CN112581184A - Air-iron combined transport fare formulation method, system, equipment and readable storage medium - Google Patents

Air-iron combined transport fare formulation method, system, equipment and readable storage medium Download PDF

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CN112581184A
CN112581184A CN202011579510.0A CN202011579510A CN112581184A CN 112581184 A CN112581184 A CN 112581184A CN 202011579510 A CN202011579510 A CN 202011579510A CN 112581184 A CN112581184 A CN 112581184A
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陈钉均
刘荣耀
倪少权
潘金山
李雪婷
吕红霞
吕苗苗
张�杰
王兵
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Abstract

The invention relates to the technical field of air-railway combined transportation, in particular to a method, a system, equipment and a readable storage medium for formulating an air-railway combined transportation fare, which comprises the steps of acquiring high-speed rail station information and airport information of each city and constructing an air-railway combined transportation network topology structure chart; aiming at balancing the benefits of passengers and air-rail joint operators, a double-layer planning model is constructed, wherein the double-layer planning model comprises an upper-layer planning model and a lower-layer planning model; and solving the lower-layer planning model by using a continuous average algorithm, then solving the upper-layer planning model by using a particle swarm algorithm, and iterating to obtain the optimal solution of the double-layer planning model. The invention improves the defects of the existing air-railway combined transportation by establishing a double-layer planning model, promotes the development of the air-railway combined transportation, optimizes the formulation process of the air-railway combined transportation fare, improves the passenger fare income and social welfare of air-railway combined transportation carriers, minimizes the general travel cost of passengers and obtains the optimized air-railway combined transportation fare.

Description

Air-iron combined transport fare formulation method, system, equipment and readable storage medium
Technical Field
The invention relates to the technical field of air-railway combined transportation, in particular to a method, a system, equipment and a readable storage medium for formulating an air-railway combined transportation ticket price.
Background
With the continuous expansion and improvement of the highway network of the high-speed railway in China, the operating mileage of the high-speed railway breaks through 3.5 kilometers, the importance degree of the high-speed railway in the transportation system of China continuously rises, and the competitiveness of the high-speed railway in the market and the aviation gradually rises. The method has the advantages that the construction pace of air-rail transport is accelerated, the system for cooperatively scheduling aviation and high-speed rail in a comprehensive transportation system is perfected, the passenger ticket income of air-rail transport carriers is improved, and the convenience and satisfaction of passenger travel are improved. The cooperative symbiosis of air and railway transportation means that in order to provide convenient and fast integrated high-speed passenger transportation service for passengers, two transportation modes of a high-speed railway and aviation can be better connected, the advantages of the two transportation modes in various markets are maximized, the advantages of the aviation and high-speed railway are complementary, and a convenient three-dimensional comprehensive transportation network is established.
The price optimization and formulation problem of the air and iron combined transport is an important link of the combined transport, and relates to the sharp problem of whether the combined transport passenger can make profit or not and whether the profit is the maximum or not, so that whether the air and iron combined transport can be better developed or not is influenced. The Chinese railway department is not a simple profit department, and can consider social benefits brought by railway transportation while realizing profit. Therefore, in the process of establishing the air-iron combined transportation ticket price, the passenger ticket income of an airline company, the passenger ticket income of a railway department and social benefits are maximized.
However, the following problems exist:
1. the passenger joint transport is a novel transport organization and service mode, is still in the initial stage at home at present, and relevant research is not deep enough, and the passenger joint transport management system mechanism is still not sound. The prior art solutions refer to high speed railways and aviation, paying more attention to their competitive rather than cooperative relationships.
2. The conventional method for establishing the fare of the high-speed railway is still too single, and the factors considered when establishing the fare are not comprehensive enough.
In summary, in the prior art, the air-rail intermodal fare formulation meeting the demand of intermodal transportation is not considered when formulating the fare, so that the benefit of aviation and high-speed rail in the related market cannot reach the maximum, better intermodal transportation service cannot be provided, even a situation of malignant competition may exist, and passengers cannot enjoy better convenient and comfortable transportation service.
Disclosure of Invention
The invention aims to provide a method, a system, equipment and a readable storage medium for formulating an air-railway combined transport fare, which are used for improving the passenger ticket income of an air-railway combined transport carrier, minimizing the generalized travel cost of passengers and obtaining the optimized air-railway combined transport fare so as to improve the problems.
