Optimization method of railway junction passenger station division scheme

Abstract

The invention relates to the technical field of traffic, and discloses a railway junction passenger station division scheme optimization method, which comprises the following steps of: establishing an objective function of minimizing total travel time of passengers in a city and total operation cost in a railway junction; establishing a target and passenger flow distribution constraint condition; the method comprises the following steps: constructing a train operation scheme optimization model based on the target function of the minimum total travel time of passengers in a city and the minimum total operation cost in a railway junction and the target and passenger flow distribution constraint condition, solving based on the passenger flow distribution condition under the train operation scheme to obtain a train operation scheme optimization result, and inputting the train operation scheme optimization result into a Logit model to carry out passenger flow distribution. Obtaining a passenger flow distribution condition under the current train operation scheme, inputting the passenger flow distribution condition into the train operation scheme optimization model for solving again to obtain a current train operation scheme optimization result, and continuously iterating to obtain an optimal train operation scheme; according to the method, by optimizing the labor division of the passenger stations in the hub, passengers can take the bus nearby, and the urban travel time of the passengers is saved.

Description

Technical Field

[0001] The invention relates to the field of transportation technology, and in particular to a method for optimizing a division of labor scheme for a railway hub passenger station. Background Art

[0002] Railway hubs are important distribution and transfer nodes for railway vehicles and passengers. The division of labor in station operations and train operation modes play an important role in improving the operating efficiency and service quality of the railway network. With the continuous improvement of my country's railway network, the number of passenger stations in hubs has continued to increase, and the number of trains running has also continued to grow, resulting in increasingly complex division of labor plans for passenger stations within hubs. The traditional division of labor model focuses on the perspective of transport organization, with "direction-based control" and "separation of high-speed and general-purpose trains" as the main division of labor. Relevant research focuses on factors such as the efficiency and cost of transport organization within the hub, and the requirements for passenger convenience are less reflected, and the needs of passengers to take the nearest train and coordinate with urban transportation development have not been fully considered.

[0003] The current division of labor in hub passenger stations has the following main problems: (1) The hub stations are mainly divided into gates, and lack consideration for trains stopping at multiple stations and train connections within the hub. Since my country has large railway hubs with multiple stations, the current division of labor is mainly guided by the efficiency of transportation organization, and most of them consider that trains have only one "origin / stop" station in the hub. Insufficient consideration is given to the convenience of passengers whose residences are far from the station. A considerable proportion of passengers need to travel across the city to take a train, and the city's travel time is long, making it impossible to "take the nearest train." In addition, there is a large number of transfer passengers in the hub, and existing research lacks detailed consideration of train connections within the hub. A large number of passengers need to transfer at different stations, which seriously affects the convenience of passenger travel. (2) There is a lack of analysis and detailed modeling of the multi-dimensional travel characteristics of hub passenger flow. The arrival and departure passenger flows of large railway hubs often come from different areas of the city. The relative position of each passenger station in the railway hub and its connectivity with the city's transportation methods determine the passenger flow attraction range of the railway passenger station. However, existing research lacks modeling of the multi-dimensional characteristics of urban passenger travel, making it difficult to accurately match the railway passenger demand in different areas of the city. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention provides a method for optimizing the division of labor plan of railway hub passenger stations. On the basis of considering the efficiency of transport organization and the convenience of passengers' travel, by deeply analyzing the multi-dimensional characteristics of railway passenger flow in the hub, from the perspective of facilitating passengers to travel nearby, a variety of operation modes such as multi-station parking in the hub and trains passing through the hub are introduced, thereby improving the train operation mode and realizing the optimization of the hub division of labor plan.

[0005] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0006] A method for optimizing a division of labor scheme for a railway hub passenger station comprises the following steps:

[0007] S1. According to the number of passengers from each travel area to each station in the railway hub, and based on the principle that passengers from different travel areas choose to get on and off at the nearest station, establish an objective function to minimize the total travel time of passengers in the city;

[0008] S2. Based on the running costs of trains in the railway hub and the operating costs of stations receiving and dispatching trains, establish an objective function that minimizes the total operating costs in the railway hub;

[0009] S3. Establish target constraints including train operation plan uniqueness constraint, standing train coupling constraint, through train coupling constraint, route adjustment quantity constraint in each direction, section passing capacity constraint, station operation capacity constraint, and vehicle storage capacity constraint;

[0010] S4. Establish passenger flow allocation constraints including train transport capacity constraints, flow conservation constraints at passenger flow origins and destinations, and flow non-negative constraints at passenger flow origins and destinations;

[0011] S5. Based on the objective function of minimizing the total travel time of passengers in the city, the objective function of minimizing the total operation cost in the railway hub, the objective constraint conditions and the passenger flow distribution constraint conditions, a train operation plan optimization model is constructed, and the passenger flow distribution under the train operation plan is solved to obtain the train operation plan optimization result;

[0012] S6. Based on the optimization result of the train operation plan, the Logit model is used to allocate the passenger flow, and the passenger flow distribution under the current train operation plan is obtained. The result is then input into the train operation plan optimization model for solving again, and the optimization result of the current train operation plan is obtained.

[0013] S7. Determine whether the train operation plan optimization result and the current train operation plan optimization result meet the set requirements. If so, obtain the optimal train operation plan. Otherwise, return to step S5.

[0014] Furthermore, the objective function for minimizing the total travel time of passengers in the city in step S1 is:

[0015]

[0016] Among them, Z1 represents the objective function of minimizing the total travel time of passengers in the city, min represents the minimum value, K represents the train set, k represents the train, R k represents the set of alternative operation plans for train k, and r represents the set of alternative operation plans for train k. kIn the operation plan, S represents the set of station nodes in the railway hub, m represents the station nodes in the railway hub, B represents the set of travel areas, b represents the travel area, g k，r Indicates whether train k chooses the running plan r, represents the subway passenger flow from travel area b to station node m in the railway hub when train k chooses the operation plan r, represents the subway travel time from travel area b to station node m in the railway hub, represents the bus passenger flow from travel area b to station node m in the railway hub when train k chooses the operation plan r, represents the bus travel time from travel area b to station node m in the railway hub, represents the private car passenger flow from travel area b to station node m in the railway hub when train k chooses the operation plan r, represents the travel time of private cars from travel community b to station node m in the railway hub, W represents the set of passenger flow origin and destination pairs, w represents the passenger flow origin and destination, ζ w represents the penalty value of the passenger flow’s origin and destination point w for not traveling, y w It represents the passenger flow that is not taken away by the passenger flow starting and ending point w.

