An airport guarantee resource scheduling method and related device

Abstract

The application discloses an airport guarantee resource scheduling method and related device, relates to the field of airport scheduling, and comprises the following steps: when detecting an airport emergency guarantee task, determining a first airport guarantee task set and a guarantee personnel set influenced by the airport emergency guarantee task; and performing personnel re-distribution on the airport emergency guarantee task and the first airport guarantee task set based on the guarantee personnel set. The application circumscribes the influence object of the airport emergency guarantee task, re-schedules only the influenced airport guarantee task and guarantee personnel, greatly reduces the operation data amount, simplifies the scheduling logic, effectively shortens the scheduling time consumption, and can realize rapid resource allocation in the emergency guarantee scene.

Description

Technical Field

[0001] This application relates to the field of airport scheduling technology, and in particular to a scheduling method and related apparatus for airport support resources. Background Technology

[0002] Airport ground support is a core component of normal flight operations, encompassing various flight support tasks such as refueling, cabin cleaning, and apron inspection and transportation. Due to the frequent occurrence of dynamic events such as flight delays and cancellations, or interference from uncertain factors such as extreme weather and equipment failures, flight support tasks are frequently encountered. Therefore, it is necessary to dispatch airport support resources at any time to ensure the execution of flight support tasks.

[0003] The current airport support resource scheduling strategy is based on full recalculation, which involves a large amount of computation and slow response, and cannot meet the rapid scheduling requirements of flight support tasks. Summary of the Invention

[0004] In view of the above problems, this application provides a method and related apparatus for scheduling airport support resources to achieve rapid resource scheduling during emergency flight support tasks. The specific solution is as follows:

[0005] The first aspect of this application provides a method for scheduling airport support resources, the method comprising:

[0006] When an airport emergency support mission is detected, determine the first set of airport support missions and the set of support personnel affected by the airport emergency support mission.

[0007] Based on the aforementioned support personnel set, personnel are redistributed between the airport emergency support task set and the first airport support task set.

[0008] One possible implementation also includes:

[0009] The allocation of airport support tasks and personnel to unaffected airports will remain unchanged.

[0010] In one possible implementation, determining the first set of airport support tasks and the set of support personnel affected by the airport emergency support task includes:

[0011] Based on the execution time of the airport emergency support mission, determine the scope of impact of the airport emergency support mission, and obtain at least one airport support mission and at least one support personnel included in the scope of impact.

[0012] In one possible implementation, determining the scope of impact of the airport emergency support mission based on its execution time includes:

[0013] Based on the execution time of the airport emergency support mission, identify the target airport support mission that conflicts with the execution time of the airport emergency support mission;

[0014] Query the personnel assigned to the target airport support task and the personnel associated with those assigned;

[0015] Determine the set of tasks to be processed for the assigned personnel and the set of tasks to be processed for the associated personnel;

[0016] Identify airport support tasks whose execution time is affected from at least one set of pending tasks.

[0017] In one possible implementation, the reassignment of personnel between the airport emergency support task and the first airport support task set based on the support personnel set includes:

[0018] The airport emergency support tasks and the airport support tasks in the first airport support task set are ordered according to their execution time.

[0019] For each sorted airport support task, a set of support personnel is selected based on the task requirements and qualifications to obtain a set of candidate support personnel for the airport support task. The task processing score of each candidate support personnel in the set is calculated. The candidate support personnel are sorted in descending order based on the task processing score and each candidate support personnel is traversed. The candidate support personnel who meet the hard constraints are determined as the support personnel to handle the airport support task.

[0020] Output the personnel redistribution results for the airport emergency support task and the first airport support task set.

[0021] In one possible implementation, calculating the task processing score for each candidate support personnel in the candidate support personnel set includes:

[0022] The task processing score of the support personnel is calculated based on the distance between the support personnel and the task execution location of the airport support mission, the qualifications of the support personnel, and the workload of the support personnel.

[0023] One possible implementation also includes:

[0024] The task allocation rate after personnel reallocation is calculated. If the task allocation rate is lower than a preset threshold, an optimization algorithm is used for secondary allocation optimization.

[0025] One possible implementation also includes:

[0026] Based on the airport event type and time window, select the corresponding airport support resource scheduling mode, which includes: global initial scheduling, rolling pre-scheduling, and incremental dynamic rescheduling.

