2016

Journal

International Journal of Machine Learning and Computing, 6(2), 105.

This paper provides an agent technology for
a decision support system. This system is designed to
detect and regulate the traffic of multimodal public
transport when many disturbances come simultaneously.
The objective of this system is to optimize the regulation
action by learning technique of regulator. The goal of this
research is to improve the quality of public transport
service provided to users and respect the use rules (safety
rules, business rules, commercial rules, etc.). So, to
improve the quality service of the user, we have to
optimize simultaneously several criteria like punctuality,
regularity and correspondence in disturbance case. In
this paper, we focus primarily on a multi agent system for
optimizing and learning of Regulation Support System of
a Multimodal Public Transport (RSSPT). We have
validated our strategy by simulating situation related to
existing transportation system.

@article{morri2016agent,
  title={Agent Technology for Multi-criteria Regulation in Public Transportation},
  author={Morri, Nabil and Hadouaj, Sameh and Said, Lamjed Ben},
  journal={International Journal of Machine Learning and Computing},
  volume={6},
  number={2},
  pages={105},
  year={2016},
  publisher={IACSIT Press}
}