Method, system, computer equipment and storage medium for automatic allocation of airport parking spaces

Abstract

The present invention relates to the field of automated processing technology, and in particular to an automatic allocation method, system, computer equipment and storage medium for airport parking stands, the method comprising the following steps: obtaining flight dynamic information, parking stand information and airlines' preference information for stands at a target airport; processing and integrating the obtained information to obtain a set of flights to be allocated stands, a set of flights to be occupied stands and a stand priority table; constructing a flight-stand weight coefficient matrix according to the stand priority table; determining an objective function for stand allocation according to the weight coefficient matrix and the set of flights to be allocated stands and the set of flights to be occupied stands, and constructing a stand allocation model, and solving it to obtain a stand allocation plan; constructing a rolling allocation model, and solving a rolling allocated stand allocation plan based on the stand allocation model after a preset update time. The present invention improves the effectiveness and real-time performance of stand allocation.

Description

Technical Field

[0001] The present invention relates to the field of automated processing technology, and in particular to an automatic allocation method, system, computer equipment and storage medium for airport parking spaces. Background Art

[0002] As the most important resource in the operation of an airport, parking stands are the location for ground support operations for flights. They are also the core for flights to arrive and depart efficiently and orderly. Therefore, parking stands are an important factor in whether an airport can improve its service quality.

[0003] However, as the flight traffic becomes increasingly dense, and the parking space resources cannot be increased in the short term, it has caused great pressure on the airport. The allocation of parking spaces is a very difficult problem for both ground dispatchers and staff in the operation control center. At present, airports mainly use the parking space allocation system for auxiliary allocation, and the parking space allocation personnel make adjustments based on the system allocation results. However, according to relevant surveys, large airports have a high flight density and a shortage of jet bridge space resources. When there are special circumstances such as flight delays, advances, and cancellations, the parking space allocation personnel need to make adjustments quickly, and often need to make adjustments to flights in an area, which invisibly increases the difficulty and intensity of the work of the parking space allocation personnel. In addition, the quality of the results of the manual allocation plan depends to a certain extent on the work experience of the parking space allocation personnel. The optimality of the parking space allocation plan is difficult to guarantee, which easily leads to a waste of parking space resources.

[0004] To sum up, the allocation scheme obtained by the existing technology is difficult to respond to sudden delays, advances, and cancellations of flights in real time, cannot effectively meet the actual needs of the airport, and makes the work of the aircraft stand allocation personnel more difficult. Therefore, how to improve the effectiveness and real-time performance of airport aircraft stand allocation has become an urgent problem to be solved. Summary of the invention

[0005] The present invention provides an automatic allocation method, system, computer equipment and storage medium for an airport parking stand, aiming to solve the problems of effectiveness and real-time performance of the existing airport parking stand allocation.

[0006] In a first aspect, the present invention provides a method for automatically allocating parking spaces at an airport, comprising the following steps:

[0007] S1: Obtain flight dynamic information, parking space information and airlines' parking space preference information of the target airport;

[0008] S2: Processing and integrating the flight dynamic information, the parking space information and the airline's parking space preference information to obtain a set of flights to be allocated parking spaces, a set of flights that have occupied parking spaces and a parking space priority table;

[0009] S3: constructing a flight-aircraft slot weight coefficient matrix according to the aircraft slot priority table;

[0010] S4: determining an objective function for parking stand allocation according to the flight-stand weight coefficient matrix, the set of flights with stands to be allocated, and the set of flights with occupied stands, constructing a parking stand allocation model, and solving the parking stand allocation model to obtain a parking stand allocation plan;

[0011] S5: constructing a rolling allocation model, and solving a rolling allocation parking stand allocation plan based on the parking stand allocation model after obtaining a preset update time of the parking stand allocation plan.

[0012] Further:

[0013] The flight dynamic information includes: historical flight information, flight information for the next day and flight splicing information, wherein the flight information for the next day includes flight number, flight attributes, flight model, flight airline, flight mission, arrival time and departure time;

[0014] The parking stand information includes parking stand static information, stand occupancy information, stand maintenance information and parking stand area information, wherein the parking stand static information includes the parking stand number, the parking stand aircraft type level, the parking stand attribute, the set of airlines that can park flights at the parking stand, the task set of flights that can be parked at the parking stand and the parking stand type;

[0015] The airline's seat preference information includes the type of airline, the type of flight, and the airline's seat preference for a specific flight type.

