Application of the Ant Colony Algorithm to the Routing Problem
DOI:
https://doi.org/10.37387/ipc.v14i1.435Keywords:
Graph, Hamiltonian path, Traveling Salesman Problem, ant colony algorithm, tourismAbstract
The main objective of this article is to determine a tourist route in Panama City through the implementation of an ant colony algorithm. This problem falls within the realm of Graph Theory, specifically in the classical challenge of finding a path that passes through multiple points of interest, complying with the restriction of visiting each point only once and ending at a specific location. If we add the additional constraint of seeking the shortest route possible, the problem becomes a Traveling Salesman Problem (TSP). Through this study, it has been concluded that the ant colony algorithm employed provides efficient solutions within a relatively short timeframe. Therefore, its implementation in other types of optimization problems is strongly recommended. The ant colony algorithm's ability to adapt and intelligently explore the solution space has proven to be highly effective in solving this tourist route problem in Panama City.
Downloads
References
Bonabeau, E., Dorigo, M., & Theraulaz, G. (1999). Swarm intelligence: from natural to artificial systems (No. 1). Oxford university press.
Chen, S.-T., Wu, T.-H., Ye, R.-J., Lee, L.-C., Huang, W.-Y., Lin, Y.-H., & Wang, B.-Y. (2023). Application of Ant Colony Optimization Computing to a Recommended Travel Itinerary Planning System with Repeatedly Used Nodes. Applied Sciences, 13(24), 13221. https://doi.org/10.3390/app132413221
Colorni, A., Dorigo, M., & Maniezzo, V. (1991, December). Distributed optimization by ant colonies. In Proceedings of the first European conference on artificial life (Vol. 142, pp. 134-142).
Deneubourg, J. L., Aron, S., Goss, S. A. P. J. M., Pasteels, J. M., & Duerinck, G. (1986). Random behaviour, amplification processes and number of participants: how they contribute to the foraging properties of ants. Physica D: nonlinear phenomena, 22(1-3), 176-186.
Dorigo, M. (1992). Optimization, learning and natural algorithms. Ph. D. Thesis, Politecnico di Milano.
Dorigo, M., Birattari, M., & Stutzle, T. (2006). Ant colony optimization. IEEE computational intelligence magazine, 1(4), 28-39.
Grassé, P. P. (1959). La reconstruction du nid et les coordinations interindividuelles chez Bellicositermes natalensis et Cubitermes sp. la théorie de la stigmergie: Essai d'interprétation du comportement des termites constructeurs. Insectes sociaux, 6, 41-80.
Jiang, X., & Wang, L. (2022). Genetic Algorithm for Tourism Route Planning Considering Time Constraints. International Journal of Engineering Trends and Technology, 70(1), 171–179. https://ijettjournal.org/archive/ijett-v70i1p219
Panigrahi, B. K., Shi, Y., & Lim, M. H. (Eds.). (2011). Handbook of swarm intelligence: concepts, principles and applications (Vol. 8). Springer Science & Business Media.
Trujillo, J. (2019). Grafos hamiltonianos aplicado al turismo de Panamá. Investigación Y Pensamiento Crítico, 7(1), 109–113. https://doi.org/10.37387/ipc.v7i1.12
Yang, X. S., Cui, Z., Xiao, R., Gandomi, A. H., & Karamanoglu, M. (Eds.). (2013). Swarm intelligence and bio-inspired computation: theory and applications. Newnes.
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 info:eu-repo/semantics/openAccess
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
1. The authors preserves the patrimonial rights (copyright) of the published works, and favors and allows their reuse.
2. The journal (and its contents) use Creative Commons licenses, specifically the CC BY NC SA type, where: "the beneficiary of the license has the right to copy, distribute, display and represent the work and make derivative works provided you acknowledge and cite the work in the manner specified by the author or licensor."
3. They can be copied, used, disseminated, transmitted and exhibited publicly, provided that: i) the authorship and the original source of its publication (magazine, publisher and URL, DOI of the work) are cited; ii) are not used for commercial purposes.
4. Conditions of self-archiving. Authors are encouraged to electronically disseminate the post-print versions (version evaluated and accepted for publication), as it favors their circulation and dissemination, increases their citation and reach among the academic community.
