Finding Multiple Global Optima Exploiting Differential Evolution’s Niching Capability

TitleFinding Multiple Global Optima Exploiting Differential Evolution’s Niching Capability
Publication TypeConference Paper
Year of Publication2011
AuthorsEpitropakis, MG, Plagianakos, VP, Vrahatis, MN
Conference NameIEEE Symposium on Differential Evolution, 2011. SDE 2011. (IEEE Symposium Series on Computational Intelligence)
Date PublishedApril
Conference LocationParis, France
Abstract

Handling multimodal functions is a very important and challenging task in evolutionary computation community, since most of the real-world applications exhibit highly multi-modal landscapes. Motivated by the dynamics and the proximity characteristics of Differential Evolution's mutation strategies tending to distribute the individuals of the population to the vicinity of the problem's minima, we introduce two new Differential Evolution mutation strategies. The new mutation strategies incorporate spatial information about the neighborhood of each potential solution and exhibit a niching formation, without incorporating any additional parameter. Experimental results on eight well known multimodal functions and comparisons with some state-of-the-art algorithms indicate that the proposed mutation strategies are competitive and very promising, since they are able to reliably locate and maintain many global optima throughout the evolution process.

DOI10.1109/SDE.2011.5952058
AttachmentSize
PDF icon EpitropakisPV.SDE2011.CameraReady.pdf684.55 KB

Scholarly Lite is a free theme, contributed to the Drupal Community by More than Themes.