Definition
Fitness approximation is used in evolutionary computation when evaluating the true fitness function is computationally expensive or time-consuming. Instead of calculating the exact value, surrogate models or simplified metrics are employed to estimate the fitness of candidate solutions. This approach accelerates the search process by allowing more generations to be evaluated within a fixed time budget, though it may introduce some error in the selection pressure.
Summary
A technique in evolutionary algorithms that estimates solution quality to reduce computational costs during optimization.
Key Concepts
- Surrogate Modeling
- Computational Efficiency
- Evolutionary Algorithms
- Selection Pressure
Use Cases
- Engineering design optimization
- Complex simulation-based problems
- Large-scale parameter tuning