Research on Public Transportation Based on Complex Network and Multi-Agent Simulation

Article Preview

Abstract:

This paper uses genetic algorithm to optimize public transportation network by extracting the topology of a local public transportation network as an instance. An optimization model is formulated and characteristics of the optimal network are analyzed. A simulation using multi-agent simulation software NetLogo is successfully implemented to verify the optimal results. Results show the validity of optimization in public transportation network by the proposed genetic algorithm. From the study, it is also found that NetLogo is of great advantage for simulation verification in complex networks.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

183-187

Citation:

Online since:

August 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Newman, M. E., The structure and function of complex networks, SIAM review, Vol45, pp.167-256, (2003).

Google Scholar

[2] Strogatz, S. H., Exploring complex networks, Nature, Vol410, pp.268-276, (2001).

Google Scholar

[3] Tisue S, Wilensky U, Netlogo: A simple environment for modeling complexity, International Conference on Complex Systems, pp.16-21, (2004).

Google Scholar

[4] Kim, B. J., Trusina, A., Minnhagen, P., Sneppen, K., Self organized scale-free networks from merging and regeneration, The European Physical Journal, Vol43, pp.369-372, (2005).

DOI: 10.1140/epjb/e2005-00065-y

Google Scholar

[5] Chakroborty P, Wivedi T, Optimal route network design for transit systems using genetic algorithms, Engineering Optimization, Vol34, pp.83-100, (2002).

DOI: 10.1080/03052150210909

Google Scholar