Study on multi-objective optimization of high-speed train operation based on clonal selection algorithm

Abstract

Along with the development of high-speed railway in China, people require not only the safety and punctuality of the train, but also a higher demand for low energy consumption and comfort simultaneously. According to the situation, clonal selection algorithm is applied to the train control system to optimize the operation process of high-speed train. Through studying with the motion equation and constraint conditions of the train, get the mathematics description of it punctuality, energy consumption and comfort, and combining multiple objective optimization theory to establish a high-speed train operation of the multi-objective optimization model. Once built, apply the clonal selection algorithm for high-speed trains implement optimize, after applying the original control sequence to immune clone, cloning mutation and clonal selection operation to get the train running at the optimal control sequence and comparing with the adaptive particle swarm optimization algorithm. The simulation results show that, clone selection algorithm have good optimization effect for high-speed trains run in the energy efficiency, comfort and punctuality.