Aircraft dynamic recovery sorting scheduling method based on re-flight strategy and related device

Abstract

The invention discloses an aircraft dynamic recovery sorting scheduling method based on a re-flight strategy and a related device, and relates to the technical field of air traffic control, and the method comprises the steps: solving an aircraft group dynamic recovery decision model based on a state parameter of a previous decision stage, and obtaining a decision variable of each aircraft in a current decision stage; according to the decision variables of the aircrafts in the current decision stage, the recovery states of the aircrafts in the current decision stage are obtained; removing successfully recycled aircrafts from the to-be-recycled aircraft set in the previous decision-making stage to obtain the to-be-recycled aircraft set in the current decision-making stage, selecting a re-flying strategy for the recycled aircrafts failed in recycling, updating the decision variables according to the re-flying strategy, and obtaining the updated decision variables of the aircrafts in the current decision-making stage; if the aircraft set to be recycled in the current decision-making stage is empty, recycling is completed; according to the method, the recovery efficiency can be improved, and the flight safety can be guaranteed.

Description

Technical Field

[0001] The present application relates to the field of aviation traffic control technology, and in particular to a method and related apparatus for dynamically recovering and sequencing aircraft based on a go-around strategy. Background Art

[0002] The safe and efficient recovery of fleets of aircraft is a key technical challenge in the aviation industry. As air traffic becomes increasingly complex, aircraft recovery processes in time-varying environments face higher safety and real-time requirements. Traditional recovery scheduling methods struggle to cope with dynamic, multi-dimensional constraints, leading to increased accident risk and decreased operational efficiency. Summary of the Invention

[0003] The purpose of this application is to provide a method and related device for dynamic aircraft recovery sequencing 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 solutions: In a first aspect, the present application provides a method for dynamically retrieving and scheduling aircraft based on a missed approach strategy, the method comprising: Step S1, obtaining state parameters of the previous decision stage; the state parameters include the set of aircraft waiting for recovery, the updated decision variables of each aircraft, the fuel consumption rate of each aircraft, the minimum safe fuel amount, the lower limit fuel amount of aircraft under different recovery scales, the upper limit fuel amount of 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: Solve the aircraft group dynamic recovery decision model using a mathematical programming solver based on the state parameters of the previous decision stage to obtain the decision variables of each aircraft in the current decision stage; Step S3, obtaining the recovery status of each aircraft in the current decision stage according to the decision variables of each aircraft in the current decision stage; the recovery status includes recovery success and recovery failure; Step S4: Based on the recovery status of each aircraft in the current decision stage, aircraft with a recovery status of successful recovery are removed from the set of aircraft waiting for recovery in the previous decision stage to obtain the set of aircraft waiting for recovery in the current decision stage. A missed approach strategy is selected for the aircraft with a recovery status of failed recovery, and decision variables are updated according to the missed approach strategy to obtain the updated decision variables of each aircraft in the current decision stage. Aircraft that are still in the waiting-for-recovery state after executing the missed approach strategy are retained in the set of aircraft waiting for recovery in the current decision stage. Step S5, determining whether the set of aircraft waiting for recovery in the current decision stage is empty, if it is empty, completing the recovery; if not, returning to step S1; Among them, the dynamic recovery decision model of the aircraft group includes an overall objective function and constraints. The overall objective function is the dynamic weighted sum of three sub-objective functions, which are respectively 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 turbulence interval constraints, aircraft status mutual exclusion constraints and mission integrity constraints.

[0005] Optionally, the overall objective function is specifically: ; in, is the overall objective function; is the fuel consumption cost sub-objective function; reward sub-objective function for fault priority; Reward sub-objective function for task priority; 、 、 All are weight coefficients; For the current decision-making stage; It is the initial decision-making stage; The final decision-making stage.

