| Name | Description |
|---|---|
| Ackley | Ackley benchmark problem. |
| Benchmark | Base-class for a benchmark optimization problem. |
| Benchmarks | Contains list of all implemented benchmark problems. |
| CurveFitting | Base-class for curvefitting by minimizing the Mean-Squared-Error (MSE), that is, minimizing Sum((y - f(x))^2), for all given data-pairs (x,y). |
| CurveFittingExp | Curve-fitting to the exponential curve f(x) = B*Pow(A, x). You may wish to use a form of regression instead, depending on your requirements for statistical minimization of error. |
| CurveFittingLin | Curve-fitting to the linear curve f(x) = A*x + B. This is meant as an example, you will want to use linear regression instead for real applications. |
| Griewank | Griewank benchmark problem. |
| Mangler | Search-space mangler, used to increase the difficulty of optimizing benchmark problems and avoid correlation with global optima such as zero. Note that this works with parallel optimizers but not with parallel meta-optimization because of the way MetaFitness is implemented. |
| Penalized | Helper-methods for Penalized benchmark problems. |
| Penalized1 | Penalized1 benchmark problem. |
| Penalized2 | Penalized2 benchmark problem. |
| QuarticNoise | Quartic Noise benchmark problem. |
| Rastrigin | Rastrigin benchmark problem. |
| Rosenbrock | Rosenbrock benchmark problem. |
| Schwefel12 | Schwefel 1-2 benchmark problem. |
| Schwefel221 | Schwefel 2-21 benchmark problem. |
| Schwefel222 | Schwefel 2-22 benchmark problem. |
| Sphere | Sphere benchmark problem. |
| SphereSleep | Sphere benchmark problem with thread-sleeping to simulate a time-consuming problem. |
| Step | Step benchmark problem. |