[0027] A second aspect of this application provides a scheduling system for airport support resources, the scheduling system comprising:

[0028] The query unit is used to determine the first set of airport support tasks and the set of support personnel affected by the airport emergency support task when an airport emergency support task is detected.

[0029] The allocation unit is used to reallocate personnel to the airport emergency support task and the first airport support task set based on the support personnel set.

[0030] A third aspect of this application provides a computer program product including computer-readable instructions that, when executed on an electronic device, cause the electronic device to implement the airport support resource scheduling method described in the first aspect or any implementation thereof.

[0031] Based on the above technical solution, this application provides a method and related apparatus for scheduling airport support resources. When scheduling, this method identifies the affected objects of airport emergency support tasks and reschedules only for the affected airport support tasks and personnel, significantly reducing the amount of computational data, simplifying the scheduling logic, and effectively shortening the scheduling time, thus enabling rapid resource allocation in emergency support scenarios. Attached Figure Description

[0032] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0033] Figure 1 A flowchart illustrating an airport support resource scheduling method provided in this application embodiment;

[0034] Figure 2 A schematic diagram of a breadth-first search provided for an embodiment of this application;

[0035] Figure 3 A schematic diagram of the structure of a scheduling system provided in an embodiment of this application;

[0036] Figure 4 This application provides a hardware structure block diagram of an electronic device. Detailed Implementation

[0037] The embodiments of this application are described below with reference to the accompanying drawings. The terminology used in the implementation section of this application is for explaining specific embodiments only and is not intended to limit the scope of this application.

[0038] As will be known to those skilled in the art, with the development of technology and the emergence of new scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0039] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms are interchangeable where appropriate; this is merely a way of distinguishing objects with the same attributes in the embodiments of this application. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of elements is not necessarily limited to those elements, but may include other elements not explicitly listed or inherent to those processes, methods, products, or apparatuses.

[0040] Airport ground support is a core component of normal flight operations, encompassing various flight support tasks such as refueling, cabin cleaning, and apron inspection and transportation. Due to the frequent occurrence of dynamic events such as flight delays and cancellations, or interference from uncertain factors such as extreme weather and equipment failures, flight support tasks are frequently encountered. Therefore, it is necessary to dispatch airport support resources at any time to ensure the execution of flight support tasks.

[0041] The current airport support resource allocation has the following problems:

[0042] Insufficient dynamic response capability. Frequent occurrence of various sudden dynamic events typically necessitates a full recalculation strategy, which is computationally intensive, slow in response, and cannot meet the business requirements for minute-level adjustments.

[0043] The problem of multiple time windows being coupled together is difficult to coordinate. Flight support tasks involve constraints from multiple time windows, including task execution time windows, personnel shift windows, and task-to-task continuity time windows. It is difficult to effectively coordinate the coupling relationship between multiple time windows, which often leads to time conflicts or resource idleness in airport support resource scheduling.

[0044] Multi-objective optimization is ineffective. Actual scheduling needs to consider multiple objectives simultaneously, such as maximizing task allocation rate, balancing personnel load, improving qualification matching, and minimizing distance cost. The conflict between multiple objectives makes it difficult to obtain an equilibrium solution in a single-stage solution, and only simple compromises can be made among the objectives.

[0045] Inaccurate resolution of constraint conflicts. When encountering constraint conflicts, it is difficult to accurately locate the scope of impact, often leading to over-adjustment (affecting unaffected areas) or under-adjustment (not completely resolving the conflict).

[0046] To address the aforementioned problems, this application provides a method for scheduling airport support resources. The method for scheduling airport support resources according to this application will be described in detail below with reference to the accompanying drawings.

[0047] Reference Figure 1 , Figure 1 A flowchart illustrating an airport support resource scheduling method provided in this application embodiment is shown below. Figure 1 As shown in the embodiment of this application, a method for scheduling airport support resources may include steps S10 and S11, which will be described in detail below.

[0048] S10. When an airport emergency support mission is detected, determine the first airport support mission set and support personnel set affected by the airport emergency support mission.

[0049] In this embodiment, the corresponding airport support resource scheduling mode can be selected according to the airport event type and time window. The airport support resource scheduling mode may include: global initial scheduling, rolling pre-scheduling and incremental dynamic rescheduling.