[0016] Furthermore, step S2 includes the following sub-steps:

[0017] Splicing the flight information for the next day according to the flight splicing information to obtain a spliced ​​flight pair, so as to obtain the set of flights to be allocated stands, wherein the spliced ​​flight pair consists of an inbound flight and a outbound flight;

[0018] Filter out the flights occupying the aircraft stands from the historical flight information according to the arrival time and the departure time, and associate them with the aircraft stand occupancy information and the aircraft stand maintenance information to obtain the set of flights occupying the aircraft stands;

[0019] The slots are divided into a plurality of priorities according to the airlines' preference for the slots under the specific flight type to obtain the slot priority table, wherein different weight coefficients are set corresponding to different priorities.

[0020] Furthermore, step S3 is specifically as follows:

[0021] The flight-airport weight coefficient matrix is ​​constructed according to the aircraft slot priority table and the weight coefficients corresponding to the different priorities.

[0022] Furthermore, the parking space allocation model is specifically as follows:

[0023] min∑ i∈I ∑ k∈K x ik *c ik (1);

[0024]

[0025]

[0026]

[0027]

[0028]

[0029]

[0030]

[0031]

[0032]

[0033] Among them, I and i are flight set and flight i, i∈I respectively;

[0034] K and k are respectively the parking stand set and parking stand k, k∈K;

[0035] x ik Indicates whether flight i is assigned to slot k;

[0036] airline ik Indicates whether the airline of flight i is included in the set of airlines that can stop at gate k;

[0037] attr ik Indicates whether the attributes of flight i are included in the parking attribute set of stand k;

[0038] type ik Indicates whether the aircraft type of flight i is included in the set of aircraft types that can be parked at parking space k;

[0039] task ik Indicates whether the tasks of flight i include the set of tasks that can be stopped at stand k;

[0040] M represents a very large number;

[0041] J i , j represent the set of flights that conflict with flight i and flight j, respectively, j∈J i ;

[0042] x jk Indicates whether flight j that conflicts with flight i is assigned to slot k;

[0043] Q and U are respectively a set of combined positions and a group of combined positions U, U∈Q;

[0044] c is the key position c in a group of combined positions, c∈U;

[0045] I U Represents a set of combined stands U that can accommodate a set of flights;

[0046] x iU Indicates whether flight i is assigned to a set of combined seats U;

[0047] x bc Indicates whether flight i is assigned to a key stand c in a group of combined stands;

[0048] C U , G is the maximum group set of flights with combined seats and the maximum group G, G∈C U ;

[0049] c ik represents the weight coefficient of slot k for flight i;

[0050] Among them, constraints (8), constraints (9), and constraints (10) are modeled using the maximum clique method.

[0051] Furthermore, the rolling allocation model is specifically:

[0052]

[0053] φ 1 =max|∑ i∈I ∑ k∈K x ik *c ik | (12);

[0054]

[0055] Among them, k 1 and k 2 Represents the weight coefficient, I r represents the set of flights currently allocated, r i Indicates whether flight i has a slot change compared with the previous allocation result, if yes, it is 1, otherwise it is 0;

[0056] The rolling allocation model has the following constraints:

[0057]

[0058]

[0059]

[0060]

[0061]

[0062]

[0063]

[0064]

[0065]

[0066]

[0067] Among them, d lk is the distance between position l and position k, y i Indicates whether the boarding gate information of flight i has been released, 1 if yes, 0 otherwise; D indicates the maximum allowable parking position change distance.

[0068] Furthermore, the process of solving the parking space allocation model is solved using a gurobi solver.

[0069] In a second aspect, the present invention further provides an airport parking stand automatic allocation system, comprising:

[0070] The data acquisition module is used to obtain the flight dynamic information, parking space information and the airlines' parking space preference information of the target airport;

[0071] The first processing module is used to process and integrate the flight dynamic information, the parking position information and the airline's parking position preference information to obtain a set of flights to be allocated parking positions, a set of flights that have occupied parking positions and a parking position priority table;

[0072] A second processing module is used to construct a flight-aircraft position weight coefficient matrix according to the aircraft position priority table;

[0073] A parking stand allocation module is used to determine the objective function of parking stand allocation according to the flight-stand weight coefficient matrix and the set of flights with stands to be allocated and the set of flights with occupied stands, and to construct a parking stand allocation model, and to solve the parking stand allocation model to obtain a parking stand allocation plan;

[0074] The rolling allocation module is used to construct a rolling allocation model and solve a rolling allocation parking stand allocation plan based on the parking stand allocation model after obtaining a preset update time of the parking stand allocation plan.

