淡江大學覺生紀念圖書館 (TKU Library)
進階搜尋


下載電子全文限經由淡江IP使用) 
系統識別號 U0002-2701201603023100
中文論文名稱 以多代理人模擬施工團隊合作效率之研究
英文論文名稱 Multi-Agent-based Project Team Collaboration Behavior Simulation
校院名稱 淡江大學
系所名稱(中) 土木工程學系碩士班
系所名稱(英) Department of Civil Engineering
學年度 104
學期 1
出版年 105
研究生中文姓名 黃献仁
研究生英文姓名 Sian-Ren Huang
電子信箱 fertilizer113@gmail.com
學號 602380478
學位類別 碩士
語文別 中文
口試日期 2016-01-12
論文頁數 87頁
口試委員 指導教授-蔡明修
委員-葉怡成
委員-林建良
中文關鍵字 溝通  團隊合作  流程效率  代理人模擬  社會網絡 
英文關鍵字 Communication  teamwork  process efficiency  Agent-based modeling  social networks 
學科別分類 學科別應用科學土木工程及建築
中文摘要 團隊合作效率的分析是專案管理之重要議題,然而多數學者大多從質化分析的角度進行探討,若能利用電腦模擬進行實驗測試以量化量的方式,相信將能觀察到更細微之現象與結果。為此,本研究結合「社會網絡(Social Network)」及「代理人模擬(Agent-based Simulation)」之理論,利用多代理人模擬工具,建立團隊合作流程效率模擬程式Project Team Collaboration Efficiency Simulator,(PTCES)」。藉以透過模擬的方式,提供專案管理人員針對團隊組織成員的合作網絡(collaborative network)與作業流程進行模擬試驗,找出流程與溝通的瓶頸,從而幫助設計專案團隊。
其次,本研究以一實際建築工程案例進行模擬驗證以及參數校正,並透過多種模型檢核方法測試,證實本研究模擬程式(PTCES)之輸出數據具備相當程度的精確度及有效性。最後,本研究以三種不同鏈結程度之溝通網絡結構設計劇情模擬方案,並應用模擬程式(PTCES)進行模擬實驗。經分析比較後發現該建築工程專案之網絡結構,在只考慮溝通鏈結數的前提下,應追求局部完全網絡狀態即可達到一定程度的效率提升。
英文摘要 Bigger the project size is; more professionals would be involved in the project team. The communications among professional members during the entire project lifecycle is the key to project success (Gould & Joyce 2013). Many essential researches (EmpyGiri et al. 2014, Labarbe & Thiel 2014, Yin et al. 2012, Easley et al. 2003) have been proposed to increasing the collaborative efficiency of project team members. Due to the dynamic and complex natures of projects, many factor-based evaluation models have been addressed to predict or to measure the efficiency of project team members, but the simulation models. Traditional modeling approaches treat a company’s employees, projects, products, customers, and partners as either aggregated averaged quantities or as passive entities or resources in a process; for example, in the discrete-event simulation approach, the project team is treated as a number of processes. Although these approaches can capture organizational dynamics and non-linearity, they ignore the fact that all those people, products, projects, pieces of equipment, assets, etc., are all different and have their own histories, intentions, desires, individual properties, and complex relationships. The agent-based approach is free of such limitations as it suggests that the modeler directly focus on individual objects in and around the organization, their individual behaviors, and their interactions. The agent based model is actually a set of interacting active objects that reflect objects and relationships in the real world and thus is a natural step forward in understanding and managing the complexity of big projects (Anon n.d.). This research is aimed at developing an agent-based project collaboration efficiency simulation model to be an experimental tool for aiding project team design
論文目次 目錄
摘要 I
Abstract II
目錄 III
圖目錄 V
表目錄 VII
1. 緒論 1
1.1 研究動機 1
1.2 研究目的 3
1.3 研究流程與方法 4
2. 文獻回顧 10
2.1 專案團隊數值模擬 10
2.1.1 數值模擬方法 10
2.1.2 虛擬團隊模式Virtual Design Team 12
2.2 代理人建模理論 16
2.2.1 代理人建模(Agent Based Modeling and Simulation,ABMS) 16
2.2.2 模型檢核與驗證方法 19
2.3 NETLOGO多代理人系統 21
2.4 社會網絡理論 22
3. 模擬系統建構 25
3.1 問題陳述 25
3.2 研究假設 27
3.3 模擬系統運作概念 27
3.4 輸入資料建置程式 28
3.4.1 輸入資料建置程式介面設計 29
3.4.2 輸入資料建置程式功能展示 29
3.5 模擬程式設計 34
3.5.1 模擬程式輸出 35
3.5.2 模型主要變數 36
3.5.3 模擬程式主要演算法 38
3.5.4 代理人模型 42
3.5.5 模擬程式執行流程: 45
3.6 模擬程式執行流程演示 46
4. 案例分析與討論 50
4.1 案例資料建立 50
4.1.1 案例說明 50
4.1.2 案例資料蒐集 51
4.1.3 建立輸入資料模型 51
4.2 案例模擬與參數校正 57
4.2.1 參數校正 57
4.2.2 案例模擬結果分析 59
4.3 模型檢核與驗證 61
4.3.1 數據離散程度(Discrete Degree): 62
4.3.2 假設檢定(Statistical Hypothesis Testing): 63
4.3.3 以歷史數據判斷有效性(Historical Data Validation): 65
4.3.4 預測驗證(Predictive validation) 66
4.3.5 參數變化敏感性分析 (Parameter Variability - Sensitivity Analysis) 70
4.4 劇情模擬分析 74
5. 結論與建議 78
5.1 結論 78
5.2 建議 79
參考文獻 80
附件 84
附件A 84
附件B 86



