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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

This paper proposes novel algorithm for non-convex multimodal constrainedoptimisation problems. It is based on sequential solving restrictions ofproblem to sections of feasible set by random subspaces (in general, manifolds)of low dimensionality. This approach varies in a way to draw subspaces,dimensionality of subspaces, and method to solve restricted problems. Weprovide empirical study of algorithm on convex, unimodal and multimodaloptimisation problems and compare it with efficient algorithms intended foreach class of problems.

A randomised non-descent method for global optimisation