[0075] In a third aspect, the present invention further provides a computer device, characterized in that it comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps in the automatic airport parking space allocation method as described above are implemented.

[0076] In a fourth aspect, the present invention further provides a storage medium, characterized in that a computer program is stored on the storage medium, and when the computer program is executed by a processor, the steps in the automatic allocation method of airport parking spaces as described above are implemented.

[0077] The beneficial effect achieved by the present invention is that a method for automatically allocating airport parking stands is proposed, which takes into account the inconsistent preferences of airlines for different stands, generates a stand priority table according to flight preference information, and optimizes the stand allocation results in combination with a series of constraints. This method can effectively reduce the workload of stand allocation personnel and improve data validity. At the same time, combined with the method of timed rolling allocation, it can immediately respond to large-scale adjustments to subsequent flights caused by flight delays, advances, and cancellations, reduce the scheduling pressure of stand allocation personnel, and improve data real-time performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 It is a schematic diagram of the steps of the method for automatically allocating airport parking spaces provided by an embodiment of the present invention;

[0079] Figure 2 It is a structural schematic diagram of an automatic allocation system for airport parking spaces provided by an embodiment of the present invention;

[0080] Figure 3 It is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0081] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0082] Please refer to Figure 1 , Figure 1 1 is a schematic diagram of the steps of the method for automatically allocating airport parking spaces provided by an embodiment of the present invention, wherein the method for automatically allocating airport parking spaces comprises the following steps:

[0083] S1: Obtain flight dynamic information, parking space information and airlines’ parking space preference information of the target airport.

[0084] The flight dynamic information includes: historical flight information, flight information for the next day and flight splicing information, wherein the flight information for the next day includes flight number, flight attributes, flight model, flight airline, flight mission, arrival time and departure time;

[0085] The parking stand information includes parking stand static information, stand occupancy information, stand maintenance information and parking stand area information, wherein the parking stand static information includes the parking stand number, the parking stand aircraft type level, the parking stand attribute, the set of airlines that can park flights at the parking stand, the task set of flights that can be parked at the parking stand and the parking stand type;

[0086] The airline's seat preference information includes the type of airline, the type of flight, and the airline's seat preference for a specific flight type.

[0087] S2: Process and integrate the flight dynamic information, the parking position information and the airline's parking position preference information to obtain a set of flights to be allocated parking positions, a set of flights with occupied parking positions and a parking position priority table.

[0088] Step S2 includes the following sub-steps:

[0089] The flight information of the future day is spliced ​​according to the flight splicing information to obtain a spliced ​​flight pair, so as to obtain the flight set to be allocated a stand, wherein the spliced ​​flight pair consists of an incoming flight and a departing flight, that is, the aircraft performs the incoming flight mission and then performs the departing flight mission, and the time from the arrival time to the departure time is the stand occupancy time;

[0090] Filter out the flights occupying the stands from the historical flight information according to the arrival time and the departure time, and associate them with the stand occupancy information and the stand maintenance information to obtain the set of flights that have occupied the stands, wherein the stand maintenance information is stored as a virtual flight in the set of flights that have occupied the stands;

[0091] The aircraft positions are divided into multiple priorities according to the airline's preference for aircraft positions under the specific flight type to obtain the aircraft position priority table, wherein different weight coefficients are set corresponding to different priorities. Preferably, the aircraft positions are divided into five categories to form five priorities, wherein the first priority category is all close aircraft positions, and the same airline's preference for aircraft positions under different flight types is inconsistent.

[0092] S3: Constructing a flight-airport weight coefficient matrix according to the aircraft slot priority table.

[0093] The flight-airport weight coefficient matrix is ​​constructed according to the aircraft slot priority table and the weight coefficients corresponding to the different priorities.

[0094] S4: Determine the objective function for parking stand allocation according to the flight-stand weight coefficient matrix, the set of flights with stands to be allocated, and the set of flights with occupied stands, construct a parking stand allocation model, and solve the parking stand allocation model to obtain a parking stand allocation plan.

