An optimization method for the division plan of a railway hub passenger station

Abstract

The present invention relates to the field of transportation technologies, and discloses an optimization method for the division of labor of railway hub passenger stations, comprising the following steps: establishing an objective function with the minimum total in-city travel time of passengers and the total operating cost within the railway hub; establishing objective and passenger flow distribution constraints; constructing an optimized train operation plan model based on the objective function with the minimum total in-city travel time of passengers and the total operating cost within the railway hub, as well as the objective and passenger flow distribution constraints, and solving the model based on the passenger flow distribution under the train operation plan to obtain the optimized result of the train operation plan, inputting the result into a Logit model for passenger flow distribution to obtain the passenger flow distribution under the current train operation plan, and inputting the result into the optimized train operation plan model for re-solving to obtain the optimized result of the current train operation plan, and continuously iterating to obtain the optimal train operation plan; by optimizing the division of labor of the passenger stations within the hub, the method realizes that passengers can board trains nearby, saving the in-city travel time of passengers.

Description

Technical Field

[0001] The present invention relates to the technical field of transportation, and particularly to an optimization method for the division plan of railway hub passenger stations. Background Art

[0002] As an important distribution and transfer node of railway vehicle flow and passenger flow, the operation division mode of its stations, train operation patterns, etc. play an important role in improving the operation efficiency and service quality of the railway network. With the continuous improvement of China's railway network, the number of passenger stations in the hub is increasing continuously, and the number of trains in operation is also growing continuously, resulting in an increasingly complex division plan for passenger stations within the hub. The traditional division mode focuses on the perspective of transportation organization, mainly using division methods such as "dividing by direction" and "separating high-speed and ordinary trains". Relevant research mainly considers elements such as the efficiency and cost of transportation organization within the hub, and reflects less on the requirements of passenger travel convenience. It fails to fully consider the needs of passengers to take the train nearby and the coordination with the development of urban transportation.

[0003] The current division methods of hub passenger stations mainly have the following problems: (1) Each station in the hub mainly divides work by taking charge of a certain direction, lacking consideration of multi-stop trains within the hub and train connection. Since there are large railway hubs with multiple stations in China, the current division is mainly oriented towards the efficiency of transportation organization, and mostly considers that a train has only a single "departure / stop" station within the hub. Insufficient consideration is given to the travel convenience of passengers living far from the station. A considerable proportion of passengers need to cross the city to take the train, and the intra-city traffic time is long, and "taking the train nearby" cannot be achieved. In addition, there is a large amount of transfer passenger flow within the hub, and the existing research lacks refined consideration of train connection within the hub. A large number of passengers need to transfer at different stations, seriously affecting the travel convenience of passengers. (2) Lack of analysis and fine modeling of the multi-dimensional travel characteristics of hub passenger flow. The arriving and departing passenger flow of large railway hubs often comes from different regions of the city. The relative positions of each passenger station in the railway hub in the city and its connectivity with intra-city transportation modes determine the passenger flow attraction range of railway passenger stations. However, the existing research lacks multi-dimensional characteristic modeling of intra-city passenger flow travel, making it difficult to accurately match the railway passenger transport demand in different regions of the city. Summary of the Invention

[0004] In view of the above deficiencies in the prior art, the present invention provides an optimization method for the division plan of railway hub passenger stations. On the basis of considering the transportation organization efficiency and passenger travel convenience, by deeply analyzing the multi-dimensional characteristics of railway passenger flow within the hub, from the perspective of facilitating passengers to take the train nearby, various operation modes such as multi-stop trains within the hub and trains passing through the hub are introduced, so as to improve the train operation mode and realize the optimization of the hub division plan.

[0005] In order to achieve the above invention object, the technical solution adopted by the present invention is as follows:

[0006] An optimization method for the division plan of a railway hub passenger station, comprising the following steps:

[0007] S1. Based on the passengers from each travel zone within the railway hub to each station, and on the principle that passengers in different travel zones choose the nearest station to get on and off, establish an objective function for minimizing the total in-city travel time of passengers;

[0008] S2. Based on the running cost of trains within the railway hub and the operation cost of stations for receiving and dispatching trains, establish an objective function for minimizing the total operation cost within the railway hub;

[0009] S3. Establish objective constraint conditions including the uniqueness constraint of the train operation plan, the coupling constraint of turnaround trains, the coupling constraint of through trains, the constraint on the adjustment quantity of routes in each direction, the section passing capacity constraint, the station operation capacity constraint, and the vehicle storage capacity constraint;

[0010] S4. Establish passenger flow distribution constraint conditions including the train transportation capacity constraint, the flow conservation constraint of the origin and destination of passenger flow, and the non-negativity constraint of the flow of the origin and destination of passenger flow;

[0011] S5. Based on the objective function for minimizing the total in-city travel time of passengers, the objective function for minimizing the total operation cost within the railway hub, the objective constraint conditions, and the passenger flow distribution constraint conditions, construct an optimization model for the train operation plan, and solve it based on the passenger flow distribution under the train operation plan to obtain the optimization result of the train operation plan;

[0012] S6. Based on the optimization result of the train operation plan, use the Logit model for passenger flow distribution to obtain the passenger flow distribution under the current train operation plan, and input it into the optimization model of the train operation plan to solve again to obtain the optimization result of the current train operation plan;

[0013] S7. Determine whether the optimization result of the train operation plan and the optimization result of the current train operation plan 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 in-city travel time of passengers in step S1 is:

[0015]

