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Fuzzy relational equations: Resolution and optimization.

机译:模糊关系方程:分辨率和优化。

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摘要

Fuzzy relational equations play an important role as a platform in various applications of fuzzy sets and systems. The resolution and optimization of fuzzy relational equations are of our particular interests from both of the theoretical and applicational viewpoints. In this dissertation, fuzzy relational equations are treated in a unified framework and classified according to different aspects of their composite operations.;For a given finite system of fuzzy relational equations with a specific composite operation, the consistency of the system can be verified in polynomial time by constructing a potential maximum/minimum solution and characteristic matrix. The solution set of a consistent system can be characterized by a unique maximum solution and finitely many minimal solutions, or dually, by a unique minimum solution and finitely many maximal solutions. The determination of all minimal/maximal solutions is closely related to the detection of all irredundant coverings of a set covering problem defined by the characteristic matrix, which may involve additional constraints. In particular, for fuzzy relational equations with sup- T composition where T is a continuous triangular norm, the existence of the additional constraints depends on whether T is Archimedean or not.;Fuzzy relational equation constrained optimization problems are investigated as well in this dissertation. It is shown that the problem of minimizing an objective function subject to a system of fuzzy relational equations can be reduced in general to a 0-1 mixed integer programming problem. If the objective function is linear, or more generally, separable and monotone in each variable, then it can be further reduced to a set covering problem. Moreover, when the objective function is linear fractional, it can be reduced to a 0-1 linear fractional optimization problem and then solved via parameterization methods. However, if the objective function is max-separable with continuous monotone or unimodal components, then the problem can be solved efficiently, and its optimal solution set can be well characterized.
机译:模糊关系方程在模糊集和系统的各种应用中作为平台发挥着重要作用。从理论和应用的角度来看,模糊关系方程的解析和优化都是我们特别感兴趣的问题。本文将模糊关系方程在统一框架下进行处理,并根据其合成运算的不同方面进行分类。对于给定的具有特定合成运算的模糊关系方程有限系统,可以通过多项式验证系统的一致性。通过构造潜在的最大/最小解和特征矩阵来确定时间。一致系统的解集的特征在于唯一的最大解和有限的多个最小解,或双重地由唯一的最小解和有限的多个最大解来表征。所有最小/最大解的确定与特征矩阵定义的一组覆盖问题的所有多余覆盖的检测密切相关,这可能涉及其他约束。特别地,对于具有T组成的模糊关系方程,其中T是一个连续的三角范数,附加约束的存在取决于T是否为阿基米德方程。本文还研究了模糊关系方程约束的优化问题。结果表明,使目标函数最小化的问题可以简化为0-1混合整数规划问题。如果目标函数在每个变量中都是线性的,或更一般而言是可分离的且是单调的,则可以进一步将其简化为集合覆盖问题。此外,当目标函数是线性分数时,可以将其简化为0-1线性分数优化问题,然后通过参数化方法进行求解。但是,如果目标函数与连续的单调或单峰分量最大可分,则该问题可以得到有效解决,并且可以很好地表征其最佳解集。

著录项

  • 作者

    Li, Pingke.;

  • 作者单位

    North Carolina State University.;

  • 授予单位 North Carolina State University.;
  • 学科 Engineering Industrial.;Artificial Intelligence.;Operations Research.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 195 p.
  • 总页数 195
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:38:13

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