[0095] The parking space allocation model is specifically as follows:

[0096] min∑ i∈I ∑ k∈K x ik *c ik (1);

[0097]

[0098]

[0099]

[0100]

[0101]

[0102]

[0103]

[0104]

[0105]

[0106] Among them, I and i are flight set and flight i, i∈I respectively;

[0107] K and k are respectively the parking stand set and parking stand k, k∈K;

[0108] x ik Indicates whether flight i is assigned to slot k;

[0109] airline ik Indicates whether the airline of flight i is included in the set of airlines that can stop at gate k;

[0110] attr ik Indicates whether the attributes of flight i are included in the parking attribute set of stand k;

[0111] type ik Indicates whether the aircraft type of flight i is included in the set of aircraft types that can be parked at parking space k;

[0112] task ik Indicates whether the tasks of flight i include the set of tasks that can be stopped at stand k;

[0113] M represents a very large number;

[0114] J i , j represent the set of flights that conflict with flight i and flight j, respectively, j∈J i ;

[0115] x jk Indicates whether flight j that conflicts with flight i is assigned to slot k;

[0116] Q and U are respectively a set of combined positions and a group of combined positions U, U∈Q;

[0117] c is the key position c in a group of combined positions, c∈U;

[0118] I U Represents a set of combined stands U that can accommodate a set of flights;

[0119] x iU Indicates whether flight i is assigned to a set of combined seats U;

[0120] x bc Indicates whether flight i is assigned to a key stand c in a group of combined stands;

[0121] C U , G is the maximum group set of flights with combined seats and the maximum group G, G∈C U ;

[0122] c ik represents the weight coefficient of slot k for flight i;

[0123] Among them, constraints (8), constraints (9), and constraints (10) are modeled using the maximum clique method.

[0124] The maximum clique method means that if a clique is not included in any other clique, that is, it is not a true subset of any other clique, then the clique is called a maximum clique. In the embodiment of the present invention, the maximum clique method can be used to change the flight conflict conditions for different constraints, so that the combined aircraft stand conflict condition is that the flight time of the main aircraft stand and the sub-aircraft stand cannot conflict, the composite aircraft stand conflict condition is that the flight time and aircraft model of the main aircraft stand and the sub-aircraft stand cannot conflict, and the taxiway conflict constraint conflict condition is that the arrival and departure times of aircraft sharing the same taxiway must be separated by more than 5 minutes. According to different constraints and corresponding conflict conditions, corresponding maximum cliques are established, thereby establishing corresponding constraints. During implementation, establishing constraints through the maximum clique method can greatly reduce the number of constraints and speed up the solution.

[0125] In the above relationship, the objective function formula (1) ensures that the airline's preference for aircraft slots is met to the greatest extent possible, and also ensures the maximum docking rate;

[0126] Constraint formula (2) ensures that each flight must be assigned to and can only be assigned to one seat;

[0127] Constraint formula (3) ensures that the flight assigned to a certain slot must meet the airline requirements for that slot;

[0128] Constraint formula (4) ensures that the flight assigned to a certain slot must meet the attribute requirements of the slot;

[0129] Constraint formula (5) ensures that the flight assigned to a certain parking space must meet the aircraft type requirements of the parking space;

[0130] Constraint formula (6) ensures that the flight assigned to a certain parking space must meet the mission requirements of the parking space;

[0131] Constraint formula (7) ensures that flights assigned to the same stand cannot have time conflicts;

[0132] Formula (8) and Formula (9) constrain the relationship between the allocation of a flight to a group of combined stands and the allocation of a flight to a single stand;

[0133] Constraint formula (10) ensures that when a flight is parked at a key stand in a combination of stands, no flight can be parked at the adjacent stands of the key stand.

[0134] The parking stand allocation model is solved by using the gurobi solver. The parking stand allocation solution obtained by solving the solution includes flight information and the allocated stands.

[0135] S5: constructing a rolling allocation model, and solving a rolling allocation parking stand allocation plan based on the parking stand allocation model after obtaining a preset update time of the parking stand allocation plan.

[0136] Preferably, the preset update time is set to ten minutes, that is, the data is updated every ten minutes, and the data processing step is performed to realize the rolling allocation of the stands. After the flight updates the estimated arrival or departure time, the flight dynamic information will change, and the input data will be re-acquired every ten minutes, and then the input data will be integrated, and the flights that have occupied the stands on site will be re-screened to obtain the set of flights to be allocated, the set of flights that have occupied the stands, and the stand priority table, and then the flight-stand weight coefficient matrix will be constructed, and then the stand allocation model will be constructed and solved, and finally a new stand allocation plan will be obtained.

