The parameters for the optimisation are left as the default values with the exception of the population size which is set to 8 and the maximum No of model evaluations, which is reduced to 80. Normally one should prefer to end the optimisation by meeting the convergence criteria. The convergence criterion is a measure of the relative change in best objective function value in the last number of loops of the optimisation where the number of loops of convergence is also user input. For the current example in which we use artificial measurements we do have the problem, however, that the best objective function will have a value of zero corresponding to a perfect fit. In this situation, which will (sadly) only happen for artificial measurements, the use of a relative change convergence criteria leads to evaluation of a ratio between two measures that are both approaching zero. For this reason the current optimisation will need to be terminated by the maximum no of model evaluations criterion.