Computationally Simple and Efficient Method for Solving Real-Life Mixed Intuitionistic Fuzzy 3D Assignment Problems

Kumar, P. Senthil

doi:10.4018/ijssci.291715

Cited by 22 publications

(10 citation statements)

References 72 publications

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“…Kumar applied fuzzy theory to transportation problems and transform the fuzzy transportation problem into a clear-cut problem. Furthermore, he presented algorithms for solving optimization problems using fuzzy and intuitionistic fuzzy sets, and found the optimal objective value [41][42][43].…”

Section: Related Workmentioning

confidence: 99%

Fuzzy TOPSIS-based privacy measurement in multiple online social networks

Guo

Yao

Lin

et al. 2023

Complex Intell. Syst.

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Information leakage has become an urgent problem in multiple Online Social Networks (OSNs). The interactive communication of users has raised several privacy concerns. However, the current related work on privacy measurement only considers the privacy disclosure of user profile settings, ignoring the importance of profile attributes. To solve the efficient measurement problem, we consider the influence of attribute weight on privacy disclosure scores and propose a privacy measurement method by quantifying users’ privacy disclosure scores in social networks. Through introducing Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), we propose a Privacy Scores calculation model based on Fuzzy TOPSIS decision method (PSFT), that is more accurate calculate users’ privacy disclosure scores and that can improve users’ privacy awareness in multiple OSNs. Users can reasonably set the attribute file configuration based on privacy scores and attribute weight. We conduct extensive experiments on synthetic data set and real data set. The results of the experiments demonstrate the effectiveness of our model.

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Section: Related Workmentioning

confidence: 99%

Fuzzy TOPSIS-based privacy measurement in multiple online social networks

Guo

Yao

Lin

et al. 2023

Complex Intell. Syst.

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“…Both internal optimization and overall optimization are great challenges [30][31][32][33][34]. We design a progressive iteration method to optimize the objective function of KAPC in two steps.…”

Section: Progressive Iterationmentioning

confidence: 99%

Knowledge-aware progressive clustering for social image

Li,

Dong,

Liu

et al. 2023

Complex Intell. Syst.

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Social image data refer to the annotated image with tags in social media, in which the tags are always labeled by users. Integrating the visual and textual information of social image can obtain accurate and comprehensive feature and improve clustering performance. However, the heterogeneous gap between tags and images makes it difficult to reasonably organize the social images. In addition, the tags are often sparse and incomplete due to personal preference and cognition differences of users. To solve these problems, we propose a novel knowledge-aware progressive clustering (KAPC) method, which employs human knowledge to guide the cross-modal clustering of social images. Firstly, we design a dual-similarity semantic expansion strategy to complement the sparse tags with human knowledge, which constructs a more complete semantic similarity matrix for tags through knowledge graphs. Secondly, we define an objective function based on information theory to bridge the heterogeneous gap, which align inter-modal cluster distribution to explore the correlation between visual and textual information. Finally, a progressive iteration method is designed to make the two modalities guide each other and obtain better performance of social image clustering. Extensive experiments on four social image datasets verify the effectiveness of the proposed KAPC method.

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“…Mathematical modeling plays a crucial role in solving real-life problems across various fields such as engineering [1,2], biology [3,4], economics [5,6], and many others. In this study, the example of an agreement between a company and three adjacent villages to provide electricity and water services will be predominantly utilized.…”

Section: Introductionmentioning

confidence: 99%

Analyzing cooperative game theory solutions: core and Shapley value in cartesian product of two sets

Slime,

El Kamli,

Ould Khal

2024

Front. Appl. Math. Stat.

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The core and the Shapley value stand out as the most renowned solutions for addressing sharing problems in cooperative game theory. These concepts are widely acknowledged for their effectiveness in tackling negotiation, resource allocation, and power dynamics. The present study aims to extend various notions of cooperative games from the standard set N to a new class of cooperative games defined on the cartesian product N×N′ (utilizing the specific coalition A*B). This extension encompasses fundamental concepts such as rationality, core, and Shapley value. The findings presented in this study demonstrate that the core concept as a solution yields a set of imputations without favoring any specific point within the set, in contrast to the Shapley value, which offers a singular solution. Moreover, the results confirm that the Shapley value satisfies the conditions defining the core of a game. Through both theoretical analysis and numerical findings, employing a practical example, it becomes evident that the Shapley value offers a more distinct solution to the sharing problem compared with the core solution.

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Computationally Simple and Efficient Method for Solving Real-Life Mixed Intuitionistic Fuzzy 3D Assignment Problems

Cited by 22 publications

References 72 publications

Fuzzy TOPSIS-based privacy measurement in multiple online social networks

Fuzzy TOPSIS-based privacy measurement in multiple online social networks

Knowledge-aware progressive clustering for social image

Analyzing cooperative game theory solutions: core and Shapley value in cartesian product of two sets

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