Distributed platform fleet flight and maintenance integrated scheduling method and device

Abstract

The present application relates to a method and device for integrated scheduling of flight and maintenance of distributed platform fleets. The method includes obtaining the current mission flight plan parameters and maintenance task parameters; calling the constructed DP‑ASRS dynamic model; optimizing and solving the DP‑ASRS dynamic model according to the mission flight plan parameters and maintenance task parameters, and outputting the current integrated scheduling plan; and using the integrated scheduling plan to perform integrated scheduling of flight and maintenance of distributed platform fleets. Among them, the objective function of the DP‑ASRS dynamic model includes: the distributed platform mission comprehensive effectiveness optimization objective function and the single platform effectiveness optimization objective function, and the constraints of the DP‑ASRS dynamic model include distributed platform carrier-based aircraft fleet allocation constraints, flight timing planning constraints, maintenance scheduling constraints, and distributed maintenance task platform transfer constraints. The purpose of effectively realizing the integrated scheduling of flight and maintenance of distributed platform fleets is achieved.

Description

Technical Field

[0001] The present application relates to the technical field of platform fleet scheduling, and in particular to a method and device for integrated flight and maintenance scheduling of a distributed platform fleet. Background Art

[0002] Carrier-based aircraft are the main combat units participating in the combat and training missions of offshore platforms. The dispatching and maintenance capabilities of carrier-based aircraft affect the performance of the platform's combat effectiveness. The dispatching flight plan of carrier-based aircraft must meet the mission requirements of large-scale, high-intensity and continuous combat, and is highly coupled with the maintenance plan. The offshore platform hangar where the maintenance mission is located has the characteristics of small space, complex environment, high degree of coordination of maintenance personnel, limited staffing of maintenance personnel, and complex maintenance process flow, which makes scheduling and planning difficult. At the same time, compared with the scheduling and planning of a single platform, the number of decision-making aircraft groups on distributed platforms is large and the status is complex. In recent years, many achievements have emerged in the phased operation scheduling of carrier-based aircraft, including several operation stages such as deployment and transportation, ammunition support, maintenance and service support, dispatching and departure, landing and recovery, and maintenance and repair.

[0003] The scheduling of carrier-based aircraft operations is based on flight plans. In traditional sortie missions, the commander first formulates a sortie flight plan through experience, and then optimizes and schedules the subsequent phased operation processes in sequence. The formulation of a sortie flight plan can directly affect the optimization effect of subsequent operation scheduling. However, most of the existing research is based on a given mission plan for optimization design, and the flight plan for carrier-based aircraft is usually a known condition, and there is no relevant research at present. However, in the process of realizing the present invention, the inventor found that with the increase in mission complexity and the development trend of distributed operations, it is no longer possible to effectively realize the integrated scheduling of flight and maintenance of distributed platform fleets by manual experience alone. Summary of the invention

[0004] Based on this, it is necessary to provide a distributed platform fleet flight and maintenance integrated scheduling method and a distributed platform fleet flight and maintenance integrated scheduling device to address the above-mentioned technical problems, which can effectively realize the distributed platform fleet flight and maintenance integrated scheduling.

[0005] In order to achieve the above objectives, the embodiments of the present invention adopt the following technical solutions:

[0006] On the one hand, an embodiment of the present invention provides a distributed platform fleet flight and maintenance integrated scheduling method, comprising the steps of:

[0007] Obtain the current mission flight plan parameters and maintenance mission parameters; the mission flight plan parameters include the number of mission waves, the number of distributed platforms, the number of carrier-based aircraft on the platform, the number of continuous rotation waves of cyclic operations, the number of wave formations for cyclic sorties, the number of carrier-based aircraft required for a single wave, the flight cycle duration, the deck operation cycle duration, the single-wave deck service support duration, the platform impact weight, and the performance evaluation index impact weight; the maintenance mission parameters include the number of maintenance skills, the number of platform maintenance personnel, and the maintenance mode;

[0008] The constructed DP-ASRS dynamic model is called; the objective functions of the DP-ASRS dynamic model include: the distributed platform task comprehensive effectiveness optimization objective function and the single platform effectiveness optimization objective function; the constraints of the DP-ASRS dynamic model include the distributed platform carrier-based aircraft fleet allocation constraints, flight timing planning constraints, maintenance scheduling constraints and distributed maintenance task platform transfer constraints;

[0009] Optimize and solve the DP-ASRS dynamic model according to the mission flight plan parameters and maintenance mission parameters, and output the current integrated scheduling plan;

[0010] An integrated scheduling solution is used to carry out integrated scheduling of flight and maintenance of distributed platform fleets.

