Method, device, equipment and readable storage medium for allocating parking spaces for cargo flights

Abstract

The present application provides a method, apparatus, device and readable storage medium for allocating parking spaces for cargo flights; the method for allocating parking spaces for cargo flights in the present application includes: receiving an allocation instruction for parking spaces for cargo flights, determining that the allocation instruction corresponds to a target cargo flight to be allocated; querying basic allocation information, obtaining flight information and cargo information of the target cargo flight and analyzing them to obtain a parking space allocation index for the target cargo flight; analyzing the basic allocation information through an allocation sub-model corresponding to the parking space allocation index in a preset allocation model to obtain parking space information for the target cargo flight; in the present application, the basic allocation information is analyzed through a preset allocation model to obtain parking space information corresponding to the target cargo flight, so that the allocation of parking spaces is more reasonable.

Description

Technical Field

[0001] The present application relates to the field of logistics technology, and in particular to a method, apparatus, device and readable storage medium for allocating parking spaces for cargo flights. Background Art

[0002] At present, the parking stand algorithm for passenger flights is relatively mature. When allocating parking stands for passenger flights, the distance from the passenger's arrival at the station to boarding, the utilization rate of close-to-parking stands, etc. are usually taken into consideration to achieve accurate allocation of parking stands for passenger flights.

[0003] The difference between a cargo aviation hub and a passenger aviation hub is that passenger flights carry cargo in the cargo version of people. The allocation of parking spaces for cargo flights does not need to consider how long it takes for people to walk before they can board the plane. More consideration is given to factors related to the cargo, such as the distance the cargo is towed, the flow time of cargo sorting on the site, etc., to ensure that cargo flights take off on time. The current development of cargo aviation is still relatively lagging, and there are not many aircraft of cargo airlines. The allocation of parking spaces for cargo flights basically relies on manual allocation. However, with the rapid development of cargo aviation and the establishment of cargo hubs, the number of cargo flights has increased, and the difficulty of allocating parking spaces for cargo flights has greatly increased. Manual allocation of cargo parking spaces is inefficient and the allocation of parking spaces is unreasonable. Summary of the Invention

[0004] The present application provides a method, apparatus, device and readable storage medium for allocating parking spaces for cargo flights, aiming to solve the technical problems of the existing cargo flight parking space allocation being difficult, inefficient and irrational.

[0005] In one aspect, the present application provides a method for allocating parking spaces for cargo flights, the method comprising the following steps:

[0006] receiving an allocation instruction for a cargo flight parking space, and determining that the allocation instruction corresponds to a target cargo flight to be allocated;

[0007] Query basic allocation information, obtain flight information and freight information of the target cargo flight, analyze them, and obtain a parking space allocation indicator for the target cargo flight;

[0008] The basic allocation information is analyzed by using an allocation sub-model corresponding to the parking space allocation index in a preset allocation model to obtain the parking space information of the target cargo flight.

[0009] In some embodiments of the present application, before analyzing the basic allocation information using the allocation sub-model corresponding to the parking slot allocation index in the preset allocation model to obtain the parking slot information of the target cargo flight, the method includes:

[0010] Obtaining historical parking stand allocation information for cargo flights as model training samples, and classifying the model training samples according to predefined parking stand allocation indicators to form model training sample subsets corresponding to different parking stand allocation indicators;

[0011] Each model training sample subset is used as the target model training sample subset;

[0012] Extracting a preset proportion of model training samples from the target model training sample subset at one time, and constructing an initial allocation model through the model training samples;

[0013] Iteratively extracting a preset proportion of model training samples from the target model training sample subset, training the initial allocation model with the model training samples to obtain a training sub-model;

[0014] Obtaining the allocation accuracy of the training sub-model, and using the training sub-model with the allocation accuracy higher than the preset allocation accuracy as the allocation sub-model;

[0015] The allocation sub-model obtained through training is acquired, and the allocation sub-model is encapsulated to form a preset allocation model.

[0016] In some embodiments of the present application, the parking space allocation indicator is a flight transit time indicator;

[0017] Analyzing the basic allocation information using an allocation sub-model corresponding to the parking space allocation index in a preset allocation model to obtain the parking space information of the target cargo flight includes:

[0018] Analyzing the basic allocation information using a first allocation sub-model corresponding to the flight transit time indicator in a preset allocation model to obtain parking space information for the target cargo flight;

[0019] Wherein, the first allocation sub-model is:

[0020]

[0021] G represents the set of all cargoes, K represents the set of all aircraft spaces, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and the UT k Indicates the unloading and hauling time of the k-th position, the ST g Indicates the sorting time of cargo g, the x jk Refers to the aircraft j in port at gate k, the LT gk Indicates the loading and hauling time of cargo g to aircraft k, the OTT g Indicates the transit time of cargo g, the W g Indicates the weight of the cargo g, the P gIndicates the inbound and outbound aircraft pair (i, j) corresponding to cargo g.

[0022] In some embodiments of the present application, the parking space allocation index is a non-direct freight crate transfer index;

[0023] Analyzing the basic allocation information using an allocation sub-model corresponding to the parking space allocation index in a preset allocation model to obtain the parking space information of the target cargo flight includes:

[0024] Analyzing the basic allocation information by using a second allocation sub-model corresponding to the non-direct freight pallet transfer indicator in the preset allocation model to obtain the parking space information of the target freight flight;

[0025] The second allocation sub-model is:

[0026]

[0027] I represents the set of all aircraft, K represents the set of all parking spaces, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and the W i is the weight of cargo loaded on aircraft i of the target cargo flight, and N i is the set of loading ports of the transshipment center corresponding to the cargo planned to be loaded on the target cargo flight aircraft i, and the W in represents the weight of cargo transported from the unloading port of the transfer center n to the target cargo flight aircraft i, It represents the distance L from the k-th parking space to the unloading and hauling.

[0028] In some embodiments of the present application, the parking space allocation index is a direct freight crate transfer index;

[0029] Analyzing the basic allocation information using an allocation sub-model corresponding to the parking space allocation index in a preset allocation model to obtain the parking space information of the target cargo flight includes:

[0030] Analyzing the basic allocation information using a third allocation sub-model corresponding to the direct-transfer freight pallet transfer indicator in the preset allocation model to obtain the parking space information of the target freight flight;

[0031] Wherein, the third allocation sub-model is:

[0032]

[0033] The G D is a set of straight-forward boxes, K represents a set of all camera positions, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and the x jkRefers to the aircraft j in port at parking position k, the D kk' is the straight rotation distance from position k to k′, and W g Indicates the weight of the cargo in g.

[0034] In some embodiments of the present application, the parking stand allocation indicator is a flight taxiing distance indicator;

[0035] Analyzing the basic allocation information using an allocation sub-model corresponding to the parking space allocation index in a preset allocation model to obtain the parking space information of the target cargo flight includes:

[0036] The basic allocation information is analyzed by the fourth allocation sub-model corresponding to the flight taxiing distance index in the preset allocation model to obtain the parking space information of the target cargo flight.

