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

In this study, we propose an improvement to the direct mating method, aconstraint handling approach for multi-objective evolutionary algorithms, byhybridizing it with local mating. Local mating selects another parent from thefeasible solution space around the initially selected parent. The direct matingmethod selects the other parent along the optimal direction in the objectivespace after the first parent is selected, even if it is infeasible. It showsbetter exploration performance for constraint optimization problems withcoupling NSGA-II, but requires several individuals along the optimal direction.Due to the lack of better solutions dominated by the optimal direction from thefirst parent, direct mating becomes difficult as the generation proceeds. Toaddress this issue, we propose a hybrid method that uses local mating to selectanother parent from the neighborhood of the first selected parent, maintainingdiversity around good solutions and helping the direct mating process. Weevaluate the proposed method on three mathematical problems with unique Paretofronts and two real-world applications. We use the generation histories of theaverages and standard deviations of the hypervolumes as the performanceevaluation criteria. Our investigation results show that the proposed methodcan solve constraint multi-objective problems better than existing methodswhile maintaining high diversity.

Improved Solution Search Performance of Constrained MOEA/D Hybridizing Directional Mating and Local Mating