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)

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.

Keywords

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

References

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), 1313–1320.
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. 616–621), IEEE Publ.
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. 17–23), IEEE Publ.
4. 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.
5. 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.