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Module 04: Genetic Algorithms: Advanced Topics - Real-Coded, Adaptive, and Parallel

Binary GAs are just the beginning. Real-coded GAs with SBX crossover handle continuous problems. Adaptive operators tune themselves. Island models parallelize. This module takes GAs from textbook to production.

Learning Objectives​

  1. Implement real-coded GAs with SBX crossover and polynomial mutation
  2. Understand adaptive operator selection and self-adaptive rates
  3. Code constraint handling (penalty functions, feasibility rules)
  4. Implement island model parallel GAs with migration
  5. Understand niching, speciation, and steady-state vs generational models

Concept Explanation​

Coming soon.

Code Examples​

Coming soon.

Exercises​

Coming soon.

Milestone Checklist​

  • Implemented SBX crossover and polynomial mutation
  • Can compare binary vs real-coded GA performance
  • Built an island model GA
  • Understand when to use niching

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