[0050] In actual airport operation support, different scenarios have different requirements for the response speed, optimization depth, and computational resource consumption of the scheduling system. Therefore, this embodiment sets up a three-level time window routing mechanism to match an appropriate scheduling mode based on the type of airport event currently received and its associated time window characteristics.

[0051] The global initial scheduling mode can be triggered by a scheduled task or a full data update event before daily departure. Its processing time window can cover the entire scheduling cycle. In this mode, the system can load all task and personnel data and call the complete optimization process to pursue the best resource matching and load balancing on a global scale.

[0052] The rolling pre-scheduling mode can be triggered by a batch refresh of tasks at regular intervals. Its time window is set from the current moment plus a look-forward amount to infinity. This mode optimizes the tasks to be scheduled in the future, while inheriting and locking the existing scheduling status before the current moment to ensure the continuous updating of future plans and avoid frequent disturbances to tasks that have been executed or are about to be executed.

[0053] The incremental dynamic reordering mode is designed for various sudden real-time events such as flight delays and manual lockouts. Its time window is between the current time and the maximum reordering window. In this mode, the system only searches and optimizes within the affected local area, achieving millisecond-level event perception and second-level solution output.

[0054] When an airport emergency support task is detected, the airport support resource scheduling mode is incremental dynamic rearrangement. An airport emergency support task can refer to a task that arises temporarily or changes outside the original scheduling plan and needs to be immediately incorporated into the resource scheduling system. Triggering scenarios for such tasks can include flight delays or cancellations, as well as support requests, task transfers due to sudden failures of ground support equipment, additional inspection tasks caused by increased airport security levels, or batch operation adjustments due to extreme weather. Specifically, in this embodiment, the scheduling system can receive real-time push notifications from external systems through a REST API gateway, automatically parse and generate tasks by listening to flight delay event streams, or identify airport emergency support tasks by periodically polling database status changes using a timed scheduling trigger, or directly trigger resource scheduling manually. Alternatively, in another optional embodiment, this embodiment can also adopt an asynchronous subscription mode based on message queues, uniformly encapsulating various emergencies into a standard message format and publishing them to middleware. The scheduling system, as a consumer, pulls these messages on demand and processes them decoupled from the overall system.

[0055] This embodiment can determine the set of impacts caused by the airport emergency support task, including the first airport support task set and the support personnel set. This facilitates the accurate separation of the finite subset actually affected from the full scheduling data, effectively avoiding blindly expanding the scope of resource scheduling. This embodiment can filter affected objects based on the overlap of execution time windows. Of course, in another optional embodiment, a predefined rule mapping table or knowledge graph can be maintained. Based on the type, level, and location of the airport emergency support task, the table can be queried to obtain the corresponding list of affected task IDs and personnel groups. For unaffected airport support tasks, the system can continue to maintain the allocation relationship between unaffected airport support tasks and their support personnel.

[0056] Specifically, this embodiment can determine the scope of impact of airport emergency support tasks based on the execution time of the airport emergency support tasks, and obtain at least one airport support task and at least one support personnel included in the scope of impact.

[0057] The system can scan the entire task pool based on the execution time period of airport emergency support tasks, marking all existing airport support tasks that overlap with that time period, have insufficient follow-up intervals, or conflict with resource usage as affected objects. For example, when it is detected that a cleaning task at a certain gate is delayed by 30 minutes due to the delay of a preceding flight, all airport support tasks that were originally scheduled to use the same gate, the same cleaning equipment, or the same support team within that 30-minute window are delayed and therefore included in the first airport support task set.

[0058] Of course, in another alternative embodiment, this embodiment can also combine multiple factors to comprehensively determine the scope of influence. For example, a geographical area isolation mechanism can be introduced, which only considers airport support tasks located in the same terminal, the same apron, or the same functional area as a candidate set of time conflicts, excluding airport support tasks that are too far apart and cannot generate actual resource competition even if the time overlaps.

[0059] This embodiment determines the scope of impact of airport emergency support tasks and realizes local resource adjustments. This avoids the waste of computing power and unnecessary scheduling interference caused by excessive adjustment scope, and also avoids the hidden conflict residue and secondary scheduling risks caused by excessively small adjustment scope.

