journal article·2023-09-26Open access

Dynamic Optimization of Construction Time-Cost for Deep and Large Foundation Pit Based on BIM Technology and Genetic Algorithm

Yingxia Yu, Junjia Han, Haoyu Gu, Yi Yang

Applied Sciences· Volume 13· Issue 19

Abstract

With the increasingly fierce market competition, optimizing the construction time-cost of deep and large foundation pit construction projects has become one of the key factors for construction enterprises to remain invincible. By dynamically optimizing the time-cost, the optimal time corresponding to the lowest engineering cost can be found. Based on a comprehensive transportation hub project, considering the time value of capital and the reward and punishment of construction time, a time-cost dynamic optimization model is constructed. Relying on BIM technology, the feasibility of construction plan is analyzed from both qualitative and quantitative perspectives, and the project parameters and resource information is obtained accurately and quickly. Using the MATLAB program, time-cost optimization based on genetic algorithm is carried out, and the static and dynamic optimization results are compared. The results show that the dynamic optimization scheme reduces the total cost by 1.68% while reducing the total construction time by 8.47%. The dynamic optimization scheme extends the construction period by 2 days while reducing the total cost by 89,500 yuan compared to static optimization. The peak value of the fund demand curve before and after optimization has decreased from 128,000 yuan to 127,000 yuan. The time-cost dynamic optimization, considering the time value of capital is more in line with engineering reality, and the optimization results are more reliable and accurate. BIM technology can accurately and quickly obtain project parameters and resource information, solving problems such as complex processes in super deep excavation and huge engineering data statistics. The genetic algorithm can efficiently and accurately search for the optimal solution within the global domain. This study combines BIM technology with the genetic algorithm to solve the dynamic optimization problem of construction period cost for deep and large foundation pits. The research results of this study provide a theoretical reference for the optimization of schedule cost for similar projects.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: BIM and Construction Integration · Infrastructure Maintenance and Monitoring · Tunneling and Rock Mechanics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Civil Engineering and Architecture, Henan University of Science and Technology, Luoyang 471000, China

School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai 264209, China

China Railway 19th Bureau Group Co., Ltd., Beijing 100176, China

Funding

National Natural Science Foundation of China · Key Scientific Research Project of China Railway 19th Bureau Group Co., Ltd.

References (21)

Show source-provided references
1. Liu, Y. (2008). Engineering Project Planning and Control. [Ph.D. Thesis, China Architecture & Building Press].
2. Optimization design of grading ring structure of HVDC voltage divider based on SPRGA
3. Gao, J., and Zhang, Y. (2023). Research on optimal water distribution in two-stage canal system of branch and lateral based on genetic algorithm optimized particle swarm algorithm. Water Sav. Irrig., 1–13. Available online: http://kns.cnki.net/kcms/detail/42.1420.TV.20230914.1122.002.html.
4. Sectional optimization design of concrete frame column based on low-carbon indicator
5. (Iran): Prediction of martensite fraction of microalloyed steel by artificial neural networks10.14311/NNW.2013.23.009 ↗
6. Modeling the correlation between heat treatment, chemical composition and bainite fraction of pipeline steels by means of artifcial neural networks10.14311/NNW.2013.23.022 ↗
7. Loading optimization of Fischer-Tropsch synthesis using artificial neural networks and genetic algorithm
8. Wang, Y. (2015). Research on Time Cost Optimization Based on Hybrid Genetic Algorithm. [Ph.D. Thesis, Dalian University of Technology].
9. Parameter optimization and forming limit prediction of sheet metal ductile fracture criterion based on neural network and genetic algorithm
10. Liao, Y. (2018). Optimization of Workshop Facility Layout Based on Genetic Algorithm. [Ph.D. Thesis, University of Nanhua].
11. Optimization of Project Group time-Cost Based on Genetic Algorithm
12. Cost optimization under the condition of minimum owner cost of project group
13. Dynamic optimization of project time cost based on genetic algorithm
14. Research on the application of improved genetic algorithm in dynamic time/cost trade-off
15. Time-cost Tradeoff Optimization of Construction Projects Using Genetic Algorithms
16. BIM-based Optimization of Design and Construction for Bridge Projects
17. Automatic Patching Research Based on Construction Project Schedule Plan of BIM
18. Research on Construction Schedule Management Based on BIM and PDCA
19. Research on Construction Schedule-cost Optimization of Grid Engineering Based on BIM and Genetic Algorithm
20. Time Cost Optimization Based Improved NSGA-Ⅱ Algorithm and BIM5D
21. Sparse Array Synthesis Based on Real Coded Genetic Algorithm