Method and related device for sequencing and scheduling aircraft dynamic recovery based on go-around strategy

Abstract

The application discloses a kind of based on the aircraft dynamic recovery sequencing scheduling method of go-around strategy and related device, it is related to air traffic control technical field, which method includes based on the state parameter of last decision stage, aircraft group dynamic recovery decision model is solved, the decision variable of each aircraft in current decision stage is obtained;According to the decision variable of each aircraft in current decision stage, the recovery state of each aircraft in current decision stage is obtained;From the aircraft set waiting for recovery in last decision stage, remove the recovery aircraft of recovery success, obtain the aircraft set waiting for recovery in current decision stage, and select go-around strategy for the recovery aircraft of recovery failure, update decision variable according to go-around strategy, obtain the decision variable of each aircraft in current decision stage after updating;If the aircraft set waiting for recovery in current decision stage is empty, then complete recovery;Otherwise, continue to execute the above steps, and the application can improve recovery efficiency and guarantee flight safety.

Description

Technical Field

[0001] This application relates to the field of air traffic control technology, and in particular to a method and apparatus for dynamic aircraft recovery, sorting and scheduling based on a go-around strategy. Background Technology

[0002] The safe and efficient recovery of aircraft fleets is a key technological challenge in the aviation industry. With increasingly complex air traffic conditions, aircraft recovery processes in time-varying environments face higher requirements for safety and real-time performance. Traditional recovery sequencing and scheduling methods struggle to cope with dynamically changing multidimensional constraints, leading to increased accident risks and decreased operational efficiency. Summary of the Invention

[0003] The purpose of this application is to provide a method and related apparatus for dynamic aircraft recovery sorting and scheduling based on a go-around strategy, which can improve the efficiency of the aircraft group recovery process while ensuring safety.

[0004] To achieve the above objectives, this application provides the following solution:

[0005] Firstly, this application provides a dynamic aircraft recovery sorting and scheduling method based on a go-around strategy, the method comprising:

[0006] Step S1: Obtain the state parameters of the previous decision-making stage; the state parameters include the set of aircraft waiting to be recovered, the updated decision variables of each aircraft, the fuel consumption rate of each aircraft, the minimum safe fuel quantity, the lower limit of the fuel quantity of the aircraft under different recovery scales, the upper limit of the fuel quantity of the aircraft under different recovery scales, the lower limit of the recovery success rate, the escape consumption time, the recovery consumption time and the wake turbulence interval between each aircraft.

[0007] Step S2: Based on the state parameters of the previous decision-making stage, use a mathematical programming solver to solve the dynamic recovery decision model of the aircraft group to obtain the decision variables of each aircraft in the current decision-making stage.

[0008] Step S3: Based on the decision variables of each aircraft in the current decision-making stage, obtain the recovery status of each aircraft in the current decision-making stage; the recovery status includes successful recovery and failed recovery.

[0009] Step S4: Based on the recovery status of each aircraft in the current decision stage, remove the aircraft with a recovery status of successful recovery from the set of aircraft waiting to be recovered in the previous decision stage to obtain the set of aircraft waiting to be recovered in the current decision stage. Select a go-around strategy for the aircraft with a recovery status of failed recovery, update the decision variables according to the go-around strategy, obtain the updated decision variables of each aircraft in the current decision stage, and retain the aircraft that are still in the waiting-to-be-recovered state after executing the go-around strategy in the set of aircraft waiting to be recovered in the current decision stage.

[0010] Step S5: Determine whether the set of aircraft waiting to be recovered in the current decision-making stage is empty. If it is empty, the recovery is completed; if it is not empty, return to step S1.

[0011] The dynamic recovery decision model for the aircraft group includes an overall objective function and constraints. The overall objective function is a dynamic weighted sum of three sub-objective functions: a fuel consumption cost sub-objective function, a fault priority reward sub-objective function, and a mission priority reward sub-objective function. The constraints include fuel safety constraints, wake turbulence separation constraints, aircraft state mutual exclusion constraints, and mission integrity constraints.

[0012] Optionally, the overall objective function is specifically:

[0013] ;

[0014] in, The overall objective function; The sub-objective function is the fuel consumption cost; The sub-objective function is a fault-priority reward function; A sub-objective function for rewarding task priority; , , All are weighting coefficients; For the current decision-making stage; This is the initial decision-making stage; This is the final decision-making stage.

