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For now, if the max limit is reached, we remove the worst solution based solely on the value assigned to the solution, without considering its optimality. I think that using a Pareto front to find the best and the most recent solutions can be more reliable:
S = {solutions}
F = ParetoFront(S)
S = S \ F
restart from 2 until S is empty
select a random candidate in F to remove
Or something similar.
The text was updated successfully, but these errors were encountered:
For now, if the max limit is reached, we remove the worst solution based solely on the value assigned to the solution, without considering its optimality. I think that using a Pareto front to find the best and the most recent solutions can be more reliable:
Or something similar.
The text was updated successfully, but these errors were encountered: