A novel hybrid decision-making model for team building in cloud service environment. Issue 12 (2nd December 2019)

• Record Type: Journal Article
• Authors: Fan, Jiashuang; Yu, Suihuai; Chu, Jianjie; Cheng, Fangmin; Fan, Hao; Wang, Long; Wang, Hui; Li, Jie
• Is Part Of: International journal of computer integrated manufacturing. Volume 32:Issue 12(2019)
• Page Start: 1134
• Page End: 1153
• Publication Date: 2019-12-02
• Subjects: Decision-making -- optimal selection -- cloud service environment -- rough set theory -- service team; Computer integrated manufacturing systems -- Periodicals; 670.427
• DOI: 10.1080/0951192X.2019.1686172
• Languages: English
• ISSNs: 0951-192X

Abstract

ABSTRACT: Cloud environment is associated with people and it has become a hot research topic owing to its characteristics of smartness. An increasing number of service providers is clustered in the cloud environment. However, the study of optimal selection of service team has not been extensively studied. To solve the problem of optimal decision-making for service team in the cloud environment, a novel hybrid decision-making approach based on improved rough set theory is proposed. There are three steps in the improved approach. First, the relationship between user requirements and team elements is analysed using the least squares method and quantification theory, and an evaluation index system for the virtual team based on user's personalised needs is constructed. Second, by combining the rough set theory and intuitionistic fuzzy number, the weight of evaluation index of the virtual team is determined. Third, a decision-making system based on the rough approximation method is developed to compare and rank the alternatives. The concepts of rough boundary and rough number are introduced to express more integrated information in handling vagueness and uncertainty. Finally, the validity and feasibility of this method are verified using the example of building a virtual team in a cloud service environment.