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研究生:巫安杰
研究生(外文):An-jie Wu
論文名稱:在不確定的環境下針對以下多目標: 最佳時間、成本和可靠度進行專案管理的研究
論文名稱(外文):Project Management for Uncertainty with Multiple Objectives Optimization of Time, Cost and Reliability
指導教授:蔣安國蔣安國引用關係
口試委員:黃宗立李維平
口試日期:2014-06-25
學位類別:碩士
校院名稱:逢甲大學
系所名稱:工業工程與系統管理學系
學門:工程學門
學類:工業工程學類
論文種類:學術論文
論文出版年:2014
畢業學年度:102
語文別:英文
論文頁數:67
中文關鍵詞:專案排程多目標最佳化學習率不確定性反應曲面法折衷規劃法
外文關鍵詞:Project schedulingUncertaintyMulti-objective optimizationResponse surface methodologyLearning effectCompromise programming
相關次數:
  • 被引用被引用:0
  • 點閱點閱:206
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:1
This research uses an approach that uses a computer simulation and statistical analysis of uncertain activity time, activity cost, due day, and project budget to address quality and the learning process in regard to project scheduling. Since the learning process affects the a scheduling problem, a Cobb-Douglas multiplicative power model is used to represent the relationship between the dependent variable which is the standard deviation of activity time and the independent variable which is the cumulative trials and the mean of activity time. Thus, the power model can be used to predict the mean value and standard deviation of activity time as trials increased. The mean value and standard deviation are further used to randomly generate activity times for project scheduling analysis. Response surface methodology RSM is used to develop a rationale of the time-cost trade-off problem. The controllable variable in RSM is the mean of activity time. Since the optimal solutions found with RSM are solutions optimized only for a single objective, multiple objectives for further optimization become necessitated with limited project budget, restricted completion time, allowable total cost probability, and acceptable completion time probability having to be considered simultaneously under the learning effect. With response functions from RSM, compromise programming is adopted to formulate the proposed project scheduling problem for multi-objective optimization. The results show that the presented approach provides an efficient and practical means of finding a robust and optimal scheduling process for project scheduling problems.
指導教授與評審委員簽名之考試合格證明書 i
博碩士紙本論文著作權授權書 ii
Abstract 5
1. Introduction 6
2. Learning Curves for Quality and Productivity 11
3. Activity Time, Activity Cost, Project Completion Time, Project Total Cost, Completion Time Probability, and Total Cost Probability 15
4. Robust Design via Experimental Design Approach 18
5. Model development 22
5.1 Generating Experimental Data for RSM Analysis 22
6. The Application 27
6.1-Case 1: Project scheduling without the learning effect. 29
6.2-Case 2: Project scheduling with the learning effect. 54
7. Conclusion 57
References 58
Appendix A. Experimental Design Matrix of Box-Behnken Design 65
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