An urban rail transit Y-type line operation optimization method based on online compilation

Abstract

The present invention discloses an urban rail transit Y-type line operation optimization method based on online marshaling, comprising: alternately handling train marshaling operations on the station siding and main line, combining the passenger flow demand in each time period, constructing a two-stage mixed integer nonlinear programming model, and collaboratively optimizing the train operation plan and the vehicle turnover plan. The first stage of the model optimizes and solves the train running interval that meets the passenger flow demand in each time period, and the second stage connects the vehicle turnover plan to form a subway Y-type line operation plan based on the online marshaling strategy. The model solving efficiency is improved through linearization processing and algorithm optimization. The present invention can significantly improve the passenger service level, effectively optimize transfer connections, improve operational efficiency, and realize the "equal interval and differential marshaling" of the line, providing a new strategy for the efficient operation of the urban rail transit Y-type line.

Description

Technical Field

[0001] The present invention relates to the technical field of rail transit operation organization, and more specifically, to an urban rail transit Y-type line operation optimization method based on online compilation. Background Art

[0002] With the continuous acceleration of urbanization, the urban rail transit network, as a core component of the public transportation system, has rapidly expanded in scale, and its service scope has also extended to suburbs, satellite towns and areas outside the central urban area, greatly expanding the living radius of urban residents. In this context, the Y-type line, with its unique line layout, can effectively cover a large area and meet diverse passenger flow needs. It has been widely used in the urban rail transit network. Typical cases include Shanghai Metro Line 10, Line 11 and Guangzhou Metro Line 3. However, compared with the traditional single line, the transportation organization mode of the Y-type line is more complex and flexible. Therefore, designing a scientific and reasonable train operation mode is crucial to improving the operating efficiency of the Y-type line and meeting the travel needs of passengers.

[0003] At present, the operation mode of Y-type lines is mainly divided into two categories: one is "parallel operation", that is, the main line and branch line trains run alternately in a specific ratio, such as Shanghai Metro Line 10 and Line 11, but this mode may sometimes increase the waiting time of suburban passengers; the other is "branch line independent operation", that is, the main line and branch line trains run independently, such as Shenzhen Metro Line 6 and 6 branch lines, but this mode may cause poor transfer between the main line and the branch line. In view of the above challenges, how to optimize the operation mode of Y-type lines to improve its overall operation level has become a key issue to be solved in the current urban rail transit field. With the continuous advancement of vehicle, signal and other technologies, especially the emergence of flexible marshaling transportation organization mode, especially the application of online coupling / disassembly (referred to as online marshaling and disassembling) technology, it provides a new perspective and approach for designing a more flexible and efficient Y-type line operation mode. For example, Shanghai Metro Line 16, Beijing Metro Line 3 and Guangzhou Metro Line 3 have begun to apply this mode. The online marshaling and disassembling mode provides a new idea for designing a more flexible and diversified Y-type line operation mode. Summary of the invention

[0004] In order to solve the above technical problems, the present invention proposes an urban rail transit Y-type line operation optimization method based on online marshaling, which provides new strategies and methods for the efficient operation of urban rail transit Y-type lines based on the actual passenger flow demand of operation. By alternating the train marshaling and disassembling operations between the station siding and the main line, a two-stage mixed integer nonlinear programming model is constructed based on the passenger flow demand during the time period. The first stage of the model aims to solve the train running interval that meets the passenger flow demand in each time period, and the second stage connects the vehicle turnover plan to form a subway Y-type line operation plan based on the online marshaling and disassembly strategy. The model also takes into account the coordinated optimization of the train operation plan and the vehicle turnover plan to ensure that the solution meets the needs of actual engineering applications.

[0005] The present invention provides an urban rail transit Y-type line operation optimization method based on online compilation and analysis, comprising:

[0006] Step S1: Collect basic information of the line to be optimized and define relevant parameters of the initialization model;

[0007] Step S2: Propose an online marshaling operation mode in which the station main line and siding line are alternately marshaled, analyze the impact of different modes on the main line capacity, and establish corresponding constraint relationships;

[0008] Step S3: Construct a two-stage online marshaling and flexible marshaling operation organization optimization model. In the first stage, a train operation plan optimization model is constructed based on the passenger flow demand during the time period. In the second stage, based on the first stage, a coordinated optimization model of the train operation plan and the car turnover plan is constructed in combination with the time connection requirements of train marshaling and the car turnover connection requirements;

[0009] Step S4: Linearize the organization optimization model and solve it using the CPLEX solver to obtain an online organized and optimized organization scheme for flexible marshaling of urban rail transit Y-type lines;

[0010] Step S5: Comprehensively evaluate the obtained urban rail transit Y-type line flexible marshaling operation organization optimization plan using preset dimensions.

[0011] In this solution, step S1 specifically includes:

[0012] Collect basic information of the line to be optimized, including the number of stations, the distance between stations, the maximum capacity of the line, the number of trains, and the passenger flow;

[0013] remember For the station, It is the station index, and the intersection station of the main line and branch line is recorded as the modified station ;

[0014] use , and Respectively represent the main line and branch line collinear sections , Main line separate section and branch line separate section , and the stations in the interval are respectively , and express.

