Abstract: In this article, the reduced order model (ROM) assisted iterative scale-decreasing two-tier surrogate method is proposed for multi-objective optimization (MOO) of axial flux motors (AFMs).

I can potentially implement changes in a PR, but would like guidance on how maintainers would prefer this fixed. Previously, I worked with @githubnemo on building the Activated LoRA feature for PEFT.

Abstract: In dynamic environments, optimization algorithms tend to track the changing optima. However, frequent changes to decision solutions often cause high switching costs and system instability.

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