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A platform for research: civil engineering, architecture and urbanism
Optimal procurement strategy for off-site prefabricated components considering construction schedule and cost
Abstract The implementation of prefabricated buildings is hindered by the high construction cost. To address this problem, it is important to determine the efficient leverage of the supply capacity of local factories to assure just-in-time delivery to the construction site, as well as to accurately model the various types of cost to achieve a near-optimal procurement strategy. This paper describes a mathematical model to optimize the procurement of prefabricated components. A genetic algorithm is applied to efficiently obtain the minimum total cost that includes installation cost, business management cost and loan interest cost. Finally, a number of numerical experiments are conducted, showing that the procurement strategy generated from the proposed mathematical model is better than the traditional procurement strategy in terms of construction duration reductions and total cost savings. The component procurement method proposed in this paper improves the scientific management ability of decision-makers, and provides purchasing framework for other prefabricated structural forms.
Highlights A nonlinear optimization model is proposed for improving off-site component procurement. The model considers the construction schedule, supply capacity, and factories' locations. The adjusted genetic algorithm has a much faster convergence rate. The effectiveness of the proposed model has been validated through real case studies.
Optimal procurement strategy for off-site prefabricated components considering construction schedule and cost
Abstract The implementation of prefabricated buildings is hindered by the high construction cost. To address this problem, it is important to determine the efficient leverage of the supply capacity of local factories to assure just-in-time delivery to the construction site, as well as to accurately model the various types of cost to achieve a near-optimal procurement strategy. This paper describes a mathematical model to optimize the procurement of prefabricated components. A genetic algorithm is applied to efficiently obtain the minimum total cost that includes installation cost, business management cost and loan interest cost. Finally, a number of numerical experiments are conducted, showing that the procurement strategy generated from the proposed mathematical model is better than the traditional procurement strategy in terms of construction duration reductions and total cost savings. The component procurement method proposed in this paper improves the scientific management ability of decision-makers, and provides purchasing framework for other prefabricated structural forms.
Highlights A nonlinear optimization model is proposed for improving off-site component procurement. The model considers the construction schedule, supply capacity, and factories' locations. The adjusted genetic algorithm has a much faster convergence rate. The effectiveness of the proposed model has been validated through real case studies.
Optimal procurement strategy for off-site prefabricated components considering construction schedule and cost
Chen, Gang (author) / Huang, Jizhuo (author) / Wang, Jun (author) / Wei, Jiangang (author) / Shou, Wenchi (author) / Cao, Zhenyuan (author) / Pan, Wenping (author) / Zhou, Jun (author)
2022-12-19
Article (Journal)
Electronic Resource
English
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