dc.contributor.advisor | 林我聰 | zh_TW |
dc.contributor.advisor | Lin,Woo-Tsong | en_US |
dc.contributor.author (Authors) | 黃蘭禎 | zh_TW |
dc.contributor.author (Authors) | Huang,Lan Chen | en_US |
dc.creator (作者) | 黃蘭禎 | zh_TW |
dc.creator (作者) | Huang,Lan Chen | en_US |
dc.date (日期) | 2003 | en_US |
dc.date.accessioned | 18-Sep-2009 14:25:25 (UTC+8) | - |
dc.date.available | 18-Sep-2009 14:25:25 (UTC+8) | - |
dc.date.issued (上傳時間) | 18-Sep-2009 14:25:25 (UTC+8) | - |
dc.identifier (Other Identifiers) | G0091356005 | en_US |
dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/35199 | - |
dc.description (描述) | 碩士 | zh_TW |
dc.description (描述) | 國立政治大學 | zh_TW |
dc.description (描述) | 資訊管理研究所 | zh_TW |
dc.description (描述) | 91356005 | zh_TW |
dc.description (描述) | 92 | zh_TW |
dc.description.abstract (摘要) | 協同規劃、預測與補貨(Collaborative Planning, Forecasting and Replenishment,CPFR),在歐美經過一些企業的採用後已經有顯著的成效,目前國內已經有一些企業相繼採用或即將採用CPFR,期望能因此降低供應鏈作業成本及提升供應鏈作業績效,以提升企業競爭力。在CPFR流程與供應鏈協同作業環境下,一個供需雙方協同,且績效良好的的銷售預測具有關鍵的重要性,是管理決策與協同合作時的的重要依據;但是多數的企業並沒有一個結構化、系統化的預測流程及方法,而是各部門透過簡單時間序列方法、天真預測法或人為經驗法則估算需求,進行多點且不同方法之預測,這樣的銷售預測較無穩定的品質,亦較難提供管理者合理的數據解釋。本研究結合時間序列、多元回歸模型與基因演算法發展出一個CPFR流程下之三階段混合預測方法,以買賣方直接之銷售資料、銷售計畫等資訊進行以「週」為單位之個別商品銷售預測。同時本研究中,亦以國內某製造業公司與其顧客(一國際大型零售連鎖店通路商)之產品銷售資料進行方法的驗證;實驗顯示,本研究所提出之預測方法之預測結果較Jeong等人(2002)所提結合多元回歸模型與基因演算法之二階段預測系統之預測結果佳;亦較傳統使用普通最小平方法求解之一般統計回歸方法預測結果佳。 | zh_TW |
dc.description.abstract (摘要) | It has been verified in pilot projects by many European and American Corporations that Collaborative Planning, Forecasting and Replenishment (CPFR) can improve supply chain performance. Enterprises nowadays in Taiwan are implementing or going to implement CPFR, with hopes to reduce their supply chain operation cost, enhance logistic performance and increase their competition capability consequently. Under CPFR process and supply chain collaboration environment, a supply and demand both sides promised identical sales forecast with well forecasting performance for order decision making and cooperation is very important. Due to the dynamic complexities of both internal and external co-operate environment, many firms resort to qualitative, navie forecasting or other simple quantitative forecasting techniques and have many forecasts in their organization. However, these forecasting techniques lack the structure and extrapolation capability of quantitative forecasting models or without stable performance, while multi-forecasts providing different views of demand. Forecasting inaccuracies exist and typically lead to dramatic disturbances in sales order and production planning.This paper presents a hybrid forecasting model for sales forecasting requirements in CPFR. A three stage model is proposed that integrate the time series model, regression