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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 郭瑞祥 | |
dc.contributor.author | Meng-Tse Cheng | en |
dc.contributor.author | 鄭孟哲 | zh_TW |
dc.date.accessioned | 2021-06-13T16:32:42Z | - |
dc.date.available | 2005-07-15 | |
dc.date.copyright | 2005-07-15 | |
dc.date.issued | 2004 | |
dc.date.submitted | 2005-07-11 | |
dc.identifier.citation | [1] Arjan, B. B., B. Jansen, T. Terlaky and K. Roos, “Sensitivity analysis in (degenerate) quadratic programming,” Econometric Institute Report 30, Econometric Institute, Erasmus University, Rotterdam, The Netherlands, 1996.
[2] Arjan, B. B., B. Jansen and T. Terlaky, “The optimal set and optimal partition approach to linear and quadratic programming,” Econometric Institute Report 30, Econometric Institute, Erasmus University, Rotterdam, The Netherlands, 1996 [3] Auslender, A. and P. Coutat, “Sensitivity analysis for generalized linear-quadratic problems,” Journal of Optimization Theory and Applications. 1983 [4] Bazaraa, M. S. and C.M. Shetty, “Nonlinear programming theory and algorithm.,” 1984. [5] Boot, J.C.G. “On sensitivity analysis in convex quadratic programming Problems,” Econometric Institute, Rotterdam, Holland, 1963. [6] Boot, J. C. G. “Binding constraint procedures of quadratic programming,” Econometric, Vol. 31, No. 3 464-498, 1963. [7] Brown, A. O., H. L. Lee and R. Petrakian, “Xilinx improves its semiconductor supply chain using product and process postponement,” Interfaces Vol. 30, 4, pp.65-80 2000. [8] Carrizosa, E. and D. R. Morales, “Goal programming model for loading and routing problem in flexible manufacturing system,” Journal of Global Optimization, 18:35-58, 2000. [9] Cohen, M.A. and H.L. Lee, “Manufacturing strategy: concepts and methods in: Kleindorfer PR,” The Management of Productivity and Technology in Manufacturing, New York: Plenum Press, pp. 153-183, 1987. [10] Christie, R. M. and S. D. Wu, “Semiconductor capacity planning: stochastic modeling and computational Studies,” IIE Transactions, 34, pp. 131-143, 2002. [11] Frederix, F., “An extended enterprise planning methodology for the discrete manufacturing industry,” European Journal of Operations Research, 129, pp.317-325, 2001. [12] Geoffrion, A.M. and G.W. Graves, Lee, S.J., “Strategic distribution system planning: a status report,” In: Hex AC, editor. Studies in Operations Management. Amsterdam: North-Holland, pp. 178-314, 1978. [13] Hung, Y. and G. Cheng, “Hybrid Capacity Modeling for Alternative Machine Types in Linear Programming Production Planning,” IIE Transactions, 34, pp.157-165, 2002 [14] Karabuk, S. and S. D. Wu, “Decentralizing Semiconductor Capacity Planning Via Internal Market Coordination,” IIE Transactions, 34, pp. 743-759, 2002. [15] Lieberman, H., “Introduction to operations research” 7th Edition Chapter 7.5 p.332-340. [16] Lee, H. L., C. Billington and B. Carter, “Hewlett-Packard gains control of inventory and service through design for localization,” Interfaces, Vol. 23, pp. 1-11, 1993. [17] Min, H. and E. Melachrinoudis, “Dynamic location and entry mode selection of multinational manufacturing facilities under uncertainty:A chance-constrained goal programming