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

KEY POINTS 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 can 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.

[1]  Christine M. Anderson-Cook,et al.  Rethinking the Optimal Response Surface Design for a First-Order Model with Two-Factor Interactions, When Protecting against Curvature , 2012 .

[2]  Christine M. Anderson-Cook,et al.  Optimization of Designed Experiments Based on Multiple Criteria Utilizing a Pareto Frontier , 2011, Technometrics.

[3]  Christine M. Anderson-Cook,et al.  Incorporating response variability and estimation uncertainty into Pareto front optimization , 2014, Comput. Ind. Eng..

[4]  Douglas C. Montgomery,et al.  Response Surface Methodology: Process and Product Optimization Using Designed Experiments , 1995 .

[5]  Christine M. Anderson-Cook,et al.  Process Optimization for Multiple Responses Utilizing the Pareto Front Approach , 2014 .

[6]  Christine M. Anderson-Cook,et al.  Adapting the Hypervolume Quality Indicator to Quantify Trade-offs and Search Efficiency for Multiple Criteria Decision Making Using Pareto Fronts , 2013, Qual. Reliab. Eng. Int..

[7]  Christine M. Anderson-Cook,et al.  A Case Study on Selecting a Best Allocation of New Data for Improving the Estimation Precision of System and Subsystem Reliability Using Pareto Fronts , 2013, Technometrics.

[8]  Yan Fu,et al.  The Effect of Initial Population Sampling on the Convergence of Multi-Objective Genetic Algorithms , 2009 .

[9]  Johannes Bader,et al.  Hypervolume-based search for multiobjective optimization: Theory and methods , 2010 .

[10]  Byran J. Smucker,et al.  On using the hypervolume indicator to compare Pareto fronts: Applications to multi-criteria optimal experimental design , 2015 .