In order to achieve the above object, the embodiments of the present application provide the following technical solutions:
a method for making an air-iron combined transport fare comprises the following steps:
s1: acquiring high-speed rail station information and airport information of each city, and constructing an air-railway transport network topology structure diagram;
s2: aiming at balancing the benefits of passengers and air-rail joint operators, a double-layer planning model is constructed, wherein the double-layer planning model comprises an upper-layer planning model and a lower-layer planning model;
s3: after the lower-layer planning model is solved by using a continuous average algorithm, the upper-layer model is converted into an unconstrained optimization problem by using a multiplier method, then the upper-layer planning model is solved by using a particle swarm algorithm, and the optimal solution of the double-layer planning model is obtained through iteration.
Further, the acquiring high-speed rail station information and airport information of each city and constructing an air-railway transport network topology structure diagram includes:
taking a city where a high-speed rail station or an airport is located as a node;
if the same high-speed rail is stopped between any two nodes, a connecting line A is arranged between the two nodes;
if the same row of flights can arrive between any two nodes, a connection B is arranged between the two nodes.
Further, the method is characterized in that a double-layer planning model is constructed by aiming at the benefit balance between the passengers and the air-rail joint operator, wherein the double-layer planning model comprises an upper-layer planning model and a lower-layer planning model, and the method comprises the following steps:
s21: constructing an upper-layer planning model by taking the maximum income of an airline company, the profit of a high-speed rail department and the achievement of the maximum social benefit as targets:
s22: the generalized travel cost of passengers is expressed by using a passenger utility function, the distribution result of passenger flow of the passenger flow in each market in the network is optimized by using a random user balance model, and a lower-layer planning model is constructed.
Further, after the lower-layer planning model is solved by using the continuous average algorithm, the upper-layer planning model is solved by using a multiplier method, and the optimal solution of the double-layer planning model is obtained through iteration, which includes:
s31: obtaining a function expression of the passenger flow of each market of the random user equilibrium model in an equilibrium state by using a continuous average algorithm;
s32: substituting the function expression into the upper-layer planning model, converting the upper-layer planning model into an unconstrained optimization problem by utilizing a multiplier method, and solving by using a particle swarm algorithm to obtain an optimal solution of the fare;
s33: judging whether the optimal solution meets the convergence precision or not, and if so, ending iteration; if not, repeating the steps until the optimal solution meets the convergence precision.
Further, the obtaining of the function expression of the passenger flow volume of each market of the random user equilibrium model in the equilibrium state by using the continuous average algorithm includes:
s310: setting an effective market set according to the air-rail transport network topology structure diagram;
s311: setting the passenger flow in the initial market to be 0 to obtain the generalized travel cost of the passengers;
s312: the random user balance network flow is loaded to obtain the passenger flow in the market
Figure BDA0002864925920000031
Wherein the content of the first and second substances,
Figure BDA0002864925920000041
the passenger flow of the traffic mode b used in the market m, j is the loading frequency, and j is 1;
s313: according to the passenger flow volume
Figure BDA0002864925920000042
Updating generalized travel cost;
s314: determining a descending direction according to the generalized travel cost, and loading the random user balance network flow again to obtain the augmented passenger flow
Figure BDA0002864925920000043
S315: updating the passenger flow volume according to the descending direction
Figure BDA0002864925920000044
Figure BDA0002864925920000045
S316: judging whether the passenger flow volume meets the convergence precision
Figure BDA0002864925920000046
Wherein
Figure BDA00028649259200000414
Is the maximum error allowance;
if yes, ending the iteration;
if not, then order
Figure BDA0002864925920000047
It jumps to S313.
Further, substituting the function expression into the upper-layer planning model, and converting the upper-layer planning model into an unconstrained optimization problem by using a multiplier method to solve to obtain an optimal solution of the fare, including:
s320: setting an initial air-iron intermodal fare to
Figure BDA0002864925920000048
Wholesale price w of high-speed railway ticketiWherein, the
Figure BDA0002864925920000049
A fare to be paid for the use of b means of transportation in market m;
s321: will be described in
Figure BDA00028649259200000410
And wiSubstituting into the lower planning model to obtain corresponding passenger flow
Figure BDA00028649259200000411
S322, the passenger volume
Figure BDA00028649259200000412
Substituting into the upper layer planning model, and using multiplier method to generate questionThe questions are converted into an unconstrained optimization problem to be solved, and a new fare is obtained by utilizing a particle swarm algorithm
Figure BDA00028649259200000413
wi+1。
Further, judging whether the optimal solution meets convergence precision or not, and if so, ending iteration; if not, repeating the steps until the optimal solution meets the convergence precision. The method comprises the following steps:
judging the fare
Figure BDA0002864925920000051
wi+1Whether convergence accuracy is satisfied;
if yes, ending the iteration;
if not, then order
Figure BDA0002864925920000052
wi+1，wi＝wi+1And goes to S321.
