Paper Info
Title
A genetic algorithm for solving fuzzy shortest path problems with mixed fuzzy arc lengths
Abstract
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 α-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.
Year
DOI
Venue
2013
10.1016/j.mcm.2011.03.040
Mathematical and Computer Modelling
Keywords
Field
DocType
Genetic algorithm,Fuzzy numbers,α-cut,Shortest path,Regression model
Mathematical optimization,Shortest path problem,Defuzzification,Fuzzy set operations,Fuzzy transportation,Yen's algorithm,Shortest Path Faster Algorithm,Fuzzy number,Mathematics,K shortest path routing
Journal
Volume
Issue
ISSN
57
1
0895-7177
Citations 
PageRank 
References 
14
0.69
10
Authors
4
Name
Order
Citations
PageRank
Reza Hassanzadeh1766.02
Iraj Mahdavi238832.30
Nezam Mahdavi-amiri337139.95
Ali Tajdin4192.52