[0016] where Z1 represents the objective function for minimizing the total in-city travel time of passengers, min represents taking the minimum value, K represents the set of trains, k represents a train, R k represents the alternative set of the operation plan of train k, and r represents the alternative set R of the operation plan of train k kThe train operation plan, where \(S\) represents the set of station nodes in the railway hub, \(m\) represents a station node in the railway hub, \(B\) represents the set of travel zones, \(b\) represents a travel zone, and \(g\) k，r indicates whether train \(k\) selects operation plan \(r\). represents the subway passenger flow from travel zone \(b\) to station node \(m\) in the railway hub when train \(k\) selects operation plan \(r\). represents the subway travel time from travel zone \(b\) to station node \(m\) in the railway hub. represents the bus passenger flow from travel zone \(b\) to station node \(m\) in the railway hub when train \(k\) selects operation plan \(r\). represents the bus travel time from travel zone \(b\) to station node \(m\) in the railway hub. represents the private car passenger flow from travel zone \(b\) to station node \(m\) in the railway hub when train \(k\) selects operation plan \(r\). represents the private car travel time from travel zone \(b\) to station node \(m\) in the railway hub. \(W\) represents the set of origin-destination pairs of passenger flow, \(w\) represents an origin-destination pair, and \(\zeta\) w represents the penalty value for uncompleted travel of origin-destination pair \(w\), and \(y\) w represents the uncarried passenger flow of origin-destination pair \(w\).

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

[0018]

[0019] where \(Z2\) represents the objective function for minimizing the total operation cost in the railway hub, \(A\) represents the set of all sections in the railway hub, \((m, n)\) represents the section from station node \(m\) to station node \(n\) in the railway hub, \(T\) represents the set of time periods, \(t\) represents a time period, indicates whether train \(k\) passes through section \((m, n)\) in time period \(t\) when it selects operation plan \(r\), and \(d\) (m，n) represents the mileage of section \((m, n)\), \(\mu\) represents the unit running cost of the train in the railway hub, and \(\eta\) k，r，m，t indicates whether train \(k\) stops at station node \(m\) in time period \(t\) when it selects operation plan \(r\), and \(v\) represents the unit operation cost of the station for receiving and dispatching trains.

[0020] Furthermore, step S3 specifically includes:

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

[0022]

[0023] where represents an arbitrary symbol, and \(g\) k,r \( = 1\) indicates that train \(k\) selects operation plan \(r\);

[0024] S32. Establish the coupling constraint for the folding train, i.e.:

[0025]

[0026] where \(k'\) represents the subsequent train of train \(k\), indicates whether there is a folding relationship between train \(k\) and the subsequent train \(k'\), represents the terminal station of the train operation plan \(r\), the number of, \(R\) k′ represents the alternative set of train operation plans for the subsequent train \(k'\), \(g\) k′，r indicates whether the subsequent train \(k'\) selects the train operation plan \(r\), represents the departure station of the train operation plan \(r\), the number of;

[0027] S33. Establish the coupling constraint for the through train, i.e.:

[0028]

[0029] where,[[]] indicates whether there is a connection relationship between train \(k\) and the subsequent train \(k'\), represents the set of train operation plans for all connection trains of train \(k\) in the alternative set of train operation plans \(R\), represents the set of train operation plans for all connection trains of the subsequent train \(k'\) in the alternative set of train operation plans \(R\), represents the connection station specified in the train operation plan \(r\), the number of;

[0030] S34. Establish the constraint on the adjustment quantity of each direction route, i.e.:

[0031]

[0032] where \(X\) represents the set of train operation directions, \(x\) represents the train operation direction, represents the set of operation routes within the railway hub, represents the operation route within the railway hub, represents and is different from the operation route within the railway hub, \(\rho\) k，x indicates whether the operation direction of train \(k\) is \(x\), indicates whether the current operation plan of train \(k\) in the railway hub is indicates whether the operation route of train \(k\) when selecting the train operation plan \(r\) in the railway hub is indicates that the operation direction is \(x\) and the operation route within the railway hub is changed from adjusted to The minimum value of the number of trains The running route of trains with the running direction of x within the railway hub is Adjusted to The maximum value of the number of trains;

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

[0034]

[0035] Among them, C (m，n) Represents the hourly passing capacity of section (m, n);

[0036] S36. Establish the station operation capacity constraint, that is:

[0037]

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

[0039] S37. Establish the vehicle storage capacity constraint, that is:

[0040]

[0041] Among them, Indicates whether train k specified in the train operation plan r performs overnight vehicle storage in vehicle storage yard c, and Q c Represents the vehicle storage capacity of vehicle storage yard c, and C represents the set of vehicle storage yards;

[0042] S38. According to the uniqueness constraint of the train operation plan, the coupling constraint of turnaround trains, the coupling constraint of through trains, the adjustment quantity constraint of the routes in each direction, the interval passing capacity constraint, the station operation capacity constraint, and the vehicle storage capacity constraint, obtain the target constraint conditions.

[0043] Furthermore, step S4 specifically includes:

[0044] S41. Establish the train transportation capacity constraint, that is:

[0045]

[0046] Among them, f w，k Represents the passenger flow volume assigned from the passenger origin-destination w to train k, and γ w，k，(m，n) Indicates whether the running route of the passenger origin-destination w on train k includes section (m, n), and P k Represents the passenger capacity of train k;

[0047] S42. Establish the flow conservation constraint of the passenger origin-destination, that is:

[0048]

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

[0050] S43. Establish the non-negative constraint of the flow of the origin-destination of passenger flow, that is:

[0051]

[0052] S44. According to the train transportation capacity constraint, the flow conservation constraint of the origin-destination of passenger flow, and the non-negative constraint of the flow of the origin-destination of passenger flow, obtain the passenger flow distribution constraint conditions.