[0006] Optionally, the fuel consumption cost sub-objective function is specifically: ; in, is the fuel consumption cost sub-objective function; For aircraft In the current decision-making stage The decision variable represents the current decision stage Is the flight arranged? On another plane Previously recycled; It is a collection of aircraft awaiting recovery; is the time difference between adjacent decision stages; for aircraft Fuel consumption rate; The fault priority reward sub-objective function is specifically: ; in, reward sub-objective function for fault priority; For aircraft the relative completeness of is the Kronecker Delta function, representing the aircraft In the current decision-making stage The value of when the recycling is successful, the subscript number 1 indicates that the recycling is successful; For aircraft In the current decision-making stage The recycling status; The task priority reward sub-objective function is specifically: ; in, Reward sub-objective function for task priority; For aircraft The relative priority of tasks.

[0007] Optionally, the fuel safety constraint is specifically: ; in, Indicates aircraft In the current decision-making stage The remaining fuel amount; Indicates aircraft In the current decision-making stage Any subsequent decision-making stage The remaining fuel amount; is the minimum oil level threshold; Indicates aircraft In the current decision-making stage Any subsequent decision-making stage Recycling status The value after being processed by the linear rectification function.

[0008] Optionally, the wake interval constraint is specifically: ; in, For aircraft In the current decision-making stage The decision variable represents the current decision stage Is the flight arranged? On another plane Previously recycled; is the time difference between adjacent decision stages; for Type aircraft and wake turbulence separation between aircraft of different types; Time is consumed for recycling; To consume time for escape; For aircraft In the current decision-making stage Recycling status The value after being processed by the linear rectification function.

[0009] Optionally, the aircraft state mutually exclusive constraint is specifically: ; in, is the Kronecker Delta function, when the aircraft In the current decision-making stage Recycling status equal Take 1 when it is, otherwise take 0; It is a mutually exclusive recycling status identifier. Represents successful recovery. Recovery failure includes standby recovery state, missed approach state and fault state. Represents the standby recovery state, Represents the go-around state. Indicates a fault condition.

[0010] Optionally, the task integrity constraint is specifically: ; Among them, among them, Indicates aircraft In the current decision-making stage The value of when the recycling is successful; For the current decision-making stage; It is the initial decision-making stage; For the final decision-making stage; It is a collection of aircraft waiting to be recovered.

[0011] Optionally, the go-around strategy is specifically: ; Among them, Case 1 represents the current decision-making stage Arrange flight On another plane It has been recycled before and successfully recycled; For aircraft In the current decision-making stage decision variables; For aircraft In the current decision-making stage Case 2 represents the PS strategy, which is to airplane Recycled again and successfully; For aircraft In the next decision-making stage Case 3 represents the SS2 strategy, which is the current decision-making stage. The next two decision-making stages airplane One plane apart Then it is recycled again and successfully; Case 4 represents the SS1 strategy, which is the strategy for the current decision stage. Any subsequent decision-making stage airplane Recycled again and successfully; For aircraft In the current decision-making stage Any subsequent decision-making stage The recycling status.

[0012] In a second aspect, the present application provides a computer device comprising: 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 any one of the above-mentioned methods for dynamic aircraft recovery sorting and scheduling based on a missed approach strategy.

[0013] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-mentioned methods for dynamic aircraft recovery sequencing and scheduling based on a missed approach strategy.

[0014] In a fourth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-mentioned aircraft dynamic recovery sequencing and scheduling methods based on a missed approach strategy.

