What is fitness inheritance in Genetic Algorithms?

Updated May 16, 2026

Short answer

Fitness inheritance estimates offspring fitness from parents instead of full evaluation.

Deep explanation

Fitness inheritance reduces computational cost by approximating offspring fitness based on parent fitness values and genetic similarity. Instead of expensive re-evaluation (e.g., simulation), the algorithm predicts fitness using weighted combinations or regression models. This is especially useful in expensive optimization problems like engineering simulations or deep learning hyperparameter tuning.

Real-world example

Used in aerodynamic design optimization where each evaluation requires CFD simulation.

Common mistakes

  • Over-relying on inheritance without periodic true evaluations, leading to drift from actual fitness landscape.

Follow-up questions

  • How does it compare to surrogate models?
  • When should it be avoided?

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