[0015] Optionally, the fuel consumption cost sub-objective function is specifically:

[0016] ;

[0017] in, The sub-objective function is the fuel consumption cost; For airplane At the current decision-making stage The decision variables represent the variables at the current decision stage. Will a plane be arranged? On another plane Previously recycled; It is a collection of aircraft awaiting recovery; The time difference between adjacent decision-making stages; for Type of aircraft fuel consumption rate;

[0018] The fault priority reward sub-objective function is as follows:

[0019] ;

[0020] in, The sub-objective function is a fault-priority reward function; For airplane The relative completeness; The Kronecker Delta function represents the aircraft. At the current decision-making stage The value at which the recycling was successful, with the subscript number 1 indicating a successful recycling; For airplane At the current decision-making stage The recycling status;

[0021] The task priority reward sub-objective function is as follows:

[0022] ;

[0023] in, A sub-objective function for rewarding task priority; For airplane The relative task priority.

[0024] Optionally, the fuel safety constraint specifically includes:

[0025] ;

[0026] in, Indicates airplane At the current decision-making stage The remaining fuel quantity; Indicates airplane At the current decision-making stage Any subsequent decision-making stage The remaining fuel quantity; This is the minimum fuel quantity threshold; Indicates the aircraft At the current decision-making stage Any subsequent decision-making stage Recycling status The value after processing by the linear rectification function.

[0027] Optionally, the wake interval constraint specifically includes:

[0028] ;

[0029] in, For airplane At the current decision-making stage The decision variables represent the variables at the current decision stage. Will a plane be arranged? On another plane Previously recycled; The time difference between adjacent decision-making stages; for Type of aircraft and Wake distance between different types of aircraft; The time consumed for recycling; Time wasted in the escape; For the aircraft At the current decision-making stage Recycling status The value after processing by the linear rectification function.

[0030] Optionally, the mutual exclusion constraint of the aircraft state is specifically as follows:

[0031] ;

[0032] in, For the Kronecker Delta function, when the aircraft At the current decision-making stage Recycling status equal The value is 1 if the condition is met, otherwise it is 0. These are mutually exclusive recycling status identifiers. Successful recovery indicates a successful recovery; recovery failures include standby recovery status, go-around status, and malfunction status. This indicates a standby recovery status. This indicates that the flight has resumed operation. This indicates a fault status.

[0033] Optionally, the task integrity constraint specifically includes:

[0034] ;

[0035] Among them, among them, Indicates airplane At the current decision-making stage The value at which the recycling was successful; For the current decision-making stage; This is the initial decision-making stage; This is the final decision-making stage; It is a collection of aircraft awaiting recovery.

[0036] Optionally, the go-around strategy specifically includes:

[0037] ;

[0038] Case 1 represents the current decision-making stage. Arrange the plane On another plane Previously recycled, and successfully recycled; For airplane At the current decision-making stage Decision variables; For airplane At the current decision-making stage The recovery status; Case 2 represents the PS strategy, which is to determine the next decision stage. airplane The recovery was successful again. For airplane In the next decision-making stage The recovery status; Case 3 represents the SS2 strategy, which is the strategy at the current decision stage. The next two decision-making stages airplane One plane apart The data was subsequently recovered successfully; Case 4 represents the SS1 strategy, which is to perform the current decision-making phase. Any subsequent decision-making stage airplane The item was successfully recovered again. For airplane At the current decision-making stage Any subsequent decision-making stage The recycling status.

[0039] In a second aspect, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the aircraft dynamic recovery sorting and scheduling method based on the go-around strategy described above.

[0040] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aircraft dynamic recovery sorting and scheduling method based on the go-around strategy described above.

[0041] Fourthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the aircraft dynamic recovery sorting and scheduling method based on the go-around strategy described above.

