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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Clustering plays an important role in the decomposition of complex products structure. Different clustering algorithms may achieve different effects of the decomposition. This paper aims to proposes a bio-inspired genetic algorithm that is implemented based on its reliable fitness function and design structure matrix (DSM) for clustering analysis of complex products. This new bio-inspired genetic algorithm captures the features of DSM, which is base on the biological evolution theory. Examples of these products include motorcycle engines that are presented for clustering. The five cluster alternatives are obtained from the regular clustering algorithm and the bio-inspired genetic algorithm, while the best cluster alternative comes from the bio-inspired genetic algorithm. The results show that this algorithm is well adaptable, especially when the product elements have complicated and asymmetric connections.

Bio-Inspired Clustering of Complex Products Structure based on DSM