[0017] Furthermore, the objective function for minimizing the total cost of operations within the railway hub in step S2 is:

[0018]

[0019] Among them, Z2 represents the objective function of minimizing the total cost of operations in the railway hub, A represents the set of all sections in the railway hub, (m, n) represents the section from station node m in the railway hub to station node n in the railway hub, T represents the time period set, t represents the time period, Indicates whether train k passes through section (m, n) in time period t when it chooses running plan r. (m，n) represents the mileage of the section (m, n), μ represents the unit running cost of the train in the railway hub, and η k，r，m，t It indicates whether train k stops at station node m in the railway hub during time period t when it selects operation plan r, and v indicates the unit operating cost of the station for receiving and sending trains.

[0020] Furthermore, step S3 specifically includes:

[0021] S31. Establish the uniqueness constraint of the train operation plan, namely:

[0022]

[0023] in, Indicates any symbol, g k,r =1 means train k chooses running plan r;

[0024] S32. Establish the coupling constraint of the standing and folding train, namely:

[0025]

[0026] Among them, k′ represents the subsequent train of train k, Indicates whether there is a standing-falling relationship between train k and the subsequent train k′, Indicates the final destination of the operation plan r Number, R k′ represents the set of alternative running plans for the subsequent train k′, g k′，r Indicates whether the subsequent train k′ chooses the running plan r, Indicates the origin station of the operation plan r Serial number;

[0027] S33. Establish the coupling constraints of the through train, namely:

[0028]

[0029] in, Indicates whether train k has a connection with the subsequent train k′. represents the set of running plans in which all the subsequent trains in the running plan alternative set R are train k, represents the set of running plans in which all the subsequent trains in the running plan alternative set R are the subsequent train k′, Indicates the connecting station specified in the operation plan r Serial number;

[0030] S34, establish the number constraints of path adjustment in each direction, namely:

[0031]

[0032] Among them, X represents the set of train running directions, x represents the train running direction, Represents the set of running paths within the railway hub, Indicates the operation path within the railway hub. Representation and The operation paths in different railway hubs, ρ k，x Indicates whether the running direction of train k is x, Indicates whether the current operation plan of train k in the railway hub is Indicates whether the running path of train k in the railway hub is Indicates the running path with running direction x within the railway hub Adjust to The minimum number of trains, The running path with running direction x and within the railway hub Adjust to The maximum number of trains;

[0033] S35. Establish the interval passing capacity constraint, namely:

[0034]

[0035] Among them, C (m，n) It represents the hourly capacity of the road section (m, n);

[0036] S36. Establish station operation capacity constraints, namely:

[0037]

[0038] Among them, G m It represents the hourly receiving and dispatching capacity of station node m in the railway hub;

[0039] S37. Establish parking capacity constraints, namely:

[0040]

[0041] in, represents whether the operation plan r stipulates whether train k is stored at the parking lot c at night, Q c represents the parking capacity of parking lot c, and C represents the parking lot collection;

[0042] S38. Obtain target constraints based on the train operation plan uniqueness constraints, standing train coupling constraints, through train coupling constraints, route adjustment quantity constraints in each direction, section passing capacity constraints, station operation capacity constraints, and vehicle storage capacity constraints.

[0043] Furthermore, step S4 specifically includes:

[0044] S41. Establish train transport capacity constraints, namely:

[0045]

[0046] Among them, f w，k represents the passenger flow from the passenger flow origin and destination w to the train k, γ w，k，(m，n) Indicates whether the passenger flow starting and ending point w on the train k contains the section (m, n), P k represents the capacity of train k;

[0047] S42. Establish the flow conservation constraints for the passenger flow origin and destination, namely:

[0048]

[0049] Among them, ER w represents the set of all trains that can provide travel services for the passenger flow origin and destination w, represents the total passenger flow at the passenger flow origin and destination point w;

[0050] S43. Establish non-negative constraints on the flow of passenger flow origins and destinations, namely:

[0051]

[0052] S44. Obtain passenger flow distribution constraints based on the train transport capacity constraints, the flow conservation constraints at the passenger flow origin and destination points, and the flow non-negative constraints at the passenger flow origin and destination points.

[0053] Furthermore, step S5 specifically includes:

[0054] S51. Based on the objective function of minimizing the total time of passengers traveling in the city, the objective function of minimizing the total cost of operations in the railway hub, the objective constraints and the passenger flow allocation constraints, a train operation plan optimization model is constructed;

[0055] S52, set the parameters K, R, R k , N, S, A, T, C, B, G m , C (m，n) , Q c d (m，n) ,μ,v, And the initial f w，k As the input of the train operation plan optimization model, the train operation plan optimization model is solved by a professional solver to obtain the initial Object (Z1) and the initial g k,r ;

[0056] Among them, Object(Z1) is the objective function value of the objective function Z1 that minimizes the total travel time of passengers in the city, and the initial f w，k Passenger flow distribution under the train operation plan;

[0057] Among them, when using a professional solver to solve the train operation plan optimization model, the objective function of minimizing the total travel time of passengers in the city in the train operation plan optimization model is used as the main objective function, and the objective function of minimizing the total operating cost in the railway hub in the train operation plan optimization model is used as the auxiliary objective function. By optimizing the main objective function and making it reach the optimal value, the auxiliary objective function is optimized.