approach, International Trans,” Operational Research, Vol.3, P65-76, 1996. [18] Padillo, J. M., R. Ingalls and S. Brown, “A strategic decision support system for supply network design and management in the semiconductor industry,” Computers Industry Engineering, Vol. 29, pp. 443-447, 1995 [19] Pyke, D.F. and A. Cohen, “Performance characteristics of stochastic integrated production-distribution systems,” European Journal of Operational Research, Vol. 68, pp. 23-48, 1993. [20] Rupp T. M. and M. Ristic, “Fine planning for supply chains in semiconductor manufacture,” Journal of Materials Processing Technology, Vol. 107, pp. 390-397, 2000. [21] Rusin, M. H., “A revised simplex method for quadratic programming,” SIAM Journal on Applied Mathematics, Vol.20, No. 2, 143-160, 1971. [22] Romero, C. “Handbook of critical issues in goal programming,” Pergamon Press, Oxford, 1991. [23] Robinson, P. E., L. L. Goa and S. T. Muggenborg, ”Designing an integrated distribution system at Dow brands,” INC. Interfaces, Vol. 23, pp. 17-107, 1993. [24] Simchi-Levi, D., P. Kaminsky and E. Simchi-Levi, “Designing and managing the supply chain,” USA, The McGraw-Hill Companies, Inc., 2000 [25] Toktay, L. B. and R. Uzsoy, “A capacity allocation problem with integer side constraints,” European Journal of Operational Research, Vol. 109, pp. 170-182, 1998. [26] Wolfe P., “A duality theorem for non-linear programming,” Quarterly of Applied Math p239-244, 1961. [27] Yao, M. J. and K.J. Min, “Repair-unit location models for power failures,” IEEE Transactions on Engineering Management, 45(1), 57-65, 1998. [28] 林悅慈, “以統計方法分析與設計半導體生產製造系統,” 國立台灣大學工業工程學研究所碩士班論文, 2000. [29] 許志義, “多目標決策,” 1995 [30] 詹偉順, “晶圓製造廠生產績效指標關係模式之構建,” 國立交通大學工業工程與管理研究所碩士班論文, 1997 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/38408 | - |
dc.description.abstract | 隨著外在環境變遷與技術快速進步,半導體供應鏈日趨複雜,競爭加劇。究其原因,半導體供應鏈生產系統遭受許多不確定性,即時的干擾和動態的變異對系統生產週期時間,在製品水準與產品產出率帶來嚴重的衝擊。
在過去的研究中,對於生產優先順序差異化、生產績效指標的衡量、供應鏈生產系統控制與監控、生產系統最佳化配置與半導體供應鏈長期規劃等議題鮮少有人提及。再則,過去簡單的供應鏈模型或是生產規劃軟體以無法有效的分析與配置複雜的半導體供應鏈。 有鑑於此,本研究探討在半導體供應鏈中生產服務優先順序化、生產路徑多樣性與生產路徑控制點差異化下,如何透過半導體供應鏈長期生產路徑設計與配置,有效的達到生產績效指標最佳化,並同時降低生產系統績效指標之變異。首先,藉由模擬資料建構反應曲面模型,來描述供應鏈各控制因子,包括生產服務優先順序、生產路徑與控制點與生產績效指標之間的關係。其次建構有優先權多目標生產規劃模型,透過生產服務優先順序組合、生產路徑組合與控制點組合優化各生產週期時間、在製品水準與顧客達交率,同時降低系統的變異。最後發展一套有效的啟發式演算法,透過降低多維多次規劃問題的複雜度,以片段二次半正定函數,有效而快速的找到近似解。 而本研究透過模擬系統加以驗證,顯示產品生產優先順序配置、產品生產路徑比例配置的不同水準設定,對系統各績效指標表現確實有顯著的影響,且經由本演算法所求得的近似解與直接原目標函數帶入套裝軟體所求的結果所求得的結果十分相似。 | zh_TW |
dc.description.abstract | Semiconductor fabrication is itself a very complicated manufacturing process. Its global, cross-company supply chain operations are even more complicated and dynamic that usual planning and scheduling solution have become impossible to employ. As semiconductor supply chain become widespread and the competition pressure is very fierce, the detrimental effects of increasing varieties and variations are magnified in the supply chain. But many important issues, such as differentiability of quality of service, adaptability, controllability and scalability of performance metrics, have not been addressed in the literature. Conventional modeling techniques of supply chain operations are no longer effective for supply chain configuration.
