Three stopping criteria are defined:
· Maximum number of model evaluations.
· Convergence in objective function space. In this case the optimisation terminates if the objective function of the best parameter set has not changed more than a user-defined minimum value in a given number of shuffling loops.
· Convergence in parameter space. In this case the optimisation terminates if the range of parameter values of the entire population in the parameter space is less than a given value (not user-defined).
The search terminates when one of these criteria is met.
Maximum No. of model evaluations
The maximum number of model evaluations allowed in the optimisation.
No. of loops of convergence
The number of iteration loops in which the objective function value of the best parameter set has not changed more than the Minimum relative change in objective function value.
Minimum relative change in objective function value
Minimum relative change allowed in the best objective function value in the last No. of loops of convergence.