Application Of The Ant Colony Algorithm For Solving The Fuzzy Traveling Salesman Problem

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dc.contributor.authorIvokhin, Eugeneen_US
dc.contributor.authorOletsky, Oleksiyen_US
dc.contributor.authorYushtin, Konstantinen_US
dc.contributor.authorGavrilenko, Valeriyen_US
dc.contributor.authorBoguslavskyi, Maksymen_US
dc.date.accessioned2025-04-07T05:41:09Z
dc.date.available2025-04-07T05:41:09Z
dc.date.issued2024
dc.description.abstractThe traveling salesman problem (TSP) is a classical combinatorial optimization problem that involves finding the shortest or fastest route among a set of cities. To formalize the uncertainty and imprecision in input data, often caused by subjective evaluations of the travel time intervals, this paper employs fuzzy numbers. The form of these fuzzy numbers is based on a Gaussian-like approach. This work examines the specifics of applying the ant colony optimization (ACO) algorithm and proposes an approach for its optimal use. The impact of the algorithm's parameters on the quality of the approximated best solution is analyzed. The problem is illustrated with numerical examples involving a sufficiently large number of cities in the transportation network.en_US
dc.identifier.citationApplication Of The Ant Colony Algorithm For Solving The Fuzzy Traveling Salesman Problem / Eugene Ivohin, Oleksiy Oletsky, Konstantin Yushtin, Valeriy Gavrilenko, Maksym Boguslavskyi // CEUR Workshop Proceedings. - 2024. - Vol. 3942. - P. 56-65.en_US
dc.identifier.issn1613-0073
dc.identifier.urihttps://ekmair.ukma.edu.ua/handle/123456789/34166
dc.language.isoenen_US
dc.relation.sourceCEUR Workshop Proceedingsen_US
dc.statusfirst publisheden_US
dc.subjectfuzzy traveling salesman problemen_US
dc.subjectant colony optimization methoden_US
dc.subjecttrapezoidal fuzzy numbersen_US
dc.subjectdefuzzificationen_US
dc.subjectperformance evaluationen_US
dc.subjectconference materialsen_US
dc.titleApplication Of The Ant Colony Algorithm For Solving The Fuzzy Traveling Salesman Problemen_US
dc.typeConference materialsen_US
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