Therefore, the first objective of this research is to use response surface method (RSM) to build up the empirical model to describe the relationship between supply-chain configuration and performance metrics under the influence of different variability sources, an optimal supply chain configuration model including mean and variance of performance measures is formulated as a polynomial goal programming model to accommodate different goal objective. Finally, an efficient solution methodology named as semi-definite quadratic approximation method is developed further to find the most optimal supply chain configuration. Our result shows that our proposed model can easily be adapted the practices in semiconductor supply chain, and the solution methodology developed in this paper is truly effective in terms of quality of our solution comparing to other heuristic providing by come commercial soft wares. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T16:32:42Z (GMT). No. of bitstreams: 1 ntu-93-R92546004-1.pdf: 567808 bytes, checksum: 5239830b8623159b6b54beb896523687 (MD5) Previous issue date: 2004 | en |
dc.description.tableofcontents | 中文摘要 Ⅰ
Abstract Ⅱ 目 錄 Ⅲ 表 次 Ⅵ 圖 次 Ⅶ 第一章 緒論 1 1.1研究背景 1 1.2研究動機 4 1.3研究目的 6 1.4研究架構 7 1.5論文架構 8 第二章 文獻探討 9 2.1半導體供應鏈上下游整合 9 2.2生產績效指標之探討 12 2.3目標規劃 14 2.3.1多目標規劃之概念 14 2.3.2多目標規劃(目標規劃)之應用 15 2.3.3使用多目標規劃對半導體供應鏈進行分析 15 2.4二次非線性規劃 16 2.4.1二次規劃 16 2.4.2對偶理論 17 2.4.3敏感度分析 17 2.4.4使用二次半正定函數進行逼近 19 第三章 供應鏈配置之穩健設計與模型構建 20 3.1問題描述與假設 20 3.2有優先權多目標規劃配置模型構建 22 3.2.1生產績效指標與變數說明 22 3.2.2建立績效指標反應曲面與模型規劃目標 23 3.2.3符號說明 25 3.2.4數學模型 26 第四章 片段二次半正定逼近求解演算法 29 4.1片段二次半正定逼近求解演算法架構 29 4.2片段二次半正定逼近求解演算法詳細說明 31 4.2.1規劃模型建構 31 4.2.2目標函數二次半正定檢驗 32 4.2.3對目標函數全域進行二次半正定規劃逼近 32 4.2.4逼近誤差檢驗 33 4.2.5找尋切割之超平面對目標函數進行切割 34 4.2.6對各區塊進行二次半正定規劃逼近 36 4.2.7結束條件檢驗 36 4.2.8各區塊二次半正定新規劃模型求解 37 4.2.9再找尋切割之超平面對目標函數再切割 37 第五章 模擬驗證 38 5.1半導體供應鏈生產環境資料 38 5.2實驗因子與規劃實驗設計 44 5.3實驗結果整理與分析 46 5.3.1建立績效指標反應曲面與規劃目標函數 46 5.3.2有優先權多目標規劃配置模型構建 48 5.3.3採用片段二次半正定逼近求解演算法進行求解 52 第六章 結論與未來展望 57 6.1結論 57 6.2研究貢獻 58 6.3研究限制與未來研究方向 58 參考文獻 60 | |
dc.language.iso | zh-TW | |
dc.title | 半導體供應鏈路徑配置之多目標最佳化模式 | zh_TW |
dc.title | A Goal Programming Model for Semiconductor Supply Chain Configuration | en |
dc.type | Thesis | |
dc.date.schoolyear | 93-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 陳正剛,張時中,蔣明晃 | |
dc.subject.keyword | 半導體供應鏈,生產配置與規劃,生產變異,多項式目標規劃,啟發式演算法, | zh_TW |
dc.subject.keyword | Semiconductor Supply Chain Configurations,Polynomial Goal Programming Model,Heuristics, | en |
dc.relation.page | 63 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2005-07-11 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 工業工程學研究所 | zh_TW |
顯示於系所單位: | 工業工程學研究所 |
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