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

For most practical optimisation problems local search outperforms randomsampling - despite the "No Free Lunch Theorem". This paper introduces aproperty of search landscapes termed Neighbours' Similar Fitness (NSF) thatunderlies the good performance of neighbourhood search in terms of localimprovement. Though necessary, NSF is not sufficient to ensure that searchingfor improvement among the neighbours of a good solution is better than randomsearch. The paper introduces an additional (natural) property which supports ageneral proof that, for NSF landscapes, neighbourhood search beats randomsearch.

The Neighbours' Similar Fitness Property for Local Search