[0015] According to the specific embodiments provided in this application, this application discloses the following technical effects: This application provides a method and related apparatus for dynamic aircraft recovery scheduling based on a missed approach strategy. By acquiring and updating aircraft decision variables and state parameters such as fuel levels in real time, the scheduling strategy can be adjusted based on real-time changes, effectively avoiding major accidents caused by queue delays caused by faulty aircraft. Furthermore, by setting wake turbulence separation constraints based on the impact of aircraft model differences on wake turbulence, the reduced airspace utilization or increased collision risk caused by fixed intervals during mixed-model recovery is avoided. The optimized safety interval improves safety. Addressing the drawback of fixed weight coefficients in the prior art, by dynamically adjusting the weight coefficients of sub-objective functions based on key parameters such as fuel remaining and task priority, the priority and resource allocation of each task are made more flexible and reasonable, reducing delays for high-priority tasks and avoiding scheduling imbalances caused by improper static weight settings. Furthermore, in the event of an aircraft recovery failure, the introduction of a missed approach strategy can improve the recovery success rate while reducing the negative impact of missed approach decisions on overall efficiency, ensuring the smooth recovery of the aircraft fleet. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 This is an application environment diagram of an aircraft dynamic recovery sequencing and scheduling method based on a missed approach strategy in one embodiment of the present application; Figure 2 A flowchart of a method for dynamic aircraft recovery sequencing and scheduling based on a missed approach strategy provided in one embodiment of the present application; Figure 3 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0019] Current aircraft recovery sequencing and scheduling methods have four main typical defects: First, static scheduling strategies (such as first-come, first-served strategies) lack a dynamic response mechanism, and the rate of major accidents caused by queue delays of faulty aircraft remains high; Second, the calculation of safety intervals is not based on the impact of aircraft model differences on wake turbulence. When recovering mixed models, fixed intervals lead to reduced airspace utilization or increased collision risk; Third, the weight coefficients in multi-objective optimization are fixed and cannot be dynamically adjusted according to key parameters such as fuel remaining, resulting in excessive delay rates for high-priority tasks; Fourth, there is a lack of mathematical modeling for go-around decisions, and resequencing delays significantly affect overall efficiency.

[0020] Due to the limitations of static scheduling, lack of safety intervals, imbalance of multiple objectives and gaps in go-around decision-making, existing technologies are difficult to resolve the contradiction between dynamic safety and real-time scheduling in aircraft group recovery.

[0021] 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 phase, resulting in errors in waiting fuel consumption estimates; the state constraints use a binary description of either / or, which cannot represent critical transition states such as go-arounds and failures; and the objective function lacks a state mutual exclusion mechanism, which causes scheduling conflicts. These issues severely limit the model's adaptability and reliability in complex scenarios.

[0022] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0023] The aircraft dynamic recovery sequencing scheduling method based on the missed approach strategy provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store data that server 104 needs to process. The data storage system can be provided separately, integrated with server 104, or located in the cloud or on another server. Terminal 102 can send the state parameters of the previous decision phase to server 104. Server 104 solves the aircraft fleet dynamic recovery decision model based on the state parameters of the previous decision phase to obtain the decision variables for each aircraft in the current decision phase. Based on the decision variables for each aircraft in the current decision phase, the recovery status of each aircraft in the current decision phase is obtained. Successfully recovered aircraft are removed from the set of aircraft awaiting recovery in the previous decision phase to obtain the set of aircraft awaiting recovery in the current decision phase. A go-around strategy is then selected for aircraft that failed to be recovered. The decision variables are updated based on the go-around strategy to obtain the updated decision variables for each aircraft in the current decision phase. If the set of aircraft awaiting recovery in the current decision phase is empty, recovery is completed; otherwise, the above steps are continued. Server 104 can provide feedback to terminal 102 on the updated decision variables for each aircraft in the current decision phase.

[0024] In an exemplary embodiment, Figure 2 As shown, a method for dynamic aircraft recovery sequencing scheduling based on a missed approach strategy is provided. The method is executed by a computer device, specifically a computer device such as a terminal or a server, or a terminal and a server. In the embodiment of the present application, the method is applied to Figure 1 The server 104 in the example is used as an example to illustrate the method, which includes the following steps S1 to S5. Step S1, obtaining the state parameters of the previous decision stage; the state parameters include the set of aircraft waiting for recovery, the updated decision variables of each aircraft, the fuel consumption rate of each aircraft, the minimum safe fuel amount, the lower limit fuel amount of aircraft under different recovery scales, the upper limit fuel amount of 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.

[0025] Step S2: Based on the state parameters of the previous decision stage, the mathematical programming solver CPLEX 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 stage; wherein, the dynamic recovery decision model of the aircraft group includes an overall objective function and constraints. The overall objective function is the dynamic weighted sum of three sub-objective functions, and the three sub-objective functions are respectively 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 interval constraints, aircraft state mutual exclusion constraints, and mission integrity constraints.

