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Selection

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

In evolutionary optimization, selection is like a survival test for candidate solutions, deciding which ones get to 'reproduce.' Selection operators are the rules determining who passes this test. They might choose the fittest solutions (those solving the problem best) or sometimes include random or less fit ones for diversity. 

Ancestors (1 superordinated path)

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

Descendants (at least 3 branches originate here)

  • Selection
    In evolutionary optimization, selection is like a survival test for candidate solutions, deciding which ones get to 'reproduce.' Selection operators are the rul
    • is_parent Selection operators ·
      elitism: select N most fit individuals and copy them to next generation roulette-wheel: probability of survival into next generation is proportional to indvidid
    • is_parent Fitness function ·
      In evolutionary optimization, a "fitness function" is like a scoring system that rates how good each candidate solution (or 'individual') is at solving the prob
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