model and use genetic algorithm to determine its coefficients efficiently. Direct sales information and related planned events in both collaborated sides is used for individual product’s “week” sales forecasting. To verify this model, we experiment on two different products and produce forecasts with datum from one manufacturer in Taiwan and its international retailer. The results shows that the hybrid sales forecasting model has better forecasting performance than not only the causal-genetic forecasting model proposed by Jeong et al. (2002), but also ordinary regression model with no genetic training process. | en_US |
dc.description.tableofcontents | 目錄致謝 I中文摘要 IIENGLISH ABSTRACT III第一章、緒論 11.1研究背景 11.2研究動機 21.3研究目的 31.4 研究方法 41.5研究架構與步驟 41.6研究範圍 51.7章節架構 5第二章、文獻探討 72.1供應鏈管理與CPFR 72.1.1供應鏈管理的定義 72.1.2供應鏈管理發展與趨勢 72.1.3協同規劃預測與補貨(CPFR) 82.1.4需求管理 122.2銷售預測與預測方法 122.2.1傳統預測技術相關理論 132.2.2協同預測 152.2.3企業預測技術之採用趨勢 162.2.4時間序列方法 172.2.5因果銷售預測函數型態 192.2.6銷售量影響因素 202.3 基因演算法 222.3.1 基因演算法運作流程 232.3.2 基因演算法之特性與優、缺點與相關改善方法之文獻 292.3.3供應鏈中使用基因演算法的因果預測系統文獻 30第三章、預測模型建構與實驗設計 323.1混合預測模型整體架構 333.2資料蒐集整理與應用 353.4多元回歸模型 363.5基因演算求最佳化之混合預測模型 393.5.1基因演算法之染色體編碼與適應函數 393.5.2基因演算法之染色體體產生與複製 413.5.3基因演算法之交配與突變、子代選擇方式 423.6驗證方法、工具與績效衡量指標 45第四章、實驗分析與模型績效驗證 474.1資料敘述與分析 474.2產品A預測實驗與績效 474.2.1階段一:時間序列子模型 474.2.2階段二:多元回歸模型 484.2.3階段三:基因演算求最佳化之混合預測模型 514.2.4小結 534.3產品B預測實驗與績效 544.3.1實驗與結果 544.3.2小結 56第五章、結論與建議 585.1結論 585.2後續研究方向與建議 59中文參考文獻 60英文參考文獻 61附錄 64表目錄表1、協同預測或CPFR流程相關文獻—著重於管理面者 2表2、協同預測或CPFR流程相關文獻—著重於預測技術者 3表3、CPFR與VMI、JMI之比較 8表4、CPFR的三階段與九流程步驟 10表5、CPFR流程模型中的銷售預測與訂單預測之差異 11表6、預測模型特性整理 13表7、因果銷售預測函數型態 20表8、產品生命週期特徵 21表9、模糊運算子交配相關公式與示意圖 27表10、本研究模型與欲比較之模型特性對照表 46表11、產品A時間序列模型參數敏感度訓練分析(賀特指數平滑法參數分析) 47表12、產品A第二階段回歸模型分析與模型參數表 50表13、產品A 基因演化模型第一期初始值 51表14、基因演算流程交配率與突變率組合績效測試前10名 51表15、產品A之10次實驗平均績效 52表16、產品B第二階段回歸模型分析與模型參數表 54表17、產品B 基因演化模型第一期初始值 55表18、產品B之10次實驗平均績效 55圖目錄圖1、本研究架構與步驟示意圖 5圖2、第二代ECR 10圖3、企業預測模型採用狀況 16圖4、基因演算法之演化流程圖 23圖5、單點交配 25圖6、雙點交配 25圖7、字罩交配 25圖8、實數編碼之簡單交配 26圖9、模糊運算子交配相關公式與示意圖 27圖10、群體差異指數之概念式意圖 30圖11、混合預測模型架構圖 34圖12、本研究各階段劃分與資料應用示意圖 35圖13、週銷售量曲線舉例 35圖14、本研究基因預測模型流程圖 45圖15、產品A時間序列實際銷售量與預測曲線圖 48圖16、產品A所屬類別T月銷售量峰度指數 49圖17、產品A PDLC階段指數與週銷售曲線圖 50圖18、產品B 時間序列實際銷售量與預測曲線圖 54 | zh_TW |
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dc.language.iso | en_US | - |
dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0091356005 | en_US |
dc.subject (關鍵詞) | 協同規劃、預測與補貨 | zh_TW |
dc.subject (關鍵詞) | 銷售預測 | zh_TW |
dc.subject (關鍵詞) | 混合預測模型 | zh_TW |
dc.subject (關鍵詞) | 基因演算法 | zh_TW |
dc.subject (關鍵詞) | Collaborative Planning, Forecasting and Replenishment | en_US |
dc.subject (關鍵詞) | CPFR | en_US |
dc.subject (關鍵詞) | Sales forecasts | en_US |
dc.subject (關鍵詞) | Hybrid forecasting model | en_US |
dc.subject (關鍵詞) | Genetic Algorithm | en_US |