[0058] Further, step S6 specifically includes:

[0059] The parameters K, W, P k , and the initial g k，r Input it into the Logit model to solve and get the current f w，k ;

[0060] The current moment f w，k Input the train operation plan optimization model again to solve and obtain the current Object (Z1) and the current g k,r .

[0061] Furthermore, the parameters K, W, P k , and the initial g k，r Input it into the Logit model to solve and get the current f w，k The specific process is:

[0062] First, obtain the train stop plan g k，r and passenger flow data K, W, P k , At the same time, the calibration parameters of passenger travel selection behavior including fare, travel time, departure time, arrival time, and seat level are obtained;

[0063] Secondly, the passenger flow origin and destination points are divided into multiple layers according to the calibration parameters of passenger travel choice behavior, and the passenger flow origin and destination points of each layer are divided into several passenger flow blocks, and several passenger flow origin and destination point sub-tables of each layer are obtained;

[0064] Finally, the passenger flow origin and destination points are allocated according to different levels and different passenger flow origin and destination points, and the passenger flow from the passenger flow origin and destination points to the train is obtained.

[0065] Furthermore, the specific process of allocating passenger flow origin and destination points according to different levels and different passenger flow origin and destination points is as follows:

[0066] Step 1: For the passenger flow starting and ending points w, based on the train stop plan g k,r , passenger flow data K, W, P k , As well as the calibration parameters of passenger travel selection behavior, a parallel bidirectional breadth-first search method is used to search to determine whether there is a train that provides travel services for the passenger flow origin and destination w and has an allocated passenger flow less than the train capacity. If so, execute Step 2, otherwise, execute Step 3;

[0067] Step 2: If the passenger flow that needs to be allocated to the passenger flow origin and destination w is q, then according to the calibration parameters of passenger travel selection behavior, calculate the probability that the passenger flow origin and destination w chooses a train k that can provide travel services and has an allocated passenger flow less than the train capacity, that is:

[0068]

[0069] Among them, p w，k represents the probability that the passenger flow origin and destination w chooses a train k that can provide travel services and has an allocated passenger flow less than the train capacity, exp represents the natural exponential function, V w，k represents the fixed utility of the passenger flow origin and destination w taking the train k that can provide travel services and has an allocated passenger flow less than the train capacity;

[0070] According to the probability of selecting a train k that can provide travel services and whose allocated passenger flow is less than the train capacity, the actual passenger flow that needs to be allocated is calculated, that is:

[0071]

[0072] Among them, min means taking the minimum value, q w , k represents the passenger flow that needs to be allocated when the passenger flow origin and destination w selects the train k that can provide travel services and has an allocated passenger flow less than the train capacity, C w，k It represents the transportation capacity that a train k that can provide travel services and whose assigned passenger flow is less than the train capacity can provide for the passenger flow origin and destination w;

[0073] Step 3: Determine whether the layer where the passenger flow origin and destination point w is located is the last layer. If so, execute step 4. Otherwise, update the remaining passenger flow of the passenger flow origin and destination point w and the remaining capacity of the train, and enter the next passenger flow origin and destination point sub-table or the next layer, and execute step 1.

[0074] Step 4: Output the passenger flow assigned to the train at the passenger flow origin and destination points.

[0075] Further, step S7 specifically includes:

[0076] Calculate the difference between the initial Object (Z1) in the train operation plan optimization result and the current Object (Z1) in the current train operation plan optimization result;

[0077] Determine whether the difference is within the set threshold range. If so, obtain the optimal train operation plan. Otherwise, return to step S5.

[0078] Among them, the optimal train operation plan is g at the current time k,r .

[0079] The present invention has the following beneficial effects:

[0080] 1. The present invention proposes an optimization method for the division of labor of a railway hub passenger station, which adjusts the train operation plan in the railway hub based on the convenience of passengers, so that passengers can take the nearest train and save the overall travel time of passengers;

[0081] 2. By considering the multi-dimensional travel characteristics of passenger flow demand, accurately matching passenger travel needs, and taking into account the multi-dimensional travel characteristics of passengers' urban transportation before and after boarding in the railway hub, the probability of choosing different train routes for the same passenger flow starting and ending points is calculated based on the passengers' demand preferences for trains. This ensures that the railway hub operation plan is optimized and adjusted under the premise that railway transport capacity resources are met and driving conditions are met, thereby maximizing passenger travel benefits, improving the adaptability of railway hubs to differentiated passenger flow demands, and also improving the quality of passenger services. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Figure 1 The present invention is a flowchart of a method for optimizing a division of labor scheme for a railway hub passenger station. DETAILED DESCRIPTION

[0083] The specific implementation modes of the present invention are described below to facilitate those skilled in the art to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0084] like Figure 1 As shown, a method for optimizing the division of labor scheme of a railway hub passenger station includes the following steps S1-S7:

[0085] S1. According to the passengers from each travel area to each station in the railway hub, and based on the principle that passengers from different travel areas choose to get on and off at the nearest station, an objective function is established to minimize the total travel time of passengers in the city.

[0086] In this embodiment, the purpose of establishing the objective function of minimizing the total travel time of passengers in the city is to facilitate the subsequent optimization of the train's running path and the stop plan in the railway hub, thereby reducing the travel time of passengers in the city.

[0087] Specifically, the objective function for minimizing the total travel time of passengers in the city in step S1 is:

[0088]

[0089] Among them, Z1 represents the objective function of minimizing the total travel time of passengers in the city, min represents the minimum value, K represents the train set, k represents the train, R k represents the set of alternative operation plans for train k, and r represents the set of alternative operation plans for train k. kIn the operation plan, S represents the set of station nodes in the railway hub, m represents the station nodes in the railway hub, B represents the set of travel areas, b represents the travel area, g k，r Indicates whether train k chooses the running plan r, represents the subway passenger flow from travel area b to station node m in the railway hub when train k chooses the operation plan r, represents the subway travel time from travel area b to station node m in the railway hub, represents the bus passenger flow from travel area b to station node m in the railway hub when train k chooses the operation plan r, represents the bus travel time from travel area b to station node m in the railway hub, represents the private car passenger flow from travel area b to station node m in the railway hub when train k chooses the operation plan r, represents the travel time of private cars from travel community b to station node m in the railway hub, W represents the set of passenger flow origin and destination pairs, w represents the passenger flow origin and destination, ζ w represents the penalty value of the passenger flow’s origin and destination point w for not traveling, y w It represents the passenger flow that is not taken away by the passenger flow starting and ending point w.

