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A Novel Interaction Protocol of a Multiagent System for the Study of Alternative Decisions Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Optimizing Urban Public Transportation with Ant Colony Algorithm

Authors : Elena Kochegurova, Ekaterina Gorokhova

Published in: Computational Collective Intelligence

Publisher: Springer International Publishing

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Abstract

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.

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previous chapter Local Termination Criteria for Stochastic Diffusion Search: A Comparison with the Behaviour of Ant Nest-Site Selection
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Metadata
Title
Optimizing Urban Public Transportation with Ant Colony Algorithm
Authors
Elena Kochegurova
Ekaterina Gorokhova
Copyright Year
2016
Book
Computational Collective Intelligence

Print ISBN: 978-3-319-45242-5

Electronic ISBN: 978-3-319-45243-2

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-45243-2_45

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