Variation operators create new candidate solutions from existing ones in evolutionary optimization. They introduce diversity and enable exploration of the search space.

Variations of variation:

Mutation

Random changes to a single solution,

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Crossover

Combine parts of two parent solutions to create offspring.

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Sampling from a learned distribution (“model-based”/“estimation of distribution algorithms”):