Multi-objective optimization of construction management of expressway engineering based on improved particle swarm optimization algorithm

被引:0
作者
Liu, Xu [1 ]
机构
[1] Sichuan Water Conservancy Vocat Coll, Management State Owned Assets Dept, 366 Yonghe Ave, Chongzhou, Peoples R China
关键词
adaptive weight; construction management; highway; multi-objective optimization; particle swarm optimization;
D O I
10.24425/ace.2024.150988
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Engineering management is an extremely important aspect of construction engineering, and a better management approach can greatly enhance the production profits of enterprises. Traditional management optimization schemes cannot adapt to current technological needs due to their inability to effectively consider the impact of each factor. Therefore, a construction management optimization scheme combining improved particle algorithm and multi-objective optimization was proposed. The improved particle algorithm enhances its performance by introducing adaptive weight and multi-objective optimization ideas. These studies confirmed that the predicted direct cost savings for the project were around 1 million yuan. The total construction period of project was optimized to 380 days, saving 34 days. The optimization technology not only reduced construction costs, but also reflected the problems that could be improved during this construction process. This study contributes to achieving multi-objective balance in the construction management process, effectively improving project efficiency, reducing project costs and risks, and providing scientific support for construction decision-making.
引用
收藏
页码:359 / 372
页数:14
相关论文
共 17 条
[1]  
Almashhadaniand M., 2023, International Journal of Business and Management Invention, V12, P284, DOI [10.35629/8028-1206284290, DOI 10.24846/V29I2Y202008]
[2]   Factor validity and reliability performance analysis of human behavior in green architecture construction engineering [J].
Bai, Xiao-ping ;
Qian, Cheng .
AIN SHAMS ENGINEERING JOURNAL, 2021, 12 (04) :4291-4296
[3]   ST-SIGMA: Spatio-temporal semantics and interaction graph aggregation for multi-agent perception and trajectory forecasting [J].
Fang, Yang ;
Luo, Bei ;
Zhao, Ting ;
He, Dong ;
Jiang, Bingbing ;
Liu, Qilie .
CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY, 2022, 7 (04) :744-757
[4]   Particle Swarm Optimization Algorithm and Its Applications: A Systematic Review [J].
Gad, Ahmed G. .
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2022, 29 (05) :2531-2561
[5]  
Jie S.U., 2021, Accounting and Corporate Management, V3, P61, DOI [10.23977/acccm.2021.030109, DOI 10.23977/ACCCM.2021.030109]
[6]   Reinforce Technology IR 4.0 Implementation for Improving Safety Management in Construction Site [J].
Kasim, Narimah ;
Razali, Sali Amirah ;
Kasim, Rozilah .
INTERNATIONAL JOURNAL OF SUSTAINABLE CONSTRUCTION ENGINEERING AND TECHNOLOGY, 2021, 12 (03) :289-298
[7]  
Liu YR, 2022, REV GEST TECNOL, V22, P153, DOI 10.20397/2177-6652/2022.v22i4.2435
[8]   Position-Transitional Particle Swarm Optimization-Incorporated Latent Factor Analysis [J].
Luo, Xin ;
Yuan, Ye ;
Chen, Sili ;
Zeng, Nianyin ;
Wang, Zidong .
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2022, 34 (08) :3958-3970
[9]   Application of stacking ensemble machine learning algorithm in predicting the cost of highway construction projects [J].
Meharie, Meseret Getnet ;
Mengesha, Wubshet Jekale ;
Gariy, Zachary Abiero ;
Mutuku, Raphael N. N. .
ENGINEERING CONSTRUCTION AND ARCHITECTURAL MANAGEMENT, 2022, 29 (07) :2836-2853
[10]  
Nsugbe E., 2023, Artif Intell Appl, V1, P35