[0015] In this solution, step S2 specifically includes:

[0016] The Y-type line train flexible marshaling operation mode uses the station mainline and siding lines to alternately handle the online coupling operation of trains. The train operation scenarios in this mode are:

[0017] S201: Train and From main line stations and branch line stations departure; train Arrive at the station first , according to the track availability, the train will choose to stop at track 1 or track 2 to clear passengers; The train then arrives and stops at the same track to clear passengers. Passengers who get off the train can directly take the coupled train at the opposite platform. and Couple on this track to form a large train , then the passengers on the platform boarded the train, and the train continued to the station and turn back;

[0018] S202: Train From the Station Departure and drive to the station Online disassembly into trains and ;train Continue straight ahead to the mainline station After that, the train will turn back. Go to the branch line station Then turn back; among them, the online dismantling operation does not require the passenger clearance operation;

[0019] S203: Train From mainline stations Departure, train From branch line station Departure; the two trains stop at the idle track, perform the passenger clearing operation and complete the online coupling, and then repeat the process of step S1.

[0020] In this solution, step S3 specifically includes:

[0021] S301: Model prerequisite setting;

[0022] Assuming that passenger arrivals follow a uniform distribution, the average passenger waiting time is approximately equal to half of the interval between trains.

[0023] Assume that all trains stop at every station, and the interval running time and stop time of trains on the same line are the same;

[0024] Assume that the train adopts fully automatic mechanical marshaling and disassembling mode for coupling and disassembling operations;

[0025] S302: Definition of decision variables and constraints in the first stage;

[0026] S303: Definition of objective function and construction of model combination in the first stage;

[0027] S304: Definition of decision variables and constraints in the second stage;

[0028] S305: Construction of the second stage objective function and model combination.

[0029] In this solution, the first stage decision variables and constraint conditions are defined specifically as follows:

[0030] By research period Train departure interval ,train and Number of groups is the decision variable;

[0031] The first-stage constraints are constructed by comprehensively considering the line departure interval constraints, passenger service constraints and vehicle operation constraints.

[0032] In this solution, the first stage objective function definition and model combination construction specifically include:

[0033] The optimization goal is to minimize the comprehensive operating costs of enterprises and passenger travel costs to ensure the maximization of transportation benefits. The objective function of the first stage is It is expressed as: in, and are enterprise operating costs and passenger travel costs respectively. and are the weights of the two respectively, and ;

[0034] A train operation plan optimization model is constructed based on the first-stage objective function and the first-stage constraint conditions consisting of line departure interval constraints, passenger flow service constraints and vehicle operation constraints.

[0035] In this solution, the second stage decision variables and constraint conditions are specifically defined as follows:

[0036] Given the train operation plan for each time period, the above train times At the station The starting time , and down trains At the station The starting time is the decision variable;

[0037] The second stage constraints are constructed by comprehensively considering the running time constraints of trains arriving at departure stations, the minimum departure interval constraints, the minimum turnaround time constraints, the turnaround track occupancy constraints, and the time constraints for the coupling and disassembly operations to and from the departure station.

[0038] In this solution, the second stage objective function and model combination construction specifically includes:

[0039] To minimize the number of trains entering and leaving the depot Deviation from train departure time As the goal, to ensure the uniformity of train departure intervals, the second stage objective function It is expressed as: ;

[0040] A collaborative optimization model of train operation plan and car bottom turnover plan is constructed based on the second-stage objective function and the second-stage constraints consisting of the train running time constraint to the departure station, the minimum departure interval constraint, the minimum turnaround time constraint, the turnaround track occupancy constraint and the coupling disassembly operation to departure time constraint.

[0041] In this solution, step S4 specifically includes:

[0042] The two-stage online marshaling and disassembling flexible marshaling operation organization optimization model is linearized and converted into a mixed integer linear programming model. The solver CPLEX is called to solve the mixed integer linear programming model to obtain an online marshaling and disassembling urban rail transit Y-type line flexible marshaling operation organization optimization plan.

[0043] In this solution, step S5 specifically includes:

[0044] Obtain the optimal solution of the two-stage online flexible marshaling operation organization optimization model, which includes the train running interval , Number of train sets ;

[0045] An evaluation system is constructed using passenger travel costs, number of trains in use and enterprise operating costs, and the evaluation system is used to evaluate the applicability and comprehensive benefits of the urban rail transit Y-type line flexible formation operation organization optimization plan from multiple dimensions.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] (1) The invention adopts a flexible marshaling technology based on an online marshaling and disassembling mode in the transportation organization of the Y-type line of urban rail transit. By alternately performing train marshaling and disassembling operations between the main line and the siding at the station, operation safety is ensured and the waiting time of passengers is significantly reduced.

[0048] (2) The impact of online train coupling / disassembly operations on mainline operations was considered, the process of online train coupling / disassembly operations was analyzed, and the impact of the time occupancy of this mode on the maximum throughput capacity of the mainline was quantified.

