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Introduce normalization of F in NSGA3 extreme point calculation #557

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@NikHoh NikHoh commented Feb 2, 2024

As the extreme point calculation is happening as a weighted and aggregated optimization (max(__F * weights)), I think it would be better to normalize __F beforehand. Otherwise, the resulting extreme points could have a bias towards objective functions (F) with higher magnitude (in case the objective values of different objective functions are highly unbalanced).

Hohmann, Nikolas added 3 commits February 2, 2024 16:26
…ulations (energy reduction method) to produce the same output
…ion calculations (energy reduction method) to produce the same output"

This reverts commit 0f45e3a.

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@blankjul blankjul self-assigned this Jul 7, 2024
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blankjul commented Jul 7, 2024

Thanks for your work and PR. Have you benchmark this change?
The NSGA3 implementation follows the original C++ code of the paper. Thus, I want to keep it as it is by default.
However, if this performs better and is benchmark, introducing this as a parameter might be a good idea.

Can you post some benchmark results here with this change?

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