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Replication

🌐 public · created AE531128 (28.11.2023) · by DDH · open in the standard editor view · 📽 open as presentation

In evolutionary optimization, replication is like making copies of the best solutions. Imagine a survival contest where top performers are cloned. These copies then undergo changes (mutations) or combine features (crossover) to create new solutions. Replication ensures good traits are passed on, increasing chances that future generations will perform even better. It's used in algorithms to solve complex problems, where keeping and tweaking successful solutions gradually leads to finding the best or a very good answer.

Ancestors (1 superordinated path)

root/ baumhaus.digital/ Design & Computation/ Perspectives in Engineering/ IOPS/ Heuristics/ Nature-inspired heuristics/ Evolutionary optimization/ Genetic Algorithm/ Replication

Descendants (at least 3 branches originate here)

  • Replication
    In evolutionary optimization, replication is like making copies of the best solutions. Imagine a survival contest where top performers are cloned. These copies
    • is_parent Individual|Genotype|Chromosome ·
      In evolutionary optimization, an "individual," also termed a "genotype" or "chromosome," is a candidate solution to a problem. Think of it like a recipe where e
    • is_parent Population ·
      Population is a set of individuals.
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