Authors: Erdbrügge, Martina
Kuhnt, Sonja
Rudak, Nikolaus
Title: Joint optimization of multiple responses based on loss functions
Language (ISO): en
Abstract: Most of the existing methods for the analysis and optimization of multiple responses require some kind of weighting of these responses, for instance in terms of cost or desirability. Particularly at the design stage, such information is hardly available or will rather be subjective. Kuhnt and Erdbrugge (2004) present an alternative strategy using loss functions and a penalty matrix which can be decomposed into a standardizing (data-driven) and a weight matrix. The effect of different weight matrices is displayed in joint optimization plots in terms of predicted means and variances of the response variables. In this article, we propose how to choose weight matrices for two and more responses. Furthermore we prove the Pareto optimality of every point that minimizes the conditional mean of the loss function.
Subject Headings: Different weight matrix
Loss function
Multiple response
Pareto optimality
Penalty matrix
Issue Date: 2011-03-02
Appears in Collections:Sonderforschungsbereich (SFB) 823

Files in This Item:
File Description SizeFormat 
DP_1011_SFB823_Erdbrügge_Kuhnt_Rudak.pdfDNB753.2 kBAdobe PDFView/Open

This item is protected by original copyright

Items in Eldorado are protected by copyright, with all rights reserved, unless otherwise indicated.