CN-122009287-A - Railway virtual marshalling train operation diagram optimization method considering dynamic marshalling

CN122009287ACN 122009287 ACN122009287 ACN 122009287ACN-122009287-A

Abstract

The invention provides a railway virtual marshalling train operation diagram optimizing method considering dynamic marshalling. The method comprises the steps of setting an objective function and constraint conditions of a dynamic-solution high-speed railway virtual marshalling train operation diagram optimization model, setting constraint conditions of the dynamic-solution high-speed railway virtual marshalling train operation diagram optimization model, wherein the constraint conditions comprise time division constraint, train interval constraint, train state symmetry constraint, station capability constraint and passenger flow constraint of a train when the train is in station stay time and interval operation, and solving the objective function of the high-speed railway virtual marshalling train operation diagram optimization model through an algorithm based on the constraint conditions to obtain an arrangement result of the high-speed railway virtual marshalling train operation diagram. The method can carefully describe the dynamic compiling and resolving process of the virtual marshalling high-speed rail train, improves the flexibility and diversity of the operation organization optimization of the virtual marshalling high-speed rail train, and realizes reasonable matching of supply and demand, thereby improving the economic benefit and implementation feasibility of railway operation.

Inventors

ZHANG QI
JI YUZHOU
LI DEWEI
BAO XINYU
ZHOU WEITENG

Assignees

北京交通大学

Dates

Publication Date: 20260512
Application Date: 20260331

Claims (4)

1. The high-speed railway virtual marshalling train operation diagram optimizing method considering dynamic marshalling is characterized by comprising the following steps of: setting an objective function and constraint conditions of a dynamic-solution high-speed railway virtual marshalling train running diagram optimization model; the constraint conditions of the dynamic compiling high-speed railway virtual marshalling train operation diagram optimization model comprise train residence time and interval operation time division constraint, train interval constraint, train state symmetry constraint, station capacity constraint and passenger flow constraint; And solving an objective function of the high-speed railway virtual marshalling train running diagram optimization model through an algorithm based on the constraint condition to obtain a marshalling result of the high-speed railway virtual marshalling train running diagram.
2. The method according to claim 1, wherein the setting the objective function and the constraint condition of the dynamic solution optimization model of the running map of the virtual marshalling train of the high-speed railway comprises: The dynamic process of re-coupling and de-coupling under the running state of the virtual grouped train interval comprises the steps of allowing high-speed trains not more than three trains to virtually group through train communication, limiting according to the number of each train group and the length of a platform in the formation when the virtual re-coupling trains stop, and adopting: ① Two short marshalling virtual reconnection trains are formed and occupy the same track at the same time; ② The virtual reconnection trains of short group and long group are formed, or 2 virtual reconnection trains of long group are formed, or 3 the trains are formed, and the station entering is decomposed and stopped in different tracks; Setting an objective function of a dynamic-solution high-speed railway virtual marshalling train running diagram optimization model by taking the minimum total train travel time as a target, wherein the objective function is as follows: (1) Respectively, trains At a station Arrival and departure times of (2), objective function Representing a train At the arrival time of the last station, Representing a train At the departure time of the first station, i.e. The two are subtracted to index the train Summing and minimizing means that the total train travel time is minimized.
3. The method of claim 2, wherein the constraint conditions for setting the dynamic solution high-speed railway virtual marshalling train operation diagram optimization model include a train on-station residence time and interval operation time division constraint, a train interval constraint, a train state symmetry constraint, a station capability constraint and a passenger flow constraint, and the method comprises the following steps: variables and symbols are defined as follows Aggregation Parameters (parameters) Decision variables Intermediate variable (1) Train time-division constraint in station residence time and interval operation: (2) (3) (4) Equation (2) represents a stop at which the train must stay longer than the minimum stop time, and equation (3) (4) represents an interval that passes, where the train interval runs with maximum and minimum constraints; (2) Train interval constraint: (5) constraint (5) means for two different trains Arriving at station Is unique in order of (2) (6) Constraint (6) represents that for two different trains The sequence of the stations is unique (7) (8) Constraint (7) (8) means that, while in virtual formation, trains within one virtual formation are not constrained by the safety tracking interval; (9) (10) Constraint (9) (10) means that trains within a virtual consist remain constrained by intra-consist tracking intervals; (11) (12) (13) (14) constraint (11) - (14) show that the virtual reconnection train is also constrained by the tracking interval inside the formation when running in the reconnection state; (15) (16) Constraint (15) (16) represents that the state of virtual reconnection of the train is included in the state of communication of the train set-up truck, i.e. when In the time-course of which the first and second contact surfaces, When (when) In the time-course of which the first and second contact surfaces, ; (17) (18) (19) (20) Constraint (17) - (20) indicates that for any two trains The whole process can virtually re-link and virtually de-encode twice, and 0-1 variable is introduced for linearizing the components (17) - (20) : (21) (22) (23) (24) Formulas (20) - (23) represent linearization (17) interval reconnection constraints; (25) (26) (27) (28) Formulas (24) - (27) represent on-site reconnection constraints for linearization (18); (29) (30) (31) (32) the equation (28) -31 represents the section de-coding constraint of the linearization (19); (33) (34) (35) (36) formulas (32) - (35) represent at-station de-encoding constraints of the linearization (20); (37) (38) (39) (40) Constraint (37) to (40), wherein the number of trains in the virtual formation and reconnection states is not more than a given parameter n+1; (3) Train state symmetry constraints: Based on the arbitrary property of the variable subscript, the class 4 variable values representing the train states must satisfy symmetry agreement, such as: (41) (42) (43) (44) similarly, for n+1 trains in the same formation or completing reconnection, n is more than or equal to 2, and the states between every two trains are kept consistent; (45) (46) (47) (48) (4) Station capability constraints: Constraint (49) represents a constraint on any station Is a time interval constraint; (49) (50) (51) (52) (53) Introducing intermediate variables (50) - (53) Representing whether two short marshalling trains are reconnecting at station departure or not, wherein Representing the train as a short consist; (54) formula (54) is station capability constraint, i.e. in the train The number of the arriving train before-the number of the train starting is smaller than that of the station Number of tracks ; (55) (56) Represents station overrun Cannot happen when two short marshalling trains virtually reconnecting ); (55) (56) Equation (57) indicates that the allowable section is not going beyond; (57) (5) Passenger flow restriction: (58) Formula (58) is a section capacity constraint; (59) (60) Equation (59) (60) is a train time window constraint, which indicates that when passenger flows are allocated, the departure time of the train must meet the expected travel time window of the passenger; (61) (62) equation (61) (62) indicates that when passenger flow is allocated, the train must stop at the OD; (63) equation (63) assigns strong constraints to passenger flow.
4. The method according to claim 3, wherein said solving the objective function of the optimization model of the virtual marshalling train operation map of the high-speed railway by an algorithm based on the constraint condition to obtain the layout result of the virtual marshalling train operation map of the high-speed railway comprises: And constructing a mathematical model by using a Python programming language, wherein the mathematical model calls a business solver Gurobi to solve an objective function of the high-speed railway virtual marshalling train operation diagram optimizing model to obtain a high-speed railway virtual marshalling train operation diagram, and the high-speed railway virtual marshalling train operation diagram comprises arrival and departure time of each train at each station, arrival and departure sequence of each train at each station, virtual marshalling state of each train when each train arrives and departs at each station, and marshalling quantity of each train and distribution results of each train on time-varying OD passenger flows.

