A COMPARATIVE STUDY OF VARIOUS METHODS OF ANN FOR SOLVING TSP PROBLEM

INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY

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Field Value
 
Title A COMPARATIVE STUDY OF VARIOUS METHODS OF ANN FOR SOLVING TSP PROBLEM
 
Creator Roy, Sharadindu
Sen Sarma, Prof Samer
chakravorty, Soumyadip
Maity, Suvodip
 
Subject Computer Science; Information Technology
TSP; Travelling Salesman Problem; ANN; Artificial Neural Network; HN; Hopfield Network; EN; Elastic Net; SRN; Simultaneous Recurrent Network
 
Description Abstract This paper represents TSP (Travelling Salesman Problem) by using Artificial Neural Networks.A comparative study of various methods of ANN is shown here for solving TSP problem.The Travelling Salesman Problem is a classical combinational optimization problem, which is a simple to state but very difficult to solve. This problem is to find the shortest possible tour through a set of N vertices so that each vertex is visited exactly once. TSP can be solved by Hopfield Network, Self-organization Map, and Simultaneous Recurrent Network. Hopfield net is a fully connected network, where every vertex is connected with each other forwardly and backwardly. So starting the walk from a vertex we can travel all the other vertex exactly once and return to starting vertex again.
 
Publisher CIRWORLD
 
Date 2005-01-30
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://cirworld.com/index.php/ijct/article/view/311
 
Source INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY; Vol 4 No 1a; 19-28
2277-3061
 
Language eng
 
Relation http://cirworld.com/index.php/ijct/article/view/311/2943
 
Rights Copyright (c) 2016 INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY
http://creativecommons.org/licenses/by/4.0
 

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