dc.title (題名) | CPFR流程下之銷售預測方法~混合預測模型 | zh_TW |
dc.title (題名) | A Hybrid Modeling Approach for Sales Forecasting in CPFR Process | en_US |
dc.type (資料類型) | thesis | en |
dc.relation.reference (參考文獻) | 中文參考文獻 | zh_TW |
dc.relation.reference (參考文獻) | 1.林郁文,「以產品生命週期為基礎之多世代產品競爭主動式雙贏定價模式」,東海大學工業工程與經營資訊研究所碩士論文,民國92年六月 | zh_TW |
dc.relation.reference (參考文獻) | 2.陳建安,「整合類神經往路與遺傳演算法為輔之模糊類神經網路於智慧型訂單選取之應用」,國立台北科技大學生產系統工程與管理研究所碩士論文,民國89年六月 | zh_TW |
dc.relation.reference (參考文獻) | 3.蘇木村、張孝德,「機器學習類神經網路、模糊系統以及基因演算法則」,全華科技圖書股份有限公司出版,民國92年二版 | zh_TW |
dc.relation.reference (參考文獻) | 4.鄭碧娥,「商情預測」,三民書局,民國82 | zh_TW |
dc.relation.reference (參考文獻) | 5.姚銘忠、張倫、林晏妃、黃曉玲,「工具機業導入協同規劃與補貨模式之探討」,第一屆知識管理與與協同規劃研討會,http://2002.kiucp.ie.thu.edu.tw/ | zh_TW |
dc.relation.reference (參考文獻) | 6.姚銘忠、張倫、黃曉玲、黃茂洲,「由二階製N階的協同計劃、預測與補貨模式之探討」,第一屆知識管理與與協同規劃研討會,http://2002.kiucp.ie.thu.edu.tw/ | zh_TW |
dc.relation.reference (參考文獻) | 7.張炳螣、張晴翔、廖嘉偉,「協同預測應用於IC半導體之整合模式」,第一屆知識管理與與協同規劃研討會,http://2002.kiucp.ie.thu.edu.tw/ | zh_TW |
dc.relation.reference (參考文獻) | 8.廖嘉偉,「前導性協同預測架構與實施系統之研究」,東海大學工業工程與經營資訊研究所碩士論文,民國92年 | zh_TW |
dc.relation.reference (參考文獻) | 英文參考文獻 | zh_TW |
dc.relation.reference (參考文獻) | 1.Anderson, E. & Simester, D. ,” Minding Your Pricing Cues,” Harvard business Review, September , 7pgs,2003 | zh_TW |
dc.relation.reference (參考文獻) | 2.Anderson, D. and Lee, H. ,” White paper: The Internet-enabled supply chain: from the “first click” to the” Last Mile “,1999, available at http://www.manufacturing.net/scm/contents/pdf/anderson_lee_wp.pdf | zh_TW |
dc.relation.reference (參考文獻) | 3.Arminger, G. ,”Sales and Order Forecasts in the CPFR Process for Retail”,pp.53-68, 2002 | zh_TW |
dc.relation.reference (參考文獻) | 4.Aviv, Y. ,”The Effect of Collaborative Forecasting on Supply Chain Performance,” Management Science, Vol.47, No.10, pp.1326-1343, 2001 | zh_TW |
dc.relation.reference (參考文獻) | 5.Aviv, Y. ,“Gaining Benefits from Joint Forecasting and Replenishment Processes: the Case of Auto-Correlated Demand,” Manufacturing & Service Operations Management,Vol.4, No.1,pp.55-74, 2002 | zh_TW |
dc.relation.reference (參考文獻) | 6.Bajic, V. ,"Automobiles and Implicit Markets: An Estimate of a Structural Demand Model for Automobile Characteristics," Applied Economics,vol.2, pp. 541-551, 1993 | zh_TW |
dc.relation.reference (參考文獻) | 7.Chase, C. W. ,"Business Forecasting: A Process Not An Application," Journal of Business Forecasting,Vol.11, No.3,pp.12-13, 1992 | zh_TW |
dc.relation.reference (參考文獻) | 8.Chase, C. W. and Chase, Jr. ,"The Realities of Business Forecasting," Journal of Business Forecasting, Vol.14, No.1, p.2, 26, 1995 | zh_TW |
dc.relation.reference (參考文獻) | 9.Chase, C. W. and Chase, Jr., "What Do You Need to Know When Building A Sales Forecasting System," Journal of Business Forecasting, Vol.15, No.3, pp.2,23, 1996 | zh_TW |
