SwarmOps Random Sampling (RND)
SwarmOps algorithms are being removed and may not be compatible with future releases of Analyzer. Users should be cautious when using them in models
Note: SwarmOps algorithms are being removed and may not be compatible with future releases of Analyzer. Users should be cautious when using them in models
Version
SwarmOps 3.0
Description
SwarmOps Random searches the design space completely at random. This can be used as a baseline performance to compare other optimizers.
References
SwarmOps Manual (p. 19)
Control Parameters
| Name | Default Value | Description |
|---|---|---|
| Optimization Parameters | ||
| Seed | Random number generator seed value (optional). Specifying the same seed value between two different optimization runs would help generate identical results provided all other parameters stay the same. This is a good way to analyze the effect of different parameters on the optimization. | |
| Stopping Criteria | ||
| AbsoluteConvergenceTolerance | 0.0001 | Maximum absolute change in fitness value between successive evaluations to indicate convergence. The value specified must be greater than 0. |
| ConsecutiveFunctionEvaluations | 200 | The number of consecutive iterations for which the convergence criteria must be met to indicate convergence. Thus option must have a positive integer value. |
| MaxFunctionEvaluations | 3000 | Maximum number of iterations. Thus option must have a positive integer value. |