[0042] According to the specific embodiments provided in this application, the following technical effects are disclosed:

[0043] This application provides a dynamic aircraft recovery sequencing and scheduling method and related apparatus based on a go-around strategy. By acquiring and updating aircraft decision variables and state parameters such as fuel quantity in real time, the scheduling strategy can be adjusted according to real-time changes, effectively avoiding major accidents caused by queuing delays of faulty aircraft. Furthermore, based on the impact of aircraft type differences on wake turbulence, wake turbulence separation constraints are set to avoid the decrease in airspace utilization or increased collision risk caused by fixed separations during mixed aircraft recovery. The optimized safety separation improves safety. Addressing the deficiency of fixed weight coefficients in existing technologies, the weight coefficients of the sub-objective function are dynamically adjusted based on key parameters such as fuel remaining capacity and task priority, making the priority and resource allocation of each task more flexible and reasonable. This reduces delays of high-priority tasks and avoids scheduling imbalances caused by improper static weight settings. In addition, in the event of aircraft recovery failure, the introduction of a go-around strategy can improve the recovery success rate while reducing the negative impact of go-around decisions on overall efficiency, ensuring the smooth recovery of the aircraft group. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is an application environment diagram of an aircraft dynamic recovery sorting and scheduling method based on a go-around strategy in one embodiment of this application;

[0046] Figure 2 A flowchart illustrating an aircraft dynamic recovery sorting and scheduling method based on a go-around strategy, provided as an embodiment of this application;

[0047] Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0048] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0049] Current aircraft recovery sequencing and scheduling methods suffer from four main defects: First, static scheduling strategies (such as first-come, first-served strategies) lack dynamic response mechanisms, resulting in a high rate of major accidents caused by queuing delays for faulty aircraft; second, safety interval calculations do not consider the impact of aircraft type differences on wake turbulence, leading to reduced airspace utilization or increased collision risks when recovering mixed aircraft types using fixed intervals; third, fixed weight coefficients in multi-objective optimization cannot be dynamically adjusted based on key parameters such as fuel reserves, resulting in excessive delay rates for high-priority tasks; and fourth, the lack of mathematical modeling in go-around decisions significantly impacts overall efficiency due to reordering delays.

[0050] Existing technologies, due to limitations in static scheduling, lack of safety intervals, imbalance of multiple objectives, and gaps in go-around decision-making, are unable to resolve the contradiction between dynamic safety and real-time scheduling in aircraft group recovery.

[0051] Further research revealed three major technical bottlenecks in existing intelligent scheduling systems: the fuel consumption model is not coupled with the time increment of the decision-making stage, leading to errors in waiting fuel consumption estimation; the state constraints use a binary description that is either / or, failing to characterize critical transition states such as go-arounds and malfunctions; and the objective function lacks a state mutual exclusion mechanism, causing scheduling conflicts. These problems severely limit the model's adaptability and reliability in complex scenarios.

[0052] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0053] The aircraft dynamic recovery sorting and scheduling method based on the go-around strategy provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be set up independently, integrated into server 104, or placed in the cloud or on another server. Terminal 102 can send the state parameters of the previous decision-making stage to server 104. Server 104 solves the dynamic recovery decision model for the aircraft group based on the state parameters of the previous decision-making stage, obtaining the decision variables for each aircraft in the current decision-making stage; based on the decision variables of each aircraft in the current decision-making stage, it obtains the recovery status of each aircraft in the current decision-making stage; it removes successfully recovered aircraft from the set of aircraft waiting to be recovered in the previous decision-making stage, obtaining the set of aircraft waiting to be recovered in the current decision-making stage, and selects a go-around strategy for recovered aircraft that failed to be recovered, updating the decision variables according to the go-around strategy, obtaining the updated decision variables for each aircraft in the current decision-making stage; if the set of aircraft waiting to be recovered in the current decision-making stage is empty, the recovery is completed; otherwise, the above steps continue. Server 104 can feed back the updated decision variables of each aircraft in the current decision-making stage to terminal 102.

[0054] In one exemplary embodiment, such as Figure 2 As shown, a dynamic aircraft recovery sorting and scheduling method based on a go-around strategy is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is applied to... Figure 1 Taking server 104 as an example, the explanation includes the following steps S1 to S5. Wherein:

[0055] Step S1: Obtain the state parameters from the previous decision-making stage. The state parameters include the set of aircraft waiting to be recovered, the updated decision variables for each aircraft, the fuel consumption rate of each aircraft, the minimum safe fuel quantity, the lower limit of fuel quantity for aircraft under different recovery scales, the upper limit of fuel quantity for aircraft under different recovery scales, the lower limit of recovery success rate, escape consumption time, recovery consumption time, and wake turbulence interval between aircraft.

