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First, thanks for the great library! PyGAD is an excellent GA framework.
I've been working on a related project (asi-evolve) that focuses specifically on diversity preservation in evolutionary algorithms. One challenge I've noticed in standard GA implementations is premature convergence — the population converges to a local optimum before exploring the search space adequately.
Proposed Feature
Add built-in diversity preservation mechanisms:
Fitness sharing — reduce fitness of similar individuals
Niching — maintain subpopulations in different regions
Crowding — replace similar parents with offspring
Reference Implementation
I've implemented these in asi-evolve under the EvolutionaryAlgorithm class. The key method is _calculate_diversity() which tracks population diversity and auto-adjusts mutation rates when diversity drops.
Would this be a welcome addition to PyGAD? I'd be happy to contribute a PR.
Activity