[0060] In determining the scope of impact of airport emergency support tasks, this embodiment can accurately capture the chain reactions triggered by airport emergency support tasks through a hierarchical propagation mechanism. Specifically, this embodiment can determine target airport support tasks that conflict with the execution time of airport emergency support tasks based on their execution time; query the personnel assigned to the target airport support tasks and their associated personnel; determine the set of pending tasks for the assigned personnel and the set of pending tasks for the associated personnel; and from at least one set of pending tasks, determine the airport support tasks whose execution time is affected, thereby obtaining the first set of affected airport support tasks and the set of support personnel.

[0061] Among them, related personnel can refer to personnel who belong to the same task processing group as the assigned personnel or have common tasks to be processed.

[0062] This embodiment can use the BFS influence domain propagation algorithm to implement the above process. The BFS (Breadth-First Search) influence domain propagation algorithm can be defined as a type of heuristic algorithm that uses BFS as a carrier to simulate the diffusion of influence or state from the source node layer by layer and delineate the influence coverage area.

[0063] Specifically, in this embodiment, an airport emergency support task can be used as a seed node to initialize the search queue. The current scheduling plan is scanned to identify all target airport support tasks that overlap with the seed node on the timeline or have insufficient follow-up intervals, marking them as first-level conflict nodes. A breadth-first search loop is then performed based on these first-level conflict nodes: for each task node in the queue, its currently bound assignee and preset associated personnel are queried. All unexecuted pending tasks under these personnel are obtained, and the planned execution time of each pending task is checked one by one to see if it has shifted or conflicted due to changes in preceding tasks. If so, the task is added to the affected set and enqueued as a new seed node, continuing to expand to the next level until the queue is empty or the preset maximum propagation depth is reached. The union of all tasks traversed at all levels is taken to obtain the first airport support task set, and all involved support personnel are aggregated into a support personnel set.

[0064] The hierarchical propagation mechanism based on BFS used in this embodiment, compared with a simple full time window scan, can perform targeted tracking along the actual task relationship chain, avoid misjudging unrelated parallel airport support tasks as affected objects, and prevent missing implicit cascading conflicts across personnel, providing a complete calculation range for subsequent local rearrangement.

[0065] For example, such as Figure 2 As shown, the airport emergency support task causes a delay in the target airport support task T_delayed. The person assigned to the target airport support task T_delayed is determined as P1, and the associated persons of person assigned as P1 are P2 and P3. The subsequent task chain of person assigned as P1 is T2 and T3, and the affected tasks are T4 and T5. The secondary propagation continues to affect tasks T6 and T7. Therefore, the final output set of the first airport support tasks includes: T_delayed, T2, T3, T4, T5, T6 and T7, and the set of support personnel includes: P1, P2 and P3.

[0066] Of course, in another alternative embodiment, this embodiment can also employ other graph traversal or retrieval strategies to determine the scope of impact. For example, a depth-first search algorithm can be used to prioritize tracing along the task chain of a single person to the deepest node, thereby determining the affected airport support tasks and personnel. Alternatively, an index table or knowledge graph can be pre-built, and when a specific type of airport emergency support task is detected, the estimated set of affected airport support tasks and personnel can be obtained by looking up the table.

[0067] S11. Based on the set of support personnel, redistribute personnel between the airport emergency support task set and the first airport support task set.

[0068] In this embodiment, the specific process of personnel reallocation can be as follows:

[0069] For the airport emergency support tasks and the airport support tasks in the first airport support task set, the airport support tasks are sorted according to their execution time. For each sorted airport support task, a set of support personnel is selected based on the task requirements and qualifications to obtain a set of candidate support personnel for the current airport support task. The task processing score of each candidate support personnel is calculated. The candidate support personnel are sorted in descending order based on the task processing score and iterated through each candidate support personnel. The candidate support personnel who meet the hard constraints are determined as the support personnel to handle the airport support task. Thus, the personnel redistribution results of the airport emergency support tasks and the first airport support task set are output.

[0070] In this embodiment, each airport support task to be processed can be arranged according to its execution time to form a task queue to be assigned. This ensures that resources for airport support tasks with earlier execution times are prioritized, avoiding the situation where later airport support tasks compete for resources and make it difficult for earlier airport support tasks to complete.

