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 this paper we study the split minimization problem that consists of twoconstrained minimization problems in two separate spaces that are connected viaa linear operator that maps one space into the other. To handle the data ofsuch a problem we develop a superiorization approach that can reach a feasiblepoint with reduced (not necessarily minimal) objective function values. Thesuperiorization methodology is based on interlacing the iterative steps of twoseparate and independent iterative processes by perturbing the iterates of oneprocess according to the steps dictated by the other process. We include in ourdeveloped method two novel elements. The first one is the permission to restartthe perturbations in the superiorized algorithm which results in a significantacceleration and increases the computational efficiency. The second element isthe ability to independently superiorize subvectors. This caters to the needsof real-world applications, as demonstrated here for a problem inintensity-modulated radiation therapy treatment planning.

The superiorization method with restarted perturbations for split minimization problems with an application to radiotherapy treatment planning