[0090] In this embodiment, g k，r Indicates whether train k chooses the running plan r. When g k，r =1 means the operation plan r is selected. k，r When =0, it means that the operation plan r is not selected.

[0091] S2. Based on the running costs of trains in the railway hub and the operating costs of stations receiving and sending trains, an objective function is established to minimize the total operating costs in the railway hub.

[0092] In this embodiment, the total operating cost within the railway hub includes the running cost of the train within the railway hub and the operating cost of the station receiving and sending trains; the purpose of establishing the objective function of minimizing the total operating cost within the railway hub is to facilitate the subsequent steps to ensure that the railway hub work is as convenient and simple as possible by minimizing the operating costs of the railway hub.

[0093] Specifically, the objective function for minimizing the total cost of operations within the railway hub in step S2 is:

[0094]

[0095] Among them, Z2 represents the objective function of minimizing the total cost of operations in the railway hub, A represents the set of all sections in the railway hub, (m, n) represents the section from station node m in the railway hub to station node n in the railway hub, T represents the time period set, t represents the time period, Indicates whether train k passes through section (m, n) in time period t when it chooses running plan r. (m，n) represents the mileage of the section (m, n), μ represents the unit running cost of the train in the railway hub, and η k，r，m，t It indicates whether train k stops at station node m in the railway hub during time period t when it selects operation plan r, and v indicates the unit operating cost of the station for receiving and sending trains.

[0096] In this embodiment, μ represents the unit running cost of the train in the railway hub, in units of RMB / vehicle-kilometer; v represents the unit operation cost of the station receiving and dispatching trains, in units of RMB / vehicle; η k，r，m，t Indicates whether train k stops at station node m in the railway hub during time period t when train k chooses operation plan r. k，r，m，t =1, it means parking. k，r，m，t =0, it means no stopping.

[0097] S3. Establish target constraints including train operation plan uniqueness constraints, standing train coupling constraints, through train coupling constraints, route adjustment quantity constraints in each direction, section passing capacity constraints, station operation capacity constraints, and vehicle storage capacity constraints.

[0098] Specifically, step S3 specifically includes S31-S38:

[0099] S31. Establish the uniqueness constraint of the train operation plan, namely:

[0100]

[0101] in, Represents an arbitrary symbol, gk.r=1 means that train k chooses operation plan r.

[0102] In this embodiment, the purpose of establishing the uniqueness constraint of the train operation plan is to ensure that each train can only select one operation plan from the operation plan alternative set.

[0103] S32. Establish the coupling constraint of the standing and folding train, namely:

[0104]

[0105] Among them, k′ represents the subsequent train of train k, Indicates whether there is a standing-falling relationship between train k and the subsequent train k′, Indicates the final destination of the operation plan r Number, R k′ represents the set of alternative running plans for the subsequent train k′, g k′，r Indicates whether the subsequent train k′ chooses the running plan r, Indicates the origin station of the operation plan r Number.

[0106] In this embodiment, the purpose of establishing the standing-and-folding train coupling constraint is to ensure that if the front-sequence car k and the rear-sequence car k′ have a standing-and-folding relationship, the final destination station of the front-sequence car k and the starting station of the rear-sequence car k′ are the same.

[0107] S33. Establish the coupling constraints of the through train, namely:

[0108]

[0109] in, Indicates whether train k has a connection with the subsequent train k′. represents the set of running plans in which all the subsequent trains in the running plan alternative set R are train k, represents the set of running plans in which all the subsequent trains in the running plan alternative set R are the subsequent train k′, Indicates the connecting station specified in the operation plan r Number.

[0110] In this embodiment, the purpose of establishing the through train coupling constraint is to determine whether train k chooses the running plan of through running with the subsequent train k'. If so, the subsequent train k' must also choose the running plan of through running with train k, otherwise both trains cannot choose this running plan; in addition, the two through trains must connect at the same station in the railway hub to ensure the continuity of the running path. Indicates whether train k has a connection with the subsequent train k′. There is a continuation relationship when There is no continuation relationship.

[0111] S34, establish the number constraints of path adjustment in each direction, namely:

[0112]

[0113] Among them, X represents the set of train running directions, x represents the train running direction, Represents the set of running paths within the railway hub, Indicates the operation path within the railway hub. Representation and The operation paths in different railway hubs, ρ k，x Indicates whether the running direction of train k is x, Indicates whether the current operation plan of train k in the railway hub is Indicates whether the running path of train k in the railway hub is Indicates the running path with running direction x within the railway hub Adjust to The minimum number of trains, The running path with running direction x and within the railway hub Adjust to The maximum number of trains.

[0114] In this embodiment, the purpose of establishing the constraint on the number of route adjustments in each direction is to facilitate the determination of the upper and lower limits of the number of trains in each direction that are adjusted from the original operating route to the new operating route according to the passenger flow characteristics, so as to facilitate passengers in each area of ​​the city where the railway hub is located to take the nearest train, so as to ensure the convenience of passengers' travel and make the solution more reasonable and reliable. k , x indicates whether the running direction of train k is x, when ρ k ,x=1, then the running direction is x, if ρk,x=0, then the running direction is not x; Indicates whether the current operation plan of train k in the railway hub is when The running path is when The running path is not Indicates whether the running path of train k in the railway hub is when The running path is when The running path is not

[0115] S35. Establish the interval passing capacity constraint, namely:

[0116]

[0117] Among them, C (m，n) Indicates the hourly throughput capacity of the road section (m, n).

