Analysis of ant colonies algorithm and its modifications on the example of the solution of travelling salesman problem

Artur Zlatkin; Olha Marusik

Journal: Volume 22, No. 4, 2017

Pages: 21 – 26

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Analysis of ant colonies algorithm and its modifications on the example of the solution of travelling salesman problem

Abstract

In the article a detailed analysis of ant colonies algorithm – a system based on agents that imitate natural behavior of real ants – is carried out. The main modifications of ant algorithm, such as: Elitist Ant System algorithm, Ant-Q algorithm, Ant Colony System algorithm, Max-min Ant System algorithm, ASrank algorithm, are characterized. The proposed ant optimization algorithm for ttravelling salesman problem is described. Determining ant colonies algorithm as one of the most promising areas of "natural research", it is emphasized that the use of deterministic search strategy has allowed to find the optimal path much faster than by means of probabilistic strategy

Keywords

ant colonies; pheromone; travelling salesman problem; algorithm; modification

References

Subbotin, S. O., Oliynyk, A. O., Oliynyk, O. O. (2013) Non-iterative, evolutional and multi-agent methods of the synthesis of fuzzy logical and neuronet models: мonograph. In: S. O. Subbotin (ed.). Zaporizhhia: ZNTU, 375 p..
Ant colony optimization. URL: http://iridia.ulb.ac.be/~mdorigo/ACO/ACO.html
Goss, S., Aron, S. Deneubourg, J.-L., Pasteels, J.-M. (2016) Self-organized short-cuts in the Argentine ant, Naturwissens-chaften, vol. 76, pp. 579–581.
Kazharov, A. A., Kureychik, V. M. (2014) Ant algorithms for transport tasks solving. Izvestiya Rossiyskoy akademii nauk. Teoriya i sistemy upravleniya, № 1, pp. 32–45.
Shtovba, S. D. (2014) Ant algorithms, Exponenta Pro. Matematika v prilozheniyakh, № 4.
Dorigo, M. (2013) ant colony optimization. Scholarpedia.
Bonabeau, E. Dorigo, M.. Theraulaz, G. (2012) Swarm intelligence: from natural to artificial systems, Oxford University Press.
Vatutin, E. I., Titov, V. S. (2014) The analysis of the results of ant colony algorithm application in the task of the search of the way in the graph under constraints. Izvestiya Yuzhnogo federal'nogo universiteta. Tekhnicheskiye nauki, № 12 (161), pp. 111–120.

Suggested citation

Zlatkin, A., & Marusik, O. (2017). Analysis of ant colonies algorithm and its modifications on the example of the solution of travelling salesman problem . Bulletin of Cherkasy State Technological University, 22(4), 21-26.

[1] Subbotin, S. O., Oliynyk, A. O., Oliynyk, O. O. (2013) Non-iterative, evolutional and multi-agent methods of the synthesis of fuzzy logical and neuronet models: мonograph. In: S. O. Subbotin (ed.). Zaporizhhia: ZNTU, 375 p..

[2] Ant colony optimization. URL: http://iridia.ulb.ac.be/~mdorigo/ACO/ACO.html

[3] Goss, S., Aron, S. Deneubourg, J.-L., Pasteels, J.-M. (2016) Self-organized short-cuts in the Argentine ant, Naturwissens-chaften, vol. 76, pp. 579–581.

[4] Kazharov, A. A., Kureychik, V. M. (2014) Ant algorithms for transport tasks solving. Izvestiya Rossiyskoy akademii nauk. Teoriya i sistemy upravleniya, № 1, pp. 32–45.

[5] Shtovba, S. D. (2014) Ant algorithms, Exponenta Pro. Matematika v prilozheniyakh, № 4.

[6] Dorigo, M. (2013) ant colony optimization. Scholarpedia.

[7] Bonabeau, E. Dorigo, M.. Theraulaz, G. (2012) Swarm intelligence: from natural to artificial systems, Oxford University Press.

[8] Vatutin, E. I., Titov, V. S. (2014) The analysis of the results of ant colony algorithm application in the task of the search of the way in the graph under constraints. Izvestiya Yuzhnogo federal'nogo universiteta. Tekhnicheskiye nauki, № 12 (161), pp. 111–120.