About a discussion ‘‘Development a new mutation operator to solve the Traveling Salesman Problem by aid of genetic algorithms’’, by Murat Albayrak and Novruz Allahverdi, (2011). Expert System with Applications (38) (pp. 1313–1320)

Authors

  • Novruz Allahverdi Selcuk University

Keywords:

Genetic algorithms, Traveling Salesman Problem, algorithm Greedy Sub Tour Mutation (GSTM).

Abstract

In the Short Communication published in “Expert Systems with Application” in volume 41 2014, (Comments on "Albayrak, M., & Allahverdi N. (2011). Development a new mutation operator to solve the Traveling Salesman Problem by aid of Genetic Algorithms. Expert Systems with Applications, 38(3), 1313-1320": A Proposal of Good Practice; E. Osaba, E. Onieva, F. Diaz, R. Carballedo, Volume: 41, Issue: 4, Pages: 1530-1531, Part: 1, MARCH 2014) the Osoba E. et al have discussed our method to solve the Traveling Salesman Problem pointing that we use our developed new algorithm to compare different versions of a classical genetic algorithm, each of one with a different mutation operator and they write that this can generate some controversy. Here we shortly analyze the comment of Osaba E. et al to show that our comparing method has a chance of existence.

Downloads

Download data is not yet available.

References

Albayrak, M., & Allahverdi N. (2011). Development a new mutation operator to solve the Traveling Salesman Problem by aid of genetic algorithms. Expert Systems with Applications, 38(3), 1313–1320.

Freisleben, B., & Merz, P. (1996). A genetic local search algorithm for solving symmetric and asymmetric traveling salesman problems. In Proceedings of IEEE international conference on evolutionary computation (pp. 616–621), IEEE Publ.

Osaba, E., Carballedo, R., Diaz, F., & Perallos, A. (2013). Analysis of the suitability of using blind crossover operators in genetic algorithms for solving routing problems. In Proceedings of the 8th international symposium on applied computational intelligence and informatics (pp. 17–23), IEEE Publ.

Osaba, E., & Díaz, F. (2012). Comparison of a memetic algorithm and a tabu search algorithm for the traveling salesman problem. In Federated conference on computer science and information systems (FedCSIS) (pp. 131–136). IEEE.

Osaba E. et al. Comments on "Albayrak, M., & Allahverdi N. (2011). Development a new mutation operator to solve the Traveling Salesman Problem by aid of Genetic Algorithms, Expert Systems with Applications 41 (2014) 1530–1531.

Downloads

Published

01.04.2015

How to Cite

Allahverdi, N. (2015). About a discussion ‘‘Development a new mutation operator to solve the Traveling Salesman Problem by aid of genetic algorithms’’, by Murat Albayrak and Novruz Allahverdi, (2011). Expert System with Applications (38) (pp. 1313–1320). International Journal of Intelligent Systems and Applications in Engineering, 3(2), 52–53. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/109

Issue

Vol. 3 No. 2 (2015)

Section

Brief Report

License

All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.

IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.