[0053] Furthermore, step S5 specifically includes:

[0054] S51. Based on the objective function of minimizing the total in-city travel time of passengers, the objective function of minimizing the total operating cost within the railway hub, the objective constraint conditions, and the passenger flow distribution constraint conditions, construct an optimization model for the train operation plan;

[0055] S52. Take 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 optimization model for the train operation plan, and use a professional solver to solve the optimization model for the train operation plan 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 of minimizing the total in-city travel time of passengers, and the initial f w，k is the passenger flow distribution under the train operation plan;

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

[0058] Furthermore, step S6 specifically includes:

[0059] Take the parameters K, W, P k , and the initial g k，r Input it into the Logit model for solution to obtain f at the current moment w，k ;

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

[0061] Furthermore, input the parameters K, W, P k , and the initial g k，r into the Logit model for solution to obtain f at the current moment w，k The specific process is as follows:

[0062] First, obtain the train stop plan g k，r and the passenger flow data K, W, P k , and simultaneously obtain the calibration parameters of passengers' travel choice behavior including ticket price, travel time, departure time and arrival time, seat class;

[0063] Secondly, conduct multi - layer division of the passenger flow origin - destination according to the calibration parameters of passengers' travel choice behavior, and at the same time divide the passenger flow origin - destination of each layer into several passenger flow blocks to obtain several passenger flow origin - destination sub - tables of each layer;

[0064] Finally, allocate the passenger flow origin - destination according to different levels and different passenger flow origin - destination sub - tables to obtain the passenger flow volume allocated from the passenger flow origin - destination to the train.

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

[0066] Step1: For the passenger flow origin - destination w, based on the train stop plan g k,r , the passenger flow data K, W, P k , and the calibration parameters of passengers' travel choice behavior, use the parallel bidirectional breadth - first search method to search, and judge whether there is a train that provides travel services for the passenger flow origin - destination w and the allocated passenger flow volume is less than the train's capacity. If so, execute Step2, otherwise, execute Step3;

[0067] Step2: If the passenger flow volume to be allocated for the passenger flow origin - destination w is q, then according to the calibration parameters of passengers' travel choice behavior, calculate the probability that the passenger flow origin - destination w selects the train k that can provide travel services and the allocated passenger flow volume is less than the train's capacity, that is:

[0068]

[0069] Among them, p w，k represents the probability that the origin-destination pair w of passenger flow selects a train k that can provide travel services and the allocated passenger flow is less than the train's seating capacity. exp represents the natural exponential function, and V w，k represents the fixed utility of the origin-destination pair w of passenger flow taking a train k that can provide travel services and the allocated passenger flow is less than the train's seating capacity;

[0070] According to the probability that the origin-destination pair w of passenger flow selects a train k that can provide travel services and the allocated passenger flow is less than the train's seating capacity, calculate the actual passenger flow to be allocated, that is:

[0071]

[0072] Among them, min represents taking the minimum value, q w ,k represents the passenger flow to be allocated when the origin-destination pair w of passenger flow selects a train k that can provide travel services and the allocated passenger flow is less than the train's seating capacity, and C w，k represents the transportation capacity that train k, which can provide travel services and the allocated passenger flow is less than the train's seating capacity, can provide for the origin-destination pair w of passenger flow;

[0073] Step3: Determine whether the layer where the origin-destination pair w of passenger flow is located is the last layer. If so, execute Step4; otherwise, update the remaining passenger flow of the origin-destination pair w and the remaining capacity of the train, and enter the next origin-destination pair sub-table or the next layer, and execute Step1;

[0074] Step4: Output the passenger flow of the origin-destination pair allocated to the train.

[0075] Furthermore, Step S7 specifically includes:

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

[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 moment k,r .

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

[0080] 1. The optimization method for the division plan of railway hub passenger stations proposed by the present invention adjusts the train operation plan within the railway hub based on the convenience of passengers' boarding and alighting, realizes that passengers can board the train nearby, and saves the overall travel time of passengers;

[0081] 2. By considering the multi-dimensional travel characteristics of passenger flow demand, accurately matching the travel needs of passengers, taking into account the multi-dimensional travel characteristics of urban transportation before and after passengers board and alight at the railway hub, and calculating the probabilities of different train routes for the unified passenger flow origin and destination based on the passenger's demand preferences for trains, it is ensured that under the premise of meeting the railway transport capacity resources and the availability of train operation conditions, the train operation plan of the railway hub is optimized and adjusted, achieving the maximization of passenger travel benefits, improving the adaptability of the railway hub to the differentiated passenger flow demand, and at the same time enhancing the passenger service quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Figure 1 It is a schematic flow chart of an optimization method for the division of labor plan of a railway hub passenger station proposed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0083] The following describes the specific embodiments of the present invention to facilitate those skilled in the art of the present technology to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art of the present technology, as long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are within the scope of protection.

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

[0085] S1. According to the passengers from each travel zone in the railway hub to each station, and based on the principle that passengers in different travel zones choose the nearest station to board and alight, establish an objective function for minimizing the total in-city travel time of passengers.

