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

The lack of diversity in a genetic algorithm's population may lead to a badperformance of the genetic operators since there is not an equilibrium betweenexploration and exploitation. In those cases, genetic algorithms present a fastand unsuitable convergence.  In this paper we develop a novel hybrid genetic algorithm which attempts toobtain a balance between exploration and exploitation. It confronts thediversity problem using the named greedy diversification operator. Furthermore,the proposed algorithm applies a competition between parent and children so asto exploit the high quality visited solutions. These operators are complementedby a simple selection mechanism designed to preserve and take advantage of thepopulation diversity.  Additionally, we extend our proposal to the field of memetic algorithms,obtaining an improved model with outstanding results in practice.  The experimental study shows the validity of the approach as well as howimportant is taking into account the exploration and exploitation concepts whendesigning an evolutionary algorithm.

Genetic and Memetic Algorithm with Diversity Equilibrium based on Greedy Diversification