MC Manual has not been updated in many areas since 2018 (e.g. Kase bars?)
But I am specifically interested in understanding the meaning/ implications of different GA settings.
- when "least fit individuals are discarded ", - how many - as a % of population? is this changeable?
- does a (single) "crossover" always occur between 2 parents ?
Basic GA:
* This algorithm uses non-overlapping generations and Elitism mode (optional).
* For each generation, the algorithm creates an entirely new population of individuals (if the Elitism option is selected, the most fit individuals move
on to the next generation). -- This is not clear at all
-->What exactly happens with the initial population?
-->What are 'non-overlapping generations'?? and how are they created? how is the "entirely new population" created?
-> how is "Crossover probability" applied in this case?
-> how many "Elite/most fit" individual (as a % of population) move to the next generation?
--> if Elitism is not selected, how does Evolution happen altogether?
Incremental GA:
* It simply adds only one or two children to the population each time the next generation is created. These one or two children replace one or two individuals in the previous generation. --> so, does it add or replace?
--> With "Parent" replacement scheme, do children replace parents only if their fitness is better?
- "Number of individuals in population for crossover" --> what's the meaning of this and how does this work?
--> what should it be set to (cpu cores? % of population)?
-> how does "Crossover probability" work in this case?
Convergence Type/Proximal:
* as per manual, GA calculation is stopped after meeting: С [x – N] / C [x] >= P
--> shouldn't it be C[x] / C[x-N] >=P