Study On Multi-objective Optimization Of Maintenance Schedule On Catenary System In Electrical Railway

Higher reliability of power supply and Optimized maintenance schedule of Catenary System are required urgently with China's rapid development of high-speed railway. The dynamic reliability model and maintenance cost model of the Catenary System in high-speed railway have been established at first in this paper, where all the maintenance actions have been categorized into three types, and different maintenance actions lead to different reliabilities and costs. The optimization of the maintenance schedule is to achieve maximum reliability of the catenary system and minimum maintenance cost at the same time. To solve this typical multi-objective optimization problem, an advanced Choas Self-adaptive Evolutionary Algorithm, called CSEA, has been proposed in this paper. The Chaotic Initial Population helps to improve the initial diversity. The Grouping Selection Strategy has been suggested to give the dominated solutions more chance to enter the mate pool, and a Self-adaptive Genetic Operator is adopted to give the dominated solutions higher possibility to cross and variation. All of the above help to avoid prematurity and enhance the global searching ability of the algorithm. Simulation results show that, CSEA outperforms NSGA-II in terms of diversity-preservation and in converging closer to the pareto-optimal set at one-run time. At the end of this paper, the comparison of CESA with the single-objective optimizing algorithm has been done, showing that CESA can obtain the limit boundary of the single-objective optimizing algorithm and possesses advantage over it in algorithm stability and effectiveness.