Minimizing a linear objective function under a max-overlap function fuzzy relational equation constraint

Max-t-norm compositions are commonly utilized to optimize a linear objective function subject to fuzzy relational equations, especially, max-min and max-product compositions. However, the associativity is not forcefully needed in many cases. In this paper, the max-overlap function composition is con...

Full description

Saved in:
Bibliographic Details
Published inFuzzy sets and systems Vol. 447; pp. 1 - 21
Main Author Fang, Bo Wen
Format Journal Article
LanguageEnglish
Published Elsevier B.V 15.10.2022
Subjects
Online AccessGet full text
ISSN0165-0114
1872-6801
DOI10.1016/j.fss.2021.12.005

Cover

More Information
Summary:Max-t-norm compositions are commonly utilized to optimize a linear objective function subject to fuzzy relational equations, especially, max-min and max-product compositions. However, the associativity is not forcefully needed in many cases. In this paper, the max-overlap function composition is considered for the same optimization model. Then some properties of the solution set are obtained. According to these properties, the characterization of the optimal solution for the optimization model is proposed. Furthermore, a simple value matrix with rules is proposed to reduce problem size. Thus, a solution procedure is presented for determining optimal solutions without translating such an optimization problem into two sub-problems. A numerical example is provided to illustrate the procedure.
ISSN:0165-0114
1872-6801
DOI:10.1016/j.fss.2021.12.005