研究生: |
陳泯璋 Ming-Chang Chen |
---|---|
論文名稱: |
以類神經網路結合多代理人系統運用在生產規劃與存貨監控之個案研究 A Case Study on Applying Neural Networks and Multi-Agent Systems to Production Planning and Inventory Monitoring |
指導教授: |
蘇豐文
Von-Wun Soo |
口試委員: | |
學位類別: |
碩士 Master |
系所名稱: |
電機資訊學院 - 資訊系統與應用研究所 Institute of Information Systems and Applications |
論文出版年: | 2008 |
畢業學年度: | 96 |
語文別: | 中文 |
論文頁數: | 56 |
中文關鍵詞: | 多代理人 、類神經網路 、生產策略 |
外文關鍵詞: | multi-agent, neural network, production strategy |
相關次數: | 點閱:1 下載:0 |
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在現今的商業環境競爭愈來愈激烈,企業的既定生產策略常常受到不確定因
素的影響而需要作修正,例如銷售量不如預期、消費者需求改變等因素。因此如
何快速因應環境的變化而修正既定的生產策略便突顯的相當重要。
本研究在探討如何運用多代理人在生產規劃與庫存管控並以造紙業為例。傳
統的造紙業生產模式由於各部門之間的資訊並沒有彼此傳遞,其生產量仍以過去
的經驗判斷為主,各部門之間缺乏一套整合的工具導致生產變異居高不下。為了
改善此問題,本研究運用代理人傳遞與溝通訊息的功能並輔以類神經網路預測,
使各部門之間的資訊系統能達到整合,進而在生產策略能做更有效率的決策。
本研究首先會進行系統分析獲得需求,在設計階段會開始規劃代理人的類別與功
能。最後在實驗階段會以從案例公司獲得的實際資料,套入代理人程式當中並輔
以類神經預測軟體進行實驗與比較分析結果。
It is more and more competitive in modern commercial environment; the enterprises often adjust their production plans because of uncertain factors. For example, the sales fall short of their expectations, the demand of consumers change, etc. Therefore, it is very important to the enterprises to rapidly adjust their production strategy caused by the changes of extrinsic environment.
This research treats of how to employ the agents on production planning and inventory monitor, and takes the paper manufacturing industry as an example. There is little cooperation among each department in the traditional paper manufacturing industry. Therefore, the production plans still depend on historical experiences. There is high variance of production because of its lack of integrated tools among each department. In order to improve this problem, the agent-based system which can integrate information is developed by neural network in this research. It can integrate information among each department and support more efficient decision-making.
In this research, the system analysis is processed to get requirements at first, and capture the collaboration requirements among the various functions of planning, the categories and functions of agents are created in the designed stage. Finally, in the executive stage, the real data got from case enterprise are used to make an experiment.
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