A case study to demonstrate a Pareto Frontier for selecting a best response surface design while simultaneously optimizing multiple criteria

Lu Lu, Christine M. Anderson‐Cook and Timothy J. Robinson

Applied Stochastic Models in Business and Industry, 2012, vol. 28, issue 3, 206-221

Abstract: Experimenting with limited resources often means that we are trying to get more out of a single experiment and balance competing goals. Selecting a best response surface design when simultaneously optimizing multiple criteria requires carefully choosing measures and scales of different design criteria and then balancing the trade‐offs between the criteria. This paper illustrates a decision‐making process using a Pareto frontier to identify good design candidates and a Utopia point approach for selection of an optimal design based on several competing criteria. The Pareto approach shows substantial improvement over the classic desirability function method by offering the user greater flexibility in quantifying the robustness of designs to weight specifications and the sensitivity of the solutions to different choices of weights, scales, and metrics. Graphical methods are used for summarizing and extracting useful information for improved decision‐making. Copyright © 2012 John Wiley & Sons, Ltd.

Date: 2012
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/asmb.940

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmbi:v:28:y:2012:i:3:p:206-221

Access Statistics for this article

More articles in Applied Stochastic Models in Business and Industry from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().