The purpose is to research and evaluate genetic algorithms and scheduling theory methods for control of public electric transport. Methods of scheduling theory define criteria for time constraints for target functions of the optimal electric transport control task and for electrical process diagnostics task. Mathematical models and procedures are developed for control of electrical processes using scheduling theory and multi-criteria decision making and optimization of railway traffic control. Functional dependencies between electrical processes and dynamics of electric transport flow states are investigated in the research. Genetic algorithms are investigated for dynamic multi-criteria optimization of processes in real time mode. Efficiency of proposed methods is analyzed and procedures for optimal electric transport flow control.