[0049] (3) Based on the passenger flow demand during each period, the coordinated optimization of train operation and car bottom turnover is taken into consideration. An online train marshaling and operation organization optimization model for Y-type lines is constructed. The train departure time deviation value is introduced as one of the optimization objectives. This achieves the uniformity of train departure intervals and improves transportation efficiency and passenger satisfaction.

[0050] (4) By designing a linear solution algorithm suitable for the characteristics of the model, the certainty of the solution time is ensured, the solution efficiency is improved, and strong technical support is provided for rapid decision-making in actual engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments or exemplary embodiments of the present invention, the drawings required for use in the embodiments or exemplary descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained according to the drawings without paying creative work.

[0052] Figure 1 A schematic diagram of the structure of a Y-shaped urban rail transit line provided by an embodiment of the present invention is shown;

[0053] Figure 2 A schematic diagram of a flexible train marshaling operation mode and a train operation diagram for a Y-type line provided by an embodiment of the present invention are shown;

[0054] Figure 3 A schematic diagram of the train online assembly and disassembly process provided by an embodiment of the present invention is shown;

[0055] Figure 4 The diagram shows the train online disassembly operation process and the occupied time analysis diagram provided by the embodiment of the present invention;

[0056] Figure 5 The diagram shows the train online coupling operation process and the occupied time analysis diagram provided by the embodiment of the present invention;

[0057] Figure 6 The calculation process of the multi-period line operation plan provided by the embodiment of the present invention is shown;

[0058] Figure 7 The structure diagram of the subway Y-type line provided by the embodiment of the present invention is shown;

[0059] Figure 8 It shows the line OD passenger flow provided by the embodiment of the present invention;

[0060] Fig. 9 The figure shows the passenger flow in the uplink and downlink sections of the line provided by the embodiment of the present invention;

[0061] Fig.10 The train operation diagram in the online flexible marshaling operation mode provided by the embodiment of the present invention is shown;

[0062] Fig.11 A schematic diagram showing an example of a partial vehicle underbody utilization plan provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0063] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0064] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0065] The embodiment of the present invention provides an urban rail transit Y-type line operation optimization method based on online compilation and analysis, comprising:

[0066] Step S1: Collect basic information of the line to be optimized and define relevant parameters of the initialization model.

[0067] like Figure 1 The invention is shown to be applied to the Y-shaped line in urban rail transit. The basic information such as the number of stations, the distance between stations, the maximum capacity of the line, the train capacity, and the passenger flow of the line to be optimized is collected. For the station, It is the station index, and the intersection station of the main line and branch line is recorded as the modified station .use , and Respectively represent the main line and branch line collinear sections , Main line separate section and branch line separate section , and accordingly, the station sets in its interval are respectively , and express.

[0068] Step S2: Propose an online marshaling operation mode in which the station main line and siding line are alternately marshaled, analyze the impact of different modes on the main line's throughput capacity, and establish corresponding constraint relationships.

[0069] Figure 2 The diagram shows a flexible train marshaling operation mode diagram and a train operation diagram for a Y-type line provided by an embodiment of the present invention, wherein and They represent small trains running on the main line and branch line with different marshaling numbers, and are Indicates a large train after coupling. exist Section operation, at the station The train was dismantled and divided into two small trains. and Section operation, two small trains can also be at the station The train is connected to form a large train. Section operation.

[0070] In the actual train formation and disassembly process, the online coupling / disassembly operation will have a certain impact on the throughput capacity of the main line. In particular, the existing train online formation and disassembly technology cannot realize passenger coupling operation, which makes the online coupling operation have a relatively greater impact on the main line operation. To this end, the embodiment of the present invention uses the station main line and siding to alternately handle the online coupling operation of trains to ensure the safety and efficiency of train operation. Figure 3 A schematic diagram of the train online marshaling and disassembling operation process provided by an embodiment of the present invention is shown; the operation scenario of the Y-type line train flexible marshaling operation mode includes the following steps S201~S203.

[0071] S201: Train and From main line stations and branch line stations departure; train Arrive at the station first , according to the track availability, the train will choose to stop at track 1 or track 2 to clear passengers; The train then arrives and stops at the same track to clear passengers. Passengers who get off the train can directly take the coupled train at the opposite platform. and Couple on this track to form a large train , then the passengers on the platform boarded the train, and the train continued to the station And turn back.

[0072] S202: Train From the Station Departure and drive to the station Online disassembly into trains and ;train Continue straight ahead to the mainline station After that, the train will turn back. Go to the branch line station Among them, the online dismantling operation does not require the passenger removal operation.

[0073] S203: Train From mainline stations Departure, train From branch line station Departure; the two trains stop at the idle track, perform the passenger clearing operation and complete the online coupling, and then repeat the process of step S1.

