Research On Optimization Of Crew Planning Method For High-speed Railway In China

High-speed railway is an important modern transportation mode.It plays an important role in the transportation field of our country.It has the characteristics of fast running speed,large transportation capacity,good safety,and high comfort.It has obvious advantages in medium and long-distance passenger transportation.The advantages.Crew plan is one of the basic plans of high-speed railway transportation organization.It determines the division of high-speed railway crew sections and the assignment of crew members.It is an important factor that affects the efficiency and effectiveness of high-speed railway passenger transportation and reduces transportation costs.Therefore,it has important practical significance for the optimization research of the compilation method of the high-speed railway crew plan.It takes the optimization of my country’s high-speed railway crew planning method as the research object,reads a large number of relevant domestic and foreign research results,summarizes and analyzes,puts forward the current problems in this field,and conducts in-depth research on the optimization of my country’s high-speed railway crew planning method.the study.The specific work of the thesis is as follows:(1)Analyze and research the relevant theoretical basis of crew planning.Introduce and analyze the classification of the cabin crew system,the work flow of high-speed railway cabin crew,the classification of high-speed rail cabin crew plan,the impact of high-speed rail cabin crew plan preparation,etc.Also study the process of crew plan preparation and determine that the cabin crew plan is divided into cabin crew.The idea of step-by-step optimization of route planning and flight attendance schedule provides a theoretical basis for the establishment of an optimization model for the preparation method of flight attendance planning.(2)Aiming at the optimization problem of the flight attendance route plan,establish a time-space connection network to characterize the issue of the cabin attendance route plan.Taking the minimum non-crew time as the optimization objective,a set covering model is established.The column generation algorithm combined with the branch and bound algorithm is designed to solve the problem,and the algorithm programming is implemented in Python language.The specific content includes designing the multi-labeling method to generate the initial feasible solution,calling the commercial solver Gurobi to solve the main problem of the restriction,solving the sub-problems based on the shortest path idea,and defining the branching strategy.(3)For the optimization problem of the flight attendance schedule,only consider the case of a single cycle flight attendance schedule,take the optimization problem of the flight attendance route plan as an input,and transform the flight attendance schedule problem into an improved TSP problem.Taking the shortest total connection time and more balanced redundancy time between the flight attendant routes as the optimization objectives,a multi-objective optimization model is established.For the definition of the different connection modes between the flight attendance routes,based on the characteristics of the optimization objective of the flight attendance schedule problem,a tabu search algorithm is designed to solve the problem.(4)Carry out example verification and analysis on the optimization method proposed in this paper.Take the Beijing-Tianjin Intercity Railway as an example,and use the real train operation graph data of the Beijing-Tianjin Intercity Railway.The first step is to complete the division of the cabin crew section,and use it as input to solve the cabin crew routing plan.It is divided into 188 cabin crew sections,and a total of 20 cabin crew routes are formed according to the method designed in this paper.Taking 20 flight attendant transfer plans as input,the flight attendant schedule is solved,and a flight attendant schedule with a period of 37 days is established.The feasibility and optimization of the results obtained in this paper are analyzed,and compared with the literature compilation method,it proves that the model and algorithm proposed in this paper have certain practical value and optimization effect.