[0071] The airport support task at the top of the queue of tasks to be assigned is taken as the target. Based on the skill tags, license levels or equipment operation permissions required by the airport support task, the support personnel set is subjected to the first round of hard filtering to remove irrelevant personnel who do not have the corresponding qualifications, thereby obtaining the candidate support personnel set.

[0072] For each support personnel in the candidate support personnel set, a multi-dimensional evaluation method can be used to calculate their task processing score for the current airport support task. This task processing score can be a comprehensive quantitative value that integrates multiple business optimization objectives, and can be used to characterize the relative merits of the support personnel in handling the current airport support task. In this embodiment, the task processing score can be calculated based on the distance between the support personnel and the airport support task execution location, the support personnel's qualifications, and the support personnel's workload. The calculation formula is as follows:

[0073] ;

[0074] in, It can represent the task processing score; It can represent the weight of the distance dimension; It can represent the normalized value of the distance between support personnel and the mission location of airport support tasks; It can represent the weight of the qualification dimension; This can represent the normalized numerical value corresponding to the qualification level of the support personnel, for example, having five qualification levels. The possible values ​​are: 0.2, 0.4, 0.6, 0.8, and 1. It can represent the weight of the load dimension; It can represent the numerical value corresponding to the workload, specifically the normalized value of the duration of airport support tasks assigned to support personnel. , and The sum is fixed; in this embodiment, =0.4, =0.2, =0.4, , and This can be flexibly adjusted according to actual needs. For example, when the distance is very close, the focus on the distance dimension is lower, so it can be appropriately reduced. The value of can be determined by the algorithm. This embodiment can also automatically update the weight values ​​based on reinforcement learning or online feedback mechanisms, according to the execution results of historical scheduling.

[0075] Of course, in another alternative embodiment, the calculation dimensions for task processing scores are not limited to distance, load, and qualifications. More feature factors reflecting the status or business preferences of support personnel can be introduced. For example, a historical performance dimension can be introduced, scoring based on the average time or error rate of support personnel in performing similar airport support tasks in the past, prioritizing the assignment of skilled workers to handle urgent or high-risk airport support tasks; or a fatigue dimension can be introduced, combining support personnel's continuous duty time, circadian rhythm, and physiological monitoring data to dynamically decay the score, forcibly reducing the probability of fatigued personnel being selected.

[0076] This embodiment sorts all candidate support personnel in descending order of their task processing scores, with higher scores indicating greater suitability for the current airport support task. The system iterates through this ordered list, further verifying whether each candidate meets mandatory constraints beyond qualifications. These constraints can be enforced conditions for airport support task allocation, such as whether the current time slot falls within the personnel's valid shift window, whether there is sufficient physical transfer time between previous airport support tasks, and whether the personnel's continuous working hours exceed limits. This determines the personnel suitable for the current airport support task and allows them to handle the next task. This embodiment achieves multi-objective collaborative optimization of task allocation rate, load balancing, and personnel qualification matching, all while ensuring absolute compliance with mandatory constraints.

[0077] Once all airport support tasks have been assigned or confirmed to be unassignable, the system will output the assignment relationships generated in this round as the personnel reassignment results. The personnel reassignment results may also include the assignment confidence of each airport support task and the reassigned support personnel.

[0078] Furthermore, this embodiment can calculate the task allocation rate after personnel redistribution. If the task allocation rate is lower than a preset threshold, an optimization algorithm is used for secondary allocation optimization.

[0079] The task allocation rate can be obtained by dividing the number of successfully allocated tasks by the total number of tasks to be allocated. The preset threshold is the dividing line between a satisfactory solution and a solution that needs optimization. In this embodiment, the preset threshold can be 95%. When the task allocation rate is not lower than the preset threshold, it means that the personnel reallocation result obtained above meets the operational requirements and can be directly output. When the task allocation rate is lower than the preset threshold, it means that there is an allocation conflict, thus triggering a secondary allocation optimization.

[0080] This embodiment can employ an optimization algorithm for secondary allocation optimization, specifically the CP-SAT algorithm. The CP-SAT (Constraint Programming Satisfiability) algorithm can refer to: an integer constraint programming solution algorithm that transforms the constraint programming problem into a Boolean SAT form for solution, integrating CP pruning capabilities with SAT conflict-driven learning as a hybrid solution algorithm.

