TY - GEN
T1 - Scheduling Optimization for Multi-Production Line Hybrid Manufacturing of Prefabricated Components in Prefabricated Construction
AU - Wang, Yao
AU - Li, Liangbao
N1 - Publisher Copyright:
© ASCE.
PY - 2025
Y1 - 2025
N2 - Prefabricated construction, as a building model vigorously promoted by the Chinese government in recent years, represents an important direction for the future development of the construction industry. The production of prefabricated components serves as the core link of prefabricated construction, with its scheduling directly influence the production costs of construction projects. To improve the scientific nature of the production scheduling process, this study establishes a comprehensive production scheduling model for multi-production line hybrid manufacturing of prefabricated components. Subsequently, to solve the model, this paper improves the non-dominated sorting genetic algorithm (NSGA-II) by integrating with the variable neighborhood search (VNS) method and results in an improved non-dominated genetic algorithm (INSGA-II), which effectively addressing the drawback of NSGA-II's limited local search capability. Finally, this research validates the effectiveness of the established production scheduling optimization model and the improved algorithm through actual case data.
AB - Prefabricated construction, as a building model vigorously promoted by the Chinese government in recent years, represents an important direction for the future development of the construction industry. The production of prefabricated components serves as the core link of prefabricated construction, with its scheduling directly influence the production costs of construction projects. To improve the scientific nature of the production scheduling process, this study establishes a comprehensive production scheduling model for multi-production line hybrid manufacturing of prefabricated components. Subsequently, to solve the model, this paper improves the non-dominated sorting genetic algorithm (NSGA-II) by integrating with the variable neighborhood search (VNS) method and results in an improved non-dominated genetic algorithm (INSGA-II), which effectively addressing the drawback of NSGA-II's limited local search capability. Finally, this research validates the effectiveness of the established production scheduling optimization model and the improved algorithm through actual case data.
UR - https://www.scopus.com/pages/publications/105024064729
U2 - 10.1061/9780784486627.049
DO - 10.1061/9780784486627.049
M3 - 会议稿件
AN - SCOPUS:105024064729
T3 - ICCREM 2025: Decarbonization and Digitalization of the Built Environment-Shaping Resilience in a Changing World, Proceedings of the International Conference on Construction and Real Estate Management 2025
SP - 512
EP - 525
BT - ICCREM 2025
A2 - Wang, Yaowu
A2 - Lu, Weizhuo
A2 - Shen, Geoffrey Q. P.
PB - American Society of Civil Engineers (ASCE)
T2 - 2025 International Conference on Construction and Real Estate Management, ICCREM 2025
Y2 - 9 August 2025 through 10 August 2025
ER -