Hulianytskyi L., Pavlenko A.
Ant colony optimization algorithms with diversified search in the problem of optimization of airtravel itinerary

The formulated problem is to find optimal traveler’s route in airline networks, which takes into account cost of the constructed route and user conditions with time-dependent cost of connections. Ant colony system algorithms are proposed to solve the time-dependent problem represented by an extended flight graph. Unlike the available ant algorithm implementations, the developed algorithms take into account the properties of dynamic networks (time-dependent availability and connection cost) and user conditions. The improved approach to the diversification of search in ant colony system algorithms in terms of time dependence for a dense graph increased the quality of the constructed routes from different regions. The proposed algorithms are analyzed for efficiency based on the analysis of the results of a computational experiment from real data. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords: ant algorithms, dynamic discretization discovery, flight network, route optimization, search diversification, time-extended networks, Air transportation, Ant colony optimization, Ant algorithms, Dynamic discretization, Extended networks, Route optimization, search diversification, Computational efficiency

Cite:
Hulianytskyi L., Pavlenko A. (2019). Ant colony optimization algorithms with diversified search in the problem of optimization of airtravel itinerary. Cybernetics and Systems Analysis, 55 (6), 110–121. doi: https://doi.org/10.1007/s10559-019-00208-6 http://jnas.nbuv.gov.ua/article/UJRN-0001044337 [In Ukrainian].