Genetic Algorithms

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Advanced programming[1]

In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation, crossover and selection[2]

  • Please first review the characteristics of algorithms.
  • Please then review the characteristics of heuristics.

The basic pattern of genetic algorithms[edit]

  1. A random set of solutions would be generated on the sample documents
  2. And tested against the human labelling
  3. Best fit solutions retained
  4. New generation created by mutating/crossing
  5. Algorithm repeated
  6. Until a good fit obtained

Use of genetic algorithms[edit]


Some videos[edit]



Helpful resources[edit]


Terms associated with genetic algorithms[edit]

References[edit]