English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In the first part of this work [32], we introduce a convex parabolicrelaxation for quadratically-constrained quadratic programs, along with asequential penalized parabolic relaxation algorithm to recover near-optimalfeasible solutions. In this second part, we show that starting from a feasiblesolution or a near-feasible solution satisfying certain regularity conditions,the sequential penalized parabolic relaxation algorithm convergences to a pointwhich satisfies Karush-Kuhn-Tucker optimality conditions. Next, we presentnumerical experiments on benchmark non-convex QCQP problems as well aslarge-scale instances of system identification problem demonstrating theefficiency of the proposed approach.

Parabolic Relaxation for Quadratically-constrained Quadratic Programming -- Part II: Theoretical & Computational Results