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研究生：	蘇世昌 Su, Shin-Chang
論文名稱：	考慮工作流量之工程設施配置模式 A construction site layout model with consideration of working flows
指導教授：	馮重偉 Feng, Chung-Wei
學位類別：	碩士 Master
系所名稱：	工學院 - 土木工程學系 Department of Civil Engineering
論文出版年：	2003
畢業學年度：	91
語文別：	中文
論文頁數：	95
中文關鍵詞：	設施配置、基因演算法
外文關鍵詞：	genetic algorithm, facility layout
相關次數：	點閱：80 下載：4
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施工前的施工規劃往往是影響日後施工效率、以及節省施工成本與人員物力的一項重大因素。良好的設施配置，可以避免施工過程中機具操作與材料運輸的滯殆，不僅縮短設施間的移動成本，更可增加整體施工的生產力而促成專案的成功。故設施配置規劃是施工規劃過程中極為重要的一環。
基於設施配置的重要性，過去有許多相關的研究提出。研究結果卻與實際情形差異頗大而無法配合實際專案需求。主要原因包括（1）設施間關係程度判斷過於主觀，無法兼顧專案施工作業與設施間相互的影響。（2）未考量實際路徑分布情形與工作流量。造成設施配置的過程中，無法考量實際工作流量對於設施位置的影響。（3）設施表示法過於粗略。利用矩形表示設施的不規則形狀易造成無謂空間浪費；忽略出入口位置的設定，使實際配置結果無法考慮設施出入口與路徑關係。（4）無法針對所求出的解答進行權衡分析，過去研究對求解設施配置問題所遭遇設施面積重疊現象，大多採用消除法去除不合理解。常使規劃工程師無法進行權衡分析，不能提供較為彈性之設施配置決策參考。
本研究針對以往研究的瓶頸，並依據實際施工作業需求，利用基因演算法發展工程設施配置模式以協助工程師對工址與施工設施之管理。根據專案中各作業項目與設施間關係，客觀地設定設施間之關係係數。並依據此關係係數兼顧工作流量，求取最佳之設施間路徑分佈。此外，設施的表示法加入了出入口位置的設定以及設施容許有不規則形狀，以求更實際地描述設施狀況。
研究成果顯示，此模式配合以基因演算法為基礎所編寫的電腦程式，不僅能求取符合實際專案需求的最佳設施配置，並且能使規劃工程師能對於所求之解答進行權衡分析，提供更具彈性的決策參考。

An appropriate facility layout not only avoids the conflicts of different operations and reduces costs of moving equipments and delivering materials, but also improves the productivity and quality of the construction project. It is one of most crucial issues for a construction project.
Construction site layout problems have been widely studied by many researches. However, there are still several issues needed to be resolved. These issues are (1) the relationships between facilities are subjectively determined (2) the workflows between facilities are ignored (3) different types of facilities sizes and shapes are not considered (4) the solution are not flexible enough for what-if analysis. Therefore, there is a need to develop a more flexible site layout model for construction site engineers.
This research proposed a site layout model to overcome the above-mentioned issues. First, the relationships between facilities are objectively determined based on project schedule. Then, workflows and routes between facilities are decided by the designed locations of the facilities. In addition, the facilities with irregular shapes are incorporated within the layout model, which makes the facility layout more practical. Furthermore, an elite non-dominated genetic algorithm (ENDGA) based on the Pareto Front approach is developed to solve this newly established model.
A computer implementation coded by Visual Basic is built to provide a practical tool for construction site engineers. This new facility layout model not only provides more realistic solutions for the construction site layout planning, but also let the construction site engineers perform what-if analysis according to solutions on the trade-off curve.

