Title :
An accelerated approach for solving fuzzy relation equations with a linear objective function
Author :
Wu, Yan-Kuen ; Guu, Sy-Ming ; Liu, Julie Yu-Chih
Author_Institution :
Dept. of Ind. Manage., Van-Nun Inst. of Technol., Taoyuan, Taiwan
fDate :
8/1/2002 12:00:00 AM
Abstract :
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 (1999). 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 show that our initial upper bound is sharp.
Keywords :
computational complexity; fuzzy set theory; integer programming; minimax techniques; branch-and-bound; fuzzy relation equations; integer programming; jump-tracking; linear objective function; max-min composition; optimization; upper bound; Acceleration; Councils; Equations; Industrial relations; Lattices; Linear programming; Optimization methods; Testing; Upper bound; Vectors;
Journal_Title :
Fuzzy Systems, IEEE Transactions on
DOI :
10.1109/TFUZZ.2002.800657