A dynamic multi-objective evolutionary optimization with pre-learning

Changrong Mei

doi:10.1016/j.swevo.2026.102447

A dynamic multi-objective evolutionary optimization with pre-learning

2026-06-20

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AI

DOI：10.1016/j.swevo.2026.102447

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• A pre-learning response framework is proposed to improve dynamic response in DMOPs. • Pre-evolutionary generator explores useful information in the new environment. • Kernel density-based structure expansion enriches promising region representation. • Dual-source linear prediction improves the reliability of directional prediction. • Bidirectional nearest neighbor matching adjusts individual optimization directions.

A dynamic multi-objective evolutionary optimization with pre-learning

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