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- W2382372018 abstract "NSGA-II is widely used in multi-objective evolutionary optimization for its high convergence and time efficiency.However,the population maintenance based on crowding distance in NSGA-II has not worked well in maintaining the diversity of solution sets.This paper proposes an improved strategy to dynamically maintain diversity by setting a self-adaptive threshold value,and the better diversity individuals have more chances to survive.Comparing new algorithm to NSGA-II and e-MOEA in five test problems,the results show that improved algorithm efficiently promotes the diversity and achieves efficient convergence at the same time." @default.
- W2382372018 created "2016-06-24" @default.
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- W2382372018 date "2010-01-01" @default.
- W2382372018 modified "2023-09-26" @default.
- W2382372018 title "Improved diversity maintenance strategy in NSGA-II" @default.
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