臺灣博碩士論文加值系統

運輸問題是作業研究領域中常見的問題，指派問題則是運輸問題的特例。一般均利用線性規劃或其他特殊解法，求得問題的最適解，即使用最少資源，得到最大利潤。運輸和指派問題的求解已有許多相關的研究(Reeb, 2002)(董振寧，2004)，但大部份的研究均只考慮一項資源或因素。僅有少部分研究同時考慮兩項以上之因素(薄喬萍，2006)，而現有之方法(Liang, 2008), 在求解時多半過於複雜，不符合實際需求。
現實生活中，運輸問題常需同時考慮許多資源或因素，而上述研究在計算時過於複雜。為改善這項缺點，本研究結合了資料包絡分析(Data Envelopment Analysis, DEA)和線性規劃(Liner Programming, LP)等技術，提出三種解決多目標運輸問題的方法：(1)修改薄喬萍法(MBM)：薄喬萍(2006)的方法係利用線性規劃解決多目標指派問題，本研究將該方法加以修正，使其能解決多目標運輸問題(2)直覺法(HEU)：本研究證明，將個別單一目標運輸問題之最適解，加權相加後，仍符合原運輸問題之限制條件(3)應用資料包絡分析法(DEA)。利用一組隨機產生的數據，以Microsoft Excel進行計算，分別比較三種方法在解決多目標運輸問題時之優劣。
研究結果顯示，當需要解決同時考慮許多資源或因素的運輸問題時，本研究所提出之方法，能有效解決此多目標運輸問題。比起現有研究，本研究所提出之方法，執行步驟相對簡單、易懂，具實用參考價值，可提供管理者在實務應用中作為一參考方法。

Transportation and assignment problem are common problems in operation research. Using liner programming, optimal solution that spend least resource and obtain most revenue can be found. Most of the studies just focus on solving the single-objective problem, only some of them try to solve the multi-objective transportation problem. Moreover, the existing technologies in solving multi-objective transportation problem are so complex that makes the model almost unrealistic.
In real world, many factors and/or resources must be considered simultaneously in solving the transportation problem. Unfortunately, the existing technologies are too complex to use. This study proposes new approaches that combine DEA and linear programming. Three methods that are easy to understand and easy to use in real world are proposed in this study: (1) modified Bao’s method (MBM), (2) the heuristic method (HEU), and (3) the DEA method (DEA). Random data are used to illustrate the proposed methods.
The results show that the proposed methods can solve the multi-objective transportation problem with simple and easy processes. Especially the DEA method, it does not need decision maker or manager to decide the weights. Through DEA, became we are able to decide the objective weight of each datum; it is convenient for decision makers or manager in real world for possible application.

1.Introduction 1
1.1 Research Background and Motivation 1
1.2 Research Objective 2
1.3 Organization of This Thesis 2
2.Literature Review 4
2.1 Transportation and Assignment Problem 4
2.2 Linear Programming 6
2.3 Multi-Objective Problem 7
2.4 Data Envelopment Analysis 8
3.Methodology 12
3.1 Modified Bao’s Method 13
3.2 The Heuristic Method 15
3.3 The DEA Method 17
4.Numerical Example 18
4.1 Proposed Methods 20
4.2 Two-Objective Transportation Problem 21
4.3 Multi-Objective Transportation Problem 25
5.Conclusion and Future Research 31
Reference 33
List of Tables
Table 1 Random data for shipping cost 21
Table 2 Random data for shipping time 21
Table 3 The results solved by MBM 22
Table 4 The result solved by HEU 23
Table 5 Total amount of recourse 24
Table 6 Random data for shipping resources 26
Table 7 The results of three methods 27
Table 8 The ratio of three methods 28
List of Figures
Figure 1 Researchprocess 3
Figure 2 Research framework 12
Figure 3 Total cost and time solved by MBM 22
Figure 4 Total cost and time solved by HEU 23
Figure 5 Comparison of three models on total cost 24
Figure 6 Comparison of three models on total time 24
Figure 7 Total amount of resource solved by three methods 25
Figure 8 The diagram of curves for three methods 28
Figure 9 Total resources of three methods 29

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