[0026] Step S3, obtaining the recovery status of each aircraft in the current decision stage according to the decision variables of each aircraft in the current decision stage; the recovery status includes recovery success and recovery failure.

[0027] In step S4, based on the recovery status of each aircraft in the current decision stage, the recovery aircraft with a recovery status of successful recovery are removed from the set of aircraft waiting for recovery in the previous decision stage to obtain the set of aircraft waiting for recovery in the current decision stage. A go-around strategy is selected for the recovery aircraft with a recovery status of failed recovery, and the decision variables are updated according to the go-around strategy to obtain the updated decision variables of each aircraft in the current decision stage. The aircraft that are still in the waiting-for-recovery state after executing the go-around strategy are retained in the set of aircraft waiting for recovery in the current decision stage.

[0028] Step S5, judging whether the set of aircraft waiting for recovery in the current decision stage is empty, if it is empty, completing the recovery; if not, returning to step S1.

[0029] By implementing the above-mentioned steps S1 to S5, the present application can adjust the scheduling strategy according to real-time changes by acquiring and updating the aircraft's decision variables and fuel level and other state parameters in real time, effectively avoiding major accidents caused by queuing delays of faulty aircraft. Moreover, based on the impact of aircraft model differences on wake turbulence, by setting wake interval constraints, the reduction in airspace utilization or increase in collision risk caused by fixed intervals during the recovery of mixed aircraft models is avoided, and the optimized safety interval improves safety. In response to the defect of fixed weight coefficients in the existing technology, by dynamically adjusting the weight coefficients of the sub-objective functions, based on key parameters such as fuel remaining and task priority, the priority and resource allocation of each task are made more flexible and reasonable, which can reduce delays in high-priority tasks and avoid scheduling imbalances caused by improper static weight settings. In addition, in the case of aircraft recovery failure, by introducing a go-around strategy, the recovery success rate can be improved, while reducing the negative impact of the go-around decision on the overall efficiency, ensuring the smooth recovery of the aircraft group.

[0030] Furthermore, the parameter names, symbols, parameter values ​​and remarks of the state parameters in step S1 are shown in Tables 1 and 2: Table 1 Status Parameters Table 1 Table 2 Status Parameters Table 2 Furthermore, the optimization goal of the Aircraft Recovery Scheduling Problem (ARSP) is to consider multiple objectives such as the aircraft's fuel level, integrity, and mission priority in the event of a missed approach. The following 0-1 linear programming objective function is designed and formally expressed as: (1); in, is the overall objective function; is the fuel consumption cost sub-objective function; reward sub-objective function for fault priority; Reward sub-objective function for task priority; 、 、 These are weighted coefficients, which are used to flexibly balance cost and efficiency goals according to the Air Traffic Controller's preference. They increase when fuel is scarce. ; Increases when the number of high-risk failure aircraft increases ; Increase when high priority tasks are intensive ; For the current decision-making stage; It is the initial decision-making stage; The final decision-making stage.

[0031] Furthermore, effective sorting based on the different fuel consumption rates of each aircraft and the different recovery interval requirements of different aircraft can reduce the overall fuel consumption cost. This design implicitly encourages the completion of the recovery task as soon as possible through reasonable recovery sorting to minimize the total recovery completion time. The fuel consumption cost sub-objective function is specifically: (2); in, is the fuel consumption cost sub-objective function; For aircraft In the current decision-making stage The decision variable represents the current decision stage Is the flight arranged? On another plane If it is recycled before, the value is 1, otherwise it is 0; It is a collection of aircraft awaiting recovery; is the time difference between adjacent decision stages, ; for aircraft Fuel consumption rate; pass Directly reward the priority recovery of faulty aircraft. If the aircraft with high fault probability (i.e. Large) is scheduled first ( ), the absolute value of the negative cost term increases and the objective function value decreases. The fault priority reward sub-objective function is specifically: (3); in, reward sub-objective function for fault priority; For aircraft The relative completeness of , which is standardized between 0 and 1; is the Kronecker Delta function, representing the aircraft In the current decision-making stage The value of when the recycling is successful, the subscript number 1 indicates that the recycling is successful; For aircraft In the current decision-making stage The recycling status; High priority tasks ( Large) aircraft were dispatched in advance ( ), the objective function value is significantly reduced. The task priority reward sub-objective function is specifically: (4); in, Reward sub-objective function for task priority; For aircraft The relative task priority, normalized between 0 and 1.

