We develop a framework for automated optimization of stochastic simulation models using Response Surface Methodology …. The framework is especially intended for simulation models where the calculation of the corresponding stochastic response … function is very expensive or time-consuming. Response Surface Methodology is frequently used for the optimization of …

can be estimated by optimization of the goodness-of-fit. We compared the efficiency and accuracy of the Response Surface … Methodology and the Nelder and Mead Simplex Method for optimization of microsimulation models. To this end, we tested several … respect to accuracy, Response Surface Methodology performed better in case of optimization of the microsimulation model …

the complete analysis of continuous optimization problems. Standard reasonable descents give a unified approach to all … central results outside optimization: the fundamental theorem of algebra, the maximum and the minimum principle of complex … function theorem. These optimization proofs compare favorably with the usual proofs and are all based on the same strategy …

We consider the Nelder and Mead Simplex Method for the optimization of stochastic simulation models. Existing and new … functions. We found that gradually decreasing the noise during an optimization run is the most preferred approach for stochastic … objective functions. The amount of computation effort needed for successful optimization is very sensitive to the timing of …

are considered: controlled and uncontrolled. Simulation results show that uncontrolled arrivals of ships perform worst in …