[0074] In the online train assembly and disassembly flexible marshaling operation scenario proposed in the embodiment of the present invention, the reduction of the line capacity caused by the online coupling and disassembly operations is analyzed. Figure 4 and Figure 5 The figure shows the online disassembly and coupling process of trains. The upper part describes the train arrival and departure operations and coupling and disassembly operations in the form of a time-space diagram, and the lower part describes the time occupied by each sub-operation in the form of a Gantt chart. express The train running interval in the time period; and Respectively represent the time of train dismantling and coupling operation; and They represent the total time required for train disassembly and train coupling respectively; , , They respectively represent the time required for a train to process route entry, for a train to leave the station and for a train to enter the station. Indicates that the train is heading up to the station The boarding and alighting stops of and Indicates that the train is going down in the reconfiguration station The drop-off and pick-up stops are scheduled at the designated locations.

[0075] Figure 4 The process and time of online disassembly of Y-type line trains are described. Arrival at the station Disintegrated into trains and train , where train Continue to the area Running in train After leaving the station, the train You still need to wait until the entry is completed before continuing to the section Compared with the traditional operation mode, this mode takes up more time for train dismantling operations and train Waiting for the train The departure time and the exit route processing time are shown in the figure. As shown. and For upbound trains and train At the station The actual stop time can be calculated by equations (1) and (2). To ensure the safety of the line operation, the running interval in this mode is It should meet the requirement of not less than the time taken by the dismantling operation plus the minimum tracking interval of the main line. , as shown in formula (3-4).

[0076]

[0077] Figure 5 The process and time of on-line coupling operation of trains on Y-type lines are described. Since the on-line coupling operation occupies two tracks of the station, its impact on the line capacity mainly has two aspects.

[0078] (1) Switch occupancy conflicts between mainline and branch line trains entering the station: Subsequent trains The entry route needs to wait for the previous train The station entry is completed and the turnout is cleared. Figure 5 The second column The pit stop needs to be in the first column Therefore, the interval between trains should not be less than the train The time for handling the route, entering the platform, stopping at the station to get off passengers, and the train The entry time of the platform is as shown in formula (5):

[0079] (2) Conflict of occupancy of the same track: Trains that enter the same track consecutively must wait for the previous train to leave the platform and clear the switch before the subsequent train can enter the track. Figure 5 The third column The inbound operation needs to be in the first column Therefore, the interval between trains entering the same track should not be less than the interval between trains entering the track. The actual stop time of the train is The departure time of the third train The processing route and entry time of the platform. and For downbound trains and train At the station The actual stop time is calculated by equations (6) and (7), and the conflict constraint on the same track occupancy can be expressed by equation (8).

[0080]

[0081] Step S3: Construct a two-stage online flexible marshaling operation organization optimization model. In the first stage, a train operation plan optimization model is constructed based on the passenger flow demand during the time period. In the second stage, based on the first stage, a collaborative optimization model of the train operation plan and the car turnover plan is constructed in combination with the time connection requirements of train formation and disassembly and the car turnover connection requirements.

[0082] S301: Setting model prerequisites.

[0083] In this embodiment of the present invention, the model is constructed based on the following assumptions:

[0084] Assuming that passenger arrivals follow a uniform distribution, the average waiting time for passengers is approximately equal to half of the interval between trains.

[0085] Assuming that all trains stop at every station, the interval running time and stop time of trains on the same line are the same.

[0086] It is assumed that the train adopts a fully automatic mechanical marshaling and disassembling method for coupling and disassembling operations.

[0087] S302: Definition of decision variables and constraints in the first stage.

[0088] By research period Train departure interval ,train and Number of groups is the decision variable, taking into account the line departure interval limit, time period passenger flow demand, and the number of trains available.

[0089] (1) Departure interval constraints

[0090] Based on the process analysis of online train assembly and disassembly operations, the maximum train departure interval is affected by the time occupied by online assembly and disassembly operations, the minimum tracking interval of the main line, and the , and the minimum return departure interval of the route At the same time, in order to ensure the quality of passenger service, the research period The train departure interval within the period should not exceed the maximum departure interval , as shown in formula (9).

[0091] (2) Passenger flow service constraints

[0092] Formulas (10) and (11) represent the study period The passenger flow transport demand constraints within the period are as follows: Formula (10) ensures that the train capacity can meet the passenger flow demand, and Formula (11) is the maximum passenger flow demand of each section within the period. in: For the research period; is the number of passengers in a single vehicle; , Respectively represent the number of trains on the main line and branch line; , , The research period Inner section , and The maximum up and down cross-sectional passenger flow; For the research period From the station Departure and arrival stations The number of passengers.

[0093] (3) Vehicle operation constraints

[0094] Vehicle operation constraints mainly include vehicle operation number and train formation number constraints. Among them, the vehicle operation number is mainly affected by the number of available vehicles on the line. The number of train formations is mainly limited by the available platform length and the maximum number of train formations under the infrastructure capacity. Restriction, as shown in formula (15).

[0095] in: Indicates rounding up; and Train and The minimum full turnaround time under the respective operating routes; and Indicates that the train is at the station The interval running time of uplink and downlink; and Indicates that the train is at the station The up and down stop time; Indicates that the station is at the turnaround point The minimum return time.

[0096] S303: Definition of objective function and construction of model combination in the first stage.

