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

張昇(Shen Chang) ； 吳翌禎(I-Chen Wu)

《中國土木水利工程學刊》 31卷2期 (2019/04) Pp. 129-140

https://doi.org/10.6652/JoCICHE.201904_31(2).0001

摘要

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。

關鍵字

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

並列摘要

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.

並列關鍵字

BIM ； rebar takeoff ； multiple objective optimization ； genetic algorithm ； a star search algorithm