[0032] Furthermore, the constraints include fuel safety constraints, wake turbulence separation constraints, aircraft state mutual exclusion constraints, and mission integrity constraints.

[0033] The fuel safety constraint (i.e., aircraft i in the current decision stage The remaining fuel volume should not be less than the subsequent decision stage The fuel volume should be higher than the minimum fuel volume threshold at the time of successful recovery), specifically: (5); in, Indicates aircraft In the current decision-making stage The remaining fuel amount; Indicates aircraft In the current decision-making stage Any subsequent decision-making stage The remaining fuel amount; is the minimum oil level threshold, ; Indicates aircraft In the current decision-making stage Any subsequent decision-making stage Recycling status The value processed by the linear rectification function (output 1 if the recovery is successful, otherwise output 0). This constraint ensures that the remaining fuel of the aircraft does not fall below the safety threshold in all subsequent stages; is a linear rectification function, .

[0034] In order to simulate the wake-vortex turbulence effect between different types of aircraft, the minimum time interval that needs to be maintained between different types of aircraft recovered one after another to ensure safe recovery is Should not be less than The wake separation constraint is specifically: (6); in, For aircraft In the current decision-making stage The decision variable represents the current decision stage Is the flight arranged? On another plane Previously recycled; is the time difference between adjacent decision stages; for Type aircraft and Wake turbulence separation between aircraft of different types, ; Time is consumed for recycling; To consume time for escape; For aircraft In the current decision-making stage Recycling status The value after being processed by the linear rectification function.

[0035] In order to ensure the logical rationality and physical feasibility of the scheduling system, the same aircraft can only be in one state at the same decision stage (time point) and cannot have multiple states at the same time. Define state mutual exclusivity, combined with set constraints, if and only if hour , otherwise it is 0. The aircraft state mutual exclusion constraint is specifically: (7); in, is the Kronecker Delta function, when the aircraft In the current decision-making stage Recycling status equal Take 1 when it is, otherwise take 0; It is a mutually exclusive recycling status identifier. Represents successful recovery. Recovery failure includes standby recovery state, missed approach state and fault state. Represents the standby recovery state, Represents the go-around state. Indicates a fault condition.

[0036] Mission integrity constraints only apply when aircraft i is successfully recovered , the constraint ensures that each aircraft is successfully recovered at most once (physical rationality), avoiding double counting. The task integrity constraints are specifically: (8); in, Indicates aircraft In the current decision-making stage The value of when the recycling is successful; For the current decision-making stage; It is the initial decision-making stage; For the final decision-making stage; It is a collection of aircraft waiting to be recovered.

[0037] Furthermore, the go-around strategy is specifically as follows: (9); Among them, Case 1 represents the current decision-making stage Arrange flight On another plane It has been recycled before and successfully recycled; For aircraft In the current decision-making stage decision variables; For aircraft In the current decision-making stage Case 2 represents the PS strategy, which is to airplane Recycled again and successfully; For aircraft In the next decision-making stage Case 3 represents the SS2 strategy, which is the current decision-making stage. The next two decision-making stages airplane One plane apart Then it is recycled again and successfully; Case 4 represents the SS1 strategy, which is the strategy for the current decision stage. Any subsequent decision-making stage airplane Recycled again and successfully; For aircraft In the current decision-making stage Any subsequent decision-making stage The recycling status.

