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研究生:徐國慶
研究生(外文):Kuo-Ching Shu
論文名稱:構建決策支援系統模擬物流派車策略之研究:以王屋科技為例
論文名稱(外文):Simulation Analysis of Vehicle Dispatching Strategies Using Decision Support Models: A Case Study of Wang-House
指導教授:韓復華韓復華引用關係
指導教授(外文):Anthony Fu-Wha Han
學位類別:碩士
校院名稱:國立交通大學
系所名稱:運輸科技與管理學系
學門:運輸服務學門
學類:運輸管理學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:86
中文關鍵詞:供應鏈管理物流派送策略蒙地卡羅模擬
外文關鍵詞:Supply Chain ManagementLogisticsDispatching StrategyMonte Carlo Simulation
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近年來由於全球化的競爭日趨明顯,許多企業皆把全球化佈局列為企業發展重點,並積極改善整個企業流程相關的成本。企業的供應鏈包括產品設計、採購、倉儲、生產、運輸配送、行銷及售後服務等,如何在滿足顧客需求的前提下,以最低的成本,將產品有效率地配送至顧客的運輸問題是供應鏈中一個重要的課題。有鑑於運輸配送對於供應鏈的重要性,本研究以一個案公司為實例對象,針對物流系統中貨物配送的時機與配送路線的最佳化為目標來設計一套決策支援系統(DSS),並利用現有的資料來模擬訂單的發生,用以測試本研究所設計的配送策略的績效,包括配送的運輸成本與服務水準。
本研究的個案對象為王屋科技公司,主要的產品為燈俱用的變壓器,其位於廣東省珠江三角洲內,因河川眾多,收費站林立,致使運輸配送成本高居不下。本研究針對物流配送的議題,設計一套決策支援系統,包括四項模組:人機界面模組、派車排程決策模組、車輛路線決策模組與資料庫模組。其中,派車排程決策模組是用來決定各訂單的派車交貨日期;車輛路線決策模組是用來計算派車的最短路徑。
本研究以蒙地卡羅演算法來模擬訂單的發生,並以延遲(Postponement)的概念設計三項派車策略:併裝(Consolidation)、延遲(Postponement, 90%)與快速回應(Quick Responsive),之後再以之前所設計的DSS模組來模擬求解這三項策略的績效,並分析其在成本與服務水準的得失(trade off)變化。
模擬分析後發現:Œ快速回應的策略有最好的回應能力,服務水準最高,但是因為配送次數頻繁,所以造成其運輸成本最高;併裝的策略也就是完全延遲的策略有最低的運輸成本,因為此策略的重點為降低配送次數、增加承載率,但是其服務水準為最低:Ž延遲加上一經濟配送容量限制的策略的績效介於上述兩者中間。在需求小時,延遲策略會降低配送次數,使得運輸成本下降;在需求大時,延遲策略會適當的提前配送,使得服務水準增加。
與現況作比較時,採用延遲(90%)的策略可降低運輸成本61%,將使運輸成本由佔總成本的8%降至3.2%。

This research attempts to design the logistic dispatching strategies of supply chain, and discusses the trade-off between the transportation cost and the level of service. The analytical framework of this research is based on the decision support system and Monte Carlo simulation. In this thesis, we take Wang-House as the case for our study. This company’s main products are the transformer of lamps and lanterns. The half of it’s customers locate in China, and the others locate in Europe and America. It faces a problem of high transportation cost in China.
First, we construct a decision support system (DSS). The DSS includes four main models: dialog interface/system control model, dispatching scheduling decision model, vehicle routing decision model and database management model. The dispatching scheduling decision model is to determine the dispatching date of each order. And the vehicle routing decision model is to determine the shortest path of dispatching.
Second, we use the Monte Carlo simulation to simulate the real orders, and take advantage of these orders to test the performance of our dispatching strategies.
Third, we use the concept of postponement to design three dispatching strategies: consolidation, postponement (90%) and quick response. After we have the simulate orders and making strategies, we can use the DSS models to test the results of different strategies.
Finally, through the simulate tests, we have conclusions: 1.For the quick response strategy, it has the highest level of service. But it also has the highest transportation cost because the high frequency dispatching. 2.For the consolidation strategy, it has the lowest transportation cost, but it also has the lowest level of service. 3.For the postponement (90%) strategy, the results of this strategy are between quick response and consolidation. When the demands are low, this strategy can lower the transportation cost by reducing the dispatching frequency. When the demands are high, this strategy will dispatch in advance to increase the level of service.
And the postponement (90%) strategy can reduce the transportation cost from 8% to 3.2%.

中文摘要..................................................Ⅰ
英文摘要..................................................Ⅱ
目錄......................................................III
表目錄....................................................V
圖目錄....................................................VI
第一章 緒論..............................................1
1.1 問題背景概述........................................1
1.2 研究動機與目的......................................2
1.3 研究架構與內容......................................2
1.4 研究方法與流程......................................4
第二章 文獻回顧..........................................7
2.1 物流與供應鏈管理....................................7
2.1.1 供應鏈管理的起源................................7
2.1.2 供應鏈管理的定義................................10
2.1.3 供應鏈相關理論與原則............................11
2.2 決策支援系統在物流配送上之應用......................15
2.2.1 資料庫管理模組..................................16
2.2.2 模式庫管理模組..................................16
2.2.3 人機交談界面/系統控制模組.......................16
2.3 數學分析模式在物流配送上的應用......................17
第三章 個案分析與DSS功能架構.............................19
3.1 王屋科技個案現況與問題分析..........................19
3.1.1產業概況與公司簡介...............................19
3.1.2王屋科技供應鏈現況分析...........................22
3.1.3 王屋科技問題分析................................28
3.2 DSS之功能架構與流程.................................29
3.3 資料庫/模式庫/使用者介面之設計......................29
3.2.1 資料庫子系統之功能規劃與設計....................29
3.2.2 模式庫子系統之功能規劃與設計....................30
3.2.3 系統控制與人機界面之功能規劃與設計..............32
第四章 DSS資料庫之建立....................................34
4.1 配送道路地圖資料蒐集與道路實況調查..................34
4.1.1 配送道路地圖資料蒐集與整理......................34
4.1.2 王屋科技路網結構分析............................35
4.1.3 王屋科技運輸相關成本分析........................37
4.2 配送道路資料庫檔案建立..............................38
4.3 客戶訂單資料庫檔案格式..............................38
第五章 個案模式庫之建立...................................40
5.1 排程決策模組........................................40
5.1.1 王屋科技作業流程分析............................40
5.1.2 貨物排程模組規劃設計與流程......................41
5.2 路線決策模組........................................42
5.2.1 路線決策模組求解步驟與方法......................42
5.2.2 配送路線結果....................................43
第六章 物流派車策略模擬分析...............................46
6.1 需求訂單序列的產生..................................46
6.2 派車策略分析........................................56
6.3 模擬輸出項目........................................57
6.4 模擬結果分析........................................59
6.4.1 承載率分析......................................59
6.4.2 運輸成本分析....................................60
6.4.3 遲交訂單比率分析................................62
6.4.4 服務水準分析....................................63
6.4.5 配送次數分析....................................65
6.4.6 交貨時間分析....................................66
6.5 敏感度分析..........................................68
6.6 小結................................................72
第七章 結論與建議.........................................74
參考文獻..................................................76

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