13,715
Views
11
CrossRef citations to date
0
Altmetric
Original Articles

Permutation rules and genetic algorithm to solve the traveling salesman problem

&
Pages 283-291 | Received 01 Nov 2018, Accepted 19 Apr 2019, Published online: 26 May 2019

References

  • Aarts, E. H., Korst, J. H., & van Laarhoven, P. J. (1988). A quantitative analysis of the simulated annealing algorithm: A case study for the traveling salesman problem. Journal of Statistical Physics, 50(1-2), 187–206. doi: 10.1007/BF01022991
  • Ardalan, Z., Karimi, S., Poursabzi, O., & Naderi, B. (2015). A novel imperialist competitive algorithm for generalized traveling salesman problems. Applied Soft Computing, 26, 546–555. doi: 10.1016/j.asoc.2014.08.033
  • Bernardino, R., & Paias, A. (2018). Solving the family the traveling salesman problem. European Journal of Operational Research, 267(2), 453–466. doi: 10.1016/j.ejor.2017.11.063
  • Chakraborty, B., & Chaudhuri, P. (2003). On the use of genetic algorithm with elitism in robust and nonparametric multivariate analysis. Austrian Journal of Statistics, 32(1-2), 13–27.
  • Chen, S. M., & Chien, C. Y. (2011). Solving the traveling salesman problem based on the genetic simulated annealing ant colony system with particle swarm optimization techniques. Expert Systems with Applications, 38(12), 14439–14450. doi: 10.1016/j.eswa.2011.04.163
  • Dong, G. F., Guo, W. W., & Tickle, K. (2012). Solving the traveling salesman problem using cooperative genetic ant systems. Expert Systems with Applications, 39(5), 5006–5011. doi: 10.1016/j.eswa.2011.10.012
  • Fiechter, C.-N. (1994). A parallel tabu search algorithm for large traveling salesman problems. Discrete Applied Mathematics, 51(3), 243–267. doi: 10.1016/0166-218X(92)00033-I
  • Gendreau, M., Laporte, G., & Semet, F. (1998). A tabu search heuristic for the undirected selective travelling salesman problem. European Journal of Operational Research, 106(2-3), 539–545. doi: 10.1016/S0377-2217(97)00289-0
  • Goldberg, D. (1989). Genetic algorithm in search, optimization, and machine learning. Addison Wesley Reading Menlo Park.
  • Grefenstette, J., Gopal, R., Rosmaita, B., & VanGucht, D. (1985). Genetic algorithms for the traveling salesman problem. Proceedings of the 1st International Conference on Genetic Algorithms and their Applications, New Jersey, 160–168.
  • Gunduz, M., Kiran, M. S., & Ozceylan, E. (2014). A hierarchic approach based on swarm intelligence to solve traveling salesman problem. Turkish Journal of Electrical Engineering & Computer Sciences, 23, 103–117. doi: 10.3906/elk-1210-147
  • Jati, G. K., Manurung, R., & Suyanto, S. (2013). Discrete firefly algorithm for traveling salesman problem: A new movement scheme. Elsevier Inc.
  • Jun-man, K., & Yi, Z. (2012). Application of an improved ant colony optimization on generalized traveling salesman problem. Energy Procedia, 17, 319–325. doi: 10.1016/j.egypro.2012.02.101
  • Knox, J. (1994). Tabu search performance on the symmetric traveling salesman problem. Computers & Operations Research, 21, 867–876. doi: 10.1016/0305-0548(94)90016-7
  • Larranaga, P., Kuijpers, C. M. H., Murga, R. H., Inza, I., & Dizdarevic, S. (1999). Genetic algorithms for the travelling salesman problem: A review of representations and operators. Artificial Intelligence Review, 13, 129–170. doi: 10.1023/A:1006529012972
  • Lawler, E. L., Lenstra, J. K., Kan, A. H. R., & Shmoys, D. B. (1985). The traveling salesman problem. New York: Wiley.
  • Leung, K. S., Jin, H. D., & Xu, Z. B. (2004). An expanding self-organizing neural network for the traveling salesman problem. Neurocomputing, 62, 267–292. doi: 10.1016/j.neucom.2004.02.006
