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Dynamic time-cost-quality tradeoff of rockfill dam construction based on real-time monitoring

基于实时监控的面板堆石坝施工进度-成本-质量动态均衡

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Abstract

Time, cost, and quality are three key control factors in rockfill dam construction, and the tradeoff among them is important. Research has focused on the construction time-cost-quality tradeoff for the planning or design phase, built on static empirical data. However, due to its intrinsic uncertainties, rockfill dam construction is a dynamic process which requires the tradeoff to adjust dynamically to changes in construction conditions. In this study, a dynamic time-cost-quality tradeoff (DTCQT) method is proposed to balance time, cost, and quality at any stage of the construction process. A time-cost-quality tradeoff model is established that considers time cost and quality cost. Time, cost, and quality are dynamically estimated based on real-time monitoring. The analytic hierarchy process (AHP) method is applied to quantify the decision preferences among time, cost, and quality as objective weights. In addition, an improved non-dominated sorting genetic algorithm (NSGA-II) coupled with the technique for order preference by similarity to ideal solution (TOPSIS) method is used to search for the optimal compromise solution. A case study project is analyzed to demonstrate the applicability of the method, and the efficiency of the proposed optimization method is compared with that of the linear weighted sum (LWS) and NSGA-II.

抽象

目 的

施工进度-成本-质量均衡是面板堆石坝工程成功的关键。目前的均衡研究建立在静态经验数据上, 仅针对规划和设计阶段, 难以适应施工过程的动态性和不确定性。基于面板堆石坝施工质量实时监控技术, 考虑动态决策偏好, 本文提出施工进度-质量-成本动态均衡方法, 以实现面向过程管理的进度-质量-成本均衡。

创新点

1. 提出基于面板堆石坝施工质量实时监控技术的施工进度、质量和成本动态预测方法; 2. 提出施工决策偏好动态量化方法; 3. 提出施工进度-质量-成本多目标均衡求解算法。

方 法

1. 通过分析实时监控数据, 更新仿真模型参数, 仿真得到施工进度, 再推导出质量和成本(图4、公式(8)和(10)); 2. 采用层次分析法, 动态量化施工过程中的管理者决策偏好, 得到进度-质量-成本三目标间的权重(图5); 3. 采用改进的带精英策略的非支配排序遗传算法(公式(13)), 求解动态均衡问题的Pareto 解, 并运用逼近理想解的排序法筛选出最优折衷方案(图5)。

结 论

1. 基于实时监控进行施工进度、质量和成本的动态预测, 提高了均衡结果与实际施工过程的一致性; 2. 动态量化决策偏好, 并在优化求解中予以考虑, 有助于最优折衷方案的筛选; 3. 在施工过程中任意阶段开展的施工进度-质量-成本动态均衡适应了施工条件的动态变化, 可有效指导现场施工管理。

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Correspondence to Bin-ping Wu.

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Project supported by the Innovative Research Groups of the National Natural Science Foundation of China (No. 51621092), the National Basic Research Program (973 Program) of China (No. 2013CB035904), and the Natural Science Foundation of China (No. 51439005)

ORCID: Bin-ping WU, http://orcid.org/0000-0002-9398-9078

Introducing editorial board member

Prof. Deng-hua ZHONG is a new editorial board member of Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering) in 2017. He is the director of State Key Laboratory of Hydraulic Engineering Simulation and Safety at Tianjin University. He has been an academician of the Chinese Academy of Engineering since 2009.

Prof. ZHONG received his PhD degree from Tianjin University in 1992. He was a senior visiting scholar of Massachusetts Institute of Technology, University of Mannheim, and University of Kiel. He has been devoted to the research on hydraulic engineering construction and related theories and technologies. He has successfully presided over 10 scientific research projects, including the National Basic Research Program (973 Program) of China, the National Natural Science Foundation of China, and the National Key Technology R&D Program of China. Moreover, he is also a prolific researcher with five authored academic books and over 100 technical papers published in journals and conferences. For his outstanding achievements, Prof. ZHONG was awarded three Second Prizes of State Scientific and Technological Progress, two in 2005 and 2007 as the first Prize Winner and one in 2011 as the second Prize Winner. Besides, he was honored with several other remarkable prizes, including (1) China Youth Science and Technology Award in 2004, (2) the National Science Fund for Distinguished Young Scholars in 2005, and (3) Guanghua Engineering Science and Technology Award for Young Scientist in 2008.

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Zhong, Dh., Hu, W., Wu, Bp. et al. Dynamic time-cost-quality tradeoff of rockfill dam construction based on real-time monitoring. J. Zhejiang Univ. Sci. A 18, 1–19 (2017). https://doi.org/10.1631/jzus.A1600564

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