[0081] Specifically, after triggering the secondary allocation optimization, the system can construct a CP-SAT model and use a Hint (solution hint information) injection mechanism to accelerate convergence. The system can inject the allocation relationships with high confidence and no violation of hard constraints from the above personnel redistribution results as Hints into the variable domain of the CP-SAT model, providing a high-quality starting point for solving the CP-SAT model. This allows the CP-SAT model to perform a local fine search in the neighborhood of this starting point, avoiding blind traversal in the full solution space.

[0082] Furthermore, this embodiment sets a change penalty term for allocation changes during secondary allocation optimization to achieve minimal personnel changes. Specifically, when using the CP-SAT algorithm, an objective function F is defined, which has constraint terms. Before and after the reassignment of the affected task, the allocated support personnel are compared. If the support personnel have changed, a change cost term is added to the objective function F. The objective function F can be represented as follows:

[0083] ;

[0084] in, It can represent constraint terms; It can represent a change cost item. ; This can represent: the weighting of changes in resource task allocation; | This can indicate whether there were changes in the support personnel before and after the reassignment. If there were changes in the support personnel before and after the reassignment, then | The value can be 1. If there is no change in the number of support personnel before and after the redistribution, then... The value of can be 0; It can indicate the current matching status of resources and tasks; It can indicate the matching status of resources and tasks before the update.

[0085] Since the larger the number of personnel variables, the smaller the value of the objective function F, this embodiment needs to maximize the objective function F during the secondary allocation optimization to minimize personnel changes.

[0086] This embodiment combines a three-dimensional dynamic scoring heuristic with CP-SAT precise optimization. A hint mechanism guides the search direction, ensuring feasible solutions are generated within seconds while simultaneously guaranteeing optimality. Furthermore, fixed domain protection and change penalty terms minimize personnel scheduling changes.

[0087] To prevent precise optimization from hindering real-time scheduling, a tiered timeout protection mechanism is implemented. If the CP-SAT model finds a better solution within the time limit, the new personnel reallocation result is updated and output. If no better solution is found within the time limit, or the CP-SAT model determines that no solution is feasible, the personnel reallocation result before secondary optimization is output as a fallback solution to ensure the continuity of airport operations. Specifically, for incremental dynamic rescheduling scenarios, the timeout can be limited to 15 seconds; for rolling pre-scheduling scenarios, the timeout can be limited to 30 seconds; and for global initial scheduling scenarios, the timeout can be limited to 60 seconds. This ensures that usable scheduling instructions can be output under any extreme circumstances, guaranteeing the continuity of airport operations.

[0088] Of course, in another alternative embodiment, this embodiment can also use the integer linear programming algorithm as the optimization algorithm to find the optimal solution by constructing a linear objective function and a set of inequality constraints.

[0089] Thus, this embodiment provides a complete scheduling system, such as Figure 3 As shown, the scheduling system may include an access and routing layer, a heuristic engine layer, a CP-SAT precision optimization layer, and a status and verification layer.

[0090] The access and routing layer can include a REST API (REST Application Programming Interface) gateway, a flight delay event stream, a timed scheduling trigger, a manual intervention module (receiving manual intervention instructions), and a pattern routing gateway. The REST API gateway, flight delay event stream, timed scheduling trigger, and manual intervention module can each trigger resource scheduling. The pattern routing gateway can determine the current airport support resource scheduling mode based on the airport event type and time window, and can also determine the data processing mode based on the data scale, including monolithic solving and block parallel processing.

[0091] The heuristic engine layer can include a state tracking module, a 3D scoring engine, a greedy solution constructor, and a quality valve. The state tracking module can track the location, load, and other states of support personnel; the 3D scoring engine can assess the task processing scores of support personnel; the greedy solution constructor can quickly generate feasible solutions; the quality valve can determine whether the personnel redistribution results meet the requirements. If the redistribution rate is not less than 95%, the redistribution results are directly output; if the redistribution rate is less than 95%, the CP-SAT precise optimization layer is triggered.

[0092] The CP-SAT precise optimization layer can include a model builder, a constraint injector, and a solver controller. The model builder can construct decision variables and inject hints; the constraint injector can construct hard constraints, soft constraints, and objective functions; the solver controller can run in parallel on multiple cores and has a hierarchical timeout protection mechanism and a fallback mechanism for no solution.

