Methodology for risk assessment of engineering procurement construction project based on the probabilistic hesitant fuzzy multiple attributes group decision making

IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Intelligent & Fuzzy Systems Pub Date : 2023-10-15 DOI:10.3233/jifs-231726
Dongmei Feng, Yifan Kang
{"title":"Methodology for risk assessment of engineering procurement construction project based on the probabilistic hesitant fuzzy multiple attributes group decision making","authors":"Dongmei Feng, Yifan Kang","doi":"10.3233/jifs-231726","DOIUrl":null,"url":null,"abstract":"With the continuous development of China’s economic system, the development of the construction industry is becoming more and more rapid, and the number and scale of construction projects are increasing. Due to the characteristics of large projects and long cycles, there are a large number of construction parties involved in construction projects. The increase in the number of participating partners makes it difficult for their projects to be integrated and managed by management departments such as owners, let alone for various parties to collaborate in the construction of projects. In order to effectively solve this problem, the engineering procurement construction (EPC) general contracting model has emerged. The risk assessment of EPC project is classical multiple attributes group decision making (MAGDM). The probabilistic hesitancy fuzzy sets (PHFSs) are used as a tool for characterizing uncertain information during the risk assessment of EPC project. In this paper, the classical grey relational analysis (GRA) method is extended to PHFSs. Firstly, the basic concept, comparative formula and Hamming distance of PHFSs are introduced. Then, the definition of the score values is employed to obtain the attribute weights based on the information entropy. Then, probabilistic hesitancy fuzzy GRA (PHF-GRA) method is built for MAGDM under PHFSs. Finally, a practical case study for risk assessment of EPC project is designed to validate the proposed method and some comparative studies are also designed to verify the applicability.","PeriodicalId":54795,"journal":{"name":"Journal of Intelligent & Fuzzy Systems","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2023-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Intelligent & Fuzzy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/jifs-231726","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

With the continuous development of China’s economic system, the development of the construction industry is becoming more and more rapid, and the number and scale of construction projects are increasing. Due to the characteristics of large projects and long cycles, there are a large number of construction parties involved in construction projects. The increase in the number of participating partners makes it difficult for their projects to be integrated and managed by management departments such as owners, let alone for various parties to collaborate in the construction of projects. In order to effectively solve this problem, the engineering procurement construction (EPC) general contracting model has emerged. The risk assessment of EPC project is classical multiple attributes group decision making (MAGDM). The probabilistic hesitancy fuzzy sets (PHFSs) are used as a tool for characterizing uncertain information during the risk assessment of EPC project. In this paper, the classical grey relational analysis (GRA) method is extended to PHFSs. Firstly, the basic concept, comparative formula and Hamming distance of PHFSs are introduced. Then, the definition of the score values is employed to obtain the attribute weights based on the information entropy. Then, probabilistic hesitancy fuzzy GRA (PHF-GRA) method is built for MAGDM under PHFSs. Finally, a practical case study for risk assessment of EPC project is designed to validate the proposed method and some comparative studies are also designed to verify the applicability.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于概率犹豫模糊多属性群决策的工程采购建设项目风险评估方法
随着中国经济体制的不断发展,建筑业的发展越来越快,建筑工程的数量和规模也越来越大。由于项目大、周期长的特点,建设项目涉及的施工方数量众多。参与合作伙伴数量的增加,使其项目难以被业主等管理部门整合管理,更难以实现各方在项目建设中的协同合作。为了有效解决这一问题,工程采购建设(EPC)总承包模式应运而生。EPC项目风险评估是典型的多属性群决策(MAGDM)。在EPC项目风险评估中,利用概率犹豫模糊集(PHFSs)来表征不确定性信息。本文将经典的灰色关联分析(GRA)方法推广到phfs。首先介绍了phfs的基本概念、比较公式和汉明距离。然后,利用分数值的定义,根据信息熵获得属性权重;然后,建立了PHF-GRA(概率犹豫模糊GRA)方法。最后,以EPC项目风险评估为例,对所提方法进行了验证,并进行了对比研究,验证了所提方法的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of Intelligent & Fuzzy Systems
Journal of Intelligent & Fuzzy Systems 工程技术-计算机:人工智能
CiteScore
3.40
自引率
10.00%
发文量
965
审稿时长
5.1 months
期刊介绍: The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
期刊最新文献
Systematic review and meta-analysis of the screening and identification of key genes in gastric cancer using DNA microarray database DBSCAN-based energy users clustering for performance enhancement of deep learning model Implementation of a dynamic planning algorithm in accounting information technology administration Robust multi-frequency band joint dictionary learning with low-rank representation Investigation on distributed scheduling with lot-streaming considering setup time based on NSGA-II in a furniture intelligent manufacturing
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1