A genetic algorithm for solving fuzzy shortest path problems with mixed fuzzy arc lengths

被引：47

作者：

Hassanzadeh, Reza ^{[1
]}

Mahdavi, Iraj ^{[1
]}

Mahdavi-Amiri, Nezam ^{[2
]}

Tajdin, Ali ^{[1
]}

机构：

[1] Mazandaran Univ Sci & Technol, Dept Ind Engn, Babol Sar, Iran

[2] Sharif Univ Technol, Fac Math Sci, Tehran, Iran

来源：

MATHEMATICAL AND COMPUTER MODELLING | 2013年 / 57卷 / 1-2期

关键词：

Genetic algorithm; Fuzzy numbers; alpha-cut; Shortest path; Regression model; NETWORK;

D O I：

10.1016/j.mcm.2011.03.040

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

We are concerned with the design of a model and an algorithm for computing the shortest path in a network having various types of fuzzy arc lengths. First, a new technique is devised for the addition of various fuzzy numbers in a path using alpha-cuts by proposing a least squares model to obtain membership functions for the considered additions. Due to the complexity of the addition of various fuzzy numbers for larger problems, a genetic algorithm is presented for finding the shortest path in the network. For this, we apply a recently proposed distance function for comparison of fuzzy numbers. Examples are worked out to illustrate the applicability of the proposed approach. (C) 2011 Elsevier Ltd. All rights reserved.

引用

页码：84 / 99

页数：16

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