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

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

[0088]

[0089] where Z1 represents the objective function for minimizing the total in-city travel time of passengers, min represents taking the minimum value, K represents the set of trains, k represents a train, R k represents the alternative set of train operation plans for train k, and r represents the alternative set of train operation plans R for train k kThe train operation plan, where 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 zones, b represents the travel zone, and g k，r indicates whether train k selects operation plan r, represents the subway passenger flow from travel zone b to station node m in the railway hub when train k selects operation plan r, represents the subway travel time from travel zone b to station node m in the railway hub, represents the bus passenger flow from travel zone b to station node m in the railway hub when train k selects operation plan r, represents the bus travel time from travel zone b to station node m in the railway hub, represents the private car passenger flow from travel zone b to station node m in the railway hub when train k selects operation plan r, represents the private car travel time from travel zone b to station node m in the railway hub. W represents the set of origin-destination pairs of passenger flow, w represents the origin-destination of passenger flow, and ζ w represents the penalty value for un-traveled trips of origin-destination w of passenger flow, and y w represents the passenger flow not taken away by origin-destination w of passenger flow.

[0090] In this embodiment, g k，r indicates whether train k selects operation plan r. When g k，r = 1, it indicates that operation plan r is selected. When g k，r = 0, it indicates that operation plan r is not selected.

[0091] S2. According to the running cost of the train in the railway hub and the operation cost of the station for receiving and dispatching trains, establish an objective function for minimizing the total operation cost in the railway hub.

[0092] In this embodiment, the total operation cost in the railway hub includes the running cost of the train in the railway hub and the operation cost of the station for receiving and dispatching trains; the purpose of establishing the objective function for minimizing the total operation cost in 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 railway hub operation cost.

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

[0094]

[0095] where Z2 represents the objective function for minimizing the total operation cost in the railway hub, A represents the set of all sections in the railway hub, (m, n) represents the section from station node m to station node n in the railway hub, T represents the set of time periods, and t represents the time period, Indicates whether train k passes through section (m, n) during time period t when choosing operation plan r, d (m，n) Indicates the mileage of section (m, n), μ represents the unit running cost of the train in the railway hub, η k，r，m，t Indicates whether train k stops at station node m in the railway hub during time period t when choosing operation plan r, and v represents the unit operation cost of the station for receiving and dispatching trains.

[0096] In this embodiment, μ represents the unit running cost of the train in the railway hub, with the unit of yuan per vehicle-kilometer; v represents the unit operation cost of the station for receiving and dispatching trains, with the unit of yuan per vehicle; η k，r，m，t Indicates whether train k stops at station node m in the railway hub during time period t when choosing operation plan r. When η k，r，m，t = 1, it indicates a stop. When η k，r，m，t = 0, it indicates no stop.

[0097] S3. Establish objective constraint conditions including the uniqueness constraint of train operation plans, the coupling constraint of turnaround trains, the coupling constraint of through trains, the constraint on the number of path adjustments in each direction, the interval passing capacity constraint, the station operation capacity constraint, and the vehicle storage capacity constraint.

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

[0099] S31. Establish the uniqueness constraint of train operation plans, that is:

[0100]

[0101] Among them, represents an arbitrary symbol, and gk.r = 1 indicates that train k chooses operation plan r.

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

[0103] S32. Establish the coupling constraint of turnaround trains, that is:

[0104]

[0105] Among them, k′ represents the subsequent train of train k, indicates whether there is a turnaround relationship between train k and the subsequent train k′, represents the number of the final destination station of operation plan r of R k′ represents the set of alternative operation plans for the subsequent train k′, g k′，r indicates whether the subsequent train k′ chooses operation plan r, represents the origin station of operation plan r Number

[0106] In this embodiment, the purpose of establishing the coupling constraint for the folding train is to ensure that if there is a folding relationship between the front train k and the rear train k', then the final station of the front train k is the same as the departure station of the rear train k'.

[0107] S33. Establish the coupling constraint for the through train, that is:

[0108]

[0109] where indicates whether there is a connection relationship between train k and the subsequent train k', represents the set of train operation plans in the alternative set R of operation plans where all subsequent trains are train k, represents the set of train operation plans in the alternative set R of operation plans where all subsequent trains are the subsequent train k', represents the connecting station specified in the operation plan r Number

[0110] In this embodiment, the purpose of establishing the coupling constraint for the through train is to determine whether train k selects an operation plan to run through with the subsequent train k'. If so, then the subsequent train k' must also select an operation plan to run through with train k. Otherwise, neither train can select this operation plan. In addition, the two trains running through must connect at the same station within the railway hub to ensure the continuity of the operation route. where indicates whether there is a connection relationship between train k and the subsequent train k'. When then there is a connection relationship. When then there is no connection relationship.

[0111] S34. Establish the constraint on the adjustment quantity of the routes in each direction, that is:

[0112]

[0113] where X represents the set of train operation directions, x represents the train operation direction, represents the set of operation routes within the railway hub, represents the operation route within the railway hub, represents the operation route within the railway hub that is different from , ρ k，x indicates whether the operation direction of train k is x, indicates whether the current operation plan of train k in the railway hub is the operation route indicates whether the selected operation plan r of train k in the railway hub is the operation route Indicates that the running direction is x and the running route within the railway hub is Adjusted to The minimum value of the number of trains, The running direction is x and the running route within the railway hub is Adjusted to The maximum value of the number of trains.