An air-rail intermodal fare formulation system, the system comprising:
an information acquisition module: the system comprises a network management system, a network management system and a network management system, wherein the network management system is used for acquiring high-speed rail station information and airport information of each city and constructing an air-railway transport network topology structure chart;
a model construction module: aiming at balancing the benefits of passengers and air-rail joint operators, a double-layer planning model is constructed, wherein the double-layer planning model comprises an upper-layer planning model and a lower-layer planning model;
a model solving module: after the lower-layer planning model is solved by using a continuous average algorithm, the upper-layer model is converted into an unconstrained optimization problem by using a multiplier method, then the upper-layer planning model is solved by using a particle swarm algorithm, and the optimal solution of the double-layer planning model is obtained through iteration.
An air-rail intermodal fare formulation apparatus comprising a memory for storing a computer program and a processor; the processor is used for realizing the steps of the air-iron combined transport fare formulation method when executing the computer program.
A readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the above-mentioned air-rail intermodal fare formulation method.
The invention has the beneficial effects that: the method is beneficial to overcoming the defects of the existing air-iron combined transportation, promoting the development of the air-iron combined transportation and optimizing the formulation process of the air-iron combined transportation ticket price, and has the advantages of quick and simple modeling process, unified standard, high efficiency of the calculation method, real and reliable method, comprehensive consideration and good operability, universality and availability.
The invention establishes a double-layer planning model which fully considers the double benefits of a pair of spears of a passenger and air-iron combined operator, the upper layer planning model is constructed by taking the maximum income of an airline company and the maximum social benefit achieved by a high-speed rail department as the target, the lower layer planning model expresses the generalized travel cost of passengers by using a passenger utility function, and a random user balance model with capacity constraint is used for optimizing the optimal response passenger flow distribution result of the passengers in each market of the passenger flow in the network; and taking the specified ranges of passenger flow, line capacity and fare as constraints, quickly solving the random user balance model with capacity constraint by using a continuous average method, solving the model planned at the upper layer by using a particle swarm algorithm, and iterating to finally obtain the optimal solution in the double-layer planning model, namely the air-rail intermodal fare.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the embodiments of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic flow chart of a method for making an air-iron combined transport fare according to embodiment 1 of the present invention;
FIG. 2 is a flowchart of the step of S31 described in embodiment 1 of the present invention;
FIG. 3 is a flowchart of the step of S32 described in embodiment 1 of the present invention;
fig. 4 is a topology structure diagram of an air-rail transport network in embodiment 1 of the present invention;
fig. 5 is a schematic structural diagram of an air-iron intermodal fare formulation device according to embodiment 3 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers or letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined or explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Example 1
As shown in fig. 1, the present embodiment provides a method for establishing an air-iron intermodal ticket price, which sets that an airline and a railway department have reached an intermodal agreement, and the railway department sells a certain number of high-iron tickets at a relatively low price to the airline to support intermodal transportation, thereby increasing social welfare. The setting accords with the situation of China, and high-speed rail stations and airports in the same city can be out of the same place.
The method comprises the following steps:
s1: acquiring high-speed rail station information and airport information of each city, and constructing an air-railway transport network topology structure diagram;
further, the S1 specifically includes:
taking a city where a high-speed rail station or an airport is located as a node;
if the same high-speed rail is stopped between any two nodes, a connecting line A is arranged between the two nodes;
if the same row of flights can arrive between any two nodes, a connection B is arranged between the two nodes.
Preferably, the line a and the line B are different lines, such as: dashed and straight lines are used for distinction.
Referring to fig. 4, O, H, D shows three nodes, O, D shows no direct transportation, H is a transit point, which is used as an intermodal transportation hub, and the high-speed rail station in the node is located at a different place from the airport.