[0037] The fourth camera position allocation sub-model is:

[0038]

[0039] I represents the set of all aircraft, K represents the set of all parking spaces, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and A ik It refers to the distance from the target cargo flight aircraft i to the landing position k, D ik It refers to the distance that the target cargo flight aircraft i taxis from parking position k to takeoff.

[0040] In some embodiments of the present application, querying basic allocation information, obtaining flight information and freight information of the target cargo flight and analyzing them to obtain a parking space allocation index for the target cargo flight includes:

[0041] querying the flight schedule and the flight cargo details in the basic allocation information, extracting the flight information of the target cargo flight from the flight schedule, and extracting the cargo information of the target cargo flight from the flight cargo details;

[0042] The constraint conditions are configured according to the flight information, the objective function is configured according to the freight information, and linear programming is performed according to the constraint conditions and the objective function to obtain parking space allocation indicators.

[0043] In another aspect, the present application provides a device for allocating parking spaces for cargo flights, the device comprising:

[0044] a receiving and determining module, configured to receive an allocation instruction for a cargo flight parking space and determine that the allocation instruction corresponds to a target cargo flight to be allocated;

[0045] An information analysis module is used to query basic allocation information, obtain flight information and freight information of the target cargo flight, and analyze them to obtain a parking space allocation index for the target cargo flight;

[0046] The parking space allocation module is used to analyze the basic allocation information through the allocation sub-model corresponding to the parking space allocation index in the preset allocation model to obtain the parking space information of the target cargo flight.

[0047] On the other hand, the present application further provides a cargo flight parking stand allocation device, the cargo flight parking stand allocation device comprising:

[0048] one or more processors;

[0049] Memory; and

[0050] One or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the processor to implement the method for allocating cargo flight parking spaces.

[0051] On the other hand, the present application also provides a readable storage medium having a computer program stored thereon, and the computer program is loaded by a processor to execute the steps in the method for allocating parking spaces for cargo flights.

[0052] The technical solution of the present application receives a parking space allocation instruction for a cargo flight, determines that the allocation instruction corresponds to a target cargo flight to be allocated, queries basic allocation information, obtains and analyzes flight information and cargo information of the target cargo flight, and obtains a parking space allocation index for the target cargo flight; analyzes the basic allocation information using an allocation sub-model corresponding to the parking space allocation index in a preset allocation model to obtain the parking space information of the target cargo flight; and allocates parking spaces for cargo flights using an allocation model in the technical solution of an embodiment of the present application, making parking space allocation for cargo flights more convenient and efficient. Furthermore, the flight information and cargo information of the target cargo flight are analyzed to obtain the parking space allocation index for the target cargo flight. The basic allocation information is analyzed using an allocation sub-model corresponding to the parking space allocation index in the preset allocation model to obtain the parking space information of the target cargo flight. This allocation sub-model is relatively concise and can also ensure the accuracy of parking space allocation, so that parking space allocation for cargo flights takes into account the flight information and cargo information of different cargo flights, making parking space allocation more reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0054] Figure 1 This is a schematic diagram of a scenario for allocating parking spaces for cargo flights provided in an embodiment of the present application;

[0055] Figure 2 This is a flow chart of an embodiment of a method for allocating parking spaces for cargo flights provided in an embodiment of the present application;

[0056] Figure 3 This is a flow chart of an embodiment of constructing a preset allocation model in the method for allocating parking spaces for cargo flights in an embodiment of the present application;

[0057] Figure 4 This is a flow chart of an embodiment of a method for allocating parking spaces for cargo flights provided in an embodiment of the present application;

[0058] Figure 5 This is a schematic structural diagram of an embodiment of a device for allocating parking spaces for cargo flights provided in an embodiment of the present application;

[0059] Figure 6 It is a schematic structural diagram of an embodiment of the cargo flight parking space allocation equipment provided in the embodiments of the present application. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of the present invention.

[0061] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the said features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0062] In this application, the word "exemplary" is used to mean "serving as an example, illustration, or illustration." Any embodiment described in this application as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is given to enable any person skilled in the art to make and use the invention. In the following description, details are listed for the purpose of explanation. It should be understood that one of ordinary skill in the art will recognize that the invention can be practiced without these specific details. In other instances, well-known structures and processes are not described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.

[0063] The embodiments of the present application provide a method, apparatus, device, and readable storage medium for allocating parking spaces for cargo flights, which are described in detail below.

[0064] The method for allocating cargo flight parking stands in an embodiment of the present invention is applied to an allocation device for cargo flight parking stands. The allocation device for cargo flight parking stands is arranged in an allocation device for cargo flight parking stands. The allocation device for cargo flight parking stands is provided with one or more processors, memories, and one or more applications, wherein the one or more applications are stored in the memories and configured to be executed by the processors to implement the method for allocating cargo flight parking stands. The allocation device for cargo flight parking stands can be a terminal, such as a mobile phone or a tablet computer. The allocation device for cargo flight parking stands can also be a server, or a service cluster consisting of multiple servers.

[0065] like Figure 1 As shown, Figure 1This is a schematic diagram of a scenario for allocating cargo flight parking stands in an embodiment of the present application. The scenario for allocating cargo flight parking stands in an embodiment of the present invention includes a cargo flight parking stand allocating device 100 (the cargo flight parking stand allocating device 100 is integrated with a cargo flight parking stand allocating device). The cargo flight parking stand allocating device 100 runs a readable storage medium corresponding to the allocation of cargo flight parking stands to execute the steps of allocating cargo flight parking stands.

[0066] It is understandable that Figure 1 The cargo flight parking stand allocation equipment in the cargo flight parking stand allocation scenario shown, or the devices included in the cargo flight parking stand allocation equipment, do not constitute a limitation on the embodiments of the present invention. That is, the number of devices and types of devices included in the cargo flight parking stand allocation scenario, or the number of devices and types of devices included in each device do not affect the overall implementation of the technical solution in the embodiments of the present invention, and can all be regarded as equivalent replacements or derivatives of the technical solution claimed for protection in the embodiments of the present invention.

[0067] The cargo flight parking stand allocation device 100 in the embodiment of the present invention is mainly used to receive cargo flight parking stand allocation instructions, determine that the allocation instructions correspond to the target cargo flight to be allocated; query basic allocation information, obtain the flight information and cargo information of the target cargo flight and analyze them to obtain the parking stand allocation index of the target cargo flight; analyze the basic allocation information through the allocation sub-model corresponding to the parking stand allocation index in the preset allocation model to obtain the parking stand information of the target cargo flight.

[0068] In the embodiment of the present invention, the cargo flight parking stand allocation device 100 may be an independent cargo flight parking stand allocation device, or may be a cargo flight parking stand allocation device network or cargo flight parking stand allocation device cluster composed of cargo flight parking stand allocation devices. For example, the cargo flight parking stand allocation device 100 described in the embodiment of the present invention includes but is not limited to a computer, a network host, a single network cargo flight parking stand allocation device, a set of multiple network cargo flight parking stand allocation devices, or a cloud cargo flight parking stand allocation device composed of multiple cargo flight parking stand allocation devices. The cloud cargo flight parking stand allocation device is composed of a large number of computers or network cargo flight parking stand allocation devices based on cloud computing.