[0114] In this embodiment, the purpose of establishing the adjustment quantity constraint for each direction route is as follows: to facilitate determining the upper and lower limits of the number of trains adjusted from the original running route to the new running route in each direction 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 train nearby, ensure the convenience of passenger travel, and make the solution result more reasonable and reliable. Among them, ρ 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 is the running route within the railway hub When Then the running route is When Then the running route is not Indicates whether the running route of train k is when choosing the operation plan r within the railway hub When Then the running route is When Then the running route is not

[0115] S35. Establish the passing capacity constraint for the section, that is:

[0116]

[0117] Among them, C (m，n) Represents the hourly passing capacity of the section (m, n).

[0118] In this embodiment, the purpose of establishing the passing capacity constraint for the section is as follows: to ensure that the number of trains passing through each section within the railway hub in each time period does not exceed the passing capacity of the section. Among them, Indicates whether train k passes through the section (m, n) at time period t when choosing the operation plan r. When Then it passes through the section (m, n) at time period t. When Then it does not pass through the section (m, n) at time period t.

[0119] S36. Establish the station operation capacity constraint, that is:

[0120]

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

[0122] In this embodiment, the purpose of establishing the station operation capacity constraint is: to ensure that the number of trains operating at each station in the railway hub during each time period does not exceed the operation capacity of the station; in addition, since the occupation of the station operation capacity by originating, terminating, and passing trains is different, separate statistics are required.

[0123] S37. Establish the car storage capacity constraint, that is:

[0124]

[0125] Among them, indicates whether train k specified in train operation plan r performs night car storage in car storage yard c, and Q c represents the car storage capacity of car storage yard c, and C represents the set of car storage yards.

[0126] In this embodiment, the purpose of establishing the car storage capacity constraint is: to ensure that the car storage capacity of each car storage yard in the railway hub meets the needs of trains for night car storage operations; among them, indicates whether train k specified in train operation plan r performs night car storage in car storage yard c. When then it performs night car storage in car storage yard c. When then it does not perform night car storage in car storage yard c.

[0127] S38. Obtain the target constraint conditions according to the uniqueness constraint of the train operation plan, the coupling constraint of turnaround trains, the coupling constraint of through trains, the constraint on the adjusted quantity of each direction route, the section passing capacity constraint, the station operation capacity constraint, and the car storage capacity constraint.

[0128] S4. Establish the passenger flow distribution constraint conditions including the train transportation capacity constraint, the flow conservation constraint of passenger flow origin-destination, and the non-negativity constraint of passenger flow origin-destination.

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

[0130] S41. Establish the train transportation capacity constraint, that is:

[0131]

[0132] Among them, f w，k represents the passenger flow volume assigned from passenger flow origin-destination w to train k, and γ w，k，(m，n) indicates whether the operation path of passenger flow origin-destination w on train k includes section (m, n), and P k represents the seating capacity of train k.

[0133] In this embodiment, the purpose of establishing the train transportation capacity constraint is to ensure that the passenger flow density of each train in each section does not exceed its train capacity, so as to avoid overcrowding; where γ w，k，(m，n) represents whether the operation path of the passenger flow origin-destination w on the train k includes the section (m, n). When γ w，k，(m，n) = 1, it includes the section (m, n). When γ w，k，(m，n) = 0, it does not include the section (m, n).

[0134] S42. Establish the flow conservation constraint of the passenger flow origin-destination, that is:

[0135]

[0136] where ER w represents the set of all trains that can provide travel services for the passenger flow origin-destination w, represents the total passenger flow of the passenger flow origin-destination w.

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

[0138] S43. Establish the non-negative flow constraint of the passenger flow origin-destination, that is:

[0139]

[0140] In this embodiment, the purpose of establishing the non-negative flow constraint of the passenger flow origin-destination is to ensure that the passenger flow and the unassigned passenger flow assigned to any train for any passenger flow origin-destination are not negative.

[0141] S44. According to the train transportation capacity constraint, the flow conservation constraint of the passenger flow origin-destination, and the non-negative flow constraint of the passenger flow origin-destination, obtain the passenger flow distribution constraint conditions.

[0142] S5. Based on the objective function of minimizing the total in-city travel time of passengers, the objective function of minimizing the total operation cost in the railway hub, the objective constraint conditions, and the passenger flow distribution constraint conditions, construct an optimization model for the train operation plan, and solve it based on the passenger flow distribution under the train operation plan to obtain the optimized result of the train operation plan.

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

[0144] S51. Based on the objective function of minimizing the total in-city travel time of passengers, the objective function of minimizing the total operation cost in the railway hub, the objective constraint conditions, and the passenger flow distribution constraint conditions, construct an optimization model for the train operation plan.

[0145] S52. Take 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, and use a professional solver to solve the train operation plan optimization model 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 are all known conditions.

[0147] Among them, Object(Z1) is the objective function value of the objective function Z1 with the minimum total travel time of passengers in the city, and the initial f w，k 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 operation cost in the railway hub in the train operation plan optimization model is used as the auxiliary objective function. After optimizing the main objective function to 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 operation cost of trains in the hub, and the cost of receiving and dispatching trains at the station. Since the scales of the two objective functions are different, the main - auxiliary objective function mode is adopted. The main objective is the travel time of passengers in the city, and the auxiliary objectives are the operation cost of trains in the hub and the cost of receiving and dispatching trains at the station. First, optimize the main objective function to reach the optimal value; when the main objective function reaches the optimal value, optimize the auxiliary objective function to reach the optimal value under the condition that the main objective function is at the optimal value. It can be seen from the objective function and the constraint conditions that the train operation plan optimization model is a mixed multi - objective linear integer programming model and can be solved using a professional solver (such as GUROBI).