[0011] On the other hand, a distributed platform fleet flight and maintenance integrated scheduling device is also provided, including:

[0012] The data acquisition module is used to obtain the current mission flight plan parameters and maintenance mission parameters; the mission flight plan parameters include the number of mission waves, the number of distributed platforms, the number of carrier-based aircraft on the platform, the number of continuous rotation waves of cyclic operations, the number of wave formations for cyclic sorties, the number of carrier-based aircraft required for a single wave, the flight cycle duration, the deck operation cycle duration, the single-wave deck service support duration, the platform impact weight and the efficiency evaluation index impact weight; the maintenance mission parameters include the number of maintenance skills, the number of platform maintenance personnel and the maintenance mode;

[0013] The model calling module is used to call the constructed DP-ASRS dynamic model; the objective functions of the DP-ASRS dynamic model include: the distributed platform task comprehensive effectiveness optimization objective function and the single platform effectiveness optimization objective function; the constraints of the DP-ASRS dynamic model include the distributed platform carrier-based aircraft fleet allocation constraints, flight timing planning constraints, maintenance scheduling constraints and distributed maintenance task platform transfer constraints;

[0014] The optimization output module is used to optimize and solve the DP-ASRS dynamic model according to the mission flight plan parameters and maintenance mission parameters, and output the current integrated scheduling plan;

[0015] The scheduling execution module is used to utilize the integrated scheduling solution to perform integrated scheduling of flight and maintenance of distributed platform fleets.

[0016] One of the above technical solutions has the following advantages and beneficial effects:

[0017] The above-mentioned distributed platform fleet flight and maintenance integrated scheduling method and device, through the currently required distributed platform fleet flight and maintenance integrated scheduling, first obtains the current mission flight plan parameters and maintenance task parameters, and then calls the DP-ASRS dynamic model constructed for the distributed platform, and uses the acquired known parameter data to optimize and solve the DP-ASRS dynamic model, outputs the distributed platform task comprehensive efficiency optimization objective function and the single platform efficiency optimization objective function to maximize the optimal scheduling plan that meets the constraints of the model, that is, the current integrated scheduling plan is obtained, and finally the integrated scheduling plan is used to carry out the distributed platform fleet flight and maintenance integrated scheduling, thereby achieving the purpose of effectively realizing the distributed platform fleet flight and maintenance integrated scheduling, and has strong real-time and applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for describing the embodiments will be briefly introduced below. 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.

[0019] Figure 1 This is a schematic diagram of double-shift continuous dispatch;

[0020] Figure 2 A schematic diagram of the platform's flight plan;

[0021] Figure 3 This is a schematic diagram of the carrier-based aircraft maintenance plan;

[0022] Figure 4 A schematic diagram of reactive rescheduling in one embodiment;

[0023] Figure 5 A schematic diagram of a flow chart of a method for integrated flight and maintenance scheduling of a distributed platform fleet in one embodiment;

[0024] Figure 6 A flowchart of a single machine maintenance network in an embodiment;

[0025] Figure 7 Schematic diagram of initial value settings of accumulated flight time for three groups of cases in one embodiment, (a) is the distribution of initial values ​​of accumulated flight time, (b) is the distribution of available time before the next scheduled maintenance;

[0026] Figure 8 This is a Gantt chart of the dual-layer optimization scheduling of platform 3 in case 2 in an embodiment, (a) is the Gantt chart of the wave dispatch flight sequence, and (b) is the Gantt chart of the maintenance plan;

[0027] Fig. 9 Schematic diagram of the allocation result of the platform 3 fleet in one embodiment, (a) is the cumulative flight time allocation result, (b) is the available time distribution allocation result before the next scheduled maintenance;

[0028] Fig.10 This is a baseline scheduling Gantt chart of platform 2 in case 2 in an embodiment, (a) is a wave dispatch flight sequence Gantt chart, and (b) is a maintenance plan Gantt chart;

[0029] Fig.11 This is a Gantt chart of independent maintenance reactive scheduling of platform 2 in case 2 in an embodiment, (a) is a Gantt chart of wave dispatch flight sequence, and (b) is a Gantt chart of maintenance plan;

[0030] Fig.12 This is a Gantt chart of cross-platform maintenance linkage reactive scheduling for Case 2 Platform 2 in an embodiment, (a) is a Gantt chart of wave dispatch flight sequence, and (b) is a Gantt chart of maintenance plan;

[0031] Fig.13 Schematic diagram of the module structure of a distributed platform fleet flight and maintenance integrated scheduling device in one embodiment. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0033] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by those skilled in the art to which the present application belongs. The terms used herein in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0034] In addition, the technical solutions between the various embodiments of the present invention can be combined with each other, but it must be based on the fact that ordinary technicians in the field can implement it. When the combination of technical solutions is mutually contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0035] Compared with the scheduling and planning of a single platform, the number of distributed platform decision-making clusters is large and the status is complex. The scale and mode of deployment between platforms vary greatly, and the dynamic characteristics are strong. These have brought challenges to the integrated scheduling of distributed cluster wave dispatch and maintenance. Experience-based manual scheduling has been difficult to meet the requirements of reliability and timeliness. How to allocate platforms and plan the dispatch sequence of participating units under the concept of distributed maritime operations, integrate maintenance resources between platforms to disperse maintenance pressure, improve the availability and combat effectiveness of participating units, and achieve coordinated, efficient and orderly dispatch and maintenance of multiple platforms is the core issue that restricts the comprehensive effectiveness of distributed maritime operations. It is also a key technology that urgently needs to be solved in distributed decision-making command and maintenance support, and it is of great significance to the evolution of the battle situation.