[0093] The state and verification layer can include a scheduler, a conflict verification module, and a result output and serialization module. The scheduler can be used for bidirectional mapping and atomic operations; the conflict verification module can perform local or global verification; and the result output and serialization module can be used to transform the final personnel redistribution results encapsulated in JSON format API responses and output them externally.

[0094] This application provides a method for scheduling airport support resources. When scheduling, this method identifies the affected objects of airport emergency support tasks and only reschedules the affected airport support tasks and personnel. This significantly reduces the amount of computational data, simplifies the scheduling logic, and effectively shortens the scheduling time, enabling rapid resource allocation in emergency support scenarios.

[0095] The above describes a method for scheduling airport support resources according to embodiments of this application. The following describes a system applying the above-described method for scheduling airport support resources, which may include:

[0096] The query unit is used to determine the first set of airport support tasks and the set of support personnel affected by the airport emergency support task when an airport emergency support task is detected.

[0097] The allocation unit is used to reallocate personnel between the airport emergency support task set and the primary airport support task set based on the support personnel set.

[0098] In one possible implementation, the allocation unit can also be specifically configured as follows:

[0099] The allocation of airport support tasks and personnel to unaffected airports will remain unchanged.

[0100] In one possible implementation, the query unit determines the first set of airport support tasks and the set of support personnel affected by the airport emergency support task, which can be specifically configured as follows:

[0101] Based on the execution time of the airport emergency support mission, determine the scope of impact of the airport emergency support mission, and obtain at least one airport support mission and at least one support personnel included in the scope of impact.

[0102] In one possible implementation, the query unit determines the scope of impact of the airport emergency support task based on the execution time of the task, which can be specifically configured as follows:

[0103] Based on the execution time of the airport emergency support mission, identify the target airport support mission that conflicts with the execution time of the airport emergency support mission; query the personnel assigned to the target airport support mission and the personnel associated with the personnel assigned to the personnel; determine the set of pending tasks for the personnel assigned to the mission and the set of pending tasks for the personnel associated with the mission; from at least one set of pending tasks, identify the airport support mission whose execution time is affected.

[0104] In one possible implementation, the allocation unit can be specifically configured as follows:

[0105] For the airport emergency support tasks and the airport support tasks in the first airport support task set, sort them according to execution time. For each sorted airport support task, filter the support personnel set based on task requirements and qualifications to obtain the candidate support personnel set for the airport support task. Calculate the task processing score for each candidate support personnel in the candidate support personnel set. Sort the candidate support personnel in descending order based on the task processing score and iterate through each candidate support personnel. Determine the candidate support personnel who meet the hard constraints as the support personnel to handle the airport support task. Output the personnel redistribution results for the airport emergency support tasks and the first airport support task set.

[0106] In one possible implementation, the allocation unit calculates the task processing score for each candidate support personnel in the candidate support personnel set, which can be specifically configured as follows:

[0107] The task processing score of the support personnel is calculated based on the distance between the support personnel and the location where the airport support task is performed, the qualifications of the support personnel, and the workload of the support personnel.

[0108] In one possible implementation, the airport support resource scheduling system may also include an optimization unit:

[0109] The optimization unit is used to calculate the task allocation rate after personnel reallocation. If the task allocation rate is lower than the preset threshold, the optimization algorithm is used for secondary allocation optimization.

[0110] In one possible implementation, the airport support resource scheduling system may also include a decision-making unit:

[0111] The decision unit is used to select the corresponding airport support resource scheduling mode based on the airport event type and time window. The airport support resource scheduling modes include: global initial scheduling, rolling pre-scheduling, and incremental dynamic rescheduling.

[0112] This application also provides an electronic device in its embodiments. (See reference...) Figure 4 The diagram illustrates a structural schematic of an electronic device suitable for implementing the airport support resource scheduling method in the embodiments of this application. The electronic device in the embodiments of this application may include, but is not limited to, fixed terminals such as mobile phones, laptops, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, etc. Figure 4 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0113] like Figure 4 As shown, the electronic device may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage device 408 into a random access memory (RAM) 403. When the electronic device is powered on, the RAM 403 also stores various programs and data required for the operation of the electronic device. The processing unit 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0114] Typically, the following devices can be connected to I / O interface 405: input devices 406 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 407 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 408 including, for example, memory cards, hard drives, etc.; and communication devices 409. Communication device 409 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 4 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have alternatively.