It can be seen that there are three effective markets in the figure: OH, HD, OD, let M denote the active market, the set of M is M ═ { OH, HD, OD },
in the figure, there are 4 transportation modes, i.e., airplane, high-speed rail, airplane-to-airplane, high-speed rail-to-airplane, where B denotes a transportation mode, a denotes an airplane, and R denotes a high-speed rail, and B is set to { a, R, AA, AR }.
S2: aiming at balancing the benefits of passengers and air-rail joint operators, a double-layer planning model is constructed, wherein the double-layer planning model comprises an upper-layer planning model and a lower-layer planning model;
further, the S2 specifically includes:
s21: constructing an upper-layer planning model by taking the maximum income of an airline company, the profit of a high-speed rail department and the achievement of the maximum social benefit as targets;
Object:
Figure BDA0002864925920000081
Figure BDA0002864925920000082
s.t.
Figure BDA0002864925920000083
Figure BDA0002864925920000084
Figure BDA0002864925920000085
wherein the content of the first and second substances,
Figure BDA0002864925920000086
represents the fare required to be paid in market m using R transportation means,
Figure BDA0002864925920000087
the traffic volume representing the means of transportation used in market m,
Figure BDA0002864925920000088
representing the utility function of the passenger (i.e. the passenger perceived travel cost: the sum of the expenses the passenger perceives during actual travel),
Figure BDA0002864925920000089
represents the total fare of the air-iron combined transport,
Figure BDA00028649259200000810
representing the fare of high-speed rail in the air-iron combined transport.
In the objective function (1)
Figure BDA00028649259200000811
Indicating the income of tickets in the m markets of the high-speed railway department,
Figure BDA00028649259200000812
the social benefit achieved by promoting the joint transportation is expressed, and the social benefit achieved is expressed as the minimum generalized travel cost of passengers after the joint transportation is achieved in the embodiment for simple representation.
The objective function (2) represents the income of passenger tickets of the airlines in various markets.
Constraint (3) represents the capacity constraint for each market.
The constraint (4) represents the constraint of the air-iron combined transport fare, and the formula (5) represents the constraint value of the high-iron fare, which cannot be lower than the cost price and cannot be higher than the maximum fare value.
S22: the generalized travel cost of passengers is expressed by using a passenger utility function, a random user balance model optimizes the passenger flow distribution result of the passenger flow in each market in the network, and a lower-layer planning model is constructed:
Object：
Figure BDA0002864925920000091
Subject to:
Figure BDA0002864925920000092
Figure BDA0002864925920000093
Figure BDA0002864925920000094
Figure BDA0002864925920000095
wherein, theta is a non-negative parameter and describes the random characteristic of the model, and the value of theta is positively correlated with the understanding degree of a traveler on the market and the traffic mode; q is the total passenger volume of the entire market.
In the objective function (6), the target function is,
Figure BDA0002864925920000096
expressing an entropy value, wherein theta is a non-negative parameter and describes the random characteristic of the model, and the value size of the theta is positively correlated with the understanding degree of a traveler on the market and the traffic mode; sigmam∈M∑b∈B
Figure BDA0002864925920000097
Representing the total cognitive cost of the passenger.
Constraint (7) represents total flow conservation, in this embodiment, assuming total passenger flow Q throughout the market is given.
Constraint (8) represents the flow balance, Q, between individual markets according to the flow conservation theorem in the network diagrammRepresenting the total flow in market m.
Constraint (9) represents a capacity constraint in each market.
The constraint (10) represents a non-negative constraint of the flow. In order to solve the above problem, the present embodiment does not consider traffic congestion, but sets a limit to the traffic capacity, that is, the traffic capacity Q of each market.
For the passenger, the influence factors of the generalized travel cost of the passenger researched by the embodiment include travel time, fare and passenger discomfort, and the passenger achieving the joint transportation should have a certain deduction item in one item of discomfort degree. For simplicity, we selected a representative passenger in each market whose cognitive cost can be expressed as:
Figure BDA0002864925920000101
wherein alpha is1,α2,α3In order to determine the coefficient to be determined,
Figure BDA0002864925920000102
represents travel time in market m using b transportation means,
Figure BDA0002864925920000103
the fare required to be paid by the passengers using the b transportation mode in the market m is represented;
Figure BDA0002864925920000104
representing the discomfort degree of passengers when using the b-mode of transportation to change passengers, the discomfort degree is closely related to the passenger flow on the path,
Figure BDA0002864925920000105
can be expressed as:
Figure BDA0002864925920000106
when in use
Figure BDA0002864925920000107
When xi is 0. For passengers who select the air-iron combined transportation fare, xi is an important part, embodies the advantages of air-iron combined transportation, and is an important factor for attracting passenger flow by air-iron combined transportation.
