NOVRUZ ALLAHVERDİ

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; 3, pp. 13131320.

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" [1]: A Proposal of Good Practice; E. Osaba, E. Onieva, F. Diaz, R. Carballedo, Volume: 41, Issue: 4, Pages: 1530-1531, Part: 1, March 2014) [4] 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.

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[1] [1] 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), 13131320.

[2] [2] 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. 616621), IEEE.

[3] [3] 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. 1723). IEEE.

[4] [4] Osaba E., Onieva E., Diaz F., Carballedo R. 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; Volume: 41, Issue: 4, Pages: 1530-1531, Part: 1, March 2014)

[5] [5] 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. 131136, IEEE.

[6] [6] Osaba E., Carballedo R., Diaz F., Onieva E., Lopez P., Perallos A. On the influence of using initialization functions on genetic algorithms solving combinatorial optimization problems: a first study on the TSP. 2014 IEEE Conference on Evolvıng and Adaptıve Intellıgent Systems (EAIS 2014), Linz, Austria; 06/2014.

[7] [7] Osaba E., Carballedo R., Diaz F., Onieva E., I. de la Iglesia, Perallos A. (2014), Crossover vs. Mutation: A Comparative Analysis of the Evolutionary Strategy of Genetic Algorithms Applied to Combinatorial Optimization Problems. The Scientific World Journal, August, 2014, 22 p.