학술논문

Optimization-Based Three-Way Decisions With Interval-Valued Intuitionistic Fuzzy Information
Document Type
Periodical
Source
IEEE Transactions on Cybernetics IEEE Trans. Cybern. Cybernetics, IEEE Transactions on. 53(6):3829-3843 Jun, 2023
Subject
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Robotics and Control Systems
General Topics for Engineers
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Mathematical models
Optimization
Computational modeling
Optimized production technology
Numerical models
Rough sets
Fuzzy sets
Interval-valued intuitionistic fuzzy loss function
interval-valued intuitionistic fuzzy sets (IVIFSs)
Karush–Kuhn–Tucker (KKT) condition
optimization models
three-way decisions
Language
ISSN
2168-2267
2168-2275
Abstract
Due to the effectiveness and advantages of interval-valued intuitionistic fuzzy sets (IVIFSs) in evaluating uncertainty and risk, we introduce IVIFSs into loss functions of decision-theoretic rough sets (DTRSs) and propose an optimization-based approach to interval-valued intuitionistic fuzzy three-way decisions. First, based on the classical DTRSs and two previous optimization models, we construct a new concise linear programming model for simultaneously determining the threshold pair. Our model is mathematically equivalent to the DTRSs and the previous models under the Karush–Kuhn–Tucker (KKT) condition. Second, we extend the constructed model via the IVIFSs of loss functions and we discuss the relations between these loss functions based on a similarity measure function-based ranking method and a multiple score function-based ranking method for IVIFSs. Third, we develop our extended models via two ranking methods and we prove the existence and uniqueness of the optimal solution of the model. The optimization-based method, along with its algorithm for three-way decisions, is designed in an interval-valued intuitionistic fuzzy environment. Compared to the latest existing methods, our method has three advantages (see Advantages 1–3). Finally, an illustrative example is considered, and the advantages of our approach are demonstrated by this example.