[0069] Those skilled in the art will understand that Figure 1 The application environment shown in the figure is only one application scenario of the present application solution and does not constitute a limitation on the application scenario of the present application solution. Other application environments may also include Figure 1More or fewer cargo flight parking stand allocation devices as shown in , or the cargo flight parking stand allocation device network connection relationship, such as Figure 1 Only one cargo flight parking stand allocation device is shown. It can be understood that the cargo flight parking stand allocation scenario can also include one or more other cargo flight parking stand allocation devices, which are not limited here. The cargo flight parking stand allocation device 100 can also include a memory for storing historical cargo flight allocation data.

[0070] In addition, in the scenario of allocating cargo flight parking stands in the present application, the cargo flight parking stand allocation device 100 can be provided with a display device, or the cargo flight parking stand allocation device 100 can be provided with no display device and can be communicatively connected to an external display device 200, wherein the display device 200 is used to output the results of the execution of the cargo flight parking stand allocation method in the cargo flight parking stand allocation device. The cargo flight parking stand allocation device 100 can access a backend database 300 (the backend database can be in the local memory of the cargo flight parking stand allocation device, or can also be set up in the cloud). The backend database 300 stores information related to the allocation of cargo flight parking stands, for example, the backend database 300 stores basic allocation information related to cargo flight allocation.

[0071] It should be noted that Figure 1 The schematic diagram of the allocation scenario of cargo flight parking spaces shown is merely an example. The scenario of the allocation scenario of cargo flight parking spaces described in the embodiment of the present invention is intended to more clearly illustrate the technical solution of the embodiment of the present invention and does not constitute a limitation on the technical solution provided by the embodiment of the present invention.

[0072] Based on the above scenario of allocating parking spaces for cargo flights, an embodiment of a method for allocating parking spaces for cargo flights is proposed.

[0073] like Figure 2 As shown, Figure 2 201 is a flow chart of an embodiment of a method for allocating parking spaces for cargo flights according to an embodiment of the present application. The method for allocating parking spaces for cargo flights includes steps 201-203:

[0074] 201 : Receive an allocation instruction for a cargo flight parking space, and determine whether the allocation instruction corresponds to a target cargo flight to be allocated.

[0075] The method for allocating parking spaces for cargo flights in this embodiment is applied to equipment for allocating parking spaces for cargo flights. The type of equipment for allocating parking spaces for cargo flights is not specifically limited. For example, the equipment for allocating parking spaces for cargo flights may be a terminal or a server. This embodiment uses a terminal as an example for illustration.

[0076] The terminal receives an allocation instruction for a parking space for a cargo flight, where the allocation instruction may be actively triggered by the user, for example, the user clicks a "parking space allocation" button on the terminal display interface to actively trigger the parking space allocation instruction; in addition, the allocation instruction may also be automatically triggered by the terminal, for example, the triggering condition for the allocation instruction is pre-set in the terminal as: cargo flight update; the terminal monitors the status information of the cargo flight in real time, and when the terminal detects updated information that the cargo flight will enter the airport one hour later, the terminal automatically triggers the allocation instruction for the cargo flight.

[0077] The terminal receives an allocation instruction for a cargo flight parking space, and obtains a target cargo flight identifier associated with the allocation instruction, wherein the target cargo flight identifier refers to identification information of the target cargo flight to be allocated, such as the flight name, flight number, etc. The terminal determines that the allocation instruction corresponds to the target cargo flight to be allocated based on the target cargo flight identifier.

[0078] 202 , query basic allocation information, obtain flight information and cargo information of the target cargo flight, analyze them, and obtain a parking space allocation index for the target cargo flight.

[0079] The terminal accesses the local database or cloud database to query the basic allocation information in the local database or cloud database, where the basic allocation information refers to the dependent information when allocating parking spaces. The basic allocation information includes the flight schedule, the flight cargo details table, the parking space type information table, the parking space to taxiway distance information table, the parking space corresponding to the transfer center loading and unloading port information table, the parking space to the transfer center loading and unloading and towing distance table, the close parking space matching, the compound parking space matching information table, the conflicting adjacent parking space matching table, etc.

[0080] The terminal obtains the flight information and freight information of the target cargo flight from the basic allocation information, wherein the flight information includes the flight's landing time, take-off time, take-off location, destination point, and aircraft model information, etc., and the freight information includes: freight volume, cargo transportation address information, cargo type, cargo name, etc. The terminal analyzes the flight information and freight information of the target cargo flight, determines the main focus data of the target cargo flight's parking space allocation, and uses the main focus data of the target flight's parking space allocation as the parking space allocation indicator for the target cargo flight.

[0081] In this embodiment, the parking stand allocation index refers to the main data of interest in the allocation of parking stands for cargo flights, such as the flight turnaround time index (the flight turnaround time index refers to the index of the stopover time of a cargo flight at the airport), the non-direct cargo crate transshipment index (a non-direct cargo crate refers to a crate loaded with cargo to different destinations. When the non-direct cargo crates on a cargo flight arrive at the airport, the airport logistics management staff needs to re-unload and re-load the cargo in the non-direct cargo crate. The non-direct cargo crate transshipment index refers to the index of the loading and unloading time during the transshipment of cargo in the non-direct cargo crate), the direct cargo crate transshipment index (a direct cargo crate refers to a crate loaded with cargo to the same destination. When the direct cargo crates on a cargo flight arrive at the airport, the airport logistics management staff needs to transport the direct cargo crates as a whole. The direct cargo crate transshipment index refers to the index of the transportation distance of the direct cargo crate), the flight taxi distance index (the flight taxi distance index refers to the index of the taxiing distance of a cargo flight from landing to the parking stand, and / or the index of the taxiing distance of a cargo flight from the parking stand to takeoff), etc.

[0082] In this embodiment, the terminal analyzes the flight information and cargo information of the target cargo flight to obtain a parking slot allocation index for the target cargo flight. Specifically, the terminal pre-sets parking slot allocation constraints, determines an initial set of selectable parking slots based on the flight information and constraints, analyzes the initial set of parking slots and cargo information to determine the parking slot allocation index for the target cargo flight, and selects an allocation sub-model based on the parking slot allocation index to select a unique parking slot from the initial set of parking slots.

[0083] For example, an airport has a total of 36 parking spaces. The constraint is that an aircraft can only be assigned to one space. The aircraft's flight information indicates a one-hour layover from 10:00 AM to 11:00 AM. The terminal combines the flight information and the constraint to determine that there are 12 available parking spaces between 10:00 AM and 11:00 AM. The terminal uses these 12 spaces as the initial parking space set. The terminal then analyzes the cargo information and the initial parking space set to determine the parking space allocation index for the target cargo flight. This allows the terminal to select an allocation sub-model based on the parking space allocation index to select a unique parking space from the 12 parking spaces.