  • Li, A. (2010). The operator of genetic algorithms to improve its properties. Journal of Modern Applied Science, 3, 60–62.
  • Li, M., Ma, J., Zhang, Y., Zhou, H., & Liu, J. (2015). Firefly algorithm solving multiple traveling salesman problem. Journal of Computational and Theoretical Nanoscience, 12(7), 1277–1281. doi: 10.1166/jctn.2015.3886
  • Mahi, M., Baykan, Ö. K., & Kodaz, H. (2015). A new hybrid method based on particle swarm optimization, ant colony optimization and 3-Opt algorithms for traveling salesman problem. Applied Soft Computing, 30, 484–490. doi: 10.1016/j.asoc.2015.01.068
  • Malek, M., Guruswamy, M., Pandya, M., & Owens, H. (1989). Serial and parallel simulated annealing and tabu search algorithms for the traveling salesman problem. Annals of Operations Research, 21(1), 59–84. doi: 10.1007/BF02022093
  • Masutti, T. A. S., & De Castro, L. N. (2009). A self-organizing neural network using ideas from the immune system to solve the traveling salesman problem. Information Sciences, 179(10), 1454–1468. doi: 10.1016/j.ins.2008.12.016
  • Matai, R., Mittal, M. L., & Singh, S. (2010). Traveling salesman problem, theory and applications. INTECH.
  • Mavrovouniotis, M., Muller, F. M., & Yang, S. (2017). Ant colony optimization with local search for dynamic traveling salesman problems. IEEE Transactions on Cybernetics, 47(7), 1743–1756. doi: 10.1109/TCYB.2016.2556742
  • Osaba, E., Javier, D. S., Sadollah, A., Bilbao, M. N., & Camacho, D. (2018). A discrete water cycle algorithm for solving the symmetric and asymmetric traveling salesman problem. Applied Soft Computing, 71, 277–290. doi: 10.1016/j.asoc.2018.06.047
  • Osaba, E., Yang, X.-S., Diaz, F., Garcia, P., & Carballedo, R. (2016). An improved discrete bat algorithm for symmetric and asymmetric traveling salesman problems. Engineering Applications of Artificial Intelligence, 48, 59–71. doi: 10.1016/j.engappai.2015.10.006
  • Ouaarab, A., Ahiod, B., & Yang, X.-S. (2014). Discrete cuckoo search algorithm for the travelling salesman problem. Neural Computing and Applications, 24, 1659–1669. doi: 10.1007/s00521-013-1402-2
  • Pasti, R., & De Castro, L. N. (2006). A neuro-immune network for solving the traveling sales man problem. Proceedings of the International Joint Conference on Neural Networks (IJCNN’06), IEEE, 16–21 July 2006, Vancouver, BC, Canada, 3760–3766.
  • Peker, M., Şen, B., & Kumru, P. Y. (2013). An efficient solving of the traveling salesman problem: The ant colony system having parameters optimized by the Taguchi method. Turkish Journal of Electrical Engineering & Computer Sciences, 21, 2015–2036. doi: 10.3906/elk-1109-44
  • Reinelt, G. (1997). TSPLIB. Retrieved from http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/. Universität Heidelberg, Germany
  • Sivanandam, S. N., & Deepa, S. N. (2007). Introduction to genetic algorithms. Springer.
  • Taillard, E. D., & Helsgaun, K. (2019). POPMUSIC for traveling salesman problem genetic algorithm for the traveling salesman problem. European Journal of Operational Research, 272(2), 420–429. doi: 10.1016/j.ejor.2018.06.039
  • Tsai, C. F., Tsai, C. W., & Tseng, C. C. (2004). A new hybrid heuristic approach for solving large traveling salesman problem. Information Sciences, 166(1-4), 67–81. doi: 10.1016/j.ins.2003.11.008
  • Yousefikhoshbakht, M., & Sedighpour, M. (2013). New imperialist competitive algorithm to solve the travelling salesman problem. International Journal of Computer Mathematics, 90(7), 1495–1505. doi: 10.1080/00207160.2012.758362
  • Zakir, H. A. (2010). Genetic algorithm for the traveling salesman problem using sequential constructive crossover operator. International Journal of Biometrics & Bioinformatics, 3(6), 96–105.