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Surrogate-assisted differential evolutionary algorithm with dynamic region exploration for expensive optimization problems
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DOI：10.1016/j.asoc.2025.113619.png)
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Abstract
En 中文
• Surrogate-assisted DE algorithm with dynamic region exploration (DREDE) is proposed. • A criterion is proposed to find a valley sample and establish a suspected region. • Dynamic global/local/suspected search at different algorithm stages. • Stage-adaptive coefficients select varying sample sizes for local surrogate model training. • A method for improving the accuracy of subsequent models is proposed.
Keywords:
surrogate-assisted DE
dynamic region exploration
suspected region
stage-adaptive coefficients
model accuracy improvement
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