[0150] S6. Based on the optimized results of the train operation plan, use the Logit model for passenger flow distribution to obtain the passenger flow distribution under the current train operation plan, and input it into the train operation plan optimization model for re-solving to obtain the optimized results of the current train operation plan.

[0151] Specifically, step S6 specifically includes:

[0152] Input the parameters K, W, P k , and the initial g k，r into the Logit model for solution to obtain the f w，k at the current moment. The specific process is as follows:

[0153] First, obtain the train stopping plan g k，r and the passenger flow data K, W, P k , and at the same time obtain the calibration parameters of passengers' travel choice behavior including fare, travel time, departure time and arrival time, and seat class.

[0154] Secondly, conduct multi-layer division of the passenger flow origin-destination according to the calibration parameters of passengers' travel choice behavior. At the same time, divide the passenger flow origin-destination of each layer into several passenger flow blocks to obtain several passenger flow origin-destination sub-tables of each layer.

[0155] Finally, allocate the passenger flow origin-destination according to different levels and different passenger flow origin-destination sub-tables to obtain the passenger flow volume allocated from the passenger flow origin-destination to the train.

[0156] In this embodiment, in the actual allocation process, in addition to considering the travel choice characteristics of passengers, it is also necessary to control the allocation of passenger flow according to the actual situation, that is, consider factors such as fare, travel time, departure time and arrival time, and seat class, in order to obtain an accurate passenger flow distribution and thus obtain an optimal train operation plan.

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

[0158] Step1: For the passenger flow origin-destination w, based on the train stopping plan g k，r , the passenger flow data K, W, P k , and the calibration parameters of passengers' travel choice behavior, use the parallel bidirectional breadth-first search method for search, and judge whether there is a train that provides travel services for the passenger flow origin-destination w and the allocated passenger flow volume is less than the train's capacity. If so, execute Step2; otherwise, execute Step3.

[0159] Step 2: If the passenger flow volume to be allocated for the origin-destination point w is q, then according to the calibrated parameters of passengers' travel choice behavior, calculate the probability that the origin-destination point w selects a train k that can provide travel services and the allocated passenger flow volume of which is less than the train's capacity, that is:

[0160]

[0161] where p w , k represents the probability that the origin-destination point w selects a train k that can provide travel services and the allocated passenger flow volume of which is less than the train's capacity, exp represents the natural exponential function, and V w，k represents the fixed utility of the origin-destination point w taking a train k that can provide travel services and the allocated passenger flow volume of which is less than the train's capacity.

[0162] According to the probability that the origin-destination point w selects a train k that can provide travel services and the allocated passenger flow volume of which is less than the train's capacity, calculate the actually required allocated passenger flow volume, that is:

[0163]

[0164] where min represents taking the minimum value, q w , k represents the passenger flow volume to be allocated for the origin-destination point w selecting a train k that can provide travel services and the allocated passenger flow volume of which is less than the train's capacity, and C w，k represents the transportation capacity that a train k that can provide travel services and the allocated passenger flow volume of which is less than the train's capacity can provide for the origin-destination point w.

[0165] Step 3: Determine whether the layer where the origin-destination point w is located is the last layer. If so, execute Step 4; otherwise, update the remaining passenger flow volume of the origin-destination point w and the remaining capacity of the train, and enter the next origin-destination point sub-table or the next layer, and execute Step 1.

[0166] Step 4: Output the passenger flow volume allocated from the origin-destination point to the train.

[0167] Input the f at the current moment w，k into the train operation plan optimization model again for solution, and obtain the Object(Z1) at the current moment and the g at the current moment 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 optimized result of the train operation plan and the current Object(Z1) at the current moment in the optimized result of the current train operation plan.

[0171] Determine whether the difference is within the set threshold range. If so, obtain the optimal train operation plan; otherwise, return to step S5.

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

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

[0174] In summary, the optimization method for the division plan of railway hub passenger stations proposed by the present invention is no longer limited to the traditional station division plan of dividing by direction, but to meet the travel needs of passengers going in the same direction who can choose different stations to take the train according to the convenience of urban traffic within the hub. On the premise that the train is allowed to stop at multiple stations within the hub, the train operation plan within the railway hub is adjusted based on the convenience of passengers taking the train to enable passengers to take the train nearby 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 the urban traffic before and after passengers take the train within the railway hub are considered. Thus, the probability of different train routes being selected by unified passenger flow origin-destination points is calculated based on the demand preference of passengers for trains, ensuring that the train operation plan of the railway hub is optimized and adjusted on the premise that railway transport capacity resources are met and train operation conditions are available, realizing the maximization of passenger travel benefits, improving the adaptability of the railway hub to different passenger flow demands, and at the same time enhancing the passenger service quality.

[0175] In the present invention, specific embodiments are used to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

[0176] Those of ordinary skill in the art will realize that the embodiments described herein are provided to assist the reader in understanding the principles of the present invention, and it should be understood that the scope of protection of the present invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific deformations and combinations that do not depart from the essence of the present invention based on these technical revelations disclosed in the present invention, and these deformations and combinations are still within the scope of protection of the present invention.

