Open AccessAlgorithm and peer‐to‐peer negotiation strategies for train dispatching problems in railway bottleneck sections
Author(s) -
Liu Jin,
Chen Lei,
Roberts Clive,
Nicholson Gemma,
Ai Bo
Publication year - 2019
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2019.0020
Subject(s) - bottleneck , negotiation , genetic algorithm , computation , computer science , peer to peer , variety (cybernetics) , engineering , real time computing , operations research , distributed computing , computer network , algorithm , artificial intelligence , machine learning , embedded system , political science , law
Train delays occur often in daily railway operations due to a variety of initiating incidents. On a heavily loaded mainline railway, a single train delay may lead to a series of secondary delays across the network. In this study, the authors describe a peer‐to‐peer system to solve train rescheduling problems in railway network bottlenecks. A designed Genetic Algorithm is chosen as the local search algorithm on each side. Based on the local search algorithm, different negotiation protocols are raised to find globally feasible solutions. The proposed approach is tested in a railway bottleneck section in the UK, and the computational result is compared with a centralised method to show its performance in terms of computation time and optimality.