Tight SDP Relaxations for Cardinality-Constrained Problems

Angelika Wiegele () and Shudian Zhao ()
Additional contact information
Angelika Wiegele: Institut für Mathematik, Alpen-Adria-Universität Klagenfurt, Universitätsstraße 65-67
Shudian Zhao: Institut für Mathematik, Alpen-Adria-Universität Klagenfurt, Universitätsstraße 65-67

A chapter in Operations Research Proceedings 2021, 2022, pp 167-172 from Springer

Abstract: Abstract We model the cardinality-constrained portfolio problem using semidefinite matrices and investigate a relaxation using semidefinite programming. Experimental results show that this relaxation generates tight lower bounds and even achieves optimality on many instances from the literature. This underlines the modeling power of semidefinite programming for mixed-integer quadratic problems.

Keywords: Semidefinite programming; Cardinality-constrained problem; Mixed-integer nonlinear programming (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-3-031-08623-6_26

Ordering information: This item can be ordered from
http://www.springer.com/9783031086236

DOI: 10.1007/978-3-031-08623-6_26

Access Statistics for this chapter

More chapters in Lecture Notes in Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().