Claims

1. An optimization method for the division plan of a railway hub passenger station, characterized in that, It includes the following steps: S1. Based on the passengers from each travel zone in the railway hub to each station, and following the principle that passengers in different travel zones choose the nearest station to get on and off, establish an objective function for minimizing the total in-city travel time of passengers; S2. Based on the running costs of trains in the railway hub and the operating costs of stations for receiving and dispatching trains, establish an objective function for minimizing the total operating costs in the railway hub; S3. Establish objective constraint conditions including the uniqueness constraint of train operation plans, the coupling constraint of turnaround trains, the coupling constraint of through trains, the constraint on the number of route adjustments in each direction, the section passing capacity constraint, the station operation capacity constraint, and the car storage capacity constraint; S4. Establish passenger flow distribution constraint conditions including the train transportation capacity constraint, the flow conservation constraint of passenger flow origin and destination, and the non-negative flow constraint of passenger flow origin and destination; S5. Based on the objective function for minimizing the total in-city travel time of passengers, the objective function for minimizing the total operating costs in the railway hub, the objective constraint conditions, and the passenger flow distribution constraint conditions, construct an optimization model for train operation plans, and solve it based on the passenger flow distribution under the train operation plan to obtain the optimized result of the train operation plan; S6. Based on the optimized result of the train operation plan, use the Logit model for passenger flow distribution to obtain the passenger flow distribution under the current train operation plan, and input it into the optimization model for train operation plans to solve again to obtain the optimized result of the current train operation plan; S7. Determine whether the optimized result of the train operation plan and the optimized result of the current train operation plan meet the set requirements. If so, obtain the optimal train operation plan; otherwise, return to step S5.

2. The optimization method of the division plan of the railway hub passenger station according to claim 1, characterized in that The objective function for minimizing the total in-city travel time of passengers in step S1 is: Among them, Z1 represents the objective function of minimizing the total in-city travel time of passengers, min represents taking the minimum value, K represents the set of trains, k represents a train, R k represents the set of alternative operation plans for train k, and r represents an alternative operation plan r in the set of alternative operation plans R k of train k. S represents the set of station nodes in the railway hub, m represents a station node in the railway hub, B represents the set of travel zones, b represents a travel zone, g k,r represents whether train k selects operation plan r, represents the subway passenger flow from travel zone b to station node m in the railway hub when train k selects operation plan r, represents the subway travel time from travel zone b to station node m in the railway hub, represents the bus passenger flow from travel zone b to station node m in the railway hub when train k selects operation plan r, represents the bus travel time from travel zone b to station node m in the railway hub, represents the private car passenger flow from travel zone b to station node m in the railway hub when train k selects operation plan r, represents the private car travel time from travel zone b to station node m in the railway hub. W represents the set of origin-destination pairs of passenger flow, w represents an origin-destination pair, represents the penalty value for uncompleted travel of origin-destination pair w of passenger flow, y w represents the passenger flow not taken away by origin-destination pair w of passenger flow.

3. The optimization method of the division plan of the railway hub passenger station according to claim 2, characterized in that, The objective function for minimizing the total operating costs in the railway hub in step S2 is: Among them, Z2 represents the objective function with the minimum total operating cost within the railway hub, A represents the set of all sections within the railway hub, (m, n) represents the section from station node m to station node n within the railway hub, T represents the set of time periods, and t represents a time period. Indicates whether train k passes through section (m, n) during time period t when choosing operation plan r, d (m,n) Represents the mileage of section (m, n), μ represents the unit running cost of the train within the railway hub, η k,r,m,t Indicates whether train k stops at station node m within the railway hub during time period t when choosing operation plan r, and v represents the unit operation cost of the station for receiving and dispatching trains.

4. The optimization method of the division plan of the railway hub passenger station according to claim 3, characterized in that Step S3 specifically includes: S31. Establish the uniqueness constraint of train operation plans, that is: Among them, represents an arbitrary symbol, g k,r = 1 indicates that train k selects operation plan r; S32. Establish the coupling constraint of turnaround trains, that is: Among them, k′ represents the subsequent train of train k, indicates whether there is a turning-back relationship between train k and the subsequent train k′, represents the terminal station of the train operation plan r number, R k′ represents the alternative set of train operation plans for the subsequent train k′, g k′,r indicates whether the subsequent train k′ selects the train operation plan r, represents the departure station of the train operation plan r number; S33. Establish the coupling constraint of through trains, that is: Among them, indicates whether there is a connection relationship between train k and the subsequent train k'; represents the set of train operation plans in the alternative set R of operation plans where all the subsequent connecting trains are train k; represents the set of train operation plans in the alternative set R of operation plans where all the subsequent connecting trains are the subsequent train k'; indicates the connecting station specified in the operation plan r number; S34. Establish the constraint on the number of route adjustments in each direction, that is: Among them, X represents the set of train running directions, and x represents the train running direction. represents the set of running routes within the railway hub. represents the running route within the railway hub. represents and different running routes within the railway hub, ρ k,x represents whether the running direction of train k is x. represents whether the current operation plan of train k within the railway hub is represents whether the running route of train k when choosing operation plan r within the railway hub is represents the minimum number of trains with running direction x and whose running routes within the railway hub are adjusted from to ; the maximum number of trains with running direction x and whose running routes within the railway hub are adjusted from to ; S35. Establish the section passing capacity constraint, that is: Among them, C (m,n) represents the hourly passing capacity of the road section (m, n); S36. Establish the station operation capacity constraint, that is: Among them, G m represents the hourly train receiving and dispatching capacity of station node m in the railway hub; S37. Establish the car storage capacity constraint, that is: Among them, indicates whether train k conducts overnight parking at stabling yard c as specified in train operation plan r, Q c indicates the parking capacity of stabling yard c, and C represents the set of stabling yards; S38. Based on the uniqueness constraint of train operation plans, the coupling constraint of turnaround trains, the coupling constraint of through trains, the constraint on the number of route adjustments in each direction, the section passing capacity constraint, the station operation capacity constraint, and the car storage capacity constraint, obtain the objective constraint conditions.