圖目錄
圖1.1 研究流程與方法 4
圖2.1 作業執行行為模式 (資料來源: Levitt,1996) 15
圖2.2社會網絡分析工具UCINET 6 24
圖2.3 網絡圖繪製工具NetDraw 24
圖3.1 研究概念圖 26
圖3.2 模擬系統運作概念 28
圖3.3 輸入資料建置程式功能架構 29
圖3.4 基本數據建置頁面 30
圖3.5 基礎資訊/技能清單建置畫面 30
圖3.6 基礎成員清單建置畫面 31
圖3.7 基礎作業項目清單建置畫面 31
圖3.8 人員資料編輯頁面 32
圖3.9 流程資料編輯頁面 33
圖3.10 溝通網絡矩陣輸入頁面 33
圖3.11 預覽頁面 34
圖3.12 多代理人作業執行演算法 40
圖3.13 資訊/技能合作學習網絡演算法 41
圖3.14 網絡溝通擴張演算法 42
圖3.15 代理人系統類別圖 44
圖3.16 模擬程式執行流程圖 45
圖3.17 模擬程式初始畫面 46
圖3.18 參數設定畫面 47
圖3.19 建置(SETUP)畫面 48
圖3.20 模擬運行結束畫面 49
圖3.21 輸出檔案擷取畫面 49
圖4.1 案例專案流程網圖 53
圖4.2 專案排程甘特圖 53
圖4.3案例團隊組織架構圖 55
圖4.4正式網絡分布圖 55
圖4.5 初始網絡分布圖 56
圖4.6 溝通網絡矩陣圖 56
圖4.7 案例模擬溝通比率網絡分布圖 61
圖4.8 Ec參數變化影響圖 72
圖4.9 PD參數變化影響圖 73
圖4.10 單純組織架構網絡分布圖 75
圖4.11 局部完全網絡分布圖 75
圖4.12 完全網絡狀態分布圖 75


表目錄
表1.1作業基本資料表(部分) 7
表1.2人員基本資料表(部分) 7
表2.1 近年採用VDT之相關研究議題 13
表2.2代理人建模相關文獻 17
表2.3 NetLogo特性與語法特點 21
表2.4 近年應用NetLogo之相關研究 22
表4.1 作業基本資料表(部分) 52
表4.2 人員基本資料表(部分) 54
表4.3 校正後模擬結果彙整表 58
表4.4 案例模擬與實際值比較表 58
表4.5 模擬各作業溝通比率彙整表 60
表4.6 離散程度測定指標計算表 63
表4.7 T檢驗分析結果判斷表 64
表4.8 案例各樓層施工網圖歷史資料表 65
表4.9 各樓層模擬結果與實際值比較表 66
表4.10 問題一實驗結果比較表(ave- Ec=0.78) 68
表4.11 問題二實驗結果比較表(ave- Ec=0.78) 68
表4.12 模擬參數敏感度分析組合表 70
表4.13 參數影響曲線(Ec)平均斜率表 72
表4.14 參數影響曲線(PD)平均斜率表 73
表4.15 劇情模擬結果比較表 76

