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.
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.