Optimizing Urban Public Transportation with Ant Colony Algorithm; Lecture Notes in Computer Science; Vol. 9875 : Computational Collective Intelligence. Pt. 1
| Parent link: | Lecture Notes in Computer Science Vol. 9875 : Computational Collective Intelligence. Pt. 1.— 2016.— [P. 489-497] |
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| סיכום: | Title screen Transport system in most cities has some problems and should be optimized. In particular, timetable of the city public transportation needs to be changed. Metaheuristic methods for timetabling were considered the most efficient. Ant algorithm was chosen as one of these methods. It was adapted for optimization of an urban public transport timetable. A timetable for one bus route in the city of Tomsk, Russia was created on the basis of the developed software. Different combinations of parameters in ant algorithm allow obtaining new variants of the timetable that better fit passengers’ needs. Режим доступа: по договору с организацией-держателем ресурса |
| שפה: | אנגלית |
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2016
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| גישה מקוונת: | http://dx.doi.org/10.1007/978-3-319-45243-2_45 |
| פורמט: | אלקטרוני Book Chapter |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=651623 |