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Title: Quality quandaries: Understanding aspects influencing different types of multiple response optimization

Journal Article · · Quality Engineering
 [1];  [2];  [3]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Indiana Univ. of Pennsylvania, Indiana, PA (United States)
  3. Univ. of South Florida, Tampa, FL (United States)
+ Show Author Affiliations

In this study, optimizing with several responses can benefit from an objective approach of eliminating non-contenders, understanding trade-offs between competing responses, and then identifying a final choice that matches optimization priorities. To offer insights that help guide thoughtful decisions, we explore and summarize different patterns of solution sets and their trade-offs for different types of optimization with responses that are to be maximized and/or to achieve a target.

Research Organization:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOD; USDOE
Grant/Contract Number:
AC52-06NA25396
OSTI ID:
1331282
Report Number(s):
LA-UR-16-23124
Journal Information:
Quality Engineering, Journal Name: Quality Engineering; ISSN 0898-2112
Publisher:
American Society for Quality ControlCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 2 works
Citation information provided by
Web of Science

References (7)

On using the hypervolume indicator to compare Pareto fronts: Applications to multi-criteria optimal experimental design journal May 2015
Adapting the Hypervolume Quality Indicator to Quantify Trade-offs and Search Efficiency for Multiple Criteria Decision Making Using Pareto Fronts journal September 2012
Optimization of Designed Experiments Based on Multiple Criteria Utilizing a Pareto Frontier journal November 2011
Process Optimization for Multiple Responses Utilizing the Pareto Front Approach journal May 2014
A Case Study on Selecting a Best Allocation of New Data for Improving the Estimation Precision of System and Subsystem Reliability Using Pareto Fronts journal November 2013
Incorporating response variability and estimation uncertainty into Pareto front optimization journal October 2014
Rethinking the Optimal Response Surface Design for a First-Order Model with Two-Factor Interactions, When Protecting against Curvature journal July 2012

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Related Subjects

97 MATHEMATICS AND COMPUTING
Mathematics