[0056] Step S2: Based on the state parameters of the previous decision-making stage, the CPLEX mathematical programming solver is used to solve the dynamic recovery decision model of the aircraft group to obtain the decision variables of each aircraft in the current decision-making stage. The dynamic recovery decision model of the aircraft group includes an overall objective function and constraints. The overall objective function is a dynamic weighted sum of three sub-objective functions, namely, the fuel consumption cost sub-objective function, the fault priority reward sub-objective function, and the mission priority reward sub-objective function. The constraints include fuel safety constraints, wake separation constraints, aircraft state mutual exclusion constraints, and mission integrity constraints.

[0057] Step S3: Based on the decision variables of each aircraft in the current decision-making stage, obtain the recovery status of each aircraft in the current decision-making stage; the recovery status includes successful recovery and failed recovery.

[0058] Step S4: Based on the recovery status of each aircraft in the current decision stage, remove the aircraft with a recovery success status from the set of aircraft waiting to be recovered in the previous decision stage to obtain the set of aircraft waiting to be recovered in the current decision stage. Select a go-around strategy for the aircraft with a recovery failure status, update the decision variables according to the go-around strategy, obtain the updated decision variables of each aircraft in the current decision stage, and retain the aircraft that are still in the waiting-to-be-recovered state after executing the go-around strategy in the set of aircraft waiting to be recovered in the current decision stage.

[0059] Step S5: Determine whether the set of aircraft waiting to be recovered in the current decision-making stage is empty. If it is empty, the recovery is completed; if it is not empty, return to step S1.

[0060] By implementing steps S1 to S5, this application can adjust the scheduling strategy according to real-time changes by acquiring and updating aircraft decision variables and state parameters such as fuel quantity, effectively avoiding major accidents caused by queuing delays of faulty aircraft. Furthermore, based on the impact of aircraft type differences on wake turbulence, by setting wake separation constraints, it avoids the decrease in airspace utilization or increased collision risk caused by fixed intervals during mixed aircraft recovery, and the optimized safety interval improves safety. Addressing the deficiency of fixed weight coefficients in existing technologies, this application dynamically adjusts the weight coefficients of sub-objective functions based on key parameters such as fuel remaining capacity and task priority, making the priority and resource allocation of each task more flexible and reasonable, reducing delays of high-priority tasks and avoiding scheduling imbalances caused by improper static weight settings. In addition, in the event of aircraft recovery failure, the introduction of a go-around strategy can improve the recovery success rate while reducing the negative impact of go-around decisions on overall efficiency, ensuring the smooth recovery of the aircraft group.

[0061] Furthermore, the parameter names, symbols, parameter values, and remarks of the state parameters in step S1 are shown in Tables 1 and 2:

[0062] Table 1 State Parameter Table 1

[0063]

[0064] Table 2 State Parameter Table 2

[0065]

[0066] Furthermore, the optimization objective of the Aircraft Recovery Scheduling Problem (ARSP) considers multiple dimensions such as the aircraft's fuel reserves, operational status, and mission priority under go-around conditions. The overall objective function of the 0-1 linear programming problem is designed as follows, formally expressed as:

[0067] (1);

[0068] in, The overall objective function; The sub-objective function is the fuel consumption cost; The sub-objective function is a fault-priority reward function; A sub-objective function for rewarding task priority; , , These are all weighting coefficients, which are used to flexibly balance cost and efficiency objectives based on the AirTraffic Controller's preferences, increasing when fuel is scarce. Increased risk when the number of high-risk aircraft malfunctions increases. Increase when high-priority tasks are intensive ; For the current decision-making stage; This is the initial decision-making stage; This is the final decision-making stage.

[0069] Furthermore, by effectively prioritizing aircraft based on their varying fuel consumption rates and recovery interval requirements, overall fuel costs can be reduced. This design implicitly incentivizes faster recovery completion through rational sequencing, thereby minimizing the total recovery time. The fuel consumption cost sub-objective function is as follows:

[0070] (2);

[0071] in, The sub-objective function is the fuel consumption cost; For airplane At the current decision-making stage The decision variables represent the variables at the current decision stage. Will a plane be arranged? On another plane The value is 1 if the previous recycling is successful, and 0 otherwise. It is a collection of aircraft awaiting recovery; The time difference between adjacent decision-making stages. ; for Type of aircraft fuel consumption rate;

[0072] pass Direct rewards are given to priority recovery of malfunctioning aircraft; if the probability of malfunction is high (i.e., Larger ones are prioritized for scheduling. If the absolute value of the negative cost term increases, the objective function value decreases. The fault priority reward sub-objective function is specifically as follows:

[0073] (3);

[0074] in, The sub-objective function is a fault-priority reward function; For airplane The relative completeness is standardized to between 0 and 1; The Kronecker Delta function represents the aircraft. At the current decision-making stage The value at which the recycling was successful, with the subscript number 1 indicating a successful recycling; For airplane At the current decision-making stage The recycling status;

[0075] High priority tasks ( The large aircraft was scheduled in advance. When this occurs, the objective function value decreases significantly. The specific sub-objective function for task priority reward is as follows:

[0076] (4);

[0077] in, A sub-objective function for rewarding task priority; For airplane The relative task priority is standardized to between 0 and 1.