[0097] The optimization goal is to minimize the comprehensive cost of enterprise operation and passenger travel cost, as shown in formula (16). and are enterprise operating costs and passenger travel costs respectively. and are the weights of the two respectively, and ;

[0098] Enterprise operating costs mainly include operating mileage costs and train formation and disbanding costs , as shown in formula (17-20). The operating mileage cost is mainly composed of the operating cost per vehicle kilometer. and train operating mileage in each section Determine, where the section operating mileage is calculated as formula (19), For trains from the station To the station The train assembly and disassembly costs are mainly composed of the single train coupling / disassembly costs. / Decide.

[0099]

[0100] Passenger travel costs mainly include passenger waiting time at the platform and additional waiting time for passengers caused by online train assembly and disassembly operations , as shown in formulas (21-24). According to relevant research, the waiting time of passengers on the platform can be approximately calculated by the product of passenger flow and half of the corresponding train departure interval, as shown in formula (22). The additional waiting time of passengers mainly includes the additional waiting time of main line and branch line passengers during the online coupling and disassembly of trains. During the online coupling operation, passengers on the main line train can go directly to the opposite platform to take the coupled train on another track. Passengers on the branch line train need to wait for the coupling of this train because they arrive after the coupled train has left. The additional waiting time generated is respectively and , calculated by formula (24). In the online dismantling operation, the additional waiting time of passengers on the main line and branch line trains is and .

[0101]

[0102] The train operation plan optimization model constructed in the first phase is finally expressed as the following formula:

[0103] Based on the first-stage model established by solving steps S302-S303, in the second stage, under the known train operation plan for each time period, the above train number is At the station The starting time , and down trains At the station The starting time As decision variables, the running time of trains arriving at the departure station, the minimum departure interval, the minimum turnaround time, the occupancy of the turnaround track, and the departure time constraints of the coupling and disassembly operations are considered.

[0104] (1) Train running time constraints at the departure and arrival stations

[0105] The one-way running time of a train from its departure station to its final destination includes the train mileage time and the time spent at the station. At the station Arrival time And down trains At the station Arrival time Equations (26) and (27) must be satisfied.

[0106] (2) Minimum departure interval constraints

[0107] The departure time interval between two adjacent trains should meet the following minimum departure interval constraints.

[0108] (3) Minimum return time constraint

[0109] To ensure smooth train turnaround, the train turnaround time at each station should not be less than the minimum turnaround time of the station, as shown in formula (30). and train At the station Large train sets ( + ) form, the return time constraints of the two are consistent and can be considered together. In order to more accurately describe the relationship between train turnaround and connection in this scenario, we introduce a 0-1 variable , and As the model decision variable, Downward train Arrival at the station After that, it can turn back and continue to perform the task of the up train. ,when When the train is up Arrival at the station Then turn back and continue to perform the down train mission ; Otherwise, there is no transfer connection between the two trains.

[0110] (4) Reentry track occupancy constraints

[0111] At the turnaround station The number of trains that can perform reversing operations at the same time should be less than the number of reversing tracks available at the station. . Introducing 0-1 variables , and As an intermediate variable, When the train is in the down direction Train in the up direction Arrive at the station before departure ;when When the train is in the upward direction Train in down direction Arrive at the station before departure . Then the train turnaround track constraints at each turnaround station can be expressed by formula (31-33).

[0112] (5) Time constraints for the arrival and departure of the coupling and disassembly operations

[0113] Based on the proposed flexible marshaling operation mode, in order to ensure the main line train With branch line trains In order to smoothly connect and carry out the coupling and disassembly operations at the reshuffling station, the arrival time of the two trains in the down direction must be precisely controlled. If the coupling operation is carried out in the down direction, the time interval between the two trains arriving at the reshuffling station should be at least equal to the sum of the additional time required for the passenger drop-off and the time required for entering the platform due to the coupling operation, while if the disassembly operation is carried out in the up direction, the time interval between the two trains leaving the reshuffling station should be at least equal to the sum of the additional time required for the exit route and the time required for leaving the platform due to the disassembly operation.

[0114] First, make sure to relocate the station The train arrival and departure times for the down direction train Train Arrival time , which can be obtained from formula (34), the upward train Train Departure time It can be obtained by formula (35). Then, the 0-1 variable is introduced and As the decision variable of the model, When the train is in the down direction With train At the reorganization station, the coupling operation is carried out to form a large-scale train. When the train is in the upward direction With train The disassembly operation is performed at the reorganization station. In summary, the time constraints for the train coupling and disassembly operation can be expressed by formulas (36) and (37).

[0115] S305: Construction of the second stage objective function and model combination.

[0116] In solving the train operation plan, while satisfying the train operation plan, the uniformity of train departure intervals should be maintained under the premise of ensuring the turnover efficiency of the vehicle bottom. Therefore, in the train operation plan optimization problem, the number of train in and out of the depot is minimized. Deviation from train departure time As the target, as shown in formula (38).