dc.relation.reference (參考文獻) | 10.Charles, C.W. and Chase, Jr. ,“Composite Forecasting: Combing Forecasts for Improved Accuracy,” The journal of business forecasting, Vol.19, pp.2, 20-22, 2000 | zh_TW |
dc.relation.reference (參考文獻) | 11.Chu, C.W. and Zhang. G. P. ,”A Comparative study of linear and nonlinear models for aggregate retail sale forecasting,” International Journal of Production Economics, Vol.86, pp.217-231, 2003 | zh_TW |
dc.relation.reference (參考文獻) | 12.Diehn, D. ,”Seven Steps to Build a Successful Collaborative Forecasting Process,” The journal of business forecasting, Vol.19,No.4,pp.23-29, 2000-2001 | zh_TW |
dc.relation.reference (參考文獻) | 13.Goldberg, D. E. ,“Generic Algorithms in Search, Optimization and Machine Learning,” Addison-Wesley Publishion, 1989 | zh_TW |
dc.relation.reference (參考文獻) | 14.Jeong, B. ,Jung, H. S. and Park, N. K.,”A computerized casual forecasting system using genetic algorithms in supply chain mgmt,” the Journal of Systems and Software, vol.60, pp. 223-237, 2002 | zh_TW |
dc.relation.reference (參考文獻) | 15.Herrera, M. L. and Verdegay, J. H. ,”Fuzzy connectives based crossover operation to model genetic algorithms population diversity,” Fuzzy Set and Systems 92, pp.21-30, 1997 | zh_TW |
dc.relation.reference (參考文獻) | 16.Helms, M. ,Ettkin, L. P. and Chapman, S. ,“Supply Chain Forecasting—Collaborative forecasting supports supply chain management,” Business Process Management Journal, Vol.6, Iss.5, pp.392-394 | zh_TW |
dc.relation.reference (參考文獻) | 17.Holmström, J. ,Främling, K. ,Kaipia, R. and Saranen, J. ,“Collaborative Planning Forecasting and Replenishment: New Solutions Needed for Mass Collaboration,” the Journal of Supply Chain Management ,Vol.7, No.3, pp.136-145, 2002 | zh_TW |
dc.relation.reference (參考文獻) | 18.Jain, L. ,”Which Forecasting Model should We Use? ,”The journal of business forecasting, Vol.19,No.3,pp.2,28,35, 2000 | zh_TW |
dc.relation.reference (參考文獻) | 19.Jain, L. ,”Benchmarking forecasting models,” The Journal of Business Forecasting, Methods and System,Vol.21,No.3 ,pp.18-20,30, 2002 | zh_TW |
dc.relation.reference (參考文獻) | 20.Kolter, P. ,”Marketing management-Analysis, Planning,Implementation and Control,”9th ed, Englewood Cliffs, N. J., Prentice-Hall Inc., 1991 | zh_TW |
dc.relation.reference (參考文獻) | 21.Lapide, L. ,“New developments in business forecasting : Debunking executive conventional wisdom ,” The journal of business forecasting, vol.19,No.2, pp.16-17, 2000 | zh_TW |
dc.relation.reference (參考文獻) | 22.LeVee, G. S. ,"The Key to Understanding the Forecasting Process, "Journal of Business Forecasting, Vol.11, No.4, pp.12-16, 1992 | zh_TW |
