A two‐stage many‐objective evolutionary algorithm with dynamic generalized Pareto dominance
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.23016
Abstract: Many‐objective evolutionary algorithms (MaOEAs) are widely used to solve many‐objective optimization problems. As the number of objectives increases, it is difficult to achieve a balance between the population diversity and the convergence. Additionally, the selection… read more here.
Keywords: many objective; generalized pareto; two stage; dynamic generalized ... See more keywords
On some dynamic generalized information measures for bivariate lifetimes
Sign Up to like & getrecommendations! Published in 2018 at "Communications in Statistics - Theory and Methods"
DOI: 10.1080/03610926.2017.1395051
Abstract: ABSTRACT Several generalizations to the concept of Kullback-Leibler divergence measure and Kerridge inaccuracy measure are available in the literature. In a recent paper Kundu (Metrika, 78:415–435, 2015) considered a generalized K-L divergence measure of order… read more here.
Keywords: measures bivariate; generalized information; information measures; measure ... See more keywords
A Novel Dynamic Generalized Opposition-Based Grey Wolf Optimization Algorithm
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DOI: 10.3390/a11040047
Abstract: To enhance the convergence speed and calculation precision of the grey wolf optimization algorithm (GWO), this paper proposes a dynamic generalized opposition-based grey wolf optimization algorithm (DOGWO). A dynamic generalized opposition-based learning strategy enhances the… read more here.
Keywords: wolf optimization; grey wolf; opposition based; generalized opposition ... See more keywords