S3: after the lower-layer planning model is solved by using a continuous average algorithm, the upper-layer model is converted into an unconstrained optimization problem by using a multiplier method, then the upper-layer planning model is solved by using a particle swarm algorithm, and the optimal solution of the double-layer planning model is obtained through iteration.
Further, the S3 specifically includes:
s31: obtaining a function expression of the passenger flow of each market of the random user equilibrium model in an equilibrium state by using a continuous average algorithm;
further, referring to fig. 2, the S31 specifically includes:
s310: setting an effective market set m according to the air-rail transport network topology structure diagram;
s311: setting the passenger flow in the initial market to be 0 to obtain the generalized travel cost of the passengers;
s312: loading random user balance network flow (using a one-time random user balance model to distribute the flow and obtain the flow in each market under certain generalized travel cost) to obtain the passenger flow in the market
Figure BDA0002864925920000111
Wherein the content of the first and second substances,
Figure BDA0002864925920000112
the passenger flow of the traffic mode b used in the market m, j is the loading frequency, and j is 1;
s313: according to the passenger flow volume
Figure BDA0002864925920000113
Updating generalized travel cost;
s314: determining a descending direction according to the generalized travel cost, and loading the random user balance network flow again to obtain the augmented passenger flow
Figure BDA0002864925920000114
S315: updating the passenger flow volume according to the descending direction
Figure BDA0002864925920000115
Figure BDA0002864925920000116
S316: judging whether the passenger flow volume meets the convergence precision
Figure BDA0002864925920000117
Wherein
Figure BDA00028649259200001115
Is the most importantLarge error tolerance values;
if yes, ending the iteration;
if not, then order
Figure BDA0002864925920000118
It jumps to S313.
S32: substituting the function expression into the upper-layer planning model, converting the upper-layer planning model into an unconstrained optimization problem by utilizing a multiplier method for solving, and then obtaining an optimal solution of the fare by using a particle swarm algorithm;
further, referring to fig. 3, the S32 specifically includes:
s320: setting an initial air-iron intermodal fare to
Figure BDA0002864925920000119
Wholesale price w of high-speed railway ticketiWherein, the
Figure BDA00028649259200001110
A fare to be paid for the use of b means of transportation in market m;
s321: will be described in
Figure BDA00028649259200001111
And wiSubstituting into the lower planning model to obtain corresponding passenger flow
Figure BDA00028649259200001112
S322, the passenger flow volume is calculated
Figure BDA00028649259200001113
Substituting into the upper-layer planning model, converting the problem into unconstrained optimization problem by multiplier method, and solving to obtain new fare
Figure BDA00028649259200001114
wi+1。
S33: judging whether the optimal solution meets the convergence precision or not, enabling the iteration frequency to be 1000, and if so, ending the iteration; if not, repeating the steps until the optimal solution meets the convergence precision.
Further, the S33 specifically includes:
judging the fare
Figure BDA0002864925920000121
wi+1Whether convergence accuracy is satisfied;
if yes, ending the iteration;
if not, then order
Figure BDA0002864925920000122
wi+1，wi＝wi+1And goes to S321.
Example 2
Corresponding to the above method embodiment, the embodiment of the present disclosure further provides an air-iron combined transport fare formulation system, and the air-iron combined transport fare formulation system described below and the air-iron combined transport fare formulation method described above may be referred to correspondingly.
The system comprises the following modules:
an information acquisition module: the system comprises a network management system, a network management system and a network management system, wherein the network management system is used for acquiring high-speed rail station information and airport information of each city and constructing an air-railway transport network topology structure chart;
a model construction module: aiming at balancing the benefits of passengers and air-rail joint operators, a double-layer planning model is constructed, wherein the double-layer planning model comprises an upper-layer planning model and a lower-layer planning model;
a model solving module: and solving the lower-layer planning model by using a continuous average algorithm, then solving the upper-layer planning model by using a multiplier method, and obtaining the optimal solution of the double-layer planning model through iteration.
It should be noted that, regarding the system in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated herein.
Example 3
Corresponding to the above method embodiment, the embodiment of the present disclosure further provides an air-iron combined transport fare formulating device, and the air-iron combined transport fare formulating device described below and the air-iron combined transport fare formulating method described above can be referred to correspondingly.