Description

Railway virtual marshalling train operation diagram optimization method considering dynamic marshalling Technical Field The invention relates to the technical field of high-speed railway train running diagram optimization, in particular to a railway virtual marshalling train running diagram optimization method considering dynamic compiling and solving. Background The virtual marshalling is a technology for carrying out train reconnection by replacing physical connection with wireless communication between the trains, and under the application of the technology, the marshalling and the unbinding places of the trains are not limited to stations or vehicle sections any more, and the trains can be dynamically composed and unbinding in the interval running process, so that the train tracking interval can be shortened, and the line capacity, especially the capacity of bottleneck sections, is improved. At present, the actual application of the virtual marshalling technology remains in the actual vehicle test stage, and actual vehicle tests are carried out on different lines at home and abroad to verify the feasibility of the virtual marshalling technology, but the virtual marshalling technology is not widely applied on a large scale, and the existing research is still mainly based on theoretical research. In the prior art, the research on the operation optimization of the virtual marshalling trains is mostly focused on the urban rail field, the research on the high-speed railway virtual marshalling trains is mostly discussed around feasibility and calculation of key technical parameters, and the research on the operation optimization of the high-speed railway virtual marshalling trains is not yet available in Chinese literature, so that similar research in the urban rail field is selected for comparison. Aiming at the problem of compiling and optimizing the train running diagram under the virtual flexible grouping, the method for compiling the urban rail train running diagram for researching the virtual flexible grouping is provided, 0-1 variable is used for representing the states of adjacent train grouping and unbinding, and a model is built by taking train departure interval as a target. However, the scheme assumes that the trains in peak time are all operated in long marshalling mode, the trains in flat time are all operated in short marshalling mode, the passenger flow demand in the actual operation process is complex, particularly, the high-speed railway ticket is considered for pre-selling, the passenger flow is difficult to distinguish by using peak and flat general system, and the operation diagram is optimized for more refined passenger flow demand. Aiming at the optimization problem of the train running scheme under the online compiling and solving, the scheme takes the minimum enterprise operation cost as an optimization target, a flexible train running scheme optimizing model under the online compiling and solving mode is built, and a corresponding solving method is designed, but the scheme designs a two-stage algorithm solution, a train compiling and solving station is determined in the first stage, the train compiling and solving station is compared with the enterprise operation cost as input in the second stage, and the train compiling and solving place and the marshalling scheme are not integrally decided, so that the solving difficulty is reduced, but the optimality of the scheme is difficult to guarantee at the same time. At present, when the prior art scheme solves the problem of optimizing the running diagram of the high-speed rail train, the following defects exist: (1) In engineering practice, the high-speed rail motor train unit in the prior art generally only carries out reconnection or disconnection on a motor train section (station) in a non-operating state, generally does not carry out the braiding and disconnecting operation in one operation process, and can only be mechanically connected with adjacent trains through couplers. In the existing virtual marshalling train running diagram optimizing technology, connection is established between trains through train-to-train wireless communication, so that the trains can perform static re-marshalling operation at any station. At present, a train operation diagram optimizing method considering dynamic compiling and resolving of a train section is blank, and a train operation diagram optimizing method describing a dynamic compiling and resolving process of a train in a section operation state is lacked, so that the lifting effect of transportation capacity under dynamic compiling and resolving of a virtual marshalling technology is not fully exerted. (2) In engineering practice, the high-speed rail trains only allow two trains to be re-connected in a short-train mode, in the existing virtual grouping operation diagram optimization technology, virtual formation is composed of two trains, three-train and more train grouping researches are relati