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CPT‐TODIM method for bipolar fuzzy multi‐attribute group decision making and its application to network security service provider selection
Author(s) -
Zhao Mengwei,
Wei Guiwu,
Wei Cun,
Guo Yanfeng
Publication year - 2021
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.22367
Subject(s) - computer science , fuzzy logic , selection (genetic algorithm) , service provider , field (mathematics) , prospect theory , network security , computer security , service (business) , operations research , artificial intelligence , mathematics , business , finance , marketing , pure mathematics
Abstract Network security is a very important issue in recent years. For many new or traditional enterprises, utilizing internet to store and analyze data has become an indivisible part of their production and operation. But many enterprises do not have enough ability to ensure the security of information, so the choice of the optimal network security service provider has become a practical problem faced by many ordinary companies. In this paper, we establish bipolar fuzzy interactive multi‐criteria decision‐making (TODIM) based on the cumulative prospect theory (CPT‐TODIM) model for dealing with the problem of multi‐attribute group decision making, and this special model is applied to the field of network security about the issue of network security service provider selection. The second and third parts of this paper introduce the knowledge of bipolar fuzzy and the initial CPT‐TODIM method. In the fourth part, we discuss the bipolar fuzzy CPT‐TODIM model in detail. In the last two parts of this article, the method proposed in this paper is applied to the field of network security provider selection and compared with other methods. The results show that bipolar fuzzy CPT‐TODIM method with unique advantages in some aspects is reasonable and effective, and can be applied to more uncertain decision fields. It is hoped that this method can help enterprises make better decisions.