[0078] Furthermore, the constraints include fuel safety constraints, wake separation constraints, aircraft state mutual exclusion constraints, and mission integrity constraints.

[0079] The fuel safety constraints (i.e., aircraft i at the current decision-making stage) The remaining fuel quantity should not be less than that required in subsequent decision-making stages. The fuel quantity should be higher than the minimum fuel quantity threshold at the moment of successful recovery, specifically:

[0080] (5);

[0081] in, Indicates airplane At the current decision-making stage The remaining fuel quantity; Indicates airplane At the current decision-making stage Any subsequent decision-making stage The remaining fuel quantity; The minimum fuel level threshold, ; Indicates the aircraft At the current decision-making stage Any subsequent decision-making stage Recycling status The value after being processed by the linear rectifier function (output 1 when recovery is successful, output 0 otherwise), this constraint ensures that the aircraft's remaining fuel level is not lower than the safety threshold in all subsequent stages; It is a linear rectified function. .

[0082] To simulate the wake-vortex turbulence effects between different types of aircraft, the minimum time interval required between successive recoveries of different types of aircraft is determined to ensure safe recovery. It should be no less than The wake separation constraint is specifically as follows:

[0083] (6);

[0084] in, For airplane At the current decision-making stage The decision variables represent the variables at the current decision stage. Will a plane be arranged? On another plane Previously recycled; The time difference between adjacent decision-making stages; for Type of aircraft and Wake turbulence spacing between different types of aircraft ; The time consumed for recycling; Time wasted in the escape; For the aircraft At the current decision-making stage Recycling status The value after processing by the linear rectification function.

[0085] To ensure the logical rationality and physical feasibility of the scheduling system, an aircraft can only be in one state at the same decision-making stage (point in time), and cannot simultaneously possess multiple states. Utilizing... Define state mutual exclusion, combined with set constraints, if and only if hour Otherwise, it is 0. The mutual exclusion constraint of the aircraft state is as follows:

[0086] (7);

[0087] in, For the Kronecker Delta function, when the aircraft At the current decision-making stage Recycling status equal The value is 1 if the condition is met, otherwise it is 0. These are mutually exclusive recycling status identifiers. Successful recovery indicates a successful recovery; recovery failures include standby recovery status, go-around status, and malfunction status. This indicates a standby recovery status. This indicates that the flight has resumed operation. This indicates a fault status.

[0088] Mission integrity constraints apply only when aircraft i is successfully recovered. The constraint ensures that each aircraft can be successfully recovered at most once (physical plausibility), avoiding double counting. The mission integrity constraint specifically includes:

[0089] (8);

[0090] in, Indicates airplane At the current decision-making stage The value at which the recycling was successful; For the current decision-making stage; This is the initial decision-making stage; This is the final decision-making stage; It is a collection of aircraft awaiting recovery.

[0091] Furthermore, the aforementioned go-around strategy specifically includes:

[0092] (9);

[0093] Case 1 represents the current decision-making stage. Arrange the plane On another plane Previously recycled, and successfully recycled; For airplane At the current decision-making stage Decision variables; For airplane At the current decision-making stage The recovery status; Case 2 represents the PS strategy, which is to determine the next decision stage. airplane The item was successfully recovered again. For airplane In the next decision-making stage The recovery status; Case 3 represents the SS2 strategy, which is the strategy at the current decision stage. The next two decision-making stages airplane One plane apart The data was subsequently recovered successfully; Case 4 represents the SS1 strategy, which is to perform the current decision-making phase. Any subsequent decision-making stage airplane The item was successfully recovered again. For airplane At the current decision-making stage Any subsequent decision-making stage The recycling status.

