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Activity Number: 200 - New Developments in the Design of Experiments
Type: Contributed
Date/Time: Tuesday, August 4, 2020 : 10:00 AM to 2:00 PM
Sponsor: Quality and Productivity Section
Abstract #312737
Title: Design Optimization Based on D-optimality for Multiple Responses
Author(s): Damola Akinlana* and Lu Lu
Companies: University of South Florida and University of South Florida
Keywords: Multiple Responses; Optimal Designs; Coordinate Exchange Algorithm; Pareto Front; D-optimality
Abstract:

Due to various resource restrictions, there has been increased needs to measure multiple responses in a single experiment. Central composite designs have been broadly used for estimating response surfaces from experiments with multiple responses, which typically require a large number of runs across the super space of all relevant design factors. However, in many of these experiments, each individual response is often affected by only a subset of design factors, and such information might be obtained from earlier screening experiments. We propose a more cost-efficient design selection strategy based on utilizing this prior knowledge and the Pareto front approach to select D-optimal designs with balanced performance on multiple responses. A Pareto aggregate coordinate exchange algorithm has been adapted to efficiently identify the Pareto front based on D-efficiencies measured for multiple responses. The method is illustrated with two examples and compared with existing methods on a variety of design characteristics.


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