Optimization of partially monotonic functions subject to bipolar fuzzy relation equations

A method to solve a latticed optimization problem constrained by a bipolar fuzzy relation equation is presented in this paper, under the hypothesis of a partially monotonic objective function. The solving strategy consists of transforming the problem into optimizing an order-preserving function in a...

Full description

Saved in:
Bibliographic Details
Published inInformation sciences Vol. 648; p. 119497
Main Authors Cornejo, M. Eugenia, Lobo, David, Medina, Jesús
Format Journal Article
LanguageEnglish
Published Elsevier Inc 01.11.2023
Subjects
Bipolar fuzzy relation equation
Extended aggregator
Negation operator
Nonlinear optimization
Extended aggregator
Negation operator
Bipolar fuzzy relation equation
Nonlinear optimization
Online AccessGet full text

Cover

More Information
Summary:A method to solve a latticed optimization problem constrained by a bipolar fuzzy relation equation is presented in this paper, under the hypothesis of a partially monotonic objective function. The solving strategy consists of transforming the problem into optimizing an order-preserving function in all arguments subject to another bipolar fuzzy relation equation. As a result, all the solutions of the original optimization problem can be deduced from the extremal elements of the feasible domain of the transformed problem. The presented approach embraces the particular case of linear optimization constrained by bipolar fuzzy relation equations.
ISSN:0020-0255
1872-6291
DOI:10.1016/j.ins.2023.119497