Abstract
This paper describes and compares mono- and multi-objective Ant Colony System approaches designed to solve the problem of finding the path that minimizes resources while maximizing safety for a military unit in realistic battlefields. Several versions of the previously presented CHAC algorithm, with two different state transition rules are tested. Two of them are extreme cases, which only consider one of the objectives; these are taken as baseline. These algorithms, along with the Multi-Objective Ant Colony Optimization algorithm, have been tested in maps with different difficulty. hCHAC, an approach proposed by the authors, has yielded the best results.
Supported by NadeWeb (TIC2003-09481-C04-01) and PIUGR (9/11/06) projects
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Mora, A.M., Merelo, J.J., Millán, C., Torrecillas, J., Laredo, J.L.J., Castillo, P.A. (2007). Comparing ACO Algorithms for Solving the Bi-criteria Military Path-Finding Problem. In: Almeida e Costa, F., Rocha, L.M., Costa, E., Harvey, I., Coutinho, A. (eds) Advances in Artificial Life. ECAL 2007. Lecture Notes in Computer Science(), vol 4648. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74913-4_67
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DOI: https://doi.org/10.1007/978-3-540-74913-4_67
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