Modeling And Solving Crew Scheduling Problem For Urban Rail Based On Time-Space Network

Crew scheduling is the main contents of urban rail transit operation plan and in the process of actual operation,most of the crew scheduling plans are dependent on experience,which can't ensure economy,flexibility and effectiveness.A crew scheduling plan of good quality consider the optimal balance among the balance between work and rest of crew,operational efficiency and the cost of operation.This article intends to constructing reasonable model and design science algorithm to realize the optimization of crew scheduling based on operating characteristics of urban rail transit in China.1)This paper specifies the crew of urban rail as the object of research,clarifying the research field of optimal allocation of transport resources from the meso level.Based on the analysis of specific content and mutual relations of all sections of organizational planning in the urban rail transit operation,the input and output of crew scheduling are clear.And the concept and basic steps of crew scheduling are further elaborated to provide a theoretical basis for modeling.2)After analyzing common modeling methods of crew scheduling,it is decided that crew scheduling comes down to the vehicle routing problem(VRP).Optimization model of crew scheduling with the goal of minimizing the total wait time and number of crew is built through getting the topology network of train graph and considering the constraints in the actual operation process of urban rail transit.3)According to the characteristic of optimization model of crew scheduling proposed in this paper,it is determined to apply genetic algorithm to solve this work.And the process and procedure of designed genetic algorithm such as coding,generating the initial solution,gene cross and genetic mutation is illustrated.4)The analysis of feasibility and effectiveness of the algorithm and model is implemented on the basis of the data on one circle line.The algorithm's effectiveness and practicability of the optimization model which is for crew scheduling can be demonstrated,offering meaningful reference for crew scheduling in urban rail transit.