[0115] This application also provides a computer program product, including computer-readable instructions, which, when executed on an electronic device, cause the electronic device to implement any of the airport support resource scheduling methods provided in this application.

[0116] This application also provides a computer-readable storage medium carrying one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any of the airport support resource scheduling methods provided in this application.

[0117] It should also be noted that the system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. In addition, in the system embodiment drawings provided in this application, the connection relationship between modules indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines.

[0118] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware, or it can be implemented by special-purpose hardware including application-specific integrated circuits, special-purpose CPUs, special-purpose memory, special-purpose components, etc. Generally, any function performed by a computer program can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be diverse, such as analog circuits, digital circuits, or special-purpose circuits. However, for this application, software program implementation is more often the preferred implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium, such as a computer floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, training equipment, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0119] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0120] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, training device, or data center to another website, computer, training device, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

[0121] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0122] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0123] The above are merely embodiments of this application and are not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for scheduling airport support resources, characterized in that, The airport support resource scheduling method includes: When an airport emergency support mission is detected, determine the first set of airport support missions and the set of support personnel affected by the airport emergency support mission. Based on the aforementioned support personnel set, personnel are redistributed between the airport emergency support task set and the first airport support task set.

2. The airport support resource scheduling method according to claim 1, characterized in that, Also includes: The allocation of airport support tasks and personnel to unaffected airports will remain unchanged.

3. The airport support resource scheduling method according to claim 1, characterized in that, The determination of the first airport support task set and support personnel set affected by the airport emergency support task includes: Based on the execution time of the airport emergency support mission, determine the scope of impact of the airport emergency support mission, and obtain at least one airport support mission and at least one support personnel included in the scope of impact.

4. The airport support resource scheduling method according to claim 3, characterized in that, Determining the scope of impact of the airport emergency support mission based on its execution time includes: Based on the execution time of the airport emergency support mission, identify the target airport support mission that conflicts with the execution time of the airport emergency support mission; Query the personnel assigned to the target airport support task and the personnel associated with those assigned; Determine the set of tasks to be processed for the assigned personnel and the set of tasks to be processed for the associated personnel; Identify airport support tasks whose execution time is affected from at least one set of pending tasks.

5. The airport support resource scheduling method according to claim 1, characterized in that, The process of reallocating personnel between the airport emergency support task set and the first airport support task set based on the support personnel set includes: The airport emergency support tasks and the airport support tasks in the first airport support task set are ordered according to their execution time. For each airport support task after sorting, a set of support personnel is selected based on the qualifications required for the task, and a set of candidate support personnel for the airport support task is obtained. The task processing score of each candidate support personnel in the set of candidate support personnel is calculated. The candidate support personnel are sorted in descending order based on the task processing score and each candidate support personnel is traversed. The candidate support personnel who meet the hard constraints are determined as the support personnel to handle the airport support task. Output the personnel redistribution results for the airport emergency support task and the first airport support task set.

6. The airport support resource scheduling method according to claim 5, characterized in that, The calculation of the task processing score for each candidate support personnel in the candidate support personnel set includes: The task processing score of the support personnel is calculated based on the distance between the support personnel and the task execution location of the airport support mission, the qualifications of the support personnel, and the workload of the support personnel.

7. The method for scheduling airport support resources according to claim 1 or 5, characterized in that, Also includes: The task allocation rate after personnel reallocation is calculated. If the task allocation rate is lower than a preset threshold, an optimization algorithm is used for secondary allocation optimization.

8. The airport support resource scheduling method according to claim 1, characterized in that, Also includes: Based on the airport event type and time window, select the corresponding airport support resource scheduling mode, which includes: global initial scheduling, rolling pre-scheduling, and incremental dynamic rescheduling.

9. A scheduling system for airport support resources, characterized in that, The airport support resource dispatching system includes: The query unit is used to determine the first set of airport support tasks and the set of support personnel affected by the airport emergency support task when an airport emergency support task is detected. The allocation unit is used to reallocate personnel to the airport emergency support task and the first airport support task set based on the support personnel set.

10. A computer program product, characterized in that, It includes computer-readable instructions that, when executed on an electronic device, cause the electronic device to implement the airport support resource scheduling method as described in any one of claims 1 to 8.

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