Bi-objective optimization framework for prefabricated construction service combination selection using genetic simulated annealing algorithm
Engineering, Construction and Architectural Management
ISSN: 0969-9988
Article publication date: 3 April 2023
Abstract
Purpose
The purpose of this paper is to develop a bi-objective optimization framework to select prefabricated construction service composition. An improved algorithm-genetic simulated annealing algorithm (GSA) is employed to demonstrate the application of the framework.
Design/methodology/approach
The weighted aggregate multi-dimensional collaborative relationship is used to quantitatively evaluate the synergistic effect. The quality of service is measured using the same method. The research proposed a service combination selection framework of prefabricated construction that comprehensively considers the quality of service and synergistic effect. The framework is demonstrated by using a GSA that can accept poor solutions with a certain probability. Furthermore, GSA is compared with the genetic algorithm (GA), simulated annealing algorithm (SA) and particle swarm optimization algorithm (PSO) to validate the performance.
Findings
The results indicated that GSA has the largest optimal fitness value and synergistic effect compared with other algorithms, and the convergence time and convergence iteration of the improved algorithm are generally at a low level.
Originality/value
The contribution of this study is that the proposed framework enables project managers to clarify the interactions of the prefabricated construction process and provides guidance for project collaborative management. In addition, GSA helps to improve the probability of successful collaboration between potential partners, therefore enhancing client satisfaction.
Keywords
Acknowledgements
The research work was supported by the National Natural Science Foundation of China [Grant No. 72171025], the Natural Science Foundation of Shaanxi province [Grant No. 2019JQ-500], the General Foundation for Soft Science of Shaanxi province [Grant No. 2022KRM012], the Foundation for Youth Innovation Team of Shaanxi Universities [Grant No. 21JP010], the Fundamental Research Funds for the Central Universities [Grant No. 300102231640] and the Youth Innovation Team of Shaanxi Universities.
Citation
Du, Q., Qi, X., Zou, P.X.W. and Zhang, Y. (2023), "Bi-objective optimization framework for prefabricated construction service combination selection using genetic simulated annealing algorithm", Engineering, Construction and Architectural Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/ECAM-10-2022-1000
Publisher
:Emerald Publishing Limited
Copyright © 2023, Emerald Publishing Limited