A Two-Stage Evolutionary Algorithm With Balanced Convergence and Diversity for Many-Objective Optimization
Author:
Affiliation:
1. School of Computer Science, China University of Geosciences, Wuhan, China
2. Department of Automation, Tsinghua University, Beijing, China
Funder
National Natural Science Foundation of China
Natural Science Foundation for Distinguished Young Scholars of Hubei
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering,Software
Link
http://xplorestaging.ieee.org/ielx7/6221021/9893288/09691808.pdf?arnumber=9691808
Reference66 articles.
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3. Improved metaheuristic based on the R2 indicator for many-objective optimization;gómez;Proc Annu Conf Genet Evol Comput,2015
4. Diversity Assessment in Many-Objective Optimization
5. Using the Averaged Hausdorff Distance as a Performance Measure in Evolutionary Multiobjective Optimization
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