[0094] Priority Sequencing (PS) strategy: Allows an aircraft to attempt recovery again immediately after a failed recovery attempt, without having to re-queue or wait. This strategy is suitable for situations where the aircraft is severely low on fuel, experiences an emergency, or has no other high-priority aircraft available for recovery on the deck.

[0095] SS1 strategy (Standard Sequencing): This strategy requires failed aircraft to be added to the existing sequencing queue and reordered based on factors such as fuel status and mission priority. It is suitable for situations where multiple aircraft are returning simultaneously, overall recovery efficiency needs to be optimized, and pilots are in good condition. It also requires the recovery sequencing tool to have real-time planning capabilities and be able to dynamically adjust to the recovery situation in real time.

[0096] SS2 strategy (Safety Sequencing): also known as "interval waiting mode," requires failed aircraft to wait over the sea platform until another aircraft has been successfully recovered before attempting to return. This is suitable for situations where consecutive failures need to be avoided to prevent deck chaos or where pilots require brief adjustments.

[0097] This application also provides an application scenario in which the aforementioned aircraft dynamic recovery sorting and scheduling method based on a go-around strategy is applied. To simplify the problem, the following assumptions are made for the aircraft recovery sorting scenario: to avoid frequent go-arounds, the success rate of aircraft recovery after a go-around is set to 100%, and the recovery success rate remains stable in other processes; the scenario mainly studies the processing of the sorting stage and the re-sorting problem after a go-around, therefore it is assumed that the return time of all formations is the same; the time for different altitude level transitions within the Marshall line is ignored; sudden disturbances (such as temporary insertions beyond the recovery scale) are not included in the model. Specifically: the aircraft dynamic recovery sorting and scheduling method based on a go-around strategy provided in this embodiment can be applied to the aircraft recovery sorting scenario. The aircraft recovery sorting scenario includes an aircraft recovery sorting stage; the aircraft recovery sorting stage obtains the updated decision variables for each aircraft in the current decision stage based on the state parameters of the previous decision stage. The aircraft dynamic recovery sorting and scheduling method based on a go-around strategy provided in this embodiment belongs to the aircraft recovery sorting stage.

[0098] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 3As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores and processes data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When executed by the processor, the computer program implements a dynamic aircraft recovery sequencing and scheduling method based on a go-around strategy.

[0099] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0100] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0101] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0102] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0103] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0104] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0105] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0106] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A dynamic aircraft recovery sorting and scheduling method based on a go-around strategy, characterized in that, The aircraft dynamic recovery and scheduling method based on the go-around strategy includes: Step S1: Obtain the state parameters of the previous decision-making stage; the state parameters include the set of aircraft waiting to be recovered, the updated decision variables of each aircraft, the fuel consumption rate of each aircraft, the minimum safe fuel quantity, the lower limit of the fuel quantity of the aircraft under different recovery scales, the upper limit of the fuel quantity of the aircraft under different recovery scales, the lower limit of the recovery success rate, the escape consumption time, the recovery consumption time and the wake turbulence interval between each aircraft. Step S2: Based on the state parameters of the previous decision-making stage, use a mathematical programming solver to solve the dynamic recovery decision model of the aircraft group to obtain the decision variables of each aircraft in the current decision-making stage. Step S3: Based on the decision variables of each aircraft in the current decision-making stage, obtain the recovery status of each aircraft in the current decision-making stage; the recovery status includes successful recovery and failed recovery. Step S4: Based on the recovery status of each aircraft in the current decision stage, remove the aircraft with a recovery status of successful recovery from the set of aircraft waiting to be recovered in the previous decision stage to obtain the set of aircraft waiting to be recovered in the current decision stage. Select a go-around strategy for the aircraft with a recovery status of failed recovery, update the decision variables according to the go-around strategy, obtain the updated decision variables of each aircraft in the current decision stage, and retain the aircraft that are still in the waiting-to-be-recovered state after executing the go-around strategy in the set of aircraft waiting to be recovered in the current decision stage. Step S5: Determine whether the set of aircraft waiting to be recovered in the current decision-making stage is empty. If it is empty, the recovery is completed; if it is not empty, return to step S1. The dynamic recovery decision model for the aircraft group includes an overall objective function and constraints. The overall objective function is a dynamic weighted sum of three sub-objective functions, namely, a fuel consumption cost sub-objective function, a fault priority reward sub-objective function, and a mission priority reward sub-objective function. The constraints include fuel safety constraints, wake turbulence separation constraints, aircraft state mutual exclusion constraints, and mission integrity constraints. The aforementioned go-around strategy is as follows: ； Case 1 represents the current decision-making stage. Arrange the plane On another plane Previously recycled, and successfully recycled; For airplane At the current decision-making stage Decision variables; For airplane At the current decision-making stage The recovery status; Case 2 represents the PS strategy, which is to determine the next decision stage. airplane The recovery was successful again. For airplane In the next decision-making stage The recovery status; Case 3 represents the SS2 strategy, which is the strategy at the current decision stage. The next two decision-making stages airplane One plane apart The data was subsequently recovered successfully; Case 4 represents the SS1 strategy, which is to perform the current decision-making phase. Any subsequent decision-making stage airplane The recovery was successful again. For airplane At the current decision-making stage Any subsequent decision-making stage The recycling status.

