Abstract
Most semidefinite programming algorithms found in the literature require strictly feasible starting points (X° ≻ 0, S° ≻ 0) for the primal and dual problems respectively. So-called ‘big-M’ methods (see e.g. [807]) are often employed in practice to obtain feasible starting points.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer Science+Business Media New York
About this chapter
Cite this chapter
de Klerk, E., Terlaky, T., Roos, K. (2000). Self-Dual Embeddings. In: Wolkowicz, H., Saigal, R., Vandenberghe, L. (eds) Handbook of Semidefinite Programming. International Series in Operations Research & Management Science, vol 27. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4381-7_5
Download citation
DOI: https://doi.org/10.1007/978-1-4615-4381-7_5
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-6970-7
Online ISBN: 978-1-4615-4381-7
eBook Packages: Springer Book Archive