Search Results for author: Yingyu Zhang

Found 3 papers, 0 papers with code

A Many-Objective Evolutionary Algorithm Based on Decomposition and Local Dominance

no code implementations13 Jul 2018 Yingyu Zhang, Yuanzhen Li, Quan-Ke Panb, P. N. Suganthan

Recent studies show that a well designed combination of the decomposition method and the domination method can improve the performance , i. e., convergence and diversity, of a MOEA.

Evolutionary Algorithms

A Decomposition-Based Many-Objective Evolutionary Algorithm with Local Iterative Update

no code implementations27 Jun 2018 Yingyu Zhang, Bing Zeng

In addition, the time complexity of the proposed algorithm is the same as that of MOEA/D, and lower than that of other known MOEAs, since it considers only individuals within the current neighborhood at each update.

Evolutionary Algorithms

A mullti- or many- objective evolutionary algorithm with global loop update

no code implementations25 Jan 2018 Yingyu Zhang, Bing Zeng, Yuanzhen Li, Junqing Li

The decomposition-based MOEAs emphasize convergence and diversity in a simple model and have made a great success in dealing with theoretical and practical multi- or many-objective optimization problems.

Evolutionary Algorithms

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