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Correction to: Complex & Intelligent Systems https://doi.org/10.1007/s40747-022-00766-x
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The sixth paper included in the special issue is entitled “Surrogate-assisted evolutionary algorithm for expensive constrained multi-objective discrete optimization problems” authored by Q. Gu et al., which proposes a random forest-assisted evolutionary algorithm to deal with expensive constrained multi-objective discrete optimization problems. Also, an improved stochastic ranking strategy based on the fitness mechanism and adaptive probability operator is presented, which considers both convergence and diversity to advance the quality of candidate solutions. Numerical experiments on benchmark problems demonstrate that the proposed algorithm is very promising for the expensive constrained multi-objective discrete optimization problems.
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Wang, H., Sun, C., Ding, J. et al. Correction to: Evolutionary optimization of large complex problems. Complex Intell. Syst. 8, 3593 (2022). https://doi.org/10.1007/s40747-022-00801-x
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DOI: https://doi.org/10.1007/s40747-022-00801-x