基於建築資訊模型之鋼筋撿料多目標決策之研究

EMPLOYING MULTI-OBJECTIVE OPTIMIZATION TO REBAR QUANTITY TAKEOFF BASED ON BUILDING INFORMATION MODEL

10.6652/JoCICHE.201904_31(2).0001

張昇(Shen Chang)；吳翌禎(I-Chen Wu)

建築資訊模型 ； 鋼筋撿料 ； 多目標決策 ； 基因演算法 ； A星演算法 ； BIM ； rebar takeoff ； multiple objective optimization ； genetic algorithm ； a star search algorithm

中國土木水利工程學刊

31卷2期（2019 / 04 / 01）

129 - 140

繁體中文

鋼筋工程是攸關整體建築是否能夠具有耐震性能的一種施工技術，然而對營建業來說該工程成本影響其獲利甚大。近年來，隨著建築資訊模型持續發展，如何從已完成之三維模型進行鋼筋撿料之自動優化實具研究價值。因此本研究提出一個考量最佳鋼筋撿料、運送成本的多目標問題，其解決方案主要包含兩個步驟：（1）使用A星演算法基於法律規範與施工可行性，對Tekla軟體建模後之各主構件產生餘料較少的可行撿料方案清單；（2）再使用基因演算法對建物（染色體）之各構件（基因）的撿料方案進行排列組合，以期達到考量最少鋼筋餘料、最低運輸成本的最適解之目的。

Rebar engineering is a construction technique that has the amount of influence on the aseismatic performance of the entire building. However, for the construction industry, the cost of reinforcement will affect its profitability. In recent years, with the continuous development of the Building Information Modeling (BIM), how to carry out the automatic optimization of reinforced materials from the completed three-dimensional model has practical research value. Therefore, this study proposes a multi-objective optimization problem that considers the rebar quantity takeoff and transportation costs. The solution consists of two processes: (1) after establishing BIM model with Tekla software, using A Star Search Algorithm based on regulations and construction feasibility produces a variety of feasible solutions for the main components; (2) then using the Genetic Algorithm to combine the feasible rebar takeoff schemes of the components (genes) of the building (chromosome). To attain the purpose to get the best compromised solution that considering the minimum residual rebar materials and the lowest transportation cost.

1. Ahmadkhanlou, F.,Adeli, H.(2005).Optimum cost design of reinforced concrete slabs using neural dynamics model.Engineering Applications of Artificial Intelligence,18(1),65-72.
2. Bryde, D.,Broquetas, M.,Volm, J. M.(2013).The project benefits of Building Information Modelling (BIM).International Journal of Project Management,31(7),971-980.
3. Chen, C.-L. S.,Hart, S. M.,Tham, W. M.(1996).A simulated annealing heuristic for the one-dimensional cutting stock problem.European Journal of Operational Research,93(3),522-535.
4. Dijkstra, E. W.(1959).A note on two problems in connexion with graphs.Numerische Mathematik,1(1),269-271.
5. Dorigo, M.,Maniezzo, V.,Colorni, A.(1996).Ant system: Optimization by a colony of cooperating agents.IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics),26(1),29-41.
6. Gilmore, P. C.,Gomory, R. E.(1961).A linear programming approach to the cutting-stock problem.Operations Research,9(6),849-859.
7. Gómez-Romero, J.,Bobillo, F.,Ros, M.,Molina-Solana, M.,Ruiz, M. D.,Martín-Bautista, M. J.(2015).A fuzzy extension of the semantic Building Information Model.Automation in Construction,57,202-212.
8. Hadi, M. N. S.(2003).Neural networks applications in concrete structures.Computers & Structures,81(6),373-381.
9. Hart, P. E.,Nilsson, N. J.,Raphael, B.(1968).A formal basis for the heuristic determination of minimum cost paths.IEEE Transactions on Systems Science and Cybernetics,4(2),100-107.
10. Holland, J.(1975).Adaptation in Natural and Artificial Systems.The University of Michigan Press.
11. Ilter, D.,Ergen, E.(2015).BIM for building refurbishment and maintenance: current status and research directions.Structural Survey,33(3),228-256.
12. Kantorovich, L. V.(1960).Mathematical methods of organizing and planning production.Management Science,6(4),366-422.
13. Lee, C.,Ahn, J.(2003).Flexural design of reinforced concrete frames by genetic algorithm.Journal of Structural Engineering,129(6),762-774.
14. Lepš, M.,Šejnoha, M.(2003).New approach to optimization of reinforced concrete beams.Computers & Structures,81(18),1957-1966.
15. Lu, Q.,Won, J.,Cheng, J. C. P.(2016).A financial decision making framework for construction projects based on 5D Building Information Modeling (BIM).International Journal of Project Management,34(1),3-21.
16. Mangal, M.,Cheng, J. C. P.(2018).Automated optimization of steel reinforcement in RC building frames using building information modeling and hybrid genetic algorithm.Automation in Construction,90,39-57.
17. Motawa, I.,Almarshad, A.(2013).A knowledge-based BIM system for building maintenance.Automation in Construction,29,173-182.
18. Porwal, A.,Hewage, K. N.(2012).Building Information Modeling-based analysis to minimize waste rate of structural reinforcement.Journal of Construction Engineering and Management,138(8),943-954.
19. Sahab, M. G.,Ashour, A. F.,Toropov, V. V.(2005).A hybrid genetic algorithm for reinforced concrete flat slab buildings.Computers & Structures,83(8),551-559.
20. Saini ∗ a, B.,Sehgala, V. K.,Gambhirb, M. L.(2006).Genetically optimized artificial neural network based optimum design of singly and doubly reinforced concrete beams.Asian Journal of Civil Engineering,7(6),603-619.
21. Won, J.,Cheng, J. C. P.,Lee, G.(2016).Quantification of construction waste prevented by BIM-based design validation: Case studies in South Korea.Waste Management,49,170-180.
22. Zheng, C.,Lu, M.(2016).Optimized reinforcement detailing design for sustainable construction: slab case study.Procedia Engineering,145,1478-1485.
23. 中國土木水利工程學會(2016).結構混凝土建築規範 (ACI 318-14).台灣:科技圖書股份有限公司.
24. 行政院交通部，道路交通安全規則，台灣 (2018)。
25. 連立川,劉燕妮,張鵬程(2016)。基於 Revit 的鋼筋下料裁切優化初步程式研究。第 2016 第 20 屆營建工程與管理學術研討，台南:
26. 陳永祥,楊敦凱(2010)。RC 房屋結構梁配筋施工圖自動化設計之研究。結構工程，25(1)，107-122。