dc.relation.reference (參考文獻) | 23.Makridakis, S. and Wheelwright, S. C. ,“Forecasting Methods for Management,” 5th ed., N.Y.: John Wiley & Sons, pp.571-582, 1979 | zh_TW |
dc.relation.reference (參考文獻) | 24.MaCarthy, T. M. and Golicic, S. L. , ”Implementing Collaborative Forecasting to Improve Supply Chain Performance,” International Journal of Physical Distribution & Logistics Management, Vol.32, No.6, pp.431-454, 2002 | zh_TW |
dc.relation.reference (參考文獻) | 25.Mills, T. C. ,”Time Series Techniques for Economics, ”Cambridge University Press, United Kingdom, 1990 | zh_TW |
dc.relation.reference (參考文獻) | 26.Murray, J. and Sarantis, N. ,” Price-quality relations and hedonic price indexes for cars in the United Kingdom,” International Journal of the Economics of Business, Vol. 6,Iss.1,pp. 5, 23, 1999 | zh_TW |
dc.relation.reference (參考文獻) | 27.Mulhern, F. J.,Williams,J. D. and Leone,R. P. ,“Variability of Brand Price Elasticity across Retail Stores: Ethnic, Income, and Brand Determinants,” Journal of Retailing, Vol.74,No.3,pp.427-446, 1998 | zh_TW |
dc.relation.reference (參考文獻) | 28.Nolan, W. Jr. ,”Game Plan for A Successful Collaboration Forecasting process”, the Journal of Business Forecasting, Spring pp.2-6, 2001 | zh_TW |
dc.relation.reference (參考文獻) | 29.Ozturkmen, Z. A. ,“Forecasting in the Rapid Changing Telecommunications Industry: AT&T’s Experience,” The journal of business forecasting,Vol.19,No.3, pp.3-4, 2000 | zh_TW |
dc.relation.reference (參考文獻) | 30.Rice, G. and Mahmoud, E. , "Political Risk Forecasting by Canadian Firms," International Journal of Forecasting, Vol.6, No.1, pp.89-120, 1990 | zh_TW |
dc.relation.reference (參考文獻) | 31.Safavi, A. ,”Choosing The Right Forecasting Software and System,” The journal of business forecasting, Vol.21,No.3, pp.6-12,14, 2000 | zh_TW |
dc.relation.reference (參考文獻) | 32.Shankar, V. and Krishnamurthi, L. ,“Relating Price Sensitivity to Retail Promotional Variables and Pricing Policy: An Empirical Analysis,” Journal of Retailing, Vol.72,No.3, pp.249-271,1996 | zh_TW |
dc.relation.reference (參考文獻) | 33.Seifert, D. ,“Collaborative Planning, Forecasting and Replenishment,” Preprint Edition, pp.39-52, 2002 | zh_TW |
dc.relation.reference (參考文獻) | 34.Stank, T. P. and Keller, S. B. ,“Supply Chain Collaboration and Logistical Service performance,” Journal of Business Logistics, Vol22, No.1, pp.29-45, 2001 | zh_TW |
dc.relation.reference (參考文獻) | 35.Voss, G. B. and Seiders, K. ,”Exploring the Effect of Retail Sector and Firm Characteristics on Retail Price Promotion Strategy,” Journal of Retailing, Vol. 79, pp.37-52, 2003 | zh_TW |
dc.relation.reference (參考文獻) | 36.Wilson, N. ,”Game Plan for A Successful Collaboration Forecasting process,” the Journal of Business Forecasting, Vol.20,No.1, pp.2-6, 2001 | zh_TW |