2. The aircraft dynamic recovery sorting and scheduling method based on the go-around strategy according to claim 1, characterized in that, The overall objective function is as follows: ； in, The overall objective function; The sub-objective function is the fuel consumption cost; The sub-objective function is a fault-priority reward function; A sub-objective function for rewarding task priority; , , All are weighting coefficients; This is the current decision-making stage; This is the initial decision-making stage; This is the final decision-making stage.

3. The aircraft dynamic recovery sorting and scheduling method based on a go-around strategy according to claim 1 or 2, characterized in that, The fuel consumption cost sub-objective function is as follows: ； in, The sub-objective function is the fuel consumption cost; For airplane At the current decision-making stage The decision variables represent the variables at the current decision stage. Will a plane be arranged? On another plane Previously recovered aircraft and another plane A group of aircraft that are awaiting recovery and belong to the same decision-making stage; It is a collection of aircraft awaiting recovery; The time difference between adjacent decision-making stages; for Type of aircraft fuel consumption rate; The fault priority reward sub-objective function is as follows: ； in, The sub-objective function is a fault-priority reward function; For airplane The relative completeness; The KroneckerDelta function represents the aircraft. At the current decision-making stage The value at which the recycling was successful, with the index 1 indicating a successful recycling; For airplane At the current decision-making stage The recycling status; The task priority reward sub-objective function is as follows: ； in, A sub-objective function for rewarding task priority; For airplane The relative task priority.

4. The aircraft dynamic recovery sorting and scheduling method based on go-around strategy according to claim 1, characterized in that, The fuel safety constraints are specifically as follows: ； in, Indicates airplane At the current decision-making stage The remaining fuel quantity; Indicates airplane At the current decision-making stage Any subsequent decision-making stage The remaining fuel quantity; This is the minimum fuel quantity threshold; Indicates the aircraft At the current decision-making stage Any subsequent decision-making stage Recycling status The value after processing by the linear rectification function.

5. The aircraft dynamic recovery sorting and scheduling method based on go-around strategy according to claim 1, characterized in that, The wake separation constraint is specifically as follows: ； in, For airplane At the current decision-making stage The decision variables represent the variables at the current decision stage. Will a plane be arranged? On another plane Previously recycled; The time difference between adjacent decision-making stages; for Type of aircraft and Wake distance between different types of aircraft; The time consumed for recycling; Time wasted in the escape; For the aircraft At the current decision-making stage Recycling status The value after processing by the linear rectification function.

6. The aircraft dynamic recovery sorting and scheduling method based on the go-around strategy according to claim 1, characterized in that, The mutual exclusion constraint on the aircraft state is as follows: ； in, For the Kronecker Delta function, when the aircraft At the current decision-making stage Recycling status equal The value is 1 if the condition is met, otherwise it is 0. These are mutually exclusive recycling status identifiers. Successful recovery indicates a successful recovery; recovery failures include standby recovery status, go-around status, and malfunction status. This indicates a standby recovery status. This indicates that the flight has resumed operation. This indicates a fault status.

7. The aircraft dynamic recovery sorting and scheduling method based on go-around strategy according to claim 1, characterized in that, The task integrity constraint is specifically as follows: ； in, Indicates airplane At the current decision-making stage The value at which the recycling was successful; This is the current decision-making stage; This is the initial decision-making stage; This is the final decision-making stage; It is a collection of aircraft awaiting recovery.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the aircraft dynamic recovery sorting and scheduling method based on the go-around strategy according to any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the aircraft dynamic recovery sorting and scheduling method based on the go-around strategy as described in any one of claims 1-7.

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