[0117]

[0118] The number of train entry and exit times is expressed by formula (39), where and is a 0-1 variable, indicating whether the train is an incoming or outgoing train, otherwise it indicates a normal connecting train. The calculation formula is shown in (40-42). The main line and branch line trains are in a large train formation Therefore, at this station, only the train number The number of times of storage in and out is calculated based on this.

[0119] In order to improve the efficiency of model solution and ensure the rationality of variable value range and the uniformity of train departure interval, the following strategies are adopted in this stage: first, set the initial value of the decision variable of the model and clarify its search range; second, introduce the train departure time deviation value as the optimization target. According to the train departure interval obtained in the first stage, the train At the station The initial starting time is , and down trains At the station The initial starting time is , then the train departure time deviation value can be expressed by formula (43). The train operation plan solution model proposed in this stage can finally be expressed as follows

[0120] Step S4: Linearize the organization optimization model and solve it using the CPLEX solver to obtain an online organized and optimized organization scheme for flexible marshaling of urban rail transit Y-type lines;

[0121] S401: First-stage model linearization

[0122] Number of train sets , As a model decision variable, it has a great influence on the optimization result of the train operation plan. If its value is uncertain, the model will be difficult to solve effectively. However, in actual urban rail transit operations, the number of train formations is limited, and the most common ones are 3+3 or 4+2. Therefore, the number of train formations is specified as a finite number of parameters, for example, the number of train formations is set to and , thus the train operation plan optimization problem can be decomposed into several sub-problems, and the objective function value of each sub-problem can be obtained by independent and parallel solutions, and finally the optimal solution can be determined by comparing the objective function values.

[0123] The first-stage constraint conditions and objective functions established in the embodiment of the present invention contain decision variables The multiplication or division of can be done by introducing a positive integer variable As the independent variable, combined with the transformation of the number of train formations in (1), the constraints (10), (11) and objectives (17-23) in stage 1 are linearized.

[0124] The vehicle operation number constraint (12) is a nonlinear constraint. Considering that the actual full turnover time of a train generally does not exceed the sum of the minimum full turnover time of the train and the interval between train runs, the constraint (12-15) can be linearly transformed by increasing the value of (12) by 1 and converting it into the following equation (45).

[0125] The objective function of this stage is nonlinear, where the enterprise operating cost Involving decision variables The passenger travel cost Involving decision variables By transforming the objective function and introducing the normalization coefficient and To make the two components of the objective have similar orders of magnitude, the objective function is adjusted to formula (46). In addition, the calculation formula (24) for the additional waiting time of passengers has a nonlinear formula , split the equation into constraint equations (47) and (48), and then decompose the model into two linear sub-problems to solve the optimal solution independently and in parallel, so that the objective (16-24) can be linearized.

[0126] S402: Second stage model linearization

[0127] The minimum return time constraint is a nonlinear constraint condition, for which a large positive integer is introduced , linearly transform formula (30) into formula (49).

[0128] In order to handle the nonlinear reentry track occupancy constraint, an arbitrary large positive integer is introduced , linearize formula (31-33) and convert it into formula (50-52).

[0129] The arrival and departure time constraints of the hook disassembly operation in equations (36) and (37) are both nonlinear constraints. By introducing an arbitrary large positive integer It can be converted into a linear constraint, such as formula (53-54).

[0130] The model at this stage contains two optimization objectives: the number of trains entering and leaving the depot Deviation from train departure time , since there is a priority between the two objectives, the weight can be introduced through the linear weighting method , The original objective function 38 is converted into a single objective function as shown in formula (55). At the same time, the train departure time deviation value The calculation formula 43 is a nonlinear formula. By introducing the variable and Linearize it into equation (56-58).

[0131] S403: Finally, the two-stage model is transformed into a mixed integer linear programming model, and a solution algorithm is designed. Then, the solver CPLEX can be called in Python to solve the model and obtain an online urban rail transit Y-type line flexible grouping operation organization optimization plan.

[0132] The solution algorithm inputs the train set , and all model parameters, model related parameters are shown in Table 1;

[0133] Initialize loop n=0, from the train set Select the number of train formations in sequence, and let , select different grouping numbers in the loop to form model sub-problems; decompose formula (24) into , , forming a linear model sub-problem; solving the sub-problem in distributed parallel and recording the optimal solution and And its objective function value and , compare the objective function value and , record the minimum value And the corresponding solution is taken as the current optimal solution ;

[0134] End the loop and select the target function by comparing the above results The minimum optimal solution, i.e. the number of train sets and train departure intervals ;

[0135] Based on the departure intervals obtained in the first phase and the train's full turnaround time, calculate the train's initial departure time and ;

[0136] The initial departure time of the train in the first phase , As the input for solving the second stage model, set its objective function weight ;

[0137] Set up each up train At the station Departure time The adjustable range is , Downward train number At the station The starting time The adjustable range is ;

[0138] Calculate the transformation linear model of stage 2 and generate the train operation plan as output;

[0139] Increase the interval between train runs , Number of train sets , train operation plan as output.

[0140] Step S5: Comprehensively evaluate the obtained urban rail transit Y-type line flexible marshaling operation organization optimization plan using preset dimensions.

