最大-最小模糊关系不等式系统的最宽区间解的求解

IF 3.2 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS
Zhen-Zhen Chen , Yan-Kuen Wu , Xiao-Ming Li , Meng-Li Zhu
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引用次数: 0

摘要

建立了最大最小模糊关系不等式(FRI)系统,对教学信息资源分配和点对点文件共享系统进行建模。考虑到最优解的不稳定性和脆弱性,研究人员设计了最大最小FRI的最宽区间解,允许解在一定范围内波动。因此,系统中仍然存在许多,甚至无限的最宽区间解。为了更好地展示各种最宽区间解之间的差异,本文提出了系统宽度最大的最宽区间解。宽度最大的最宽区间解,顾名思义,与其他解相比,具有最大的区间宽度。因此,它有助于鲁棒解和稳定的系统行为。在新的理论见解的基础上,提出了一种新的求解方法,以获得最大宽度的最宽区间解。最后给出了数值算例,说明了该方法的具体步骤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Solving on widest-interval solutions with the maximum width for a system of max-min fuzzy relational inequalities
The system of max-min fuzzy relational inequalities (FRI) was established to model the problems of instructional information resource allocation and peer-to-peer file-sharing systems. Considering the instability and fragility of the optimal solution, researchers design the widest-interval solution of the max-min FRI to allow the solution to fluctuate within a certain range. As a result, there are still numerous, or even infinite, widest-interval solutions in the system. To better demonstrate the differences among the various widest-interval solutions, this paper proposes the widest-interval solutions with the maximum width for the system. The widest-interval solutions with the maximum width, as its name indicates, have the largest interval width compared to other solutions. Consequently, it can contribute to the robust solution and stable system behavior. Built upon new theoretical insights, a novel solution method is developed to obtain widest-interval solutions with the maximum width. A numerical illustration is presented to demonstrate the detailed procedure of this method.
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来源期刊
Fuzzy Sets and Systems
Fuzzy Sets and Systems 数学-计算机:理论方法
CiteScore
6.50
自引率
17.90%
发文量
321
审稿时长
6.1 months
期刊介绍: Since its launching in 1978, the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies. In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods. Furthermore, fuzzy sets have strong logical underpinnings in the tradition of many-valued logics.
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