[0084] It is understood that the constraints for parking space allocation pre-set in the terminal include:

[0085] Unique allocation constraint: An aircraft can only be assigned to one slot, that is,

[0086]

[0087] Among them, K represents the set of all camera positions, x ikIt means that the target cargo flight aircraft i is assigned to the parking space k, and I represents the set of all aircraft;

[0088] Composite camera constraint: If the composite camera is used for one of them, the other one cannot be used, that is,

[0089]

[0090] Among them, x ik It means that the target cargo flight aircraft i is assigned to the parking space k, x jk refers to the aircraft j in port at parking position k, P S represents the set of aircraft pairs whose arrival and departure times do not meet the safety interval, that is, P S ={(i,j)∈P:max(A i -D j ,A j -D i ) S}, A i is the arrival time of aircraft i, Dj is the departure time of aircraft j, Aj is the arrival time of aircraft j, D i is the departure time of aircraft i, I S Refers to the pre-set safety time interval.

[0091] Aircraft type matching constraint: The aircraft slot cannot be assigned an incompatible aircraft type, i.e.

[0092]

[0093] Among them, x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and θ represents the aircraft-parking space pair with mismatched aircraft type and parking space, that is, i refers to the target cargo flight aircraft, k refers to the target cargo flight aircraft i assigned to the parking space k, I represents the set of all aircraft, and K represents the set of all parking spaces.

[0094] The parking space lock constraint means that the aircraft cannot be assigned during the period when the parking space is unavailable, i.e.

[0095]

[0096] Among them, x ik It means that the target cargo flight aircraft i is assigned to the parking space k, i refers to the target cargo flight aircraft, k refers to the target cargo flight aircraft i is assigned to the parking space k, and U represents the aircraft-parking space pair with time conflict, that is, U = {(i, k)∈I×K:min(max(A i -E i , B i -D i ):(B i , E​i )∈U k )<0}

[0097] A i is the arrival time of aircraft i, D i is the departure time of aircraft i, E i Refers to whether aircraft i is on the east runway, if yes, it is 1, otherwise it is 0, B i is the set of crates on plane i, U k It refers to the set of unavailable periods of slot k.

[0098] Safety interval constraint: Two aircraft whose arrival and departure times do not meet the safety interval cannot be assigned to the same parking space, that is,

[0099]

[0100] Among them, x ik It means that the target cargo flight aircraft i is assigned to the parking space k, x jk refers to the aircraft j in port at parking position k, P S represents the set of aircraft pairs whose arrival and departure times do not meet the safety interval, that is, P S ={(i,j)∈P:max(A i -D j ,A j -D i ) s}, A i is the arrival time of aircraft i, Dj is the departure time of aircraft j, Aj is the arrival time of aircraft j, D i is the departure time of aircraft i, I S Refers to the pre-set safety time interval.

[0101] Pushback interval constraint: Two aircraft whose departure times do not meet the pushback interval cannot be assigned to adjacent parking spaces, i.e.,

[0102]

[0103] Among them, x ik It means that the target cargo flight aircraft i is assigned to the parking space k, x jk refers to the aircraft j in port at parking position k, P D represents the set of aircraft pairs whose departure times do not satisfy the pushback interval, that is, P D ={(i,j)∈P:|D i -D j | D}, Dj is the departure time of aircraft j, D i is the departure time of aircraft i, I D Indicates the rollout interval.​​

[0104] In this embodiment, the terminal analyzes the flight information and cargo information of the target cargo flight to obtain the parking slot allocation index for the target cargo flight. Thus, when the terminal allocates parking slots for the cargo flight, it selects an allocation sub-model to perform information analysis based on the parking slot allocation index, thereby achieving reasonable parking allocation. Specifically:

[0105] 203 : Analyze the basic allocation information using an allocation sub-model corresponding to the parking space allocation index in a preset allocation model to obtain parking space information of the target cargo flight.

[0106] In this embodiment, a preset allocation model is preset in the terminal. The preset allocation model refers to an algorithm obtained through deep learning of a neural network. That is, the terminal trains the initial allocation model through model training samples to obtain a preset allocation model, for example, an SVM classifier. The terminal inputs basic allocation information into the preset allocation model, analyzes the basic allocation information through an allocation sub-model corresponding to the parking space allocation index in the preset allocation model, selects feature information corresponding to the target cargo flight in the basic allocation information through the allocation sub-model for analysis, and obtains the parking space information of the target cargo flight.

[0107] It is understandable that the parking stand allocation index in this embodiment can be one or more. When the parking stand index is one, an allocation sub-model is selected to analyze the basic allocation information to obtain unique parking stand information for the target cargo flight. When the parking stand index is multiple, if the obtained parking stand information for the target cargo flight is not unique, the terminal sets weights for each parking stand allocation index. The terminal combines the allocation sub-models corresponding to the parking stand allocation index according to the weights to form a parking stand allocation model. The basic allocation information is analyzed using the parking stand allocation model to ultimately determine the unique parking stand information for the target cargo flight. In this embodiment, an allocation sub-model is selected based on the parking stand allocation index and the basic information is analyzed using the allocation sub-model to obtain the parking stand. This can not only meet the special needs of a single cargo flight, but also take into account the parking stand allocation of other cargo flights, so that the terminal allocates the most reasonable parking stand to the cargo flight.

[0108] In the technical solution of the embodiment of the present application, parking stands for cargo flights are allocated through an allocation model, making the allocation of parking stands for cargo flights more convenient and efficient. Furthermore, by analyzing the flight information and cargo information of the target cargo flight, the parking stand allocation index of the target cargo flight is obtained. The basic allocation information is analyzed through the allocation sub-model corresponding to the parking stand allocation index in the preset allocation model to obtain the parking stand information of the target cargo flight. This makes the parking stand allocation of cargo flights take into account the flight information and cargo information of different cargo flights, making the parking stand allocation more reasonable.

[0109] like Figure 3As shown, Figure 3 This is a flow chart of an embodiment of constructing a preset allocation model in the method for allocating parking spaces for cargo flights in the embodiment of the present application.

[0110] In some embodiments of the present application, the steps for constructing a preset allocation model are specifically described, including steps 301-306:

[0111] 301 , obtaining historical parking stand allocation information of cargo flights as model training samples, classifying the model training samples according to predefined parking stand allocation indices, and forming model training sample subsets corresponding to different parking stand allocation indices.

[0112] The terminal obtains historical parking stand allocation information for cargo flights as model training samples. The terminal classifies the model training samples according to predefined parking stand allocation indicators (the parking stand allocation indicators are the same as those in the previous embodiment and are not described in detail in this embodiment). This creates model training sample subsets corresponding to different parking stand allocation indicators, and the model training is performed using the model training samples in the model training sample subsets. For example, if historical parking stand allocation information is allocated based on the shortest taxi distance for cargo flights, this historical parking stand allocation information is classified into the model training sample subset corresponding to the predefined flight taxi distance indicator.

[0113] 302 , each model training sample subset is used as a target model training sample subset.

