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A dynamic task-assisted constrained multimodal multi-objective optimization algorithm based on reinforcement learning
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DOI：10.1016/j.swevo.2025.102087.png)
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Abstract
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• A dynamic task-assisted method is designed to solve constrained multimodal problems. • Three auxiliary tasks evolve cooperatively. • Dynamic selection of auxiliary tasks with reinforcement learning. • A new indicator for integrated evaluation of the quality of solutions is designed.
Keywords:
dynamic task-assisted method
constrained multimodal problems
auxiliary tasks
reinforcement learning
solution quality evaluation
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