[0137] In the embodiment of the present invention, the objective function of the rolling allocation model is as follows:

[0138] The objective function mainly includes two sub-objective functions, namely, maximizing the satisfaction of airlines' preferences for slots and minimizing the number of slot changes, where k 1 and k 2 Respectively represent the weight coefficients of the two objectives. Here, k 1 Take 3, k 2 Take 1, that is, the priority is to maximize the preference of all airlines for the slots, and the second is to minimize the number of slot changes. Since the two sub-goals have different dimensions and ranges, it is necessary to normalize the different functions, that is, to transform the objective function into the following, where φ 1 and φ 2 are the maximum values ​​of the absolute values ​​of the two sub-goals, and are the normalized correction values, which serve to normalize the goals of different dimensions:

[0139]

[0140] φ 1 =max|∑ i∈I ∑ k∈K x ik *c ik | (12);

[0141]

[0142] Among them, I r represents the set of flights currently allocated, r i Indicates whether flight i has a slot change compared with the previous allocation result, if yes, it is 1, otherwise it is 0;

[0143] The rolling allocation model has the following constraints:

[0144]

[0145]

[0146]

[0147]

[0148]

[0149]

[0150]

[0151]

[0152]

[0153]

[0154] Among them, d lk is the distance between position l and position k, y i Indicates whether flight i has released boarding gate information, 1 if yes, 0 otherwise; D indicates the maximum allowable parking position change distance. Constraint (14) indicates that when changing the parking position of a flight that has released boarding gate information, the distance between the changed parking position and the parking position before the change must be less than the maximum allowable parking position change distance.

[0155] The beneficial effect achieved by the present invention is that a method for automatically allocating airport parking stands is proposed, which takes into account the inconsistent preferences of airlines for different stands, generates a stand priority table according to flight preference information, and optimizes the stand allocation results in combination with a series of constraints. This method can effectively reduce the workload of stand allocation personnel and improve data validity. At the same time, combined with the method of timed rolling allocation, it can immediately respond to large-scale adjustments to subsequent flights caused by flight delays, advances, and cancellations, reduce the scheduling pressure of stand allocation personnel, and improve data real-time performance.

[0156] The present invention also provides an automatic allocation system for airport parking spaces, please refer to Figure 2 , Figure 2 200 is a schematic diagram of the structure of an automatic airport parking stand allocation system provided by an embodiment of the present invention. The automatic airport parking stand allocation system 200 includes:

[0157] Data acquisition module 201, used to obtain flight dynamic information, parking space information and airlines' parking space preference information of the target airport;

[0158] The first processing module 202 is used to process and integrate the flight dynamic information, the parking position information and the airline's parking position preference information to obtain a set of flights to be allocated parking positions, a set of flights that have occupied parking positions and a parking position priority table;

[0159] The second processing module 203 is used to construct a flight-aircraft slot weight coefficient matrix according to the aircraft slot priority table;

[0160] The parking stand allocation module 204 is used to determine the objective function of parking stand allocation according to the flight-stand weight coefficient matrix and the set of flights with stands to be allocated and the set of flights with occupied stands, and to construct a parking stand allocation model, and to solve the parking stand allocation model to obtain a parking stand allocation plan;

[0161] The rolling allocation module 205 is used to construct a rolling allocation model and solve a rolling allocation parking stand allocation plan based on the parking stand allocation model after obtaining the preset update time of the parking stand allocation plan.

[0162] The airport parking stand automatic allocation system 200 can implement the steps in the airport parking stand automatic allocation method in the above embodiment, and can achieve the same technical effects. Please refer to the description in the above embodiment and will not be repeated here.

[0163] The present invention also provides a computer device, please refer to Figure 3 , Figure 3 300 is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. The computer device 300 includes: a memory 302, a processor 301, and a computer program stored in the memory 302 and executable on the processor 301.

[0164] The processor 301 calls the computer program stored in the memory 302 to execute the steps of the automatic allocation method for airport parking spaces provided in the embodiment of the present invention. Figure 1 , specifically including the following steps:

[0165] S1: Obtain flight dynamic information, parking space information and airlines’ parking space preference information of the target airport.

[0166] The flight dynamic information includes: historical flight information, flight information for the next day and flight splicing information, wherein the flight information for the next day includes flight number, flight attributes, flight model, flight airline, flight mission, arrival time and departure time;

[0167] The parking stand information includes parking stand static information, stand occupancy information, stand maintenance information and parking stand area information, wherein the parking stand static information includes the parking stand number, the parking stand aircraft type level, the parking stand attribute, the set of airlines that can park flights at the parking stand, the task set of flights that can be parked at the parking stand and the parking stand type;

[0168] The airline's seat preference information includes the type of airline, the type of flight, and the airline's seat preference for a specific flight type.

