考慮多模式專案排程下資源撫平之研究

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姓名

林昭凱(Jhao-Kai Lin) 查詢紙本館藏

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工業管理研究所

論文名稱

考慮多模式專案排程下資源撫平之研究
(Resource Leveling in Multi-Mode Project Scheduling)

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摘要(中)

資源撫平(Resource Leveling)問題自從資源限制專案排程(Resource Constrained Project Scheduling Problem,RCPSP)發展以來就一直倍受重視，有許多的相關研究在解決這方面的問題。可是現有的資源撫平問題，都著眼在單一模式資源限制專案排程(Single-mode Resource Constrained Project Scheduling Problem,SRCPSP)上，在現實事件的專案中，單一模式的專案非常少見。而另依方面，再現有的多模式資源限制專案排程問題中，亦未見到相關資源撫平的文獻出現，因此本篇論文希望能將資源撫平的問題拓展於多模式資源限制專案排程問題(Multi-mode Resource Constrained Project Scheduling Problem,MRCPSP)之上。
本研究以資源撫平為目標，利用遺傳演算法同時進行作業模式(Mode)的選擇以及排程的結果。此外，利用遺傳演算中適應函數(fitness function)的調整，使得此演算法可以依照管理者不同需求而去調整適應函數以達到預期中希望達到的目標。

摘要(英)

The fluctuation of required resources causes problem cause problem in project scheduling. Thus research developed resource leveling techniques to minimize the deviation between the resource requirement and the desired resourced profile. However, the resource leveling problem, can not be considered with Multi-mode Resource-Constrained Problem (MRCPSP), that is an activity can be preformed in one or more combinations of durations and resource requirements.
In this paper, we consider resource leveling in Multi-mode Project Scheduling. We describe a Genetic Algorithm for this problem. The proposed algorithm can effectibly provide the near-optimal solution for different situation and fit the goal that is project manager wanted.

關鍵字(中)

★ 專案排程
★ 資源撫平
★ 多模式資源限制專案排程問題
★ 遺傳演算法

關鍵字(英)

★ Resource leveling
★ Multi-Mode Resource Schedulin

論文目次

Abstract II
致謝 III
目錄 IV
表目錄 VI
圖目錄 VII
第 1 章緒論 1
1.1 研究背景 1
1.2 研究動機 2
1.3 研究目的 3
1.4 研究流程 5
第 2 章文獻探討 6
2.1 資源撫平的相關文獻探討 6
2.2 多模式資源線至專案排程問題的相關文獻探討 11
2.3 遺傳演算法文獻探討 14
2.3.1 編碼(encoding) 16
2.3.2 適應函數(fitness function) 16
2.3.3 選擇( selection ) 16
2.3.4 交配( Crossover ) 18
2.3.5 突變(Mutation) 20
2.3.6 收斂( convergence) 20
2.3.7 停止條件(Terminate Condition) 20
第 3 章模式架構建立 22
3.1 問題描述 22
3.2 數學模式建立 23
3.3 演算法設計 27
3.3.1 編碼方式： 27
3.3.2 起始解 29
3.3.3 交配 30
3.3.4 突變 30
3.3.5 選擇及適應函數 30
第 4 章實例驗證 33
4.1 案例產生 33
4.2 數據分析 35
4.2.1 實驗環境 35
4.2.2 實驗設計 36
4.2.3 數據分析 37
4.2.4 求解時間分析 42
4.2.5 解的改善 44
第 5 章結論與未來研究方向 46
參考文獻 47
附錄A 52
附錄B 56

參考文獻

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指導教授

曾清枝(Ching-Chih Tseng)

審核日期

2004-7-6

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