[0118] In this embodiment, the purpose of establishing the interval capacity constraint is to ensure that the number of trains passing through each interval in the railway hub in each time period does not exceed the interval capacity. Indicates whether train k passes through section (m, n) in time period t when it chooses running plan r. Then in time period t, passing through section (m, n), when Then the road section (m, n) is not passed in the time period t.

[0119] S36. Establish station operation capacity constraints, namely:

[0120]

[0121] Among them, Gm represents the hourly receiving and dispatching capacity of station node m in the railway hub.

[0122] In this embodiment, the purpose of establishing the station operating capacity constraint is to ensure that the number of trains operating at each station in the railway hub in each time period does not exceed the station's operating capacity; in addition, since the originating, terminating, and passing trains occupy the station's operating capacity differently, they need to be counted separately.

[0123] S37. Establish parking capacity constraints, namely:

[0124]

[0125] in, represents whether the operation plan r stipulates whether train k is stored at the parking lot c at night, Q c represents the parking capacity of parking lot c, and C represents the parking lot collection.

[0126] In this embodiment, the purpose of establishing the storage capacity constraint is to ensure that the storage capacity of each storage yard in the railway hub meets the needs of trains for nighttime storage operations; Indicates whether the operation plan r specifies whether train k is stored at the parking lot c at night. Then park your car at night in parking lot c. No nighttime parking is carried out in parking lot c.

[0127] S38. Obtain target constraints based on the train operation plan uniqueness constraints, standing train coupling constraints, through train coupling constraints, route adjustment quantity constraints in each direction, section passing capacity constraints, station operation capacity constraints, and vehicle storage capacity constraints.

[0128] S4. Establish passenger flow distribution constraints including train transport capacity constraints, flow conservation constraints at passenger flow origins and destinations, and flow non-negativity constraints at passenger flow origins and destinations.

[0129] Specifically, step S4 includes S41-S44:

[0130] S41. Establish train transport capacity constraints, namely:

[0131]

[0132] Among them, f w，k represents the passenger flow from the passenger flow origin and destination w to the train k, γ w，k，(m，n) Indicates whether the passenger flow starting and ending point w on the train k contains the section (m, n), P k represents the capacity of train k.

[0133] In this embodiment, the purpose of establishing the train transport capacity constraint is to ensure that the passenger flow density of each train in each section does not exceed its train capacity to avoid overcrowding; where γ w，k，(m，n) Indicates whether the passenger flow starting and ending point w on the train k contains the section (m, n). w，k，(m，n) =1, then the segment (m, n) is included. When γ w，k，(m，n) =0, then the segment (m, n) is not included.

[0134] S42. Establish the flow conservation constraints for the passenger flow origin and destination, namely:

[0135]

[0136] Among them, ER w represents the set of all trains that can provide travel services for the passenger flow origin and destination w, Represents the total passenger flow at the passenger flow origin and destination point w.

[0137] In this embodiment, the purpose of establishing the flow conservation constraint for the passenger flow origin and destination is to ensure that the sum of the passenger flow allocated to all trains at any passenger flow origin and destination does not exceed the total passenger flow at the passenger flow origin and destination.

[0138] S43. Establish non-negative constraints on the flow of passenger flow origins and destinations, namely:

[0139]

[0140] In this embodiment, the purpose of establishing the non-negative flow constraints at the passenger flow origin and destination is to ensure that the passenger flow and the unallocated passenger flow at any passenger flow origin and destination allocated to any vehicle are not negative.

[0141] S44. Obtain passenger flow distribution constraints based on the train transport capacity constraints, the flow conservation constraints at the passenger flow origin and destination points, and the flow non-negative constraints at the passenger flow origin and destination points.

[0142] S5. Based on the objective function of minimizing the total travel time of passengers in the city, the objective function of minimizing the total operating cost in the railway hub, the target constraints and the passenger flow distribution constraints, a train operation plan optimization model is constructed, and the passenger flow distribution under the train operation plan is solved to obtain the train operation plan optimization result.

[0143] Specifically, step S5 includes S51-S52:

[0144] S51. Based on the objective function of minimizing the total travel time of passengers in the city, the objective function of minimizing the total operating cost in the railway hub, the target constraints and the passenger flow distribution constraints, a train operation plan optimization model is constructed.

[0145] S52, set the parameters K, R, R k , N, S, A, T, C, B, G m , C (m，n) , Q c d (m，n) ,μ,v, And the initial f w，k As the input of the train operation plan optimization model, the train operation plan optimization model is solved by a professional solver to obtain the initial Object (Z1) and the initial g k,r .

[0146] In this embodiment, the parameters K, R, R k , N, S, A, T, C, B, G m , C (m，n) , Q c d (m，n) ,μ,v, And the initial f w，k All are known conditions.

[0147] Among them, Object(Z1) is the objective function value of the objective function Z1 that minimizes the total travel time of passengers in the city, and the initial f w，k It is the passenger flow distribution under the train operation plan.

[0148] Among them, when using a professional solver to solve the train operation plan optimization model, the objective function of minimizing the total travel time of passengers in the city in the train operation plan optimization model is used as the main objective function, and the objective function of minimizing the total operating cost in the railway hub in the train operation plan optimization model is used as the auxiliary objective function. By optimizing the main objective function and making it reach the optimal value, the auxiliary objective function is optimized.

[0149] In this embodiment, the two optimization objectives involved in the train operation plan optimization model are the travel time of passengers in the city, the operating costs of the train in the hub, and the costs of receiving and sending trains at the station. The scales of the two objective functions are different, so the main and auxiliary objective function model is adopted. The main objective is the travel time of passengers in the city, and the auxiliary objective is the operating costs of the train in the hub and the costs of receiving and sending trains at the station. First, optimize the main objective function to achieve the optimal value; when the main objective function reaches the optimal value, optimize the auxiliary objective function to achieve the optimal value under the condition that the main objective function is the optimal value. It can be seen from the objective function and constraints that the train operation plan optimization model is a mixed multi-objective linear integer programming model, which can be solved using a professional solver (such as GUROBI).

