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Model-assisted Multi-criteria Tuning of an Event Detection Software under Limited Budgets

  • 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.

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Metadaten
Author:Martin Zaefferer, Thomas Bartz-BeielsteinGND, Boris Naujoks, Tobias Wagner, Michael Emmerich
URN:urn:nbn:de:hbz:832-cos-234
ISBN:2194-2870
Series (Serial Number):CIplus (2/2012)
Document Type:Report
Language:English
Year of Completion:2012
Release Date:2012/10/31
Tag:Event Detection; Expected Improvement; Multi-criteria Optimization; Surrogate Optimization; Water Quality Monitoring
GND Keyword:Globale Optimierung; Mehrkriterielle Optimierung; Modellierung; Optimierung; Soft Computing
Contributor:Bartz-Beielstein, Thomas
Institutes and Central Facilities:Fakultät für Informatik und Ingenieurwissenschaften (F10) / Fakultät 10 / Institut für Informatik
Dewey Decimal Classification:000 Allgemeines, Informatik, Informationswissenschaft / 000 Allgemeines, Wissenschaft / 004 Informatik
Open Access:Open Access
Licence (German):License LogoCreative Commons - Namensnennung, Nicht kommerziell, Keine Bearbeitung