[0114] 303 , extracting a preset proportion of model training samples from the target model training sample subset at one time, and constructing an initial allocation model through the model training samples.

[0115] The terminal uses each model training sample subset as the target model training sample subset to train its own allocation sub-model through each target model training sample subset, that is,

[0116] The terminal extracts a preset proportion (the preset proportion can be flexibly set according to the specific scenario, for example, the preset proportion is set to 3%) of model training samples from the target model training sample subset at one time. The terminal constructs an initial allocation model by extracting the preset proportion of model training samples at one time, that is, the terminal extracts feature points in the model training samples, and then uses the feature points to construct a classification function. The terminal uses the classification function as the initial allocation model.

[0117] 304 , iteratively extracting a preset proportion of model training samples from the target model training sample subset, and training the initial allocation model using the model training samples to obtain a training sub-model.

[0118] The terminal iteratively extracts a preset proportion (the preset proportion can be flexibly set according to the specific scenario, for example, the preset proportion is set to 3%) of model training samples from the target model training sample subset, and the terminal trains the initial allocation model through the model training samples to obtain a training sub-model. That is, the terminal obtains the feature points of the model training samples, and then adjusts the parameters of the classification function according to the feature points to iteratively train the constructed initial allocation model to obtain a training sub-model.

[0119] 305, obtaining the allocation accuracy of the training sub-model, and using the training sub-model with the allocation accuracy higher than the preset allocation accuracy as the allocation sub-model;

[0120] The terminal obtains the allocation accuracy of the training sub-model, and compares the allocation accuracy of the training sub-model with the preset allocation accuracy (the preset allocation accuracy refers to the preset parking space allocation accuracy threshold. If the allocation accuracy of the preset allocation model obtained through training is higher than the accuracy threshold, the training of the preset allocation model can be stopped; conversely, if the allocation accuracy of the training sub-model obtained through training is not higher than the accuracy threshold, the training sub-model is iteratively trained, where the preset allocation accuracy can be set to 98%). If the allocation accuracy of the training sub-model is not higher than the preset allocation accuracy, the iterative training continues; if the allocation accuracy of the training sub-model is higher than the preset allocation accuracy, the training sub-model is determined to have converged, and the terminal uses the training sub-model with an allocation accuracy higher than the preset allocation accuracy as the allocation sub-model.

[0121] 306 , obtaining the allocation sub-model obtained through training, and encapsulating the allocation sub-model to form a preset allocation model.

[0122] The terminal obtains an allocation sub-model obtained by training a subset of training samples of each standard model, and the terminal encapsulates multiple allocation sub-models to form a preset allocation model. This embodiment specifically describes the steps of constructing the preset allocation model. By constructing different allocation sub-models and then encapsulating the allocation sub-models to form a preset allocation model, the allocation sub-model in the preset allocation model is selected to allocate parking spaces, which can improve the efficiency and rationality of the allocation of cargo flight parking spaces.

[0123] In some embodiments of the present application, the parking stand allocation indicator is a flight transit time indicator. The terminal selects the first allocation sub-model corresponding to the flight transit time indicator to perform parking stand allocation. Specifically:

[0124] Analyzing the basic allocation information using a first allocation sub-model corresponding to the flight transit time indicator in a preset allocation model to obtain parking space information for the target cargo flight;

[0125] Wherein, the first allocation sub-model is:

[0126]

[0127] G represents the set of all cargoes, K represents the set of all aircraft spaces, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and the UT k Indicates the unloading and hauling time of the k-th position, the ST g Indicates the sorting time of cargo g, the x jk Refers to the aircraft j in port at gate k, the LT gk Indicates the loading and hauling time of cargo g to aircraft k, the OTT g Indicates the transit time of cargo g, the W g Indicates the weight of the cargo g, the P g Indicates the inbound and outbound aircraft pair (i, j) corresponding to cargo g.

[0128] That is, the terminal uses the first allocation sub-model corresponding to the flight transit time indicator in the preset allocation model to analyze all cargo sets, all aircraft stand sets, unloading and towing time of cargo flights at each parking stand, sorting time, loading and towing time, transit time, cargo weight, etc. in the basic allocation information to obtain the parking stand information with the most reasonable transit time for the target cargo flight.

[0129] In this embodiment, the parking space allocation index is the flight transit time index. When the terminal allocates a parking space for the target cargo flight, it needs to ensure that the target cargo flight's stay time at the airport is the shortest. The terminal allocates parking spaces according to the first allocation sub-model to ensure the fastest loading and unloading of cargo, allowing the target cargo flight to take off quickly and reducing the target cargo flight's time wasted at the airport.

[0130] In some embodiments of the present application, the parking space allocation index is a non-direct freight crate transfer index; the terminal selects the second allocation sub-model to perform parking space allocation based on the non-direct freight crate transfer index, specifically:

[0131] Analyzing the basic allocation information by using a second allocation sub-model corresponding to the non-direct freight pallet transfer indicator in the preset allocation model to obtain the parking space information of the target freight flight;

[0132] The second allocation sub-model is:

[0133]

[0134] I represents the set of all aircraft, K represents the set of all parking spaces, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and the W i is the weight of cargo loaded on aircraft i of the target cargo flight, and Ni is the set of loading ports of the transshipment center corresponding to the cargo planned to be loaded on the target cargo flight aircraft i, and the W in represents the weight of cargo transported from the unloading port of the transfer center n to the target cargo flight aircraft i, It represents the distance L from the k-th parking space to the unloading and hauling.

[0135] That is, the terminal uses the second allocation sub-model corresponding to the non-direct transfer freight pallet transfer indicator in the preset allocation model to analyze all aircraft sets, all parking space sets, cargo weight, the transfer center loading port set corresponding to the planned loaded cargo, and the distance from the parking space to the unloading, etc. in the basic allocation information to obtain the most reasonable parking space information for cargo loading and unloading of the target cargo flight.

[0136] In this embodiment, the parking space allocation index is a non-direct transfer freight crate transfer index. When allocating parking spaces for target cargo flights, the terminal needs to ensure the parking spaces for the target cargo flights to facilitate cargo loading and unloading at different destinations. The terminal allocates parking spaces according to the second allocation sub-model so that the parking spaces allocated to the target cargo flights can ensure the fastest loading and unloading of cargo, facilitate cargo loading and unloading by ground staff, and reduce the workload during the cargo loading and unloading process.

[0137] In some embodiments of the present application, the parking space allocation index is a direct-to-freight crate transfer index; the terminal selects a third allocation sub-model to perform parking space allocation based on the direct-to-freight crate transfer index, specifically:

[0138] Analyzing the basic allocation information using a third allocation sub-model corresponding to the direct-transfer freight pallet transfer indicator in the preset allocation model to obtain the parking space information of the target freight flight;

[0139] Wherein, the third allocation sub-model is:

[0140]

[0141] The G D is a set of straight-forward boxes, K represents a set of all camera positions, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and the x jk Refers to the aircraft j in port at parking position k, the D kk' is the straight rotation distance from position k to k′, and W g Indicates the weight of the cargo in g.