[0150] S6. Based on the optimization results of the train operation plan, the Logit model is used to allocate passenger flow to obtain the passenger flow distribution under the current train operation plan, and the passenger flow distribution under the current train operation plan is input into the train operation plan optimization model to solve it again to obtain the optimization results of the current train operation plan.

[0151] Specifically, step S6 includes:

[0152] The parameters K, W, P k , and the initial g k，r Input it into the Logit model to solve and get the current f w，k , the specific process is:

[0153] First, obtain the train stop plan g k，r and passenger flow data K, W, P k , At the same time, the calibration parameters of passenger travel selection behavior including ticket price, travel time, departure time, arrival time, and seat grade are obtained.

[0154] Secondly, the passenger flow origin and destination points are divided into multiple layers according to the calibration parameters of passenger travel choice behavior. At the same time, the passenger flow origin and destination points of each layer are divided into several passenger flow blocks, and several passenger flow origin and destination point tables of each layer are obtained.

[0155] Finally, the passenger flow origin and destination points are allocated according to different levels and different passenger flow origin and destination points, and the passenger flow from the passenger flow origin and destination points to the train is obtained.

[0156] In this embodiment, in the actual allocation process, in addition to considering the travel selection characteristics of passengers, the allocation of passenger flow must also be controlled to a certain extent according to the actual situation, that is, considering ticket prices, travel time, departure time and arrival time, seat grade, etc., to obtain accurate passenger flow distribution, thereby obtaining the optimal train operation plan.

[0157] Specifically, the specific process of allocating passenger flow origin and destination points according to different levels and different passenger flow origin and destination points is as follows:

[0158] Step 1: For the passenger flow starting and ending points w, based on the train stop plan g k，r , passenger flow data K, W, P k , As well as the calibration parameters of passenger travel choice behavior, a parallel bidirectional breadth-first search method is used to search to determine whether there is a train that provides travel services for the passenger flow origin and destination w and has an allocated passenger flow less than the train capacity. If so, execute Step 2, otherwise, execute Step 3.

[0159] Step 2: If the passenger flow that needs to be allocated to the passenger flow origin and destination w is q, then according to the calibration parameters of passenger travel selection behavior, calculate the probability that the passenger flow origin and destination w chooses a train k that can provide travel services and has an allocated passenger flow less than the train capacity, that is:

[0160]

[0161] Among them, p w , k represents the probability that the passenger flow origin and destination w chooses a train k that can provide travel services and has an allocated passenger flow less than the train capacity, exp represents the natural exponential function, V w，k It represents the fixed utility of the passenger flow origin and destination w taking the train k that can provide travel service and whose allocated passenger flow is less than the train capacity.

[0162] According to the probability of selecting a train k that can provide travel services and whose allocated passenger flow is less than the train capacity, the actual passenger flow that needs to be allocated is calculated, that is:

[0163]

[0164] Among them, min means taking the minimum value, q w , k represents the passenger flow that needs to be allocated when the passenger flow origin and destination w selects the train k that can provide travel services and has an allocated passenger flow less than the train capacity, C w，k It represents the transportation capacity that a train k that can provide travel services and whose assigned passenger flow is less than the train capacity can provide for the passenger flow origin and destination w.

[0165] Step 3: Determine whether the layer where the passenger flow starting and ending point w is located is the last layer. If so, execute step Step 4. Otherwise, update the remaining passenger flow of the passenger flow starting and ending point w and the remaining capacity of the train, and enter the next passenger flow starting and ending point table or the next level, and execute step Step 1.

[0166] Step 4: Output the passenger flow assigned to the train at the passenger flow origin and destination points.

[0167] The current moment f w，k Input the train operation plan optimization model again to solve and obtain the current Object (Z1) and the current g k,r .

[0168] S7. Determine whether the train operation plan optimization result and the current train operation plan optimization result meet the set requirements. If so, obtain the optimal train operation plan. Otherwise, return to step S5.

[0169] Specifically, step S7 specifically includes:

[0170] Calculate the difference between the initial Object (Z1) in the train operation plan optimization result and the current Object (Z1) in the current train operation plan optimization result.

[0171] It is determined whether the difference is within the set threshold range. If so, the optimal train operation plan is obtained. Otherwise, return to step S5.

[0172] Among them, the optimal train operation plan is g at the current time k,r .

[0173] In this embodiment, steps S5-S7 are a cyclic iteration process, that is, the output result of step S5 is input into step S6, and the output result of step S6 is input into step S5, and the solution is continuously iterated. When the output conditions are met, the optimal train operation plan can be obtained. In addition, the threshold range is set to [-Gap, Gap], generally Gap≤0.05, and can also be adjusted according to the specific conditions of the railway hub.

[0174] In summary, the optimization method of the division of labor scheme of a railway hub passenger station proposed in the present invention is no longer limited to the traditional station division of labor scheme of different directions, but is to meet the travel needs of passengers going to the same direction in the hub to choose different stations to take the train according to the convenience of urban transportation. Under the premise of allowing trains to stop at multiple stations in the hub, the train operation plan in the railway hub is adjusted based on the convenience of passengers' travel, so that passengers can take the nearest train and save the overall travel time of passengers; secondly, by considering the multi-dimensional travel characteristics of passenger flow demand, the passenger travel demand is accurately matched, that is, based on the constructed train operation plan optimization model and Logit model, the multi-dimensional travel characteristics of urban transportation before and after passengers take the train in the railway hub are taken into account, so as to calculate the probability of choosing different train routes for the unified passenger flow starting and ending points based on the passenger's demand preference for trains, and ensure that the railway hub operation plan is optimized and adjusted under the premise of meeting the railway transportation capacity resources and driving conditions, so as to maximize the travel benefits of passengers, improve the adaptability of the railway hub to differentiated passenger flow demand, and also improve the quality of passenger service.