[0169] S2: Process and integrate the flight dynamic information, the parking position information and the airline's parking position preference information to obtain a set of flights to be allocated parking positions, a set of flights with occupied parking positions and a parking position priority table.

[0170] Step S2 includes the following sub-steps:

[0171] Splicing the flight information for the next day according to the flight splicing information to obtain a spliced ​​flight pair, so as to obtain the set of flights to be allocated stands, wherein the spliced ​​flight pair consists of an inbound flight and a outbound flight;

[0172] Filter out the flights occupying the aircraft stands from the historical flight information according to the arrival time and the departure time, and associate them with the aircraft stand occupancy information and the aircraft stand maintenance information to obtain the set of flights occupying the aircraft stands;

[0173] The slots are divided into a plurality of priorities according to the airlines' preference for the slots under the specific flight type to obtain the slot priority table, wherein different weight coefficients are set corresponding to different priorities.

[0174] S3: Constructing a flight-airport weight coefficient matrix according to the aircraft slot priority table.

[0175] The flight-airport weight coefficient matrix is ​​constructed according to the aircraft slot priority table and the weight coefficients corresponding to the different priorities.

[0176] S4: Determine the objective function for parking stand allocation according to the flight-stand weight coefficient matrix, the set of flights with stands to be allocated, and the set of flights with occupied stands, construct a parking stand allocation model, and solve the parking stand allocation model to obtain a parking stand allocation plan.

[0177] The parking space allocation model is specifically as follows:

[0178] min∑ i∈I ∑ k∈K x ik *c ik (1);

[0179]

[0180]

[0181]

[0182]

[0183]

[0184]

[0185]

[0186]

[0187]

[0188] Among them, I and i are flight set and flight i, i∈I respectively;

[0189] K and k are respectively the parking stand set and parking stand k, k∈K;

[0190] x ik Indicates whether flight i is assigned to slot k;

[0191] airline ik Indicates whether the airline of flight i is included in the set of airlines that can stop at gate k;

[0192] attr ik Indicates whether the attributes of flight i are included in the parking attribute set of stand k;

[0193] type ik Indicates whether the aircraft type of flight i is included in the set of aircraft types that can be parked at parking space k;

[0194] task ik Indicates whether the tasks of flight i include the set of tasks that can be stopped at stand k;

[0195] M represents a very large number;

[0196] J i , j represent the set of flights that conflict with flight i and flight j, respectively, j∈J i ;

[0197] x jk Indicates whether flight j that conflicts with flight i is assigned to slot k;

[0198] Q and U are respectively a set of combined positions and a group of combined positions U, U∈Q;

[0199] c is the key position c in a group of combined positions, c∈U;

[0200] I U Represents a set of combined stands U that can accommodate a set of flights;

[0201] x iU Indicates whether flight i is assigned to a set of combined seats U;

[0202] x bc Indicates whether flight i is assigned to a key stand c in a group of combined stands;

[0203] C U , G is the maximum group set of flights with combined seats and the maximum group G, G∈C U ;

[0204] c ik represents the weight coefficient of slot k for flight i;

[0205] Among them, constraints (8), constraints (9), and constraints (10) are modeled using the maximum clique method.

[0206] The process of solving the parking space allocation model is solved using the gurobi solver.

[0207] S5: constructing a rolling allocation model, and solving a rolling allocation parking stand allocation plan based on the parking stand allocation model after obtaining a preset update time of the parking stand allocation plan.

[0208] The rolling allocation model is specifically:

[0209]

[0210] φ 1 =max|∑ i∈I ∑ k∈K x ik *c ik | (12);

[0211]

[0212] Among them, k 1 and k 2 Represents the weight coefficient, I r represents the set of flights currently allocated, r i Indicates whether flight i has a slot change compared with the previous allocation result, if yes, it is 1, otherwise it is 0;

[0213] The rolling allocation model has the following constraints:

[0214]

[0215]

[0216]

[0217]

[0218]

[0219]

[0220]

[0221]

[0222]

[0223]

[0224] Among them, d lk is the distance between position l and position k, y iIndicates whether the boarding gate information of flight i has been released, 1 if yes, 0 otherwise; D indicates the maximum allowable parking position change distance.

[0225] The computer device 300 provided in the embodiment of the present invention can implement the steps in the method for automatic allocation of airport parking spaces in the above embodiment, and can achieve the same technical effects. Please refer to the description in the above embodiment, which will not be repeated here.