[0038] PS (Priority Sequencing): Allows an aircraft to attempt recovery again immediately after a failed recovery attempt, without having to queue up again or wait. This is suitable for situations where an aircraft is critically low on fuel, has an emergency malfunction, or has no other high-priority aircraft on deck waiting to be recovered.

[0039] SS1 (Standard Sequencing): This strategy requires failed aircraft to be integrated into the existing sequence and reordered based on factors such as fuel status and mission priority. This strategy 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.

[0040] SS2 (Safety Sequencing) is an "interval holding mode" that requires a failed aircraft to wait over the offshore platform until a subsequent aircraft has recovered and can approach again. This strategy is suitable for situations where deck chaos caused by consecutive failures needs to be avoided or when pilots need a brief adjustment.

[0041] The present application also provides an application scenario that applies the above-mentioned aircraft dynamic recovery sorting and scheduling method based on the go-around strategy. 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 of other processes remains stable; the scenario mainly studies the processing of the sorting stage and the re-sorting problem after the go-around, so it is assumed that the return time of all formations is the same; the time for switching between different altitude levels within the Marshall route is ignored; and sudden disturbances (such as temporary queue interruption beyond the recovery scale) are not included in the model. Specifically: the aircraft dynamic recovery sorting and scheduling method based on the go-around strategy provided in this embodiment can be applied in the aircraft recovery sorting scenario. The aircraft recovery sorting scenario includes an aircraft recovery sorting link; the aircraft recovery sorting link is to obtain the decision variables of each aircraft after the current decision stage based on the state parameters of the previous decision stage. The aircraft dynamic recovery sorting and scheduling method based on the go-around strategy provided in this embodiment belongs to the aircraft recovery sorting link.

[0042] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, an input / output interface (I / O) and a communication interface. The processor, memory and input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store processed data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for dynamic aircraft recovery sorting and scheduling based on a go-around strategy is implemented.

[0043] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0044] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0045] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0046] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0047] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, 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 may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0048] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0049] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, 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.

[0050] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for dynamic aircraft recovery sequencing and scheduling based on a missed approach strategy, characterized in that: The aircraft dynamic recovery sequencing and scheduling method based on the missed approach strategy includes: Step S1, obtaining state parameters of the previous decision stage; the state parameters include the set of aircraft waiting for recovery, the updated decision variables of each aircraft, the fuel consumption rate of each aircraft, the minimum safe fuel amount, the lower limit fuel amount of aircraft under different recovery scales, the upper limit fuel amount of 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 stage, a mathematical programming solver is used to solve the aircraft group dynamic recovery decision model to obtain the decision variables of each aircraft in the current decision stage; Step S3, obtaining the recovery status of each aircraft in the current decision stage according to the decision variables of each aircraft in the current decision stage; the recovery status includes recovery success and recovery failure; Step S4: Based on the recovery status of each aircraft in the current decision stage, aircraft with a recovery status of successful recovery are removed from the set of aircraft waiting for recovery in the previous decision stage to obtain the set of aircraft waiting for recovery in the current decision stage. A missed approach strategy is selected for the aircraft with a recovery status of failed recovery, and decision variables are updated according to the missed approach strategy to obtain the updated decision variables of each aircraft in the current decision stage. Aircraft that are still in the waiting-for-recovery state after executing the missed approach strategy are retained in the set of aircraft waiting for recovery in the current decision stage. Step S5, determining whether the set of aircraft waiting for recovery in the current decision stage is empty, if it is empty, completing the recovery; if not, returning to step S1; Among them, the dynamic recovery decision model of the aircraft group includes an overall objective function and constraints. The overall objective function is the dynamic weighted sum of three sub-objective functions, which are respectively 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 turbulence interval constraints, aircraft status mutual exclusion constraints and mission integrity constraints.

2. The aircraft dynamic recovery sequencing and scheduling method based on the missed approach strategy according to claim 1, characterized in that: The overall objective function is specifically: ； in, is the overall objective function; is the fuel consumption cost sub-objective function; reward sub-objective function for fault priority; Reward sub-objective function for task priority; 、 、 All are weight coefficients; For the current decision-making stage; It is the initial decision-making stage; The final decision-making stage.