5. The optimization method of the division plan of the railway hub passenger station according to claim 4, characterized in that Step S4 specifically includes: S41. Establish the train transportation capacity constraint, that is: Among them, f w,k represents the passenger flow volume assigned from the origin-destination w of the passenger flow to train k, γ w,k,(m,n) represents whether the running path of the origin-destination w of the passenger flow on train k includes the section (m, n), P k represents the seating capacity of train k; S42. Establish the flow conservation constraint of passenger flow origin and destination, that is: Among them, ER w represents the set of all trains that can provide travel services for the origin-destination w of passenger flow, represents the total passenger flow of the origin-destination w of passenger flow; S43. Establish the non-negative flow constraint of passenger flow origin and destination, that is: S44. Based on the train transportation capacity constraint, the flow conservation constraint of passenger flow origin and destination, and the non-negative flow constraint of passenger flow origin and destination, obtain the passenger flow distribution constraint conditions.

6. The optimization method of the division plan of the railway hub passenger station according to claim 5, characterized in that Step S5 specifically includes: S51. Based on the objective function for minimizing the total in-city travel time of passengers, the objective function for minimizing the total operating costs in the railway hub, the objective constraint conditions, and the passenger flow distribution constraint conditions, construct an optimization model for train operation plans; S52. Take 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, and use a professional solver to solve the train operation plan optimization model 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 with the minimum total in-city travel time for passengers, and the initial f w,k is the passenger flow distribution under the train operation plan; When using a professional solver to solve the train operation plan optimization model, the objective function of minimizing the total in-city travel time of passengers in the train operation plan optimization model is used as the main objective function, and the objective function of minimizing the total operation cost within the railway hub in the train operation plan optimization model is used as the secondary objective function. After optimizing the main objective function to reach the optimal state, the secondary objective function is optimized.

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

8. The optimization method for the division plan of railway hub passenger stations according to claim 7, characterized in that, Input the parameters K, W, P k , and the initial g k,r into the Logit model for solution to obtain f at the current moment w,k . The specific process is as follows: First, obtain the train stop plan g k,r and passenger flow data K, W, P k , At the same time, obtain the calibration parameters of passengers' travel choice behavior including fare, travel time, departure time and arrival time, and seat class; Secondly, according to the calibrated parameters of passengers' travel choice behavior, the origin-destination of passenger flow is divided into multiple layers. At the same time, the origin-destination of each layer of passenger flow is divided into several passenger flow blocks to obtain several origin-destination sub-tables for each layer. Finally, the origin-destination of passenger flow is allocated according to different layers and different origin-destination sub-tables to obtain the passenger volume of the origin-destination of passenger flow allocated to the train.

9. The optimization method of the division plan of the railway hub passenger station according to claim 8, characterized in that The specific process of allocating the origin-destination of passenger flow according to different layers and different origin-destination sub-tables is as follows: Step1: For the origin-destination of passenger flow w, based on the train stop plan g k,r , passenger flow data K, W, P k , and the calibration parameters of passengers' travel choice behavior, use the parallel bidirectional breadth-first search method to search, and judge whether there is a train that provides travel services for the origin-destination of passenger flow w and the allocated passenger flow is less than the train capacity. If so, execute Step2; otherwise, execute Step3; Step2: If the passenger volume to be allocated for the origin-destination of passenger flow w is q, then according to the calibrated parameters of passengers' travel choice behavior, calculate the probability that the origin-destination of passenger flow w selects a train k that can provide travel services and the allocated passenger volume is less than the train's capacity, that is: Among them, p w,k represents the probability that the origin-destination pair w of passenger flow selects a train k that can provide travel services and the allocated passenger flow is less than the train's seating capacity. exp represents the natural exponential function, and V w,k represents the fixed utility of the origin-destination pair w of passenger flow taking a train k that can provide travel services and the allocated passenger flow is less than the train's seating capacity; According to the probability that the origin-destination of passenger flow w selects a train k that can provide travel services and the allocated passenger volume is less than the train's capacity, calculate the actual passenger volume to be allocated, that is: where min represents taking the minimum value, q w,k represents the passenger flow volume to be allocated for the origin-destination w of the passenger flow to select a train k that can provide travel services and the allocated passenger flow volume is less than the train's seating capacity, c w,k represents the transportation capacity that a train k that can provide travel services and the allocated passenger flow volume is less than the train's seating capacity can provide for the origin-destination w of the passenger flow; Step3: Determine whether the layer where the origin-destination of passenger flow w is located is the last layer. If so, execute Step4; otherwise, update the remaining passenger volume of the origin-destination of passenger flow w and the remaining capacity of the train, enter the next origin-destination sub-table or the next layer, and execute Step1. Step4: Output the passenger volume of the origin-destination of passenger flow allocated to the train.

10. The optimization method of the division plan of the railway hub passenger station according to claim 9, characterized in that, Step S7 specifically includes: Calculate the difference between the initial Object(Z1) in the optimization result of the train operation plan and the current Object(Z1) at the current moment in the optimization result of the current train operation plan. 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 moment k,r .

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