Optimizing Urban Public Transportation with Ant Colony Algorithm

被引:1
作者
Kochegurova, Elena [1 ]
Gorokhova, Ekaterina [1 ]
机构
[1] Tomsk Polytech Univ, Lenin Ave 30, Tomsk 634050, Russia
来源
COMPUTATIONAL COLLECTIVE INTELLIGENCE, ICCCI 2016, PT I | 2016年 / 9875卷
关键词
Ant algorithm; Timetable; Transport; Optimization; OPTIMIZATION; SYSTEM; NETWORK;
D O I
10.1007/978-3-319-45243-2_45
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:489 / 497
页数:9
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