具有加法-最小积模糊关系不等式约束的最小最大规划问题

IF 4.8 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Qiu, Jianjun, Yang, Xiaopeng
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引用次数: 3

摘要

本文研究了一类新的模糊关系系统,即带有加法-最小积组合运算的模糊关系不等式,用于建立点对点文件共享系统的模型。研究了该加法-最小积系统的一些性质。然后我们描述解集的结构。此外,为了减少网络拥塞,提高数据传输的稳定性,建立并研究了一个具有加法-最小积模糊关系不等式约束的最小最大规划问题。我们将这个最小最大规划问题分解为若干子问题,每个子问题都有一个方程的约束。基于这些子问题的最优解,我们可以求解原始模糊关系最小最大规划问题。本文提出了两种计算复杂度为多项式的算法来寻找问题的最优解。通过一个算例验证了算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Min–max programming problem with constraints of addition-min-product fuzzy relation inequalities

In this paper, we study a new type of fuzzy relation system called fuzzy relational inequalities with addition-min-product composition operations to model a peer-to-peer (P2P) file sharing system. Some properties of this addition-min-product system are investigated. We then characterize the structure of the solution set. Furthermore, to reduce the network congestion and improve the stability of data transmission, a min–max programming problem with constraints of addition-min-product fuzzy relation inequalities is established and investigated. We divide this min–max programming problem into several subproblems with the constraint of a single equation. Based on the optimal solutions to these subproblems, we can solve the original fuzzy relation min–max programming problem. Two algorithms, with polynomial computational complexity, are developed to search for an optimal solution to our studied problem. The validity of the algorithms is examined through a numerical example.

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来源期刊
Fuzzy Optimization and Decision Making
Fuzzy Optimization and Decision Making 工程技术-计算机:人工智能
CiteScore
11.50
自引率
10.60%
发文量
27
审稿时长
6 months
期刊介绍: The key objective of Fuzzy Optimization and Decision Making is to promote research and the development of fuzzy technology and soft-computing methodologies to enhance our ability to address complicated optimization and decision making problems involving non-probabilitic uncertainty. The journal will cover all aspects of employing fuzzy technologies to see optimal solutions and assist in making the best possible decisions. It will provide a global forum for advancing the state-of-the-art theory and practice of fuzzy optimization and decision making in the presence of uncertainty. Any theoretical, empirical, and experimental work related to fuzzy modeling and associated mathematics, solution methods, and systems is welcome. The goal is to help foster the understanding, development, and practice of fuzzy technologies for solving economic, engineering, management, and societal problems. The journal will provide a forum for authors and readers in the fields of business, economics, engineering, mathematics, management science, operations research, and systems.
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