A new fuzzy neural network model for solving fuzzy linear programming problems and its applications

被引：11
|
作者：
Effati, Sohrab [1 ]
Pakdaman, Morteza [2 ]
Ranjbar, Mahdi [3 ]
机构：
[1] Ferdowsi Univ Mashhad, Dept Appl Math, Mashhad, Iran
[2] Islamic Azad Univ, Mashhad branch, Sama Tech & Vocat Training Sch, Mashhad, Iran
[3] Tech Inst Higher Educ Quchan, Quchan, Iran
来源：
NEURAL COMPUTING & APPLICATIONS | 2011年 / 20卷 / 08期
关键词：
Fuzzy linear programming; Fuzzy derivative; Neural networks; Fuzzy shortest path problem; Fuzzy maximum flow problem; SHORTEST-PATH PROBLEM;
D O I：
10.1007/s00521-010-0491-4
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper is concentrated on two types of fuzzy linear programming problems. First type with fuzzy coefficients in the objective function and the second type with fuzzy right-hand side values and fuzzy variables. Considering fuzzy derivative and fuzzy differential equations, these kinds of problems are solved using a fuzzy neural network model. To show the applicability of the method, it is applied to solve the fuzzy shortest path problem and the fuzzy maximum flow problem. Numerical results illustrate the method accuracy and it's simple implementation.
引用
收藏
页码：1285 / 1294
页数：10
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