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Meta-Learning-Assisted Constraint Relaxation for Constrained Black-Box Optimization
Constraint handling is central to constrained black-box optimization (BBO), where objective improvement and feasibility restoration often provide conflicting search signals. Existing $ε$-relaxation methods are simple and effective, but their relaxation schedules are usually fixed or manually designe
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