摘要  ……………………………………………………………………………………………I 
Abstract  ………………………………………………………………………………………II
誌謝  ……………………………………………………………………………………………III 
目錄  ……………………………………………………………………………………………IV
圖目錄  …………………………………………………………………………………………VII
表目錄  …………………………………………………………………………………………XII
第一章	緒論   ……………………………………………………………………………1
1	研究背景與動機	 ……………………………………………………………………1
2	研究目的  ……………………………………………………………………………2
3	研究範圍  ……………………………………………………………………………3
4	研究方法與流程	 ……………………………………………………………………3
5	論文架構  ……………………………………………………………………………5
第二章	問題陳述與文獻回顧   …………………………………………………………6
1	研究問題陳述  ………………………………………………………………………6
2	相關文獻探討  ………………………………………………………………………7
3	結論  …………………………………………………………………………………10
第三章	考慮工作流量之工程設施之配置模式   ………………………………………12
1	設施與工址空間之研究  ……………………………………………………………12
1.1	工址的空間規劃	 ……………………………………………………………………12
1.2	設施的定義與分類  …………………………………………………………………13
1.3	設施的形狀  …………………………………………………………………………14
1.4	設施的出入口	………………………………………………………………………15
2	設施的配置  …………………………………………………………………………16
2.1	設施配置的基準點與角度  …………………………………………………………16
2.2	設施的合理配置	 ……………………………………………………………………17
3	路徑表示法  …………………………………………………………………………18
3.1	路徑的基本假設	 ……………………………………………………………………19
3.2	路徑的合理分布與合理度  …………………………………………………………20
4	設施間的關係係數  …………………………………………………………………21
5	設施配置的工作流量  ………………………………………………………………25
6	規劃模式的建構	 ……………………………………………………………………26
6.1	假設條件  ……………………………………………………………………………26
6.2	模式演算流程  ………………………………………………………………………27
6.3	模式的輸入與輸出  …………………………………………………………………27
第四章  考慮工作流量之工程設施配置之求解模式	 ………………………………………30
1	基因演算法簡介	 ……………………………………………………………………30
2	基因演算法的應用  …………………………………………………………………32
2.1	基因演算法於路徑空間分布計算之應用  …………………………………………32
2.2	基因演算法於設施配置計算之應用	 ………………………………………………33
3	路徑空間分布	………………………………………………………………………34
3.1	路徑分布染色體	 ……………………………………………………………………34
3.1.1	染色體設計與運用  …………………………………………………………………34
3.1.2	合理度計算與Degree-Based Permutation	………………………………………37
3.2	工作流量適存值之計算	………………………………………………………39
3.2.1	設施間最短路徑長與廣度搜尋法  …………………………………………………39
3.2.2	工作流量計算	………………………………………………………………………41
3.3	基因演算法運作	 ……………………………………………………………………42
4	設施配置  ……………………………………………………………………………44
4.1	設施配置之染色體設計  ……………………………………………………………44
4.1.1	染色體結構  …………………………………………………………………………44
4.1.2	設施旋轉與旋轉矩陣  ………………………………………………………………45
4.2	適存值的建構	………………………………………………………………………48
4.2.1	重疊面積適存值的計算  ……………………………………………………………49
4.2.2	雙目標求解與Pareto Front應用	………………………………………………49
4.2.3	適存值計算修正	 ……………………………………………………………………52
4.3	基因演算法運用	 ……………………………………………………………………53
第五章  案例之驗證與應用  …………………………………………………………………55
1	系統模式簡介	………………………………………………………………………55
2	研究理論之驗證	 ……………………………………………………………………57
2.1	路徑分布求解能力驗證  ……………………………………………………………57
2.2	配置基本運作驗證  …………………………………………………………………59
2.3	關係係數與Pareto Front成效之驗證  ……………………………………………61
2.4	緊密排列驗證	………………………………………………………………………65
3	文獻案例應用與討論  ………………………………………………………………67
3.1	案例說明與設定	 ……………………………………………………………………67
3.2	結果分析  ……………………………………………………………………………69
4	敏感度分析  …………………………………………………………………………73
4.1	演化世代數  …………………………………………………………………………74
4.2	母體數  ………………………………………………………………………………75
4.3	交配率  ………………………………………………………………………………75
4.4	突變率  ………………………………………………………………………………76
4.5	敏感度分析結論	 ……………………………………………………………………77
5	案例實作與模式運用  ………………………………………………………………78
5.1	案例說明與設定	 ……………………………………………………………………78
5.2	模式執行結果	………………………………………………………………………80
5.3	小結	……………………………………………………………………………82
第六章  結論與未來研究方向  ………………………………………………………………84
1	結論	……………………………………………………………………………84
2	未來研究方向	………………………………………………………………………85
參考文獻  ………………………………………………………………………………………87
附錄A、程式介紹   ……………………………………………………………………………90
                                    

英文部分
1. Cheng, M.Y. (1992) "Automated Site Layout of Temporary Construction Facilities Using Geographic Information Systems(GIS)." Ph.D. Dissertation, Department of Civil Engineering, University of Texas at Austin, Texas.
