Applications of λ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda $$\end{document}-dominance degree-based rough sets in conflict problems.

Multi-attribute group decision-making is the process of evaluating alternatives or choosing the best alternative based on a number of different factors. Preference relations offer effective techniques to depict the degree of preferences of decision-makers via a comparison of any two alternatives pairwise. By presenting the rough set based on the λ\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\lambda $$\end{document}-dominance degree, this research presents a generic framework for the analysis of multi-attribute and multi-decision information systems. There are only a maximum of six sets that can be obtained after applying a rough set technique based on the λ\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\lambda $$\end{document}-dominance degree to it for any times. This means that only six sets can adequately approximate all of the universe’s rough sets, with the lower and upper approximations of each set still lying among these six sets. The present study also focuses on the development of the two kinds of approximate precision, rough degree, approximate quality, approximate accuracy, and the relationship between them. Finally, a comparison between our suggested algorithms and Sun’s method is conducted, and the results show that the developed algorithms outperform the other models. [ABSTRACT FROM AUTHOR]