Cursuri de pregatire Genetic Algorithms

Last updated

ID de curs

genealgo

Durata

28 ore (usually 4 days including breaks)

Cerințe

Basic understanding of search problems and optimization

Sinoptic

Acest curs de patru zile vizează predarea modului în care funcționează algoritmii genetici; se referă, de asemenea, la selectarea parametrilor modelului unui algoritm genetic; există multe aplicații pentru algoritmi genetici în acest curs, iar problemele de optimizare sunt abordate cu ajutorul algoritmilor genetici.

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Schița de curs

Day 1:

  • What is a genetic algorithm?
  • Chromosome fitness
  • Choosing the random initial population
  • The crossover operations
  • A numeric optimzation example

Day 2

  • When to use genetic algorithm
  • Coding the gene
  • Local maximums and mutation operation
  • Population diversity

Day 3

  • The meaning and effect of each genetic algorithm parameter
  • Varying genetic parameters
  • Optimizing scheduling problems
  • Cross over and mutation for scheduling problems

Day 4

  • Optimizing program or set of rules
  • Cross over and mutation operations for optimizing programs
  • Creating a parallel model of the genetic algorithm
  • Evaluating the genetic algorithm
  • Applications of genetic algorithm

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