參考文獻 參考文獻
中文部分
1. 王思峰、劉麗萍 (2007),「虛擬社群中誰比較可信任」,中華心理學刊,第49卷,第1期,第1-17頁。
2. 江品瑩. "以多重代理人為基礎之輕軌列車運行調度模擬模式研究." 淡江大學運輸管理學系碩士班學位論文 (2013): 1-160.
3. 吳東霖. "代理人基政治預測市場: 群聚效果與資訊擴散." 淡江大學產業經濟學系碩士班學位論文 (2011): 1-25.
4. 柯景祥, and 簡榮宏. 基於 Maxband 模型之連鎖交通號誌改善策略. Diss. 2013.
5. 洪傑霖. "預測市場與投票模型: 代理人基建模的應用." 淡江大學產業經濟學系碩士班學位論文 (2013): 1-33.
6. 徐瑋呈, and 李蔡彥. "具社會網絡模型的人群行為模擬."
7. 張火燦、劉淑寧,社會網路理論探討員工知識分享,人力資源管理學報,2(3),101-113,2002
8. 梁嘉展. "社群網路中朋友互動之模擬模型與分析研究." 臺北科技大學電機工程系所學位論文 (2013): 1-59.
9. 許麗玲,網路學習創新擴散模式建構之研究,碩士論文,2009
10. 陳信文,應用代理人模擬於即時決策系統之研究,碩士論文,國防大學中正理工學院,2008
11. 趙偉銘, and 李蔡彥. "以社會傳播模型模擬人群之集體社會行為."
12. 鄭介旗. "緊急組織協調應變效能研究." 成功大學土木工程學系學位論文 (2014): 1-115.
13. 鄭景文(2002),網絡核心性、吸收能力對部門創新與績效之影響-以航運業為例。國立海洋大學航運管理學系未出版碩士論文,基隆市。
14. 鍾濟宇. "建立以個體為基礎模型 (ABMs) 模擬急診室壅塞." 元智大學資訊管理學系學位論文 (2013): 1-89.
15. 羅嘉德、朱慶忠,2004,人際網絡結構因素對工作滿足之影響,中山管理評論2004 年十二月號. 第十二卷第四期pp.795-823.