[0175] The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

[0176] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations and combinations are still within the protection scope of the present invention.

Claims

1. A method for optimizing the division of labor plan of a railway hub passenger station, characterized in that: The following steps are involved: S1. According to the number of passengers from each travel area to each station in the railway hub, and based on the principle that passengers from different travel areas choose to get on and off at the nearest station, establish an objective function to minimize the total travel time of passengers in the city; S2. Based on the running costs of trains in the railway hub and the operating costs of stations receiving and dispatching trains, establish an objective function that minimizes the total operating costs in the railway hub; S3. Establish target constraints including train operation plan uniqueness constraint, standing train coupling constraint, through train coupling constraint, route adjustment quantity constraint in each direction, section passing capacity constraint, station operation capacity constraint, and vehicle storage capacity constraint; S4. Establish passenger flow allocation constraints including train transport capacity constraints, flow conservation constraints at passenger flow origins and destinations, and flow non-negative constraints at passenger flow origins and destinations; S5. Based on the objective function of minimizing the total travel time of passengers in the city, the objective function of minimizing the total operation cost in the railway hub, the objective constraint conditions and the passenger flow distribution constraint conditions, a train operation plan optimization model is constructed, and the passenger flow distribution under the train operation plan is solved to obtain the train operation plan optimization result; S6. Based on the optimization result of the train operation plan, the Logit model is used to allocate the passenger flow, and the passenger flow distribution under the current train operation plan is obtained. The result is then input into the train operation plan optimization model for solving again, and the optimization result of the current train operation plan is obtained. S7. Determine whether the train operation plan optimization result and the current train operation plan optimization result meet the set requirements. If so, obtain the optimal train operation plan. Otherwise, return to step S5.

2. The optimization method of the railway hub passenger station division of labor scheme according to claim 1 is characterized in that: The objective function for minimizing the total travel time of passengers in the city in step S1 is: Among them, Z1 represents the objective function of minimizing the total travel time of passengers in the city, min represents the minimum value, K represents the train set, k represents the train, R k represents the set of alternative operation plans for train k, and r represents the set of alternative operation plans for train k. k In the operation plan, S represents the set of station nodes in the railway hub, m represents the station nodes in the railway hub, B represents the set of travel areas, b represents the travel area, g k,r Indicates whether train k chooses the running plan r, represents the subway passenger flow from travel area b to station node m in the railway hub when train k chooses the operation plan r, represents the subway travel time from travel area b to station node m in the railway hub, represents the bus passenger flow from travel area b to station node m in the railway hub when train k chooses the operation plan r, represents the bus travel time from travel area b to station node m in the railway hub, represents the private car passenger flow from travel area b to station node m in the railway hub when train k chooses the operation plan r, represents the travel time of private cars from travel community b to station node m in the railway hub, W represents the set of passenger flow origin and destination pairs, w represents the passenger flow origin and destination, represents the penalty value of the passenger flow’s origin and destination point w for not traveling, y w It represents the passenger flow that is not taken away by the passenger flow starting and ending point w.

3. The method for optimizing the division of labor scheme of railway hub passenger stations according to claim 2, characterized in that: The objective function for minimizing the total cost of operations within the railway hub in step S2 is: Among them, Z2 represents the objective function of minimizing the total cost of operations in the railway hub, A represents the set of all sections in the railway hub, (m,n) represents the section from station node m in the railway hub to station node n in the railway hub, T represents the time period set, t represents the time period, Indicates whether train k passes through section (m,n) in time period t when it chooses operation plan r. (m,n) represents the mileage of the section (m,n), μ represents the unit running cost of the train in the railway hub, and η k,r,m,t It indicates whether train k stops at station node m in the railway hub during time period t when it selects operation plan r, and v indicates the unit operating cost of the station for receiving and sending trains.

4. The method for optimizing the division of labor scheme of railway hub passenger stations according to claim 3 is characterized in that: Step S3 specifically includes: S31. Establish the uniqueness constraint of the train operation plan, namely: in, Indicates any symbol, g k,r =1 means train k chooses running plan r; S32. Establish the coupling constraint of the standing and folding train, namely: Among them, k′ represents the subsequent train of train k, Indicates whether there is a standing-falling relationship between train k and the subsequent train k′, Indicates the final destination of the operation plan r Number, R k′ represents the set of alternative running plans for the subsequent train k′, g k′,r Indicates whether the subsequent train k′ chooses the running plan r, Indicates the origin station of the operation plan r Serial number; S33. Establish the coupling constraints of the through train, namely: in, Indicates whether train k has a connection with the subsequent train k′. represents the set of running plans in which all the subsequent trains in the running plan alternative set R are train k, represents the set of running plans in which all the subsequent trains in the running plan alternative set R are the subsequent train k′, Indicates the connecting station specified in the operation plan r Serial number; S34, establish the number constraints of path adjustment in each direction, namely: Among them, X represents the set of train running directions, x represents the train running direction, Represents the set of running paths within the railway hub, Indicates the operation path within the railway hub. Representation and The operation paths in different railway hubs, ρ k,x Indicates whether the running direction of train k is x, Indicates whether the current operation plan of train k in the railway hub is Indicates whether the running path of train k in the railway hub is Indicates the running path with running direction x within the railway hub Adjust to The minimum number of trains, The running path with running direction x and within the railway hub Adjust to The maximum number of trains; S35. Establish the interval passing capacity constraint, namely: Among them, C (m,n) It represents the hourly capacity of the road section (m,n); S36. Establish station operation capacity constraints, namely: Among them, G m It represents the hourly receiving and dispatching capacity of station node m in the railway hub; S37. Establish parking capacity constraints, namely: in, represents whether the operation plan r stipulates whether train k is stored at the parking lot c at night, Q c represents the parking capacity of parking lot c, and C represents the parking lot collection; S38. Obtain target constraints based on the train operation plan uniqueness constraints, standing train coupling constraints, through train coupling constraints, route adjustment quantity constraints in each direction, section passing capacity constraints, station operation capacity constraints, and vehicle storage capacity constraints.

