整合神經網路與灰色理論之預測模型設計

Integrate Neural Network with Grey Theory to Design a Prediction Model

吳綺芳(Chi-Fang Wu)

指導教授 ： 陳雲岫

元智大學/工程學院/工業工程與管理學系/碩士(2006年)

摘要

現今激烈競爭的環境，資訊科技的迅速發展和產品的推陳出新，企業對內要求高品質、低成本和高效率之外；對外更需開拓市場佔有率與尋求企業間的協同合作夥伴，以達整體營運成本的降低和提升企業競爭力，因此企業也正面臨全球化的競爭與挑戰。市場上產品需求預測的準確性與時效性對於企業於經營管理上扮演著重要的角色。把握先機成為市場上的領導者，是企業領導者所追求的目標。因此管理者必須要盡心擬定最佳策略以面對複雜的市場競爭。預測具有展望未來的能力，即成為企業能增加利潤與增強市場競爭優勢的不二法門。
製造業全球化的今日，競爭激烈的企業環境中，企業中的每一環節更顯重要。本研究擬針對提供一套較為精準且快速的預測方法，以供企業能有效預測其於市場上的供給與需求。本研究提供為一於協同規劃、預測與補貨(Collaborative Planning Forecasting and Replenishment, CPFR)模式下針對製造商與零售商之間彼此協同規劃與預測其市場銷售的變化，以快速的提供貨品予顧客進而提升顧客滿意度。本研究主要整合倒傳遞網路 (Back-propagation Network)與灰預測 模型如此來建立一預測模型。藉此能讓製造商與零售商間可有效預測未來的市場趨勢以做因應。

關鍵字

協同規劃、預測與補貨，倒傳遞神經網路，灰預測

並列摘要

Nowadays the environment of keen competition, the rapid development of in-formation technology and the weeding out the old and bringing forth the new of products result in enterprises face one is internal departments have to request high quality, low cost and high efficiency, and another is about external surroundings we must to open up our market share and seek the partners among enterprises to collabo-rate. Doing this in order to reduce the whole operating cost and raise the enterprises core competency. Thus, business is facing the global competition and challenge, too.
The accurate and timely forecast for the products demand in market is playing an important role in business management. Business administrator looks for the goal holding the first chance to be a leader on market. So administrator must draft the best tactics conscientiously in order to deal with the complicated competition on market. Forecast has the ability to look into the future and it becomes the tool that helps en-terprises increase profits and strengthen the competitive advantage.
Now the manufacturing industry globalizes and in the keen competition enter-prises surroundings, the each function of business is more important. This research developed a more correct and faster the forecast method in order to provide enter-prises could predict their supply and demand on market effectively. This research of-fered a Collaborative Planning Forecasting and Replenishment (CPFR) model to manufacturers and retailers collaborate for each other and predict the change of sales on market in order to supply products for customers rapidly and raise customer satis-faction. This research integrated back-propagation network (BPN) and grey prediction model to establish a forecast model. Make the manufacturers and retailers can forecast the market trend in the future to response the market changes.

並列關鍵字

Collaborative Planning Forecasting and Replenishment (CPFR),

參考文獻

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