TY - RPRT U1 - Forschungsbericht A1 - Zaefferer, Martin A1 - Bartz-Beielstein, Thomas A1 - Naujoks, Boris A1 - Wagner, Tobias A1 - Emmerich, Michael T1 - Model-assisted Multi-criteria Tuning of an Event Detection Software under Limited Budgets N2 - Formerly, multi-criteria optimization algorithms were often tested using tens of thousands function evaluations. In many real-world settings function evaluations are very costly or the available budget is very limited. Several methods were developed to solve these cost-extensive multi-criteria optimization problems by reducing the number of function evaluations by means of surrogate optimization. In this study, we apply different multi-criteria surrogate optimization methods to improve (tune) an event-detection software for water-quality monitoring. For tuning two important parameters of this software, four state-of-the-art methods are compared: S-Metric-Selection Efficient Global Optimization (SMS-EGO), S-Metric-Expected Improvement for Efficient Global Optimization SExI-EGO, Euclidean Distance based Expected Improvement Euclid-EI (here referred to as MEI-SPOT due to its implementation in the Sequential Parameter Optimization Toolbox SPOT) and a multi-criteria approach based on SPO (MSPOT). Analyzing the performance of the different methods provides insight into the working-mechanisms of cutting-edge multi-criteria solvers. As one of the approaches, namely MSPOT, does not consider the prediction variance of the surrogate model, it is of interest whether this can lead to premature convergence on the practical tuning problem. Furthermore, all four approaches will be compared to a simple SMS-EMOA to validate that the use of surrogate models is justified on this problem. T3 - CIplus - 2/2012 KW - Soft Computing KW - Optimierung KW - Mehrkriterielle Optimierung KW - Globale Optimierung KW - Modellierung KW - Event Detection KW - Water Quality Monitoring KW - Surrogate Optimization KW - Expected Improvement KW - Multi-criteria Optimization Y2 - 2012 U6 - https://nbn-resolving.org/urn:nbn:de:hbz:832-cos-234 UN - https://nbn-resolving.org/urn:nbn:de:hbz:832-cos-234 SN - 2194-2870 SB - 2194-2870 ER -