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

An Approach for Fuzzy Multiobjective Coordination Combinatorial Optimization using Multi Transition Neural Network Katsuhisa Yoshimoto, Student Member, Keiichiro Yasuda, Member, and Ryuichi Yokoyama, Member (Tokyo Metropolitan University) This paper proposes a method for applying Multi Transition Neural Network(MTNN) toward Fuzzy Multiobjective Coordination Combinatorial Optimization Problem(FMCOP). FMCOP has been puzzled over two kind of subjects which are pointed out until now. The one is how the membership function constructs, the other is how favorable solutions are obtained in reasonable time. To get satisfying membership function, interactive multiobjective programming which adjusts membership function interactively has been proposed. In examining whether the membership function is satisfying, plural favorable solutions are more desirable than the single optimal solution because comparison with solutions one another is made and this helps in judging membership function to be satisfying. Moreover, combinatorial optimization needs considerable computation time, so fast approximation methods have to be developed to obtain solutions in reasonable time. MTNN has transition on Hamming distance greater than 2 by means of struggle for existence in the similar consideration of simulated evolution. It can effectively search for lower energy state, while escaping from local minima iteratively. Applying MTNN to FMCOP, the above two subjects can be resolved because it is capable of searching for plural favorable solutions in reasonable time. In consequence of numerical examples, MTNN has been verified to be effective for FMCOP.