Publication Type:

Conference Proceedings

Source:

Computational Intelligence in Data Mining (In Smart Innovation, Systems and Technologies), Smart Innovation, Systems and Technologies, Springer, Volume 32, p.403–416 (2015)

Abstract:

In this paper we derive an analytical expression to describe the evolution of expected population variance for Differential Evolution (DE) variant—DE/current-to-best/1/bin (as a measure of its explorative power). The derived theoretical evolution of population variance has been validated by comparing it against the empirical evolution of population variance by DE/current-to-best/1/bin on four benchmark functions.

Cite this Research Publication

Dr. Thangavelu S., Dr. Jeyakumar G., Balakrishnan, R. M., and Dr. Shunmuga Velayutham C., “Theoretical Analysis of Expected Population Variance Evolution for a Differential Evolution Variant”, Computational Intelligence in Data Mining (In Smart Innovation, Systems and Technologies), vol. 32. Smart Innovation, Systems and Technologies, Springer, pp. 403–416, 2015.