Evolutionary algorithms and dynamic parameters for public electric transport modeling

This work is based on research in a field of intelligent agent systems, negotiation algorithm solving tasks of energy saving, optimal electric vehicle control and transport flow control in traffic jam. Main goal of research is energy saving for public electric transport. Mathematical model and evolutionary algorithm is proposed in the paper to solve multi-criteria optimization task minimizing idle time and electric energy used by public electric transport and maximize average speed of the flow in traffic jam. Paper presents a computer experiment to test proposed mathematical model and workability of evolutionary algorithm. The specific dynamic model of city transport system is created and results of evolutionary optimization are simulated.