5. The method for optimizing the division of labor scheme of railway hub passenger stations according to claim 4 is characterized in that: Step S4 specifically includes: S41. Establish train transport capacity constraints, namely: Among them, f w,k represents the passenger flow from the passenger flow origin and destination w to the train k, γ w,k,(m,n) Indicates whether the passenger flow starting and ending point w on the train k contains the section (m, n), P k represents the capacity of train k; S42. Establish the flow conservation constraints for the passenger flow origin and destination, namely: Among them, ER w represents the set of all trains that can provide travel services for the passenger flow origin and destination w, represents the total passenger flow at the passenger flow origin and destination point w; S43. Establish non-negative constraints on the flow of passenger flow origins and destinations, namely: S44. Obtain passenger flow distribution constraints based on the train transport capacity constraints, the flow conservation constraints at the passenger flow origin and destination points, and the flow non-negative constraints at the passenger flow origin and destination points.

6. The method for optimizing the division of labor scheme of railway hub passenger stations according to claim 5, characterized in that: Step S5 specifically includes: S51. Based on the objective function of minimizing the total travel time of passengers in the city, the objective function of minimizing the total operation cost in the railway hub, the objective constraints and the passenger flow allocation constraints, a train operation plan optimization model is constructed; S52, set the parameters K, R, R k , N, S, A, T, C, B, G m , C (m,n) , Q c ,d (m,n) ,μ,v, And the initial f w,k As the input of the train operation plan optimization model, the train operation plan optimization model is solved by a professional solver to obtain the initial Object (Z1) and the initial g k,r ; Among them, Object(Z1) is the objective function value of the objective function Z1 that minimizes the total travel time of passengers in the city, and the initial f w,k Passenger flow distribution under the train operation plan; Among them, when using a professional solver to solve the train operation plan optimization model, the objective function of minimizing the total travel time of passengers in the city in the train operation plan optimization model is used as the main objective function, and the objective function of minimizing the total operating cost in the railway hub in the train operation plan optimization model is used as the auxiliary objective function. By optimizing the main objective function and making it reach the optimal value, the auxiliary objective function is optimized.

7. The method for optimizing the division of labor scheme of railway hub passenger stations according to claim 6, characterized in that: Step S6 specifically includes: The parameters K, W, P k , and the initial g k,r Input it into the Logit model to solve and get the current f w,k ; The current moment f w,k Input the train operation plan optimization model again to solve and obtain the current Object (Z1) and the current g k,r .

8. The method for optimizing the division of labor scheme of railway hub passenger stations according to claim 7, characterized in that: The parameters K, W, P k , and the initial g k,r Input it into the Logit model to solve and get the current f w,k The specific process is: First, obtain the train stop plan g k,r and passenger flow data K, W, P k , At the same time, the calibration parameters of passenger travel selection behavior including fare, travel time, departure time, arrival time, and seat level are obtained; Secondly, the passenger flow origin and destination points are divided into multiple layers according to the calibration parameters of passenger travel choice behavior, and the passenger flow origin and destination points of each layer are divided into several passenger flow blocks to obtain several passenger flow origin and destination point sub-tables of each layer; Finally, the passenger flow origin and destination points are allocated according to different levels and different passenger flow origin and destination points, and the passenger flow from the passenger flow origin and destination points to the train is obtained.

9. The method for optimizing the division of labor scheme of railway hub passenger stations according to claim 8, characterized in that: The specific process of allocating passenger flow origin and destination points according to different levels and different passenger flow origin and destination points is as follows: Step 1: For the passenger flow starting and ending points w, based on the train stop plan g k,r , passenger flow data K, W, P k , As well as the calibration parameters of passenger travel selection behavior, a parallel bidirectional breadth-first search method is used to search to determine whether there is a train that provides travel services for the passenger flow origin and destination w and has an allocated passenger flow less than the train capacity. If so, execute Step 2, otherwise, execute Step 3; Step 2: If the passenger flow that needs to be allocated to the passenger flow origin and destination w is q, then according to the calibration parameters of passenger travel selection behavior, calculate the probability that the passenger flow origin and destination w chooses a train k that can provide travel services and has an allocated passenger flow less than the train capacity, that is: Among them, p w,k represents the probability that the passenger flow origin and destination w chooses a train k that can provide travel services and has an allocated passenger flow less than the train capacity, exp represents the natural exponential function, V w,k represents the fixed utility of the passenger flow origin and destination w taking the train k that can provide travel services and has an allocated passenger flow less than the train capacity; According to the probability of selecting a train k that can provide travel services and whose allocated passenger flow is less than the train capacity, the actual passenger flow that needs to be allocated is calculated, that is: Among them, min means taking the minimum value, q w,k represents the passenger flow that needs to be allocated when the passenger flow origin and destination w selects a train k that can provide travel services and has an allocated passenger flow less than the train capacity, c w,k It represents the transportation capacity that a train k that can provide travel services and whose assigned passenger flow is less than the train capacity can provide for the passenger flow origin and destination w; Step 3: Determine whether the layer where the passenger flow origin and destination point w is located is the last layer. If so, execute step 4. Otherwise, update the remaining passenger flow of the passenger flow origin and destination point w and the remaining capacity of the train, and enter the next passenger flow origin and destination point sub-table or the next layer, and execute step 1. Step 4: Output the passenger flow assigned to the train at the passenger flow origin and destination points.

10. The method for optimizing the division of labor plan of railway hub passenger stations according to claim 9, characterized in that: Step S7 specifically includes: Calculate the difference between the initial Object (Z1) in the train operation plan optimization result and the current Object (Z1) in the current train operation plan optimization result; Determine whether the difference is within the set threshold range. If so, obtain the optimal train operation plan. Otherwise, return to step S5. Among them, the optimal train operation plan is g at the current time k,r .

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