A multi-objective train timetable optimization method based on sleep period inspection

Abstract

For passengers traveling by the railway, a reasonable train timetable can improve passenger satisfaction efficiently, and improve the service quality of railway passenger transport. Existing related research focuses on reprogramming the train timetable from the perspective of train operating time and operating income, but how to optimize the train timetable from the rationality of passenger travel time has not been greatly resolved. Therefore, this paper proposes a multi-objective train timetable compilation method based on sleep period checking. In this system, the quantitative calculation method of passenger travel time preference is defined, and the passenger arrival time preference function and departure time preference function are fitted by Gaussian function. On this basis, a mixed integer programming model for train timetable optimization is developed. Aiming at this mixed integer nonlinear problem, an improved genetic algorithm based on parallel search mechanism is designed. After the new train timetable is generated, the feasibility of the new train timetable is checked based on the sleep period checking technique. If the new train schedule is feasible, it is indicated as the optimal train schedule. Otherwise, the same algorithm is used again to reschedule. Finally, the performance of the proposed model and algorithm is verified by an example analysis.