Multiple Choice Strategy for PSO Algorithm Enhanced with Dimensional Mutation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86096863" target="_blank" >RIV/61989100:27240/15:86096863 - isvavai.cz</a>
Alternative codes found
RIV/70883521:28140/15:43873608
Result on the web
<a href="http://link.springer.com/chapter/10.1007/978-3-319-19324-3_34" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-319-19324-3_34</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-19324-3_34" target="_blank" >10.1007/978-3-319-19324-3_34</a>

Result language
angličtina
Original language name
Multiple Choice Strategy for PSO Algorithm Enhanced with Dimensional Mutation
Original language description
In this study the promising Multiple-choice strategy for PSO (MC-PSO) is enhanced with the blind search based single dimensional mutation. The MC-PSO utilizes principles of heterogeneous swarms with random behavior selection. The performance previously tested on both large-scale and fast optimization is significantly improved by this approach. The newly proposed algorithm is more robust and resilient to premature convergence than both original PSO and MC-PSO. The performance is tested on four typical benchmark functions with variety of dimension settings.
Czech name
—
Czech description
—

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
S - Specificky vyzkum na vysokych skolach

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)