1. Adjustments to Software Settings Jeremy Dyson Basel, Switzerland

2. Why Are Adjustments Necessary? Optimisation is the science of selecting the best of many possible decisions in a complex real-life environment Mordecai Avriel Nonlinear Programming

3. Optimisation Minimise the Value of the Function N [Data Value i – Modelled Value i ] 2 i = 1 When the function is solved numerically (normally) rather than analytically, this means that the solution is only as exact as you make it, and it depends on: –Search method, e.g. Marquardt algorithm, for the solution –Settings for search method, including initial parameter values –How the modelled values are calculated –Settings to finish the search, i.e. an acceptable solution Settings may need adjusting to find global minimum

4. ModelMaker – Marquardt Settings Convergence Change –The size of a convergence step (0.1) Convergence Steps –Number of convergence step before optimisation stops (50) Retry Count –Number of times optimisation retries convergence steps (50) Initial Lamda –Initial value determines initial steepness of the search (0.01) Minimum Change –Minimum change in Lambda (0.00001) Fractional Change –Fractional change in Lambda (0.01)

5. ModelMaker – Simulated Annealing Why is it needed? –If the Marquardt Settings cannot find the global minimum When is it likely to be needed? –Initial parameter values inappropriate –Model has a complex minimisation function, e.g. HS kinetics What does it do? –Tries many combinations of initial parameter values

6. Acknowledgement Dr Rene Oscar Kühne for teaching me ModelMaker