[0141] The optimal solution obtained is compared with the line operation plan of the traditional line merging and branch line independent operation mode in terms of passenger travel cost, number of vehicles used and enterprise operating cost, and the applicability and comprehensive benefits of the present invention are evaluated from multiple dimensions such as passenger travel cost, number of vehicles used and enterprise operating cost.

[0142] The embodiments of the present invention are further described below with reference to the accompanying drawings and specific examples:

[0143] Figure 7 The structure diagram of the Y-shaped subway line provided by the embodiment of the present invention is shown. There are 34 stations on the line, among which the intersection station is the reconfiguration station. for Station, the line Segment is , Segment is , Segment is . Figure 8 and Fig. 9 The passenger flow data of the Y-type line is shown, including the passenger flow at the origin and destination (OD) and the passenger flow in the up and down sections. In this case, 2, 3, 4 and 6-car trains are used as common trains for the Y-type line. Table 1 presents the basic parameters of the line obtained through the collection, the objective function weight of the first stage model ( ) is set to (0.5,0.5).

[0144] Table 1 Model related parameters

[0145]

[0146] The above line data, passenger flow data and related parameters are input into the model, and Python software is used to call the commercial solver CPLEX for programming and solving. For the three train operation modes of traditional parallel line, branch line independence and flexible marshaling, a comparative analysis is conducted to obtain the various cost index results of the Y-type line under different train operation modes, as shown in Table 2. In the optimal solution (mode I), the train marshaling scheme is 3+3, that is, 3-car trains are operated on both the main line and the branch line, and 6-car trains are formed by coupling and run in the common line section. Under this solution, the train departure interval is 208 seconds.

[0147] Table 2 Comparison of operating cost indicators under different operating modes

[0148]

[0149] Modes I, II, III, IV, V and VI in Table 2 correspond to six train operation modes, namely (3+3) flexible marshaling, (4+2) flexible marshaling, (6+6) parallel-through, (6+4) parallel-through, (6+6) branch-line independent and (6+4) branch-line independent operation modes. The results in the table are compared and analyzed based on the flexible marshaling operation mode (mode I), in which the ratio of main and branch line trains in the parallel-through mode is set to 1:1. Compared with the four operation modes of parallel-through and branch-line independent, this mode can reduce passenger travel costs by 33.25%, 11.09%, 45.59% and 42.48% respectively. Although this mode needs to rely on the station main line and siding to complete the train coupling operation, which increases the train stop time and the number of train vehicles in use, the enterprise operating cost is slightly higher than that of the branch-line independent operation mode, but considering the passenger service level, the comprehensive benefits of this mode still have significant advantages. Taking into account the actual operation time of trains entering and leaving the station, online marshaling and disassembling operations have little impact on the line's capacity. However, considering the reduction in the capacity of the main line caused by online marshaling and disassembling operations, this mode is more suitable for lines with unsaturated capacity or capacity-saturated lines during off-peak passenger flow periods.

[0150] Fig.10 The train operation plan (train operation diagram) under the online flexible marshaling operation mode of the Y-type line in the period of 8:00~13:00 is shown, in which the total number of trains running is 54 pairs, the total number of trains entering and leaving the depot is 128 times, and the total deviation between the arrival and departure time of the up and down trains on the main line and the initial value is 1235.6s. Fig.11 The following example illustrates the use of some vehicle bottoms, where "U" represents an up train and "D" represents a down train.

[0151] In summary, the present invention provides an innovative online flexible marshaling operation mode for urban rail transit Y-type lines, which ensures operational safety by alternately coupling trains between the main line and the siding at the station, and significantly reduces the extra waiting time for passengers caused by train marshaling. This mode can provide a new perspective and solution for the transportation organization of urban rail transit Y-type lines, realize the "equal interval, differential marshaling" of the line, and show significant benefits in terms of passenger service level and operating costs.

[0152] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0153] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0154] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0155] Those skilled in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, and other media that can store program codes.