[0226] An embodiment of the present invention further provides a storage medium having a computer program stored thereon. When the computer program is executed by a processor, the various processes and steps in the method for automatic allocation of airport parking spaces provided in an embodiment of the present invention are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0227] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).

[0228] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0229] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0230] The embodiments of the present invention are described above in conjunction with the accompanying drawings. What is disclosed is only the preferred embodiment of the present invention. However, the present invention is not limited to the above-mentioned specific implementation manner. The above-mentioned specific implementation manner is only illustrative rather than restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms and equivalent changes without departing from the scope of protection of the purpose of the present invention and the claims, all of which are within the protection of the present invention.

Claims

1. A method for automatically allocating parking spaces at an airport, characterized in that: The following steps are involved: S1: Obtain flight dynamic information, parking space information and airlines' parking space preference information of the target airport; wherein the flight dynamic information includes: historical flight information, flight information for the next day and flight splicing information, wherein the flight information for the next day includes flight number, flight attributes, flight model, flight airline, flight mission, arrival time and departure time; The parking stand information includes parking stand static information, stand occupancy information, stand maintenance information and parking stand area information, wherein the parking stand static information includes the parking stand number, the parking stand aircraft type level, the parking stand attribute, the set of airlines that can park flights at the parking stand, the task set of flights that can be parked at the parking stand and the parking stand type; The airline's seat preference information includes the type of airline, the type of flight, and the airline's seat preference for a specific flight type; S2: Processing and integrating the flight dynamic information, the parking space information and the airline's parking space preference information to obtain a set of flights to be allocated parking spaces, a set of flights that have occupied parking spaces and a parking space priority table; S3: constructing a flight-aircraft slot weight coefficient matrix according to the aircraft slot priority table; S4: Determine the objective function of parking stand allocation according to the flight-stand weight coefficient matrix, the set of flights with stands to be allocated, and the set of flights with occupied stands, and construct a parking stand allocation model, and solve the parking stand allocation model to obtain a parking stand allocation plan; wherein the parking stand allocation model is specifically: （1）； （2）； （3）； （4）； （5）； （6）； （7）； （8）； （9）； （10）； Among them, I and i are flight set and flight i respectively. ; K and k are the parking stand set and parking stand k respectively. ; Indicates whether flight i is assigned to slot k; Indicates whether the airline of flight i is included in the set of airlines that can stop at gate k; Indicates whether the attributes of flight i are included in the parking attribute set of stand k; Indicates whether the aircraft type of flight i is included in the set of aircraft types that can be parked at parking space k; Indicates whether the tasks of flight i include the set of tasks that can be stopped at stand k; M represents a very large number; , j represent the flight set that conflicts with flight i and flight j respectively, ; Indicates whether flight j that conflicts with flight i is assigned to slot k; Q and U are respectively a set of combined camera positions and a group of combined camera positions U. ; c is the key position c in a group of combined positions, ; Represents a set of combined stands U that can accommodate a set of flights; x ij Indicates whether flight i is assigned to slot j; Indicates whether flight i is assigned to a set of combined seats U; Indicates whether flight i is assigned to a key stand c in a group of combined stands; , G represent the maximum flight cluster set and maximum cluster G of combined seats respectively. ; represents the weight coefficient of slot k for flight i; Among them, the maximum clique method is used to model the relationship between formula (8), formula (9) and formula (10); S5: constructing a rolling allocation model, and solving a rolling allocation parking stand allocation scheme based on the parking stand allocation model after obtaining the preset update time of the parking stand allocation scheme; the rolling allocation model is specifically: （11）； （12）； （13）； in, and represents the weight coefficient, represents the set of flights currently being allocated, Indicates whether flight i has a slot change compared with the previous allocation result, if yes, it is 1, otherwise it is 0; The rolling allocation model has the following constraints: （14）； （15）； （16）； （17）； （18）； （19）； （20）； （21）； （22）； （23）； in, For the aircraft With the seat The distance between Indicate flight Whether the boarding gate information has been released, if yes, it is 1, otherwise it is 0; D represents the maximum allowable parking position change distance.

2. The method for automatically allocating airport parking spaces according to claim 1, characterized in that: Step S2 includes the following sub-steps: Splicing the flight information for the next day according to the flight splicing information to obtain a spliced ​​flight pair, so as to obtain the set of flights to be allocated stands, wherein the spliced ​​flight pair consists of an inbound flight and a outbound flight; Filter out the flights occupying the aircraft stands from the historical flight information according to the arrival time and the departure time, and associate them with the aircraft stand occupancy information and the aircraft stand maintenance information to obtain the set of flights occupying the aircraft stands; The slots are divided into a plurality of priorities according to the airlines' preference for the slots under the specific flight type to obtain the slot priority table, wherein different weight coefficients are set corresponding to different priorities.