[0142] That is, the terminal analyzes all direct-transfer crate sets, all aircraft stand sets, cargo weight, direct-transfer distance, etc. in the basic allocation information through the third allocation sub-model corresponding to the direct-transfer freight crate transfer indicator in the preset allocation model, and obtains the most reasonable parking space information for direct-transfer crate transportation in the target cargo flight.

[0143] In this embodiment, the parking space allocation index is the direct-to-cargo crate transfer index. When the terminal allocates parking spaces for the target cargo flight, it needs to ensure that the parking spaces for the target cargo flight are convenient for direct-to-cargo crate transportation. The terminal allocates parking spaces according to the third allocation sub-model so that the transportation distance of each direct-to-cargo crate for the target cargo flight is the shortest, which can ensure the fastest direct-to-cargo crate consignment and reduce the workload of ground staff in direct-to-cargo crate transportation.

[0144] In some embodiments of the present application, the parking stand allocation index is a flight taxiing distance index; the terminal selects the fourth allocation sub-model to perform parking stand allocation based on the flight taxiing distance index, specifically:

[0145] The basic allocation information is analyzed by the fourth allocation sub-model corresponding to the flight taxiing distance index in the preset allocation model to obtain the parking space information of the target cargo flight.

[0146] The fourth camera position allocation sub-model is:

[0147]

[0148] I represents the set of all aircraft, K represents the set of all parking spaces, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and A ik It refers to the distance from the target cargo flight aircraft i to the landing position k, D ik It refers to the distance that the target cargo flight aircraft i taxis from parking position k to takeoff.

[0149] Specifically, the terminal uses the fourth allocation sub-model corresponding to the flight taxi distance metric in the preset allocation model to analyze the basic allocation information, including the set of all aircraft, the set of all parking stands, the taxi distance from landing to the stand, and the taxi distance from the stand to takeoff, to obtain the parking stand information with the shortest taxi distance for the target cargo flight. In this embodiment, the parking stand allocation metric is the flight taxi distance metric. When allocating parking stands for the target cargo flight, the terminal must ensure that the taxi distance for the target cargo flight is the shortest possible to facilitate aircraft takeoff and landing.

[0150] It is understandable that when allocating cargo flight parking stands, multiple indicators can be combined and new indicators can be added, such as the utilization rate of close-in stands, the location of cargo flight parking stands on the take-off and landing runways, etc.

[0151] Reference Figure 4 , Figure 4 It is a flow chart of an embodiment of a method for allocating parking spaces for cargo flights provided in an embodiment of the present application.

[0152] In some embodiments of the present application, querying basic allocation information, obtaining and analyzing flight information and freight information of the target cargo flight, and obtaining a parking space allocation index for the target cargo flight are specifically described, including steps 401-402:

[0153] 401. Query the flight schedule and the flight cargo list in the basic allocation information, extract the flight information of the target cargo flight from the flight schedule, and extract the cargo information of the target cargo flight from the flight cargo list.

[0154] The terminal queries the flight schedule and the flight cargo details in the basic allocation information, extracts the flight information of the target cargo flight from the flight schedule, and extracts the cargo information of the target cargo flight from the flight cargo details.

[0155] 402 , configuring constraints according to the flight information, configuring an objective function according to the freight information, performing linear programming according to the constraints and the objective function, and obtaining parking space allocation indicators.

[0156] The terminal configures constraints based on flight information. For example, if the flight time is 10:00-11:00, the terminal configures constraints such as available parking spaces during this period. If the flight information indicates a large cargo aircraft, the terminal configures constraints such as large parking spaces. The terminal also configures an objective function based on freight information. For example, if the freight information includes a destination of Shenzhen, the terminal configures an objective function to minimize the distance to the Shenzhen freight flight. The terminal performs linear programming based on the constraints and the objective function to obtain a parking space allocation index. In this embodiment, the terminal determines the parking space allocation index based on flight and freight information so that the parking space allocation for cargo flights meets the needs of each cargo flight.

[0157] like Figure 5 As shown, Figure 5 The figure is a schematic structural diagram of an embodiment of a device for allocating parking spaces for cargo flights.

[0158] In order to better implement the method for allocating parking spaces for cargo flights in the embodiment of the present application, based on the method for allocating parking spaces for cargo flights, the embodiment of the present application further provides a device for allocating parking spaces for cargo flights, the device for allocating parking spaces for cargo flights comprising:

[0159] A receiving and determining module 501 is configured to receive an allocation instruction for a cargo flight parking space and determine that the allocation instruction corresponds to a target cargo flight to be allocated;

[0160] An information analysis module 502 is configured to query basic allocation information, obtain flight information and freight information of the target cargo flight, and analyze the information to obtain a parking space allocation index for the target cargo flight.

[0161] The parking stand allocation module 503 is configured to analyze the basic allocation information using an allocation sub-model corresponding to the parking stand allocation index in a preset allocation model to obtain parking stand information of the target cargo flight.

[0162] In some embodiments of the present application, the cargo flight parking space allocation device includes:

[0163] Obtaining historical parking stand allocation information for cargo flights as model training samples, and classifying the model training samples according to predefined parking stand allocation indicators to form model training sample subsets corresponding to different parking stand allocation indicators;

[0164] Each model training sample subset is used as the target model training sample subset;

[0165] Extracting a preset proportion of model training samples from the target model training sample subset at one time, and constructing an initial allocation model through the model training samples;

[0166] Iteratively extracting a preset proportion of model training samples from the target model training sample subset, training the initial allocation model with the model training samples to obtain a training sub-model;

[0167] Obtaining the allocation accuracy of the training sub-model, and using the training sub-model with the allocation accuracy higher than the preset allocation accuracy as the allocation sub-model;

[0168] The allocation sub-model obtained through training is acquired, and the allocation sub-model is encapsulated to form a preset allocation model.

[0169] In some embodiments of the present application, the parking stand allocation indicator is a flight transit time indicator; the parking stand allocation module 503 includes:

[0170] Analyzing the basic allocation information using a first allocation sub-model corresponding to the flight transit time indicator in a preset allocation model to obtain parking space information for the target cargo flight;

[0171] Wherein, the first allocation sub-model is:

[0172]

[0173] G represents the set of all cargoes, K represents the set of all aircraft spaces, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and the UT k Indicates the unloading and hauling time of the k-th position, the ST g Indicates the sorting time of cargo g, the x jkRefers to the aircraft j in port at gate k, the LT gk Indicates the loading and hauling time of cargo g to aircraft k, the OTT g Indicates the transit time of cargo g, the W g Indicates the weight of the cargo g, the P g Indicates the inbound and outbound aircraft pair (i, j) corresponding to cargo g.

