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A collaborative competition multitasking framework for constrained multi-objective optimization
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AI
DOI：10.1016/j.asoc.2025.113900.png)
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Abstract
En 中文
• A CMOEA based on tri-stage collaborative competition multitasking (TCCMT) is proposed. • During the process of evolution, there is always an optimal auxiliary task to help the main task evolve, which greatly improves the utilization of computing resources. • The auxiliary tasks use the constrained adaptive regression strategy and double angle enhancement strategy.