2. Elbeltagi, E., and Hegazy, T. (2001). “A Hybrid AI-based System for Site Layout Planning in Construction.” Computer-Aided Civil and Infrastructure Engineering, 16, 79-93.
3. Feng, C. W., and Liu, L., and Burns, S. A. (1997). “Using Genetic Algorithms to Solve Construction Time-Cost Trade-Off Problems.” Journal of Computing in Civil Engineering, ASCE, 11(3), 184-189.
4. Francis, R. L., and White, J. A. (1974). Facility layout and location. Prentice-Hall, Englewook Cliffs, N.J.
5. Gen, M., and Cheng, R. (1999). Genetic Algorithms and Engineering Optimization. Wiley, New York.
6. Gen, M., and Zhou, G.., and Kim, J. R. (1999). “Genetic algorithms for solving network design problems: State-of-the-art survey.” Evolutionary Optimization, vol. 1, no. 2, pp. 121–141.
7. Hegazy, T., and Elbeltagi, E. (1999). “EVOSIT: Evolution-Based Model for Site Layout Plaaning.” Journal of Computing in Civil Engineering, ASCE, 13(3), 198-206.
8. Karray, F., and Zaneldin, E., and Hegazy, T., and Shabeeb, A., and Elbeltagi, E. (2000).”Computational Intelligence Tools for Solving the Facilities Layout Planning Problem.” Proceedings of the American Control Conference, Chicago, Illinois. June.
9. Lee, R. C., and Moore, J. M. (1967). “CORELAP: Computerized relationship layout planning.” Journal of Industrial Engineering, 8(3), 195-200.
10. Li, H., and Love, P. (1998). “Site-level Facilities Layout Using Genetic Algorithms.” Journal of Computing in Civil Engineering, ASCE, 12(4), 227-231.
11. Logan, D. L. (2000). A First Course in the Finite Element Method – 3rd ed. Books/Cole, Pacific Grove.
12. Malakooti, B. (1987). “Computer-aided facility layout selection(CAFLAS) with applications to multiple criteria manufacturing planning problem.” Large Scale Systems: Theory and Applications, Special Issue on Complex Systems Issues in Manufacturing, 12, 109-123.
13. Makki, S.A.M. (1996). “Efficient distributed breadth-first search algorithm.” Computer Communications, 19, 628-636.
14. Mawdesley, M. J., and Al-jibouri, S.H., and Yang, H. (2002). “Genetic Algorithms for Construction Site Layout in Project Planning.” Journal of Construction Engineering and Management, ASCE, Vol. 128, No. 5, 418-426.
15. Nazareth, T., and Verma, S., and Bhattacharya, S., and Bagchi, A. (1999). “The multiple resource constrained project scheduling problem: A breadth-first approach.” European Journal of Operational Research, 112, 347-366.
16. Rad, P. F., and James, B. M. (1983). “The layout of temporary construction facilities.” Cost engineering, 25(2), 19-27.
17. Tam, C. M., and Tong, K. L., and Chan, K.W. (2001). ”Genetic Alogrithm for Optimizing Supply Locations Around Tower Crane.” Journal of Construction Engineering and Management, ASCE, 127(4), 315-321.
18. Twort, A. C., and Rees, J. G. (1995). Civil engineering supervision and management, 3rd Ed. Arnold, London.
19. Yeh, I. C. (1995). “Construction site layout using annealed neutral network.” Journal of Computing in Civil Engineering, ASCE, 9(3), 201-208.
20. Zhang, J.P., and Liu, L.H., and Coble, R.J. (2002). “Hybrid intelligence utilization for construction site layout.” Automation in Construction, 11, 511-519.
21. Zouein, P. P., and Harmanani, H., and Hajar, A. (2002). “Genetic Algorithm for Solving Site Layout Problem with Unequal-Size and Constrained Facilitiies.” Journal of Computing in Civiil Engineering, ASCE, Vol. 16, No. 2, 143-151.
22. Zouein, P. P., and Tommelein, L. D. (1999). “Dynamic Layout Planning Using A Hybrid Incremental Solution Method.” Journal of Construction Engineering and Management, ASCE, 125(6), 400-408.
中文部分
23. 王聖元,（2002）. “以時程為基礎之動態設施配置” 國立成功大學土木工程學系碩士論文.
22. 張宏旭,（2001）. “基因演算法在設施配置規劃上之應用” 國立成功大學土木工程學系碩士論文.

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