# American Institute of Mathematical Sciences

October  2015, 11(4): 1321-1342. doi: 10.3934/jimo.2015.11.1321

## Construction schedule optimization for high arch dams based on real-time interactive simulation

 1 State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China, China, China

Received  January 2014 Revised  September 2014 Published  March 2015

The construction process of high arch dams is extremely complicated. Therefore, optimization of the construction schedule is essential for construction management to save a large amount of time and investment costs. Construction simulation is an important tool for the construction schedule optimization of high arch dams. Most current studies involving construction schedule simulations do not concurrently consider real-time construction situations and site managers' requirements. In this paper, the real-time interactive simulation is proposed that could solve this problem. The real-time construction process is the initial condition of the simulation, and the actual construction parameters are the basis of the simulation parameters. Additionally, site managers can change the simulation strategy dynamically or enter requirements based on real-time construction situations. For a simulation result, different schemes are optimized with the entropy weight method. With this method, the construction simulation can track the rapid changes in construction situations and provide a reasonable construction schedule, which increases the flexibility of the construction simulation. The optimized construction scheme could be an effective guide for site construction. With a 4D (three dimensional model and time) CAD model, the simulation process can be well expressed. A case study shows that the construction schedule can be established in real time, and it's a useful tool for decision-making.
Citation: Tao Guan, Denghua Zhong, Bingyu Ren, Pu Cheng. Construction schedule optimization for high arch dams based on real-time interactive simulation. Journal of Industrial & Management Optimization, 2015, 11 (4) : 1321-1342. doi: 10.3934/jimo.2015.11.1321
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