Multi-objective Fuzzy Bi-matrix Game Model: A Multicriteria Non-Linear Programming Approach

Zhang, Wei; Xing, Yumei; Qiu, Dong

doi:10.3390/sym9080159

Cited by 6 publications

(2 citation statements)

References 30 publications

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“…Many real-world problems can be listed that cover Nash Equilibrium. In [28] a multi-objective game model based on fuzzy goals has been proposed. In order to understand the concept further, consider the example of disease prediction using MEAF (Multi-objective Evolutionary Algorithm using Fuzzy Genetics); the two objectives for this EA are accuracy and interpretability.…”

Section: A Nash Equilibriummentioning

confidence: 99%

Disease Classification in Health Care Systems With Game Theory Approach

Raja

Asghar

2020

IEEE Access

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There are numerous cases in real life when we come across problems involving the optimization of multiple objectives simultaneously. One of the complexities of solving such problems is that often one or more objectives are usually conflicting under given conditions. In this study, the benefits of relying on a deployed Clinical Decision Support System (CDSS) concerning the overall reputation of a health facility has been studied. The analysis is performed in terms of a cooperative Bayesian game-theoretic model. The game is played between two players of which the first player is a patient who needs quick and accurate medical attention and the second player is the hospital administration that relies on medical experts as well as integrated multi-objective clinical data classification systems for decision-making. The proposed model ''MEAF''-Multi-objective Evolutionary Algorithm using Fuzzy Genetics attempts to address accuracy and interpretability simultaneously using Evolutionary Algorithms (EAs). This model enables a H CDSS to detect a disease accurately by using the available resources efficiently. The results of our simulation show that H CDSS produces better and accurate results in detecting disease with efficient resource utilization along with the reduced computational cost. This approach has also produced a better response for both players based on Bayesian Nash Equilibrium. Finally, the proposed model has been tested for accuracy, efficient resource utilization, and computationally cost-effective solution.

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Section: A Nash Equilibriummentioning

confidence: 99%

Disease Classification in Health Care Systems With Game Theory Approach

Raja

Asghar

2020

IEEE Access

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“…• Novel contributions to methodologies, like discrete optimization with fuzzy constraints [3], COMET [5], or fuzzy bi-matrix games [7].…”

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confidence: 99%

Fuzzy Techniques for Decision Making

Alcantud

2017

Symmetry

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This book contains the successful invited submissions to a Special Issue of Symmetry on the subject area of "Fuzzy Techniques for Decision Making".We invited contributions addressing novel techniques and tools for decision making (e.g., group or multi-criteria decision making), with notions that overcome the problem of finding the membership degree of each element in Zadeh's original model. We could garner interesting articles in a variety of setups, as well as applications. As a result, this Special Issue includes some novel techniques and tools for decision making, such as:

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Type-2 Neutrosophic Fuzzy Bimatrix Games Based on a New Distance Measure

Karmakar

Seikh²

2023

Studies in Fuzziness and Soft Computing

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Multi-objective Fuzzy Bi-matrix Game Model: A Multicriteria Non-Linear Programming Approach

Cited by 6 publications

References 30 publications

Disease Classification in Health Care Systems With Game Theory Approach

Disease Classification in Health Care Systems With Game Theory Approach

Fuzzy Techniques for Decision Making

Type-2 Neutrosophic Fuzzy Bimatrix Games Based on a New Distance Measure

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