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Evolutionary optimization

🌐 public · created AE531017 (17.10.2023) · by DDH · open in the standard editor view · 📽 open as presentation

Evolutionary Optimization mimics natural selection, like how animals evolve. Imagine a population of potential solutions. Those fitting the problem best (like the fittest animals) are chosen to 'reproduce.' They mix and mutate to create new solutions or 'offspring.' Over generations, this process 'evolves' better solutions, as unfit ones are discarded. It's a trial-and-error method using principles of evolution, effectively finding good solutions for complex problems by simulating survival of the fittest in a virtual environment.

Ancestors (1 superordinated path)

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

Descendants (at least 13 branches originate here)

  • Evolutionary optimization
    Evolutionary Optimization mimics natural selection, like how animals evolve. Imagine a population of potential solutions. Those fitting the problem best (like t
    • is_parent Genetic Algorithm
      A Genetic Algorithm is a method in evolutionary optimization that solves problems by mimicking natural evolution. Imagine a survival contest where each particip
      • is_parent 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.
      • is_parent Variation
        In evolutionary optimization, variation is the process of introducing diversity into the population of solutions. Like genetic mutations and breeding in nature,
        • is_parent Mutation ·
          for numeric genes: additive mutation, multiplicative mutation, complex (imaginary) mutation for symbolic ones: removal, addition or replacement of a symbol; met
        • is_parent Crossover ·
          Crossover
      • is_parent 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
    • is_parent Genetic programming ·
      Genetic Programming (GP) is a type of evolutionary optimization where programs themselves evolve to solve problems. Imagine a computer automatically writing and
    • is_parent Grammatical evolution ·
      Grammar Evolution is a type of evolutionary optimization where solutions are generated using a predefined set of rules, like a grammar in language. Imagine crea
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