TY - JOUR
T1 - Process scheduling for prefabricated construction based on multi-objective optimization algorithm
AU - Li, Yan
AU - Wu, Jiajun
AU - Hao, Yi
AU - Gao, Yuchen
AU - Chai, Runqi
AU - Chai, Senchun
AU - Zhang, Baihai
N1 - Publisher Copyright:
© 2024
PY - 2024/12/1
Y1 - 2024/12/1
N2 - Prefabricated construction has become an increasingly important focus area in the development of the construction industry. Determining an optimal construction process scheduling program is an urgent challenge during the project execution stage. This paper presents a multi-objective optimization problem with the objective function of minimizing the total construction time and maximizing the coordinated scheduling coefficient, and proposes a non-dominated sorting genetic algorithm based on the subspecies differentiation strategy (SD-NSGA) to solve the problem. The algorithm extends the competition phenomenon at the individual level to the subpopulation level in the traditional genetic algorithm (GA). The results demonstrate that SD-NSGA exhibits superior optimization capabilities. Compared with the initial scheme of a real residential construction project, the total working time is shortened by 35.49% and the integrated dispatch factor is increased by 365.79%. Therefore, the proposed algorithm can offer a valuable reference for determining scheduling plans in practical engineering projects.1
AB - Prefabricated construction has become an increasingly important focus area in the development of the construction industry. Determining an optimal construction process scheduling program is an urgent challenge during the project execution stage. This paper presents a multi-objective optimization problem with the objective function of minimizing the total construction time and maximizing the coordinated scheduling coefficient, and proposes a non-dominated sorting genetic algorithm based on the subspecies differentiation strategy (SD-NSGA) to solve the problem. The algorithm extends the competition phenomenon at the individual level to the subpopulation level in the traditional genetic algorithm (GA). The results demonstrate that SD-NSGA exhibits superior optimization capabilities. Compared with the initial scheme of a real residential construction project, the total working time is shortened by 35.49% and the integrated dispatch factor is increased by 365.79%. Therefore, the proposed algorithm can offer a valuable reference for determining scheduling plans in practical engineering projects.1
KW - Multi-objective optimization
KW - Non-dominated sorting genetic algorithm
KW - Prefabricated construction
KW - Process scheduling
KW - Subspecies differentiation strategy
UR - http://www.scopus.com/inward/record.url?scp=85206073239&partnerID=8YFLogxK
U2 - 10.1016/j.autcon.2024.105809
DO - 10.1016/j.autcon.2024.105809
M3 - Article
AN - SCOPUS:85206073239
SN - 0926-5805
VL - 168
JO - Automation in Construction
JF - Automation in Construction
M1 - 105809
ER -