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A4.3 Machine learning approachesA4.3.7

Application of genetic algorithms in various real-world situations

Describe the application of genetic algorithms in various real-world situations

AHL≈ 50 minCommand term: DescribePremium

In this lesson

  • Describing population, fitness function, selection, crossover, mutation, evaluation and termination
  • Describing how a genetic algorithm is applied to route planning (the travelling salesperson problem)
  • Describing applications of genetic algorithms to other optimisation problems

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What's inside

  1. LearnEvolving good solutions
  2. LearnThe parts of a genetic algorithm
  3. CheckOrder the steps
  4. LearnApplication: the travelling salesperson problem
  5. LabEvolve a delivery route
  6. CheckQuick check
  7. LearnOther real-world applications
  8. CheckMatch each term to its meaning in the route problem
  9. ExamWorked exam answer
  10. ReviewMistakes examiners see
  11. Exam practiceExam-style questions

Ends with 5 exam-style questions worth 12 marks, with a self-marking markscheme.