[0174] In some embodiments of the present application, the parking space allocation index is a non-direct freight crate transfer index;

[0175] The parking space allocation module 503 includes:

[0176] Analyzing the basic allocation information by using a second allocation sub-model corresponding to the non-direct freight pallet transfer indicator in the preset allocation model to obtain the parking space information of the target freight flight;

[0177] The second allocation sub-model is:

[0178]

[0179] I represents the set of all aircraft, K represents the set of all parking spaces, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and the W i is the weight of cargo loaded on aircraft i of the target cargo flight, and N i is the set of loading ports of the transshipment center corresponding to the cargo planned to be loaded on the target cargo flight aircraft i, and the W in represents the weight of cargo transported from the unloading port of the transfer center n to the target cargo flight aircraft i, It represents the distance L from the k-th parking space to the unloading and hauling.

[0180] In some embodiments of the present application, the parking space allocation index is a direct freight crate transfer index;

[0181] The parking space allocation module 503 includes:

[0182] Analyzing the basic allocation information using a third allocation sub-model corresponding to the direct-transfer freight pallet transfer indicator in the preset allocation model to obtain the parking space information of the target freight flight;

[0183] Wherein, the third allocation sub-model is:

[0184]

[0185] The G D is a set of straight-forward boxes, K represents a set of all camera positions, and x ikIt means that the target cargo flight aircraft i is assigned to the parking space k, and the x jk Refers to the aircraft j in port at parking position k, the D kk' is the straight rotation distance from position k to k′, and W g Indicates the weight of the cargo in g.

[0186] In some embodiments of the present application, the parking stand allocation indicator is a flight taxiing distance indicator;

[0187] The parking space allocation module 503 includes:

[0188] The basic allocation information is analyzed by the fourth allocation sub-model corresponding to the flight taxiing distance index in the preset allocation model to obtain the parking space information of the target cargo flight.

[0189] The fourth camera position allocation sub-model is:

[0190]

[0191] I represents the set of all aircraft, K represents the set of all parking spaces, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and A ik It refers to the distance from the target cargo flight aircraft i to the landing position k, D ik It refers to the distance that the target cargo flight aircraft i taxis from parking position k to takeoff.

[0192] In some embodiments of the present application, the information analysis module 502 includes:

[0193] querying the flight schedule and the flight cargo details in the basic allocation information, extracting the flight information of the target cargo flight from the flight schedule, and extracting the cargo information of the target cargo flight from the flight cargo details;

[0194] The constraint conditions are configured according to the flight information, the objective function is configured according to the freight information, and linear programming is performed according to the constraint conditions and the objective function to obtain parking space allocation indicators.

[0195] In this embodiment, the cargo flight parking stand allocation device allocates cargo flight parking stands through an allocation model, making the cargo flight parking stand allocation more convenient and efficient. Furthermore, by analyzing the flight information and cargo information of the target cargo flight, the parking stand allocation index of the target cargo flight is obtained. The basic allocation information is analyzed through the allocation sub-model corresponding to the parking stand allocation index in the preset allocation model to obtain the parking stand information of the target cargo flight. Therefore, the cargo flight parking stand allocation takes into account the flight information and cargo information of different cargo flights, making the parking stand allocation more reasonable.

[0196] The embodiment of the present invention also provides a cargo flight parking space allocation device, such as Figure 6 As shown, Figure 6 It is a schematic structural diagram of an embodiment of the cargo flight parking space allocation equipment provided in the embodiments of the present application.

[0197] The cargo flight parking stand allocation device integrates any of the cargo flight parking stand allocation devices provided in the embodiments of the present invention, and the cargo flight parking stand allocation device includes:

[0198] Preset shooting device;

[0199] Accelerometer;

[0200] one or more processors;

[0201] Memory; and

[0202] One or more applications, wherein the one or more applications are stored in the memory and configured to cause the processor to execute the steps of the method for allocating cargo flight parking spaces described in any of the embodiments of the method for allocating cargo flight parking spaces.

[0203] Specifically, the cargo flight parking space allocation device may include one or more processing core processors 601, one or more readable storage media memories 602, a power supply 603, and an input unit 604. Those skilled in the art will understand that Figure 6 The cargo flight parking stand allocation equipment structure shown in the figure does not constitute a limitation on the cargo flight parking stand allocation equipment, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. Among them:

[0204] Processor 601 serves as the control center for the cargo stand allocation system. It utilizes various interfaces and circuits to connect the various components of the entire cargo stand allocation system. By running or executing software programs and / or modules stored in memory 602 and accessing data stored in memory 602, it performs various functions and processes data for the cargo stand allocation system, thereby providing overall monitoring of the system. Optionally, processor 601 may include one or more processing cores. Preferably, processor 601 may integrate an application processor and a modem processor, with the application processor primarily processing the operating system, user interface, and application programs, while the modem processor primarily handles wireless communications. It is understood that the modem processor may not be integrated into processor 601.

[0205] Memory 602 can be used to store software programs and modules. Processor 601 executes various functional applications and data processing by running the software programs and modules stored in memory 602. Memory 602 may primarily include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function (such as a sound playback function or an image playback function). The data storage area may store data generated based on the use of equipment allocating cargo flight parking spaces. Furthermore, memory 602 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, memory 602 may also include a memory controller to provide processor 601 with access to memory 602.

[0206] The cargo flight parking stand allocation device also includes a power supply 603 for supplying power to various components. Preferably, power supply 603 can be logically connected to processor 601 via a power management system, thereby enabling the power management system to manage charging, discharging, and power consumption. Power supply 603 can also include one or more DC or AC power supplies, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and other arbitrary components.

[0207] The cargo flight parking space allocation device may further include an input unit 604, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0208] Although not shown, the cargo flight parking stand allocation device may also include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 601 in the cargo flight parking stand allocation device will load the executable files corresponding to one or more application processes into the memory 602 according to the following instructions. The processor 601 then runs the application stored in the memory 602 to implement various functions as follows:

[0209] receiving an allocation instruction for a cargo flight parking space, and determining that the allocation instruction corresponds to a target cargo flight to be allocated;

[0210] Query basic allocation information, obtain flight information and freight information of the target cargo flight, analyze them, and obtain a parking space allocation indicator for the target cargo flight;

[0211] The basic allocation information is analyzed by using an allocation sub-model corresponding to the parking space allocation index in a preset allocation model to obtain the parking space information of the target cargo flight.

[0212] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be accomplished by instructions, or by controlling related hardware through instructions. The instructions may be stored in a readable storage medium and loaded and executed by a processor.

[0213] To this end, an embodiment of the present invention provides a readable storage medium, which may include a read-only memory (ROM), random access memory (RAM), a magnetic disk, or an optical disk. A computer program is stored on the readable storage medium, which is loaded by a processor to execute the steps of any of the cargo flight parking space allocation methods provided in the embodiments of the present invention. For example, the computer program loaded by the processor may execute the following steps:

[0214] receiving an allocation instruction for a cargo flight parking space, and determining that the allocation instruction corresponds to a target cargo flight to be allocated;

[0215] Query basic allocation information, obtain flight information and freight information of the target cargo flight, analyze them, and obtain a parking space allocation indicator for the target cargo flight;

[0216] The basic allocation information is analyzed by using an allocation sub-model corresponding to the parking space allocation index in a preset allocation model to obtain the parking space information of the target cargo flight.

