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[期刊论文]

Optimal procurement strategy for off-site prefabricated components considering construction schedule and cost

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author:

Chen, Gang (Chen, Gang.) [1] | Huang, Jizhuo (Huang, Jizhuo.) [2] | Wang, Jun (Wang, Jun.) [3] | Unfold

Indexed by:

EI

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. © 2022 Elsevier B.V.

Keyword:

Construction Costs Decision making Genetic algorithms

Community:

  • [ 1 ] [Chen, Gang]College of Civil Engineering, Fuzhou University, Fujian, Fuzhou; 350116, China
  • [ 2 ] [Huang, Jizhuo]College of Civil Engineering, Fuzhou University, Fujian, Fuzhou; 350116, China
  • [ 3 ] [Wang, Jun]School of Engineering, Design and Built Environment, Western Sydney University, NSW, Australia
  • [ 4 ] [Wei, Jiangang]College of Civil Engineering, Fuzhou University, Fujian, Fuzhou; 350116, China
  • [ 5 ] [Wei, Jiangang]College of Civil Engineering, Fujian University of Technology, Fujian, Fuzhou; 350116, China
  • [ 6 ] [Shou, Wenchi]School of Engineering, Design and Built Environment, Western Sydney University, NSW, Australia
  • [ 7 ] [Cao, Zhenyuan]College of Civil Engineering, Fuzhou University, Fujian, Fuzhou; 350116, China
  • [ 8 ] [Pan, Wenping]College of Civil Engineering, Fuzhou University, Fujian, Fuzhou; 350116, China
  • [ 9 ] [Zhou, Jun]College of Civil Engineering, Fujian Chuanzheng Communications College, Fujian, Fuzhou; 350116, China

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Source :

Automation in Construction

ISSN: 0926-5805

Year: 2023

Volume: 147

9 . 6

JCR@2023

9 . 6 0 0

JCR@2023

ESI HC Threshold:35

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 11

30 Days PV: 0

Affiliated Colleges:

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