Applications of multi-agent systems from the perspective of construction management: A literature review

计算机科学 斯科普斯 透视图(图形) 独创性 管理科学 知识管理 供应链管理 知识体系 数据科学 过程管理 供应链 工程类 业务 社会学 政治学 定性研究 人工智能 法学 营销 社会科学 梅德林
作者
Liqun Xiang,Yongtao Tan,Qiping Shen,Xin Jin
出处
期刊:Engineering, Construction and Architectural Management [Emerald (MCB UP)]
卷期号:29 (9): 3288-3310 被引量:9
标识
DOI:10.1108/ecam-01-2021-0038
摘要

Purpose The applications of multi-agent systems (MASs) are considered to be among the most promising paradigms for detailed investigations and reliable problem-solving methods, and MAS applications make it possible for researchers and practitioners to better understand complex systems. Although a number of prior studies have been conducted to address complex issues that arise from construction projects, few studies have summarised the applications and discussed the capacity of MASs from the perspective of construction management. To fill the gap, this paper provides a comprehensive literature review of MAS applications from the perspective of construction management. Design/methodology/approach Web of Science and Scopus are the most commonly used international databases in conducting the literature reviews. A total of 86 relevant papers published in SCI-Expanded, SSCI and Ei Compendex journals related to the application of MASs from the perspective of construction management are selected to be analysed and discussed in this paper. Findings Based on the 86 collected publications, the utilisations of MASs to support the management of the supply chain and the improvement of project performance are identified from the perspective of construction management, the characteristics and barriers of current MAS applications are analysed, a framework for developing agent-based models to address complex problems is proposed, and future research directions of MAS applications are discussed. Originality/value This review can serve as a useful reference for scholars to enhance their understanding of the current research and guide future research on MASs. The proposed framework can help build agent-based models to address complex problems in construction management.
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