[0217] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the detailed description of other embodiments above and will not be repeated here.

[0218] In specific implementation, the above units or structures can be implemented as independent entities, or can be arbitrarily combined to be implemented as the same or several entities. The specific implementation of the above units or structures can be referred to the previous method embodiments and will not be repeated here.

[0219] The specific implementation of the above operations can be found in the previous embodiments and will not be repeated here.

[0220] The above is a detailed introduction to a method for allocating parking spaces for cargo flights provided in an embodiment of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for allocating parking spaces for cargo flights, characterized in that: The method for allocating parking spaces for cargo flights includes: Obtaining historical parking stand allocation information for cargo flights as model training samples, and classifying the model training samples according to predefined parking stand allocation indicators to form model training sample subsets corresponding to different parking stand allocation indicators; Each model training sample subset is used as the target model training sample subset; Extracting a preset proportion of model training samples from the target model training sample subset at one time, and constructing an initial allocation model through the model training samples; Iteratively extracting a preset proportion of model training samples from the target model training sample subset, training the initial allocation model with the model training samples to obtain a training sub-model; Obtaining the allocation accuracy of the training sub-model, and using the training sub-model with the allocation accuracy higher than the preset allocation accuracy as the allocation sub-model; Acquire the allocation sub-model obtained through training, and encapsulate the allocation sub-model to form a preset allocation model; receiving an allocation instruction for a cargo flight parking space, and determining that the allocation instruction corresponds to a target cargo flight to be allocated; Query basic allocation information, obtain flight information and freight information of the target cargo flight, analyze them, and obtain a parking space allocation indicator for the target cargo flight; Analyzing the basic allocation information using an allocation sub-model corresponding to the parking space allocation index in a preset allocation model to obtain parking space information for the target cargo flight; When the parking space allocation index is a flight transit time index, the allocation sub-model is a first allocation sub-model; Wherein, the first allocation sub-model is: G represents the set of all cargoes, K represents the set of all aircraft spaces, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and the UT k Indicates the unloading and hauling time of the k-th position, the ST g Indicates the sorting time of cargo g, the x jk Refers to the aircraft j in port at gate k, the LT gk Indicates the loading and hauling time of cargo g to aircraft k, the OTT g Indicates the transit time of cargo g, the W g Indicates the weight of the cargo g, the P g Indicates the inbound and outbound aircraft pair (i, j) corresponding to cargo g.

2. The method for allocating cargo flight parking spaces according to claim 1, wherein: When the parking space allocation index is a non-direct freight pallet transfer index, the allocation sub-model is a second allocation sub-model; The second allocation sub-model is: I represents the set of all aircraft, K represents the set of all parking spaces, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and the W i is the weight of cargo loaded on aircraft i of the target cargo flight, and N i is the set of loading ports of the transshipment center corresponding to the cargo planned to be loaded on the target cargo flight aircraft i, and the W in represents the weight of cargo transported from the unloading port of the transfer center n to the target cargo flight aircraft i, It represents the distance L from the k-th parking space to the unloading and hauling.

3. The method for allocating cargo flight parking spaces according to claim 1, wherein: When the parking space allocation index is a direct freight pallet transfer index, the allocation sub-model is a third allocation sub-model; Wherein, the third allocation sub-model is: The G D is a set of straight-forward boxes, K represents a set of all camera positions, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and the x jk Refers to the aircraft j in port at parking position k, the D kk' is the straight rotation distance from position k to k′, and W g Indicates the weight of the cargo in g.

4. The method for allocating parking spaces for cargo flights according to claim 1, wherein: When the parking stand allocation index is the flight taxiing distance index, the allocation sub-model is the fourth allocation sub-model; Wherein, the fourth allocation sub-model is: I represents the set of all aircraft, K represents the set of all parking spaces, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and A ik It refers to the distance from the target cargo flight aircraft i to the landing position k, D ik It refers to the distance that the target cargo flight aircraft i taxis from parking position k to takeoff.

5. The method for allocating cargo flight parking spaces according to any one of claims 1 to 4, characterized in that: The querying of basic allocation information, obtaining and analyzing flight information and freight information of the target cargo flight, and obtaining a parking space allocation index for the target cargo flight, includes: querying the flight schedule and the flight cargo details in the basic allocation information, extracting the flight information of the target cargo flight from the flight schedule, and extracting the cargo information of the target cargo flight from the flight cargo details; The constraint conditions are configured according to the flight information, the objective function is configured according to the freight information, and linear programming is performed according to the constraint conditions and the objective function to obtain parking space allocation indicators.

6. A device for allocating parking spaces for cargo flights, characterized in that: The cargo flight parking space allocation device includes: A parking stand allocation module is configured to obtain historical parking stand allocation information of cargo flights as model training samples, classify the model training samples according to predefined parking stand allocation indicators, and form model training sample subsets corresponding to different parking stand allocation indicators; use each model training sample subset as a target model training sample subset; extract a preset proportion of model training samples from the target model training sample subset at one time, and construct an initial allocation model using the model training samples; iteratively extract a preset proportion of model training samples from the target model training sample subset, train the initial allocation model using the model training samples, and obtain a training sub-model; obtain the allocation accuracy of the training sub-model, and use the training sub-model with an allocation accuracy higher than the preset allocation accuracy as the allocation sub-model; obtain the trained allocation sub-model, and encapsulate the allocation sub-model to form a preset allocation model; a receiving and determining module, configured to receive an allocation instruction for a cargo flight parking space and determine that the allocation instruction corresponds to a target cargo flight to be allocated; An information analysis module is used to query basic allocation information, obtain flight information and freight information of the target cargo flight, and analyze them to obtain a parking space allocation index for the target cargo flight; The parking stand allocation module is further configured to analyze the basic allocation information using an allocation sub-model corresponding to the parking stand allocation index in a preset allocation model to obtain parking stand information for the target cargo flight; when the parking stand allocation index is a flight transit time index, the allocation sub-model is a first allocation sub-model, wherein the first allocation sub-model is: G represents the set of all cargoes, K represents the set of all aircraft spaces, and x ik It means that the target cargo flight aircraft i is assigned to the parking space k, and the UT k Indicates the unloading and hauling time of the k-th position, the ST g Indicates the sorting time of cargo g, the x jk Refers to the aircraft j in port at gate k, the LT gk Indicates the loading and hauling time of cargo g to aircraft k, the OTT g Indicates the transit time of cargo g, the W g Indicates the weight of the cargo g, the P g Indicates the inbound and outbound aircraft pair (i, j) corresponding to cargo g.

7. A cargo flight parking space allocation device, characterized in that: The equipment for allocating parking spaces for cargo flights includes: one or more processors; Memory; and One or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the processor to implement the method for allocating cargo flight parking spaces according to any one of claims 1 to 5.

8. A readable storage medium, characterized in that: A computer program is stored thereon, and the computer program is loaded by a processor to execute the steps in the method for allocating parking spaces for cargo flights according to any one of claims 1 to 5.

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