.png){kind=icon}
Return
An accelerated approach for solving fuzzy relation equations with a linear objective function
.png){kind=icon}
PRE
AI
DOI：10.1109/TFUZZ.2002.800657.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In literature, the optimization model with a linear objective function subject to fuzzy relation equations has been converted into a 0-1 integer programming problem by Fang and Li. They proposed a jump-tracking branch-and-bound method to solve this 0-1 integer programming problem. In this paper, we propose an upper bound for the optimal objective value. Based on this upper bound and rearranging the structure of the problem, we present a backward jump-tracking branch-and-bound scheme for solving this optimization problem. A numerical example is provided to illustrate our scheme. Furthermore, testing examples show that the performance of our scheme is superior to the procedure in the paper by Fang and Li. Several testing examples do indeed show that our initial upper bound is sharp.
Keywords:
branch-and-bound method
fuzzy relation equations
jump-tracking technique
max-min composition
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
11.9
Papers:
5.0K
Citations:
2.9W
Organization
No organization information available
Cited Papers
.png){kind=icon}
ShareSaveShareSaveCatalytic combustion of 1,2-dichlorobenzene at low temperature over Mn-modified Co3O4 catalysts
PREAI
ShareSave
ShareSaveShareSave
View more