5
Keywords
-
Ask authors/readers for more resources
This paper discusses computational experiments with linear optimization problems involving semi-definite, quadratic, and linear cone constraints (SQLPs). Many test problems of this type are solved using a new release of SDPT3, a MATLAB implementation of infeasible primal-dual path-following algorithms. The software developed by the authors uses Mehrotra-type predictor-corrector variants of interior-point methods and two types of search directions: the HKM and NT directions. A discussion of implementation details is provided and computational results on problems from the SDPLIB and DIMACS Challenge collections are reported.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available