alogos._optimization.ea.operators.generation_model¶
Functions¶
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Use an overlapping generation model. |
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Use a non-overlapping generation model. |
Detailed object descriptions¶
- alogos._optimization.ea.operators.generation_model.overlapping(parent_population, offspring_population, parameters)[source]¶
Use an overlapping generation model.
Notes
Overlapping pooling together with rank-based survivor selection is equivalent to “(lambda + mu) selection” [1].
Overlapping pooling together with tournament survivor selection is equivalent to “round-robin tournament”.
“However, a much more significant effect on selection pressure occurs when using an EA with an overlapping-generation model such as a “steady-state GA”, a “µ + λ” ES, or any EP algorithm. In this case, parents and offspring compete with each other for survival. The combination of a larger selection pool (m + n) and the fact that, as evolution proceeds, the m parents provide stronger and stronger competition, results in a significant increase in selection pressure over a non-overlapping version of the same EA.” [2]_
References
- alogos._optimization.ea.operators.generation_model.non_overlapping(parent_population, offspring_population, parameters)[source]¶
Use a non-overlapping generation model.
Notes
This is also known as “generational model” of population management [2]_ or (lambda, mu) selection [3].
“With non-overlapping models, the entire parent population dies off each generation and the offspring only compete with each other for survival. Historical examples of non-overlapping EAs include “generational GAs” and the “µ, λ” variation of ESs. In non-overlapping models, if the offspring population size n is significantly larger than the parent population size m (e.g., traditional ESs), then competition for survival increases.” [4]
References