A block diagram of an air-rail intermodal fare formulation apparatus is shown in accordance with an exemplary embodiment. Referring to fig. 5, the electronic device may include: a processor, a memory. The electronic device may also include one or more of a multimedia component, an input/output (I/O) interface, and a communication component.
The processor is used for controlling the overall operation of the electronic equipment so as to complete all or part of the steps in the method for making the air-iron combined transport fare. The memory is used to store various types of data to support operation at the electronic device, which may include, for example, instructions for any application or method operating on the electronic device, as well as application-related data such as contact data, messaging, pictures, audio, video, and so forth. The Memory may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk. The multimedia components may include a screen and an audio component. Wherein the screen may be, for example, a touch screen and the audio component is used for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may further be stored in a memory or transmitted through a communication component. The audio assembly also includes at least one speaker for outputting audio signals. The I/O interface provides an interface between the processor and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component is used for carrying out wired or wireless communication between the electronic equipment and other equipment. Wireless communication, such as Wi-Fi, bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so that the corresponding communication component may include: Wi-Fi module, bluetooth module, NFC module.
In an exemplary embodiment, the electronic Device may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components, for performing the above-mentioned air rail joint fare pricing method.
In another exemplary embodiment, there is also provided a computer readable storage medium comprising program instructions which, when executed by a processor, implement the steps of the above-described air-rail intermodal fare pricing method. For example, the computer readable storage medium may be the above-mentioned memory including program instructions executable by a processor of an electronic device to perform the above-mentioned method of air rail intermodal fare pricing.
Example 4
Corresponding to the above method embodiment, the embodiment of the present disclosure further provides a readable storage medium, and a readable storage medium described below and an air iron intermodal fare making method described above can be correspondingly referred to each other.
A readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the steps of the air-rail intermodal fare formulation method of the above-described method embodiments.
The readable storage medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and various other readable storage media capable of storing program codes.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. A method for making an air-iron combined transport fare is characterized by comprising the following steps:
acquiring high-speed rail station information and airport information of each city, and constructing an air-railway transport network topology structure diagram;
aiming at balancing the benefits of passengers and air-rail joint operators, a double-layer planning model is constructed, wherein the double-layer planning model comprises an upper-layer planning model and a lower-layer planning model;
after the lower-layer planning model is solved by using a continuous average algorithm, the upper-layer model is converted into an unconstrained optimization problem by using a multiplier method, then the upper-layer planning model is solved by using a particle swarm algorithm, and the optimal solution of the double-layer planning model is obtained through iteration.
2. The air-railway intermodal fare formulation method according to claim 1, wherein the obtaining of high-speed rail station information and airport information of each city and the construction of an air-railway intermodal network topology structure diagram comprise:
taking a city where a high-speed rail station or an airport is located as a node;
if the same high-speed rail is stopped between any two nodes, a connecting line A is arranged between the two nodes;
if the same row of flights can arrive between any two nodes, a connection B is arranged between the two nodes.
3. The air-iron intermodal fare formulation method according to claim 1, wherein the objective of balancing the interests of passengers and air-iron joint operators is to construct a two-tier planning model, the two-tier planning model including an upper-tier planning model and a lower-tier planning model, including:
constructing an upper-layer planning model by taking the maximum income of an airline company, the profit of a high-speed rail department and the achievement of the maximum social benefit as targets;
the generalized travel cost of passengers is expressed by using a passenger utility function, the distribution result of passenger flow of the passenger flow in each market in the network is optimized by using a random user balance model, and a lower-layer planning model is constructed.
4. The air-iron intermodal fare formulation method according to claim 3, wherein after the lower layer planning model is solved by using the continuous average algorithm, the upper layer planning model is converted into an unconstrained optimization problem by using a multiplier method, then the upper layer planning model is solved by using a particle swarm algorithm, and an optimal solution of the double-layer planning model is obtained through iteration, including:
obtaining a function expression of the passenger flow of each market of the random user equilibrium model in an equilibrium state by using a continuous average algorithm;
substituting the function expression into the upper-layer planning model, converting the upper-layer planning model into an unconstrained optimization problem by utilizing a multiplier method, and solving to obtain an optimal solution of the fare;
judging whether the optimal solution meets the convergence precision or not, and if so, ending iteration; if not, repeating the steps until the optimal solution meets the convergence precision.
