Feedback-driven adaptive variable grouping for decomposition-based large-scale multiobjective optimization

doi:10.1016/j.swevo.2026.102416

Feedback-driven adaptive variable grouping for decomposition-based large-scale multiobjective optimization

2026-05-30

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DOI：10.1016/j.swevo.2026.102416

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• Lightweight variable classification reduces cost from O(D⋅N) to O(D). • Adaptive regrouping dynamically refines variable groups during evolution. • Group-level operator selection balances exploration and exploitation. • MOEA/D-FAVG outperforms seven LSMaOEAs on LSMOP and DTLZ tests. • Theoretical analysis proves error bounds and convergence properties.

Feedback-driven adaptive variable grouping for decomposition-based large-scale multiobjective optimization

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