Abstract
Despite being one of the world's largest railways networks, with a daily transportation of over 25 million passengers and 2.8 million tons of freight, the Indian Railways perform their signaling, traffic management and trains scheduling activities in a completely manual way. The lack of automation causes not only significant delays, but also frequent collisions where passengers die or remain seriously injured. This paper describes how we modeled the Indian Railways system as a MAS and the results of the simulations run using NetLogo on real data retrieved from the Indian Railways dataset. The simulated system is-under some assumptions-collision-free and, thanks to the integration of the MAX-SUM algorithm, minimizes the individual train delay. © 2013 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Ghosh, S., Dutta, A., Mascardi, V., & Briola, D. (2013). Exploiting MAS-based simulation to improve the indian railways’ efficiency. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8076 LNAI, pp. 278–291). Springer Verlag. https://doi.org/10.1007/978-3-642-40776-5_24
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