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A two-stage ensemble evolutionary algorithm for constrained multi-objective optimization
DOI:10.1016/j.swevo.2025.102213.png)
Abstract
En 中文
• Proposed a two-stage ensemble CMOEA for solving constrained multi-objective problems. • Developed a dynamic two-stage strategy balancing exploration and exploitation effectively. • Designed an MAB strategy to select suitable population for offspring generation. • Validated the proposed algorithm on six test suites and six real-world optimization tasks.
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