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학술대회
A Posterior Preference Articulation Method to Dual Response Surface Optimization
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- 발행일
- 200611
- 출처
- Institute for Operations Research and Management Sciences (INFORMS) 2006, pp.1-32
- 협약과제
- 06KE2100, KT WiBro 확산을 위한 마케팅전략 연구, 한성수
- 초록
- Response surface methodology (RSM) is one of popular tools to support a systematic improvement of quality of design in the product and process development stages. It consists of statistical modeling and optimization tools. RSM can be viewed as a knowledge management tool in that it systemizes knowledge about a manufacturing process through a big data analysis on products and processes. The conventional RSM aims to optimize the mean of a response, whereas dual-response surface optimization (DRSO), a special case of RSM, considers not only the mean of a response but also its variability or standard deviation for optimization. Recently, a posterior preference articulation approach receives attention in the DRSO literature. The posterior approach first seeks all (or most) of the nondominated solutions with no articulation of a decision maker (DM)’s preference. The DM then selects the best one from the set of nondominated solutions a posteriori. This method has a strength that the DM can understand the tradeoff between the mean and standard deviation well by looking around the nondominated solutions. A posterior method has been proposed for DRSO. It employs an interval selection strategy for the selection step. This strategy has a limitation increasing inefficiency and complexity due to too many iterations when handling a great number (e.g., thousands ~ tens of thousands) of nondominated solutions. In this paper, a TOPSIS-based method is proposed to support a simple and efficient selection of the most preferred solution. The proposed method is illustrated through a typical DRSO problem and compared with the existing posterior method.
- KSP 제안 키워드
- Big Data analysis, Decision makers(DMs), Improvement of quality, Interval selection, Manufacturing processes, Modeling and Optimization, Preference articulation, Process development, Products and processes, Quality of design, Response Surface Optimization