3. The aircraft dynamic recovery sequencing and scheduling method based on the missed approach strategy according to claim 1 or 2, characterized in that: The fuel consumption cost sub-objective function is specifically: ； in, is the fuel consumption cost sub-objective function; For aircraft In the current decision-making stage The decision variable represents the current decision stage Is the flight arranged? On another plane Previously recovered, the aircraft and another plane The set of aircraft that belong to the same decision stage and are waiting to be recovered; It is a collection of aircraft awaiting recovery; is the time difference between adjacent decision stages; for aircraft Fuel consumption rate; The fault priority reward sub-objective function is specifically: ； in, reward sub-objective function for fault priority; For aircraft the relative completeness of is the KroneckerDelta function, representing the aircraft In the current decision-making stage The value of when the recycling is successful, the subscript number 1 indicates that the recycling is successful; For aircraft In the current decision-making stage The recycling status; The task priority reward sub-objective function is specifically: ； in, Reward sub-objective function for task priority; For aircraft The relative priority of tasks.

4. The aircraft dynamic recovery sequencing and scheduling method based on the missed approach strategy according to claim 1, characterized in that: The fuel safety constraints are specifically: ； in, Indicates aircraft In the current decision-making stage The remaining fuel amount; Indicates aircraft In the current decision-making stage Any subsequent decision-making stage The remaining fuel amount; is the minimum oil level threshold; Indicates aircraft In the current decision-making stage Any subsequent decision-making stage Recycling status The value after being processed by the linear rectification function.

5. The aircraft dynamic recovery sequencing and scheduling method based on the missed approach strategy according to claim 1, characterized in that: The wake separation constraint is specifically: ； in, For aircraft In the current decision-making stage The decision variable represents the current decision stage Is the flight arranged? On another plane Previously recycled; is the time difference between adjacent decision stages; for Type aircraft and wake turbulence separation between aircraft of different types; Time is consumed for recycling; To consume time for escape; For aircraft In the current decision-making stage Recycling status The value after being processed by the linear rectification function.

6. The aircraft dynamic recovery sequencing and scheduling method based on the missed approach strategy according to claim 1, characterized in that: The aircraft status mutually exclusive constraints are specifically: ； in, is the Kronecker Delta function, when the aircraft In the current decision-making stage Recycling status equal Take 1 when it is, otherwise take 0; It is a mutually exclusive recycling status identifier. Represents successful recovery. Recovery failure includes standby recovery state, missed approach state and fault state. Represents the standby recovery state, Represents the go-around state. Indicates a fault condition.

7. The aircraft dynamic recovery sequencing and scheduling method based on the missed approach strategy according to claim 1, characterized in that: The task integrity constraints are specifically: ； in, Indicates aircraft In the current decision-making stage The value of when the recycling is successful; For the current decision-making stage; It is the initial decision-making stage; For the final decision-making stage; It is a collection of aircraft waiting to be recovered.

8. The aircraft dynamic recovery sequencing and scheduling method based on the missed approach strategy according to claim 1, characterized in that: The go-around strategy is specifically as follows: ； Among them, Case 1 represents the current decision-making stage Arrange flight On another plane It has been recycled before and successfully recycled; For aircraft In the current decision-making stage decision variables; For aircraft In the current decision-making stage Case 2 represents the PS strategy, which is to airplane Recycled again and successfully; For aircraft In the next decision-making stage Case 3 represents the SS2 strategy, which is the current decision-making stage. The next two decision-making stages airplane One plane apart Then it is recycled again and successfully; Case 4 represents the SS1 strategy, which is the strategy for the current decision stage. Any subsequent decision-making stage airplane Recycled again and successfully; For aircraft In the current decision-making stage Any subsequent decision-making stage The recycling status.

9. A computer device comprising: 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 sequencing and scheduling method based on a missed approach strategy according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the aircraft dynamic recovery sequencing and scheduling method based on a missed approach strategy according to any one of claims 1 to 7 is implemented.

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