A Divide-and-Conquer Approach for Solving Fuzzy Max-Archimedean t-Norm Relational Equations

A system of fuzzy relational equations with the max-Archimedean t-norm composition was considered. The relevant literature indicated that this problem can be reduced to the problem of finding all the irredundant coverings of a binary matrix. A divide-and-conquer approach is proposed to solve this pr...

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Main Authors: Jun-Lin Lin, Hung-Chjh Chuan, Laksamee Khomnotai
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Abstract and Applied Analysis
Online Access:http://dx.doi.org/10.1155/2014/315290
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spelling doaj-1127f37941a441d7b333c313d66b32082020-11-24T22:43:32ZengHindawi LimitedAbstract and Applied Analysis1085-33751687-04092014-01-01201410.1155/2014/315290315290A Divide-and-Conquer Approach for Solving Fuzzy Max-Archimedean t-Norm Relational EquationsJun-Lin Lin0Hung-Chjh Chuan1Laksamee Khomnotai2Department of Information Management and Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taoyuan 32003, TaiwanDepartment of Information Management and Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taoyuan 32003, TaiwanDepartment of Information Management and Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taoyuan 32003, TaiwanA system of fuzzy relational equations with the max-Archimedean t-norm composition was considered. The relevant literature indicated that this problem can be reduced to the problem of finding all the irredundant coverings of a binary matrix. A divide-and-conquer approach is proposed to solve this problem and, subsequently, to solve the original problem. This approach was used to analyze the binary matrix and then decompose the matrix into several submatrices such that the irredundant coverings of the original matrix could be constructed using the irredundant coverings of each of these submatrices. This step was performed recursively for each of these submatrices to obtain the irredundant coverings. Finally, once all the irredundant coverings of the original matrix were found, they were easily converted into the minimal solutions of the fuzzy relational equations. Experiments on binary matrices, with the number of irredundant coverings ranging from 24 to 9680, were also performed. The results indicated that, for test matrices that could initially be partitioned into more than one submatrix, this approach reduced the execution time by more than three orders of magnitude. For the other test matrices, this approach was still useful because certain submatrices could be partitioned into more than one submatrix.http://dx.doi.org/10.1155/2014/315290
collection DOAJ
language English
format Article
sources DOAJ
author Jun-Lin Lin
Hung-Chjh Chuan
Laksamee Khomnotai
spellingShingle Jun-Lin Lin
Hung-Chjh Chuan
Laksamee Khomnotai
A Divide-and-Conquer Approach for Solving Fuzzy Max-Archimedean t-Norm Relational Equations
Abstract and Applied Analysis
author_facet Jun-Lin Lin
Hung-Chjh Chuan
Laksamee Khomnotai
author_sort Jun-Lin Lin
title A Divide-and-Conquer Approach for Solving Fuzzy Max-Archimedean t-Norm Relational Equations
title_short A Divide-and-Conquer Approach for Solving Fuzzy Max-Archimedean t-Norm Relational Equations
title_full A Divide-and-Conquer Approach for Solving Fuzzy Max-Archimedean t-Norm Relational Equations
title_fullStr A Divide-and-Conquer Approach for Solving Fuzzy Max-Archimedean t-Norm Relational Equations
title_full_unstemmed A Divide-and-Conquer Approach for Solving Fuzzy Max-Archimedean t-Norm Relational Equations
title_sort divide-and-conquer approach for solving fuzzy max-archimedean t-norm relational equations
publisher Hindawi Limited
series Abstract and Applied Analysis
issn 1085-3375
1687-0409
publishDate 2014-01-01
description A system of fuzzy relational equations with the max-Archimedean t-norm composition was considered. The relevant literature indicated that this problem can be reduced to the problem of finding all the irredundant coverings of a binary matrix. A divide-and-conquer approach is proposed to solve this problem and, subsequently, to solve the original problem. This approach was used to analyze the binary matrix and then decompose the matrix into several submatrices such that the irredundant coverings of the original matrix could be constructed using the irredundant coverings of each of these submatrices. This step was performed recursively for each of these submatrices to obtain the irredundant coverings. Finally, once all the irredundant coverings of the original matrix were found, they were easily converted into the minimal solutions of the fuzzy relational equations. Experiments on binary matrices, with the number of irredundant coverings ranging from 24 to 9680, were also performed. The results indicated that, for test matrices that could initially be partitioned into more than one submatrix, this approach reduced the execution time by more than three orders of magnitude. For the other test matrices, this approach was still useful because certain submatrices could be partitioned into more than one submatrix.
url http://dx.doi.org/10.1155/2014/315290
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