A multi-criteria decision-making model for analyzing a project-driven supply chain under interval type-2 fuzzy sets

供应链 加权 排名(信息检索) 计算机科学 弹性(材料科学) 区间(图论) 临界性 供应链管理 运筹学 关键路径法 项目管理 过程管理 系统工程 业务 数学 人工智能 工程类 营销 核物理学 放射科 物理 组合数学 热力学 医学
作者
Y. Dorfeshan,Fariborz Jolai,Seyed Meysam Mousavi
出处
期刊:Applied Soft Computing [Elsevier BV]
卷期号:148: 110902-110902 被引量:8
标识
DOI:10.1016/j.asoc.2023.110902
摘要

Reviewing and integrating decisions in the supply chain and project management is crucial. This problem is known as a project-driven supply chain problem. By the growing dependency of project-driven companies on suppliers since they prefer to concentrate on their core and subcontracting processes, the project-based organization's dependence on suppliers has increased. A project-driven supply chain (PDSC) focuses on integrating project management activities into the supply chain. In this paper, a new model is presented for the integration of supply chain and project management decisions. Firstly, a new method is proposed to determine the resilience score of suppliers. This new model consists of three parts: the weighting of criteria, the weighting of experts, and the ranking of suppliers. To give weight to the experts, a new version of the combinative distance-based assessment (CODAS) method is presented based on the average and positive ideal concepts. Also, the importance of the criteria is specified by an expanded best-worst method (BWM). Computing the resilience score of suppliers is done through a developed CODAS method that is extended by the average and positive concepts. Furthermore, in order to consider the uncertainty of project-driven supply chain problems, interval type-2 fuzzy sets (IT2FSs) are used. Secondly, a new subtraction operation is defined to avoid producing negative in recursive critical path method (CPM) calculations in the IT2F environment. Also, the criticality score of the project's activities is defined. According to the criticality and resilience indexes of activities, suggestions are made to project management to prevent delays. Finally, a case study of hospital construction is solved to illustrate the strengths of the proposed model.
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