ASCE International Conference on Computing in Civil Engineering 2019
Integrating Fuzzy Agent-Based Modeling and Multi-Criteria Decision-Making for Analyzing Construction Crew Performance
Publication: Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation
ABSTRACT
Construction practitioners face considerable challenges when selecting economically feasible policies for maximizing crew motivation and performance. This paper proposes a methodology for integrating fuzzy agent-based modeling (FABM) with multi-criteria decision-making (MCDM) to develop a decision support system, which takes into account the complex relationships and social interactions between crews and crew members. This decision support system both accounts for the dynamic construction environment and captures the subjective and the objective factors that influence crew motivation and performance. The proposed methodology and decision support system are illustrated with a case study, which demonstrates that integration of FABM with MCDM serves to address subjective uncertainty when analyzing different policies related to crew motivation and performance. These findings can in turn help construction practitioners adopt economically feasible strategies to improve the motivation and performance of their crews, thus increasing their competitiveness in the market.
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Published In
Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation
Pages: 569 - 576
Editors: Yong K. Cho, Ph.D., Georgia Institute of Technology, Fernanda Leite, Ph.D., University of Texas at Austin, Amir Behzadan, Ph.D., Texas A&M University, and Chao Wang, Ph.D., Louisiana State University
ISBN (Online): 978-0-7844-8242-1
Copyright
© 2019 American Society of Civil Engineers.
History
Published online: Jun 13, 2019
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