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Optimization Problems and Methods in Quality Control and Improvement

Summary: [This abstract is based on the authors' abstract.] This is an overview of some of the more frequently encountered optimization problems in statistics, with a focus on quality control and improvement. Optimization procedures are described, including: direct search methods; mathematical programming algorithms such as the generalized reduced gradient method; and heuristic approaches such as simulated annealing and genetic algorithms. It is hoped that this article will stimulate more interaction between the statistics and optimization methodology communities and create more awareness of the important role of optimization methods in quality control and improvement. [This article is followed by four discussion papers (pp. 18-29) and a response (pp. 30-31).]

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  • Topics: Quality Control, Design of Experiments
  • Keywords: Quality control (QC),Operational methods,Optimization,Design of experiments (DOE),Statistical quality control (SQC),Quality improvement (QI)
  • Author: Carlyle, W. Matthew; Montgomery, Douglas C.; Runger, George C.
  • Journal: Journal of Quality Technology