A multi-agent model for traffic regulation by integrating cybercars(MAMTRIC)

In order to resolve disturbances, which can affect a network transport, a regulation process has to be performed by a real-time regulator who has a complex decision-making role including disturbance detection, practicable decisions elaboration and evaluation; and choice decision to adopt. The objective of our research task consists of providing to regulator quickly solutions in case of disturbances in the transport network by integrating cybercars. We propose a multi-agent model for modeling that problem and cooperative approach for optimizing it. The cooperative approach is based on multi-objective tabu search algorithm and multi-objective particle swarm optimization algorithm.