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] |
|---|---|
| Hovedforfatter: | |
| Institution som forfatter: | |
| Andre forfattere: | |
| Summary: | 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 |
| Sprog: | engelsk |
| Udgivet: |
2016
|
| Fag: | |
| Online adgang: | http://dx.doi.org/10.1007/978-3-319-45243-2_45 |
| Format: | xMaterials Electronisk Book Chapter |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=651623 |
MARC
| LEADER | 00000naa0a2200000 4500 | ||
|---|---|---|---|
| 001 | 651623 | ||
| 005 | 20250324114823.0 | ||
| 035 | |a (RuTPU)RU\TPU\network\16872 | ||
| 090 | |a 651623 | ||
| 100 | |a 20161117d2016 k||y0rusy50 ba | ||
| 101 | 0 | |a eng | |
| 102 | |a DE | ||
| 135 | |a drcn ---uucaa | ||
| 181 | 0 | |a i | |
| 182 | 0 | |a b | |
| 200 | 1 | |a Optimizing Urban Public Transportation with Ant Colony Algorithm |f E. A. Kochegurova, E. S. Gorokhova | |
| 203 | |a Text |c electronic | ||
| 300 | |a Title screen | ||
| 320 | |a [References: 1 tit.] | ||
| 330 | |a 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. | ||
| 333 | |a Режим доступа: по договору с организацией-держателем ресурса | ||
| 461 | |t Lecture Notes in Computer Science | ||
| 463 | |t Vol. 9875 : Computational Collective Intelligence. Pt. 1 |o 8th International Conference, ICCCI 2016, Halkidiki, Greece, September 28-30, 2016 |v [P. 489-497] |o proceedings |d 2016 | ||
| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a труды учёных ТПУ | |
| 610 | 1 | |a алгоритм муравья | |
| 610 | 1 | |a расписание | |
| 610 | 1 | |a городской общественный транспорт | |
| 610 | 1 | |a оптимизация | |
| 700 | 1 | |a Kochegurova |b E. A. |c specialist in the field of Informatics and computer engineering |c associate Professor of Tomsk Polytechnic University, candidate of technical Sciences |f 1958- |g Elena Alekseevna |3 (RuTPU)RU\TPU\pers\33442 |9 17123 | |
| 701 | 1 | |a Gorokhova |b E. S. |g Ekaterina Sergeevna | |
| 712 | 0 | 2 | |a Национальный исследовательский Томский политехнический университет |b Институт кибернетики |b Кафедра автоматики и компьютерных систем |3 (RuTPU)RU\TPU\col\18698 |9 27151 |
| 801 | 2 | |a RU |b 63413507 |c 20161117 |g RCR | |
| 856 | 4 | |u http://dx.doi.org/10.1007/978-3-319-45243-2_45 | |
| 942 | |c CF | ||