[0156] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0157] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for optimizing the operation of a Y-type urban rail transit line based on online compilation and analysis, characterized in that: The following steps are involved: Step S1: Collect basic information of the line to be optimized and define relevant parameters of the initialization model; Step S2: Propose an online marshaling operation mode in which the station main line and siding line are alternately marshaled, analyze the impact of different modes on the main line capacity, and establish corresponding constraint relationships; Step S3: Construct a two-stage online marshaling and flexible marshaling operation organization optimization model. In the first stage, a train operation plan optimization model is constructed based on the passenger flow demand during the time period. In the second stage, based on the first stage, a coordinated optimization model of the train operation plan and the car turnover plan is constructed in combination with the time connection requirements of train marshaling and the car turnover connection requirements; Step S4: Linearize the organization optimization model and solve it using the CPLEX solver to obtain an online organized and optimized organization scheme for flexible marshaling of urban rail transit Y-type lines; Step S5: comprehensively evaluating the obtained urban rail transit Y-type line flexible marshaling operation organization optimization plan using preset dimensions; The step S1 specifically includes: Collect basic information of the line to be optimized, including the number of stations, the distance between stations, the maximum capacity of the line, the number of trains, and the passenger flow; remember For the station, It is the station index, and the intersection station of the main line and branch line is recorded as the modified station ; use , and Respectively represent the main line and branch line collinear sections , Main line separate section and branch line separate section , and the stations in the interval are respectively , and express; The step S2 specifically includes: The Y-type line train flexible marshaling operation mode uses the station mainline and siding lines to alternately handle the online coupling operation of trains. The train operation scenarios in this mode are: S201: Train and From main line stations and branch line stations departure; train Arrive at the station first , according to the track availability, the train will choose to stop at track 1 or track 2 to clear passengers; The train then arrives and stops at the same track to clear passengers. Passengers who get off the train can directly board the coupled train at the opposite platform. and Couple on this track to form a large train , then the passengers on the platform boarded the train, and the train continued to the station and turn back; S202: Train From the Station Departure and drive to the station Online disassembly into trains and ;train Continue straight ahead to the mainline station After that, the train will turn back. Go to the branch line station Then turn back; among them, the online dismantling operation does not require the passenger clearance operation; S203: Train From mainline stations Departure, train From branch line station Departure; the two trains stop at the idle track, perform the passenger clearing operation and complete the online coupling, and then repeat the process of step S1.

2. According to claim 1, a method for optimizing the operation of an urban rail transit Y-type line based on online compilation and analysis is characterized in that: The step S3 specifically includes: S301: Model prerequisite setting; Assuming that passenger arrivals follow a uniform distribution, the average passenger waiting time is equal to half of the interval between trains. Assume that all trains stop at every station, and the interval running time and stop time of trains on the same line are the same; Assume that the train adopts fully automatic mechanical marshaling and disassembling mode for coupling and disassembling operations; S302: Definition of decision variables and constraints in the first stage; S303: Definition of objective function and construction of model combination in the first stage; S304: Definition of decision variables and constraints in the second stage; S305: Construction of the second stage objective function and model combination.

3. The urban rail transit Y-type line operation optimization method based on online compilation and analysis according to claim 2 is characterized in that: The first stage decision variables and constraint conditions are defined as follows: By research period Train departure interval ,train and Number of groups is the decision variable; The first-stage constraints are constructed by comprehensively considering the line departure interval constraints, passenger service constraints and vehicle operation constraints.

4. The urban rail transit Y-type line operation optimization method based on online compilation and analysis according to claim 2 is characterized in that: The first stage objective function definition and model combination construction specifically include: The optimization goal is to minimize the comprehensive operating costs of enterprises and passenger travel costs to ensure the maximization of transportation benefits. The objective function of the first stage is It is expressed as: in, and are enterprise operating costs and passenger travel costs respectively. and are the weights of the two respectively, and ; A train operation plan optimization model is constructed based on the first-stage objective function and the first-stage constraint conditions consisting of line departure interval constraints, passenger flow service constraints and vehicle operation constraints.

5. The urban rail transit Y-type line operation optimization method based on online compilation and analysis according to claim 2 is characterized in that: The second stage decision variables and constraint conditions are defined as follows: Given the train operation plan for each time period, the above train times At the station The starting time , and down trains At the station The starting time is the decision variable; The second stage constraints are constructed by comprehensively considering the running time constraints of trains arriving at departure stations, the minimum departure interval constraints, the minimum turnaround time constraints, the turnaround track occupancy constraints, and the time constraints for the coupling and disassembly operations to and from the departure station.

6. The urban rail transit Y-type line operation optimization method based on online compilation and analysis according to claim 2 is characterized in that: The second stage objective function and model combination construction specifically includes: To minimize the number of trains entering and leaving the depot Deviation from train departure time The second stage objective function is to ensure the uniformity of train departure intervals. It is expressed as: ; A collaborative optimization model of train operation plan and car bottom turnover plan is constructed based on the second-stage objective function and the second-stage constraints consisting of the train running time constraint to the departure station, the minimum departure interval constraint, the minimum turnaround time constraint, the turnaround track occupancy constraint and the coupling disassembly operation to departure time constraint.

7. The urban rail transit Y-type line operation optimization method based on online compilation and analysis according to claim 1 is characterized in that: The step S4 specifically includes: The two-stage online marshaling and disassembling flexible marshaling operation organization optimization model is linearized and converted into a mixed integer linear programming model. The solver CPLEX is called to solve the mixed integer linear programming model to obtain an online marshaling and disassembling urban rail transit Y-type line flexible marshaling operation organization optimization plan.

8. The urban rail transit Y-type line operation optimization method based on online compilation and analysis according to claim 1 is characterized in that: The step S5 specifically includes: Obtain the optimal solution of the two-stage online flexible marshaling operation organization optimization model, which includes the train running interval , Number of train sets ; An evaluation system is constructed using passenger travel costs, number of trains in use and enterprise operating costs, and the evaluation system is used to evaluate the applicability and comprehensive benefits of the urban rail transit Y-type line flexible formation operation organization optimization plan from multiple dimensions.

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