英文部分

1. Anon, Agent Based Modeling — AnyLogic Simulation Software. anylogic.com. Available at: http://www.anylogic.com/agent-based-modeling [Accessed July 15, 2015].
2. Burton, R. M. and Obel, B., “The Validity of Computational Models in Organization Science: from Model Realism to Purpose of Model”,Computational and MathematicalOrganization Theory, 1(1), 57-71, 1995.
3. Carley, K. M. and Lin, Z., “A Theoretical Study of Organizational Performance under Information Distortion”, Management Science, 43(7), 976-997, 1997.
4. Carroll, T. and Burton, R. M., ―Organizations and Complexity: Searching for the Edge of Chaos,” Computational and Mathematical Organization Theory”, 6, 319–337, 2000.
5. Dorigo, M., Gambardella, L. M., Birattari, M., Martinoli, A., Poli, R., and Stützle, T., Ant Colony Optimization And Swarm Intelligence, Springer, 2005.
6. Easley, R.F., Devaraj, S. & Crant, J.M., Relating Collaborative Technology Use to Teamwork Quality and Performance: An Empirical Analysis. Journal of Management Information Systems, 19(4). 2003.
7. Giannakis, Mihalis, and Michalis Louis. "A multi-agent based framework for supply chain risk management." Journal of Purchasing and Supply Management 17.1 (2011): 23-31.
8. Gould, F. & Joyce, N., Construction Project Management, Pearson Higher Ed. 2013.
9. Horri, T., Jin, Y. and Levitt, R. E., “Modeling and Analyzing Cultural Influences onProject Team Performance”, Computational and Mathematical Organization Theory, 10(4), 305-321, 2005.
http://www.casos.cs.cmu.edu/publications/papers/Or (assessed, 2011.08).
10. J. C. Kunz, T. R. Christiansen, G. P. Cohen, Y. Jin, and R. E. Levitt, “The virtual design team,” Communications of the ACM, vol. 41, no. 11, pp. 84–91, 1998.
11. J. Son and E. M. Rojas, “Evolution of Collaboration in Temporary Project Teams: An Agent-Based Modeling and Simulation Approach,” vol. 137, no. 8, pp. 619–628, Aug. 2011.
12. J. Thomsen, M. A. Fischer, and R. E. Levitt, “The Virtual Team Alliance (VTA): An extended theory of coordination in concurrent product development projects,” 1998.
13. Jesen, K. W., Hakonsson, D. D., Burton, R. M. and Obel, B., “The Effect of Virtualityon the Functioning of Centralized versus Decentralized Structures: An Information Processing View”, Computational and Mathematical Organization Theory, 16, pp144-170, 2010.
14. Jesen, K. W., Hakonsson, D. D., Burton, R. M. and Obel, B., ―”The Effect of Virtuality on the Functioning of Centralized versus Decentralized Structures: An Information Processing View”, Computational and Mathematical Organization Theory, 16, pp144-170, 2010.
15. Jin, Y., Levitt, R.E. “The Virtual Design Team: A Computational Model of Project Organizations.” J. Comput. Math. Organ. Theory, Vol. 2, No. 3, pp.171-195, 1996.
16. Jin, Y., Levitt, R.E., Christiansen, T.R., Kunz, J.C., “The Virtual Design Team:Modeling organizational behavior of concurrent design teams.” Artificial Intelligence for Engineering Design, Analysis and anufacturing, Vol. 9, pp.145-158, 1995.
17. Kim, J. and Burton, R. M., “The Effect of Task Uncertainty and Decentralization onProject Team Performance”, Computational and Mathematical Organization Theory, 8,365-384, 2002.
18. Labarbe, E. & Thiel, D., Information Sharing to Reduce Misperceptions of Interactions Among Complementary Projects: A Multi-Agent Approach. Journal of Artificial Societies and Social …. 2014.
19. Laumann, E., Galaskiewicz, J., and Marsden, P., (1978), “Community Structure as Interorganizational Linkages,” Annual Review of Sociology, Vol.4, No. 1, pp. 455-484.
20. Liben‐Nowell, David, and Jon Kleinberg. "The link‐prediction problem for social networks." Journal of the American society for information science and technology 58.7 (2007): 1019-1031.
21. Lin, Z. and Carley, K. M. ―”Organizational Design and Adaptation in Response toCrises: Theory and Practice”, Unpublished Paper, 2002
22. Lin, Z. and Carley, K. M., Designing Stress Resistant Organizations: Computational Theorizing and Crisis Applications, Kluwer. Boston, MA, 2003.
23. Luke, Sean. "Multiagent simulation and the MASON library." George Mason University, (2011).
24. Macal, Charles M., and Michael J. North. "Tutorial on agent-based modeling and simulation." Proceedings of the 37th conference on Winter simulation. Winter Simulation Conference, 2005.
25. Niazi, Muaz, and Amir Hussain. "Agent-based tools for modeling and simulation of self-organization in peer-to-peer, ad hoc, and other complex networks." Communications Magazine, IEEE 47.3 (2009): 166-173.
26. Pryke, S., SNA in project organisations. In pp. 1–22. 2014.
27. R. E. Levitt and M. E. Nissen, “The Virtual Design Team (VDT): a multi-agent analysis framework for designing project organizations,” pp. 115–120, 2003.
28. R. E. Levitt, “The Virtual Design Team: Designing Project Organizations as Engineers Design Bridges,” JOD, vol. 1, no. 2, Aug. 2012.
29. R. E. Levitt, J. Thomsen, T. R. Christiansen, J. C. Kunz, Y. Jin, and C. Nass, “Simulating project work processes and organizations: Toward a micro-contingency theory of organizational design,” Management Science, vol. 45, no. 11, pp. 1479–1495, 1999.
30. R. Sun, “Introduction to computational cognitive modeling,” Cambridge handbook of computational, 2008.
31. Sargent, Robert G. "Verification and validation of simulation models." Proceedings of the 37th conference on Winter simulation. winter simulation conference, 2005.
32. T. R. Christiansen, “Modeling efficiency and effectiveness of coordination in engineering design teams: VDT-the Virtual Design Team,” Stanford University, Palo Alto, CA., 1993.
33. Taboada, Manel, et al. "An agent-based decision support system for hospitals emergency departments." Procedia Computer Science 4 (2011): 1870-1879.
34. Tisue, Seth, and Uri Wilensky. "Netlogo: A simple environment for modeling complexity." International conference on complex systems. 2004.
35. Valbuena, Diego, Peter H. Verburg, and Arnold K. Bregt. "A method to define a typology for agent-based analysis in regional land-use research." Agriculture, Ecosystems & Environment 128.1 (2008): 27-36.
36. Vasara, P., Krebs, V., Peuhkuri, L., and Eloranta, E., (2003), “Arachne-Adaptive Network Strategy in a Business Environment,” Computers in Industry, Vol. 50, No. 2, pp. 127-140.
37. Wong, S. S. and Burton, R. M., “Virtual Teams: What are their Characteristics and Impact on Team Performance”, Computational and Mathematical Organization Theory, 6(4), 339-360, 2000.
38. Wooldridge, M. and Jennings, N., “Intelligent Agents: Theory and Practice,” Knowledge Engineering Review, Vol. 10, pp. 115-152, 1995.
39. Xiang, Xiaorong, et al. "Verification and validation of agent-based scientific simulation models." Agent-Directed Simulation Conference. 2005.
40. Xue, Xiaolong, et al. "An agent-based framework for supply chain coordination in construction." Automation in construction 14.3 (2005): 413-430.
41. Yin, Y., Qin, S. & Holland, R., Development of a design performance measurement matrix for improving collaborative design during a design process. International Journal of Production Economics, 60(2), pp.152–184. 2012.
論文使用權限
  • 同意紙本無償授權給館內讀者為學術之目的重製使用,於2016-02-18公開。
  • 同意授權瀏覽/列印電子全文服務,於2016-02-18起公開。


  • 若您有任何疑問,請與我們聯絡!
    圖書館: 請來電 (02)2621-5656 轉 2486 或 來信