Optimizing Urban Public Transportation with Ant Colony Algorithm

Détails bibliographiques
Parent link:Lecture Notes in Computer Science
Vol. 9875 : Computational Collective Intelligence. Pt. 1.— 2016.— [P. 489-497]
Auteur principal: Kochegurova E. A. Elena Alekseevna
Collectivité auteur: Национальный исследовательский Томский политехнический университет Институт кибернетики Кафедра автоматики и компьютерных систем
Autres auteurs: Gorokhova E. S. Ekaterina Sergeevna
Résumé: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
Publié: 2016
Sujets:
Accès en ligne:http://dx.doi.org/10.1007/978-3-319-45243-2_45
Format: Électronique Chapitre de livre
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=651623