3. The method for automatically allocating airport parking spaces as claimed in claim 2, characterized in that: Step S3 is specifically as follows: The flight-airport weight coefficient matrix is ​​constructed according to the aircraft slot priority table and the weight coefficients corresponding to the different priorities.

4. The method for automatically allocating airport parking spaces as claimed in claim 1, characterized in that: The process of solving the parking space allocation model is solved using the gurobi solver.

5. An automatic allocation system for airport parking spaces, characterized in that: include: A data acquisition module is used to acquire flight dynamic information, parking space information and airlines' parking space preference information of the target airport; wherein the flight dynamic information includes: historical flight information, flight information for the next day and flight splicing information, wherein the flight information for the next day includes flight number, flight attributes, flight model, flight airline, flight mission, arrival time and departure time; The parking stand information includes parking stand static information, stand occupancy information, stand maintenance information and parking stand area information, wherein the parking stand static information includes the parking stand number, the parking stand aircraft type level, the parking stand attribute, the set of airlines that can park flights at the parking stand, the task set of flights that can be parked at the parking stand and the parking stand type; The airline's seat preference information includes the type of airline, the type of flight, and the airline's seat preference for a specific flight type; The first processing module is used to process and integrate the flight dynamic information, the parking position information and the airline's parking position preference information to obtain a set of flights to be allocated parking positions, a set of flights that have occupied parking positions and a parking position priority table; A second processing module is used to construct a flight-aircraft position weight coefficient matrix according to the aircraft position priority table; The parking stand allocation module is used to determine the objective function of parking stand allocation according to the flight-stand weight coefficient matrix and the set of flights with stands to be allocated and the set of flights with occupied stands, and to construct a parking stand allocation model, and to solve the parking stand allocation model to obtain a parking stand allocation plan; wherein the parking stand allocation model is specifically: （1）； （2）； （3）； （4）； （5）； （6）； （7）； （8）； （9）； （10）； Among them, I and i are flight set and flight i respectively. ; K and k are the parking stand set and parking stand k respectively. ; Indicates whether flight i is assigned to slot k; Indicates whether the airline of flight i is included in the set of airlines that can stop at gate k; Indicates whether the attributes of flight i are included in the parking attribute set of stand k; Indicates whether the aircraft type of flight i is included in the set of aircraft types that can be parked at parking space k; Indicates whether the tasks of flight i include the set of tasks that can be stopped at stand k; M represents a very large number; , j represent the flight set that conflicts with flight i and flight j respectively, ; Indicates whether flight j that conflicts with flight i is assigned to slot k; Q and U are respectively a set of combined camera positions and a group of combined camera positions U. ; c is the key position c in a group of combined positions, ; Represents a set of combined stands U that can accommodate a set of flights; x ij Indicates whether flight i is assigned to slot j; Indicates whether flight i is assigned to a set of combined seats U; Indicates whether flight i is assigned to a key stand c in a group of combined stands; , G represent the maximum flight cluster set and maximum cluster G of combined seats respectively. ; represents the weight coefficient of slot k for flight i; Among them, the maximum clique method is used to model the relationship between formula (8), formula (9) and formula (10); The rolling allocation module is used to construct a rolling allocation model, and after obtaining the preset update time of the parking space allocation plan, solve the parking space allocation plan of rolling allocation based on the parking space allocation model; the rolling allocation model is specifically: （11）； （12）； （13）； in, and represents the weight coefficient, represents the set of flights currently being allocated, Indicates whether flight i has a slot change compared with the previous allocation result, if yes, it is 1, otherwise it is 0; The rolling allocation model has the following constraints: （14）； （15）； （16）； （17）； （18）； （19）； （20）； （21）； （22）； （23）； in, For the aircraft With the seat The distance between Indicate flight Whether the boarding gate information has been released, if yes, it is 1, otherwise it is 0; D represents the maximum allowable parking position change distance.

6. A computer device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps in the method for automatic allocation of airport parking spaces as described in any one of claims 1 to 4 are implemented.

7. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, the steps in the method for automatic allocation of airport parking spaces as described in any one of claims 1 to 4 are implemented.

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