Authors: Rajveer Basra, Kevin Lu, Petr Skobelev
Addresses: Brunel Business School, Brunel University, Uxbridge, UB8 3PH Middlesex, UK. ' Brunel Business School, Brunel University, Uxbridge, UB8 3PH Middlesex, UK. ' Magenta Technology, 33 Glasshouse Street, W1B 5DG London, UK
Abstract: We consider the scheduling issues of the London Underground (LU), which spans the entire city and is a vast network of inter-related railway lines. By its very nature, it is a dynamic, complex and unpredictable environment operating or being maintained 24 hours-a-day. This paper is a report on an investigation into how a Multi-agent system (MAS) may be used for resolving scheduling issues of LU. It is a previously-unexplored domain. A prototype system, MASLU is developed through the use of multi-agent system technology, in an innovative and unique manner, with a view of resolving the London Underground|s scheduling/logistics issues in real time.
Keywords: artificial intelligence; AI; multi-agent systems; MAS; intelligent agents; IA; London Underground; railway scheduling; agent-based systems; tube network; logistics; intelligent systems; intelligent scheduling.
International Journal of Intelligent Systems Technologies and Applications, 2007 Vol.2 No.1, pp.3 - 19
Published online: 02 Dec 2006 *Full-text access for editors Access for subscribers Purchase this article Comment on this article