陳正剛2006-07-252018-06-292006-07-252018-06-292004http://ntur.lib.ntu.edu.tw//handle/246246/4204為了可以在生產過程中即時而且持續的改善生產製 程，許多不同的技術已在過往陸續地被發展出來，這些技 術分別由不同學術領域的學者基於不同需求所發展出 來；然而遭到實務界的忽視卻是這些技術的共同的命運。 一個重要的理由是，這些技術往往需要複雜的數學理論與 計算，因為這些複雜的計算使得在計算機資源仍然相當昂 貴的年代，無法被應用於實際的問題上。另外一個理由 是，過去較簡易的企業經營模式與製造過程不需要如此複 雜的技術。在本計劃的第一年度中，我們重新檢視這些技 術，其中包括統計學者所發展出的演進作業程序技術與最 佳化實驗設計；由數學及控制學者所發展的擾動最佳化技 術；以及最近由離散事件控制學者所發展的排序最佳化技 術。我們也經由對這些技術的徹底了解，而發展並提出一 適用於實務界的整合演進最佳化方法。Over the years, different techniques have been developed to address issues of continuous process improvement during production. These techniques are developed in different academic communities initiated by different concerns. However, a common fate of these techniques is the negligence by industrial practitioners. An important reason was that the techniques’ unbearable mathematical sophistication had diminished their applicability during the age of expensive computing resources. Another reason was that these techniques seemed to over-shoot the needs of the relatively simple business model and manufacturing processes at that time. In the first year of this project, we re-examine these techniques, including Evolution Operations (EVOP) and Optimum Experimental Design (OED) and Ridge Analysis (RA) developed by the applied statistics community, Perturbation-based Real-Time Optimization (PRTO) by mathematics and control communities and Ordinal Optimization (OO) techniques by the discrete-event control community. After reviewing these methods, we propose an integrated, comprehensive evolutionary optimization method that can be easily applied in practice.application/pdf419926 bytesapplication/pdfzh-TW國立臺灣大學工業工程學研究所演進作業程序最佳化實驗設計擾動最佳化排序最佳化Evolutionary Operations (EVOP) PlanningOptimum Experimental Design (OED)Perturbation Optimization (PO)Ordinal Optimization (OO)reporthttp://ntur.lib.ntu.edu.tw/bitstream/246246/4204/1/922213E002100.pdf