Multi-objective optimal scheduling of automated construction equipment using non-dominated sorting genetic algorithm (NSGA-III)

被引:30
|
作者
Liu, Ying [1 ,2 ]
You, Ke [1 ,2 ,3 ]
Jiang, Yutian [5 ]
Wu, Zhangang [5 ]
Liu, Zhenyuan [4 ]
Peng, Gang [4 ]
Zhou, Cheng [1 ,2 ]
机构
[1] Huazhong Univ Sci & Technol, Natl Ctr Technol Innovat Digital Construct, Wuhan, Hubei, Peoples R China
[2] Huazhong Univ Sci & Technol, Sch Civil & Hydraul Engn, Wuhan, Hubei, Peoples R China
[3] Huazhong Univ Sci & Technol, Inst Artificial Intelligence, Wuhan, Hubei, Peoples R China
[4] Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Wuhan, Hubei, Peoples R China
[5] Shantui Construct Machinery Co Ltd, Jining, Shandong, Peoples R China
基金
中国国家自然科学基金;
关键词
Automated equipment; Flexible earthwork scheduling; Non-dominated sorting genetic algorithm (NSGA-III); Optimal Pareto solution set; SWARM OPTIMIZATION ALGORITHM; HYBRID; PERFORMANCE; SYSTEMS;
D O I
10.1016/j.autcon.2022.104587
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Unstructured and variable construction sites bring challenges that can be addressed with the adoption of the flexible earthwork scheduling problem (FESP), which requires consideration of mechanical parameters, automated construction techniques, and site constraints. This paper describes the use of the non-dominated sorting genetic algorithm (NSGA-III) for such problems, yielding better results than the NSGA-II and strength pareto evolutionary algorithm (SPEA). This method produces a set of Pareto-optimal results for each case study, which are then ranked by the analytic hierarchy process (AHP) method to determine an optimal scheduling scheme. The results help project managers and dispatchers by automating the schedule process and by graphically analyzing the solutions".
引用
收藏
页数:24
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