Geodesic
Self-configuring nature inspired algorithms for combinatorial optimization problems
Žurnal Sibirskogo federalʹnogo universiteta. Matematika i fizika, Tome 10 (2017) no. 4, pp. 463-473.

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In this work authors introduce and study the self-configuring Genetic Algorithm (GA) and the self-configuring Ant Colony Optimization (ACO) algorithm and apply them to one of the most known combinatorial optimization task — Travelling Salesman Problem (TSP). The estimation of suggested algorithms performance is fulfilled on well-known benchmark TSP and then compared with other heuristics such as Lin–Kernigan (3-opt local search) and Intelligent Water Drops algorithm (IWDs). Numerical experiments show that suggested approach demonstrates the competitive performance. Both adaptive algorithms show good results on these problems as they outperform other algorithms with their settings with average performance.
Keywords: travelling Salesman problem, genetic algorithm, ant colony optimization, intelligent water drops algorithm, self-configuration. 
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Olga Ev. Semenkina; Eugene A. Popov; Olga Er. Semenkina. Self-configuring nature inspired algorithms for combinatorial optimization problems. Žurnal Sibirskogo federalʹnogo universiteta. Matematika i fizika, Tome 10 (2017) no. 4, pp. 463-473. http://geodesic.mathdoc.fr/item/JSFU_2017_10_4_a7/

[1] D. Davendra (ed.), Traveling Salesman Problem, Theory and Applications, In. Tech. Publishing, 2010

[2] R. Schaefer, C. Cotta, J. Kolodziej, G. Rudolph, “Parallel Problem Solving from Nature”, PPSN 11th International Conference (Krakow, Poland, 2010), 11–15

[3] E. Semenkin, M. Semenkina, “Self-configuring genetic algorithm with modified uniform crossover operator”, Advances in swarm intelligence, ICSI, v. 1, LNCS, 7331, Springer, Heidelberg, 2012, 414–421

[4] E. Semenkin, M. Semenkina, “Spacecrafts' control systems effective variants choice with self-configuring genetic algorithm”, Proceedings of the 9th international conference on informatics in control, automation and robotics, v. 1, 2012, 84–93

[5] A. E. Eiben, J. E. Smith, Introduction to evolutionary computing, Springer-Verlag, Berlin–Heidelberg, 2003 | MR | Zbl

[6] M. Dorigo, L. M. Gambardella, “Ant colony system: a cooperative learning approach to the Traveling Salesman Problem”, IEEE transactions on evolutionary computation, 1997, 53–66 | DOI

[7] S. Lin, B. W. Kernigan, “An effective heuristic algorithm for the Traveling-Salesman Problem”, Operations research, 21:2 (1973), 498–516 | DOI | MR | Zbl

[8] H. Shah-Hosseini, “Problem solving by intelligent water drops”, Proceedings of IEEE congresson evolutionary computation (Swissotel the Stamford, Singapore, 2007), 3226–3231 | MR

[9] C. H. Papadimitriou, K. Steiglitz, Combinatorial optimization: Algorithms and complexity, Prentice-Hall, Englewood Cliffs, NJ, 1982 | MR | Zbl