5. The air-iron intermodal fare formulation method according to claim 4, wherein the using a continuous average algorithm to find the functional expression of the passenger flow of each market of the random user equilibrium model under the equilibrium state comprises:
setting an effective market set according to the air-rail transport network topology structure diagram;
setting the passenger flow in the initial market to be 0 to obtain the generalized travel cost of the passengers;
loading random user balance network flow to obtain the network flow in the marketPassenger flow volume of
Figure FDA0002864925910000021
Wherein the content of the first and second substances,
Figure FDA0002864925910000022
the passenger flow of the traffic mode b used in the market m, j is the loading frequency, and j is 1;
according to the passenger flow volume
Figure FDA0002864925910000023
Updating generalized travel cost;
determining a descending direction according to the generalized travel cost, and loading the random user balance network flow again to obtain the augmented passenger flow
Figure FDA0002864925910000024
Updating the passenger flow volume according to the descending direction
Figure FDA0002864925910000025
Figure FDA0002864925910000026
Judging whether the passenger flow volume meets the convergence precision
Figure FDA0002864925910000027
Where θ is the maximum allowable error value;
if yes, ending the iteration;
if not, then order
Figure FDA0002864925910000031
The generalized travel cost continues to be updated and the above steps are repeated until the convergence accuracy is met.
6. The air-iron combined transport fare formulation method according to claim 4, wherein the substituting the function expression into the upper layer planning model, and converting the upper layer planning model into an unconstrained optimization problem by a multiplier method for solving to obtain an optimal solution of the fare comprises:
setting an initial air-iron intermodal fare to
Figure FDA0002864925910000032
Wholesale price w of high-speed railway ticketiWherein, the
Figure FDA0002864925910000033
A fare to be paid for the use of b means of transportation in market m;
will be described in
Figure FDA0002864925910000034
And wiSubstituting into the lower planning model to obtain corresponding passenger flow
Figure FDA0002864925910000035
The passenger flow volume is measured
Figure FDA0002864925910000036
Substituting into the upper-layer planning model, converting the problem into unconstrained optimization problem by multiplier method, solving, and obtaining new fare by particle swarm algorithm
Figure FDA0002864925910000037
wi+1。
7. The air-iron intermodal fare formulation method according to claim 6, wherein the determination of whether the optimal solution meets convergence accuracy is made and if so, the iteration is ended; if not, repeating the steps until the optimal solution meets the convergence precision, comprising:
judging the fare
Figure FDA0002864925910000038
wi+1Whether convergence accuracy is satisfied;
if yes, ending the iteration;
if not, then order
Figure FDA0002864925910000039
wi+1，wi＝wi+1And substituting the calculated passenger flow into a lower-layer planning model, and repeatedly calculating the passenger flow until the convergence precision is met.
8. An air-iron intermodal fare formulation system, comprising:
an information acquisition module: the system comprises a network management system, a network management system and a network management system, wherein the network management system is used for acquiring high-speed rail station information and airport information of each city and constructing an air-railway transport network topology structure chart;
a model construction module: aiming at balancing the benefits of passengers and air-rail joint operators, a double-layer planning model is constructed, wherein the double-layer planning model comprises an upper-layer planning model and a lower-layer planning model;
a model solving module: after the lower-layer planning model is solved by using a continuous average algorithm, the upper-layer model is converted into an unconstrained optimization problem by using a multiplier method, then the upper-layer planning model is solved by using a particle swarm algorithm, and the optimal solution of the double-layer planning model is obtained through iteration.
9. An air-iron intermodal fare formulation device, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the method of air-iron intermodal fare formulation according to any one of claims 1 to 7 when said computer program is executed.
10. A readable storage medium, characterized by: the readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the air-iron intermodal fare formulation method according to any one of claims 1 to 7.
CN202011579510.0A 2020-12-28 2020-12-28 Air-iron combined transport fare formulation method, system, equipment and readable storage medium Pending CN112581184A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113627915A (en) * 2021-06-30 2021-11-09 中国国家铁路集团有限公司 Intermodal device and system
CN113743987A (en) * 2021-08-25 2021-12-03 东南大学 Passenger transport mode shift and ticket price making method based on air-rail link

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113627915A (en) * 2021-06-30 2021-11-09 中国国家铁路集团有限公司 Intermodal device and system
CN113743987A (en) * 2021-08-25 2021-12-03 东南大学 Passenger transport mode shift and ticket price making method based on air-rail link

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