Enhanced ODV based population seeding technique for ATSP

Author

Arthi, J. ; Nanthini, R. ; Sridevi, S. ; VicterPaul, P.

Author_Institution

Dept. of Inf. Technol., Sri Manakula Vinayagar Eng. Coll., Puducherry, India

fYear

2015

Firstpage

1

Lastpage

4

Abstract

This paper is to introduce the idea of having new population seeding technique for ATSP in genetic algorithm. Genetic algorithms are currently the most prominent and widely used computational models in search mechanisms. This enhanced technique is used in the ATSP with the aim to prove that ATSP can be solved efficiently with this technique compared to the other existing techniques. Here, ATSP is chosen as the test bed and proven for its efficiency by the datasets. We motivated to justify the proposed work using the performance factors like Convergence rate, error rate and convergence time.

Keywords

convergence; genetic algorithms; search problems; travelling salesman problems; ATSP; asymmetric travelling salesman problems; computational models; convergence rate; convergence time; enhanced ODV based population seeding technique; error rate; genetic algorithm; performance factors; search mechanisms; Cities and towns; Conferences; Convergence; Genetic algorithms; Memetics; Sociology; Statistics; Individual diversity; convergence rate; error rate; potential sequence;

fLanguage

English

Publisher

ieee

Conference_Titel

Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on

Conference_Location

Coimbatore

Print_ISBN

978-1-4799-6817-6

Type

conf

DOI

10.1109/ICIIECS.2015.7193041

Filename

7193041