[0036] In practice, the inventors found that the current theoretical research on the combination of wave-based flight sequence planning and maintenance scheduling is still in its infancy, and there are many research results in the related civil aviation field that can be used for reference. The research on problems in this field mainly revolves around two types of problems: aircraft task assignment (Tail Assignment Problem, TAP) and aircraft maintenance planning (Aircraft Maintenance Planning, AMP). Existing studies mostly solve flight planning and maintenance scheduling problems in a staged manner, and this stage-solving method can lead to an overall suboptimal solution. Some literature also points out that existing strategies and practices lack the integration of TAP and AMP problems, and there is an urgent need to unify the two within the same framework for interaction. This problem also exists in the existing carrier-based aircraft operation process. To solve such problems, some literature has proposed a new decision support system for optimizing task allocation and aircraft maintenance inspection plans to optimize aircraft maintenance task allocation. There are also literatures that propose a two-layer optimization model for aircraft planning and maintenance personnel configuration, and use a two-layer nested ant colony optimization algorithm to solve it. Lin et al. proposed a solution algorithm inspired by the yeast reproduction process, with the goal of minimizing the maintenance completion time and balancing the number of hangar resources and the maintenance cost of the fleet, and established a two-layer model based on fleet maintenance.

[0037] However, relevant research on flight sequence planning and maintenance scheduling is still in the independent development stage. It is also worth noting that compared with civil aviation, carrier-based aircraft operate in a cluster wave deployment and recovery pattern, with shorter maintenance cycles and higher frequencies, maintenance resources are highly limited and the constraints are more complex, and the optimization goal is to focus on the combat effectiveness of the fleet.

[0038] Theoretical research on the scheduling of carrier-based aircraft sortie and recovery operations is currently divided into two levels: full-process scheduling of carrier-based aircraft operations and phased scheduling. For the full-process scheduling of carrier-based aircraft operations, Ryan et al. developed an aircraft carrier deck operation decision system based on the concept of human-computer interaction, and designed a set of comparative experiments between automatic planning algorithms and manual experience decisions. On this basis, Michini et al. proposed a reverse reinforcement learning method to learn and imitate expert behavior and improve the scheduling strategy. The real-time information management integrated system also includes achievements such as Aviation Data Management and Control System (ADMACS).

[0039] Regarding the theoretical research on carrier-based aircraft maintenance scheduling, some literature has elaborated on the maintenance process of military aircraft and the constraints of maintenance personnel, and proposed a linear mixed integer programming maintenance model. There are also literatures that have established a simplified personnel allocation model for carrier-based aircraft maintenance and support and calculated the model based on the queuing theory method. Feng et al. proposed a multi-agent-based fleet maintenance personnel intelligent configuration method, which can also provide the optimal maintenance strategy compared with other traditional methods that only provide configuration results. Furthermore, Feng et al. proposed a heuristic hybrid game method to solve the fleet status maintenance problem, and the hierarchical solution framework based on the dispatch and standby fleet set significantly reduced the scale of the problem. Others have proposed a comprehensive availability constraint model that considers regular planning and random support time, and used a heuristic solution algorithm to generate a carrier-based aircraft support operation scheduling plan and equipment planned maintenance time schedule. In addition, some literature uses the carrier-based aircraft fleet wave availability and the load balance of maintenance personnel in the hangar as optimization indicators, combines the constraint characteristics of maintenance operations to propose a resource-constrained maintenance task scheduling model, and uses a heuristic algorithm to solve and calculate. The above research results are constantly deepening the research on the field of single-platform carrier-based aircraft maintenance. The complexity of the model is constantly increasing, the model abstraction method is changing from a mathematical programming model to a resource-constrained project scheduling model, and the solution algorithm is gradually changing from an optimization method to a heuristic algorithm. However, the current research level is still at the static maintenance scheduling planning of a single platform. It is urgent to strengthen the research on the dynamics and scalability of this field and realize the dynamic maintenance interaction of distributed platforms to adapt to the trend of future distributed maritime operations.

[0040] In view of the theoretical research on dynamic scheduling, Ouelhadj et al. reviewed the dynamic scheduling problem of manufacturing systems, divided dynamic scheduling into fully reactive scheduling, baseline-reactive scheduling and robust scheduling, considered the optimization goal of scheduling, faced with complex and changeable uncertain scheduling environment, implemented scheduling correction according to specific disturbance factors, and adopted reactive scheduling instead of proactive scheduling method, which is more practical. The uncertain interference events involved in reactive scheduling theory and methods include queue jumping of temporary tasks, delay of some processes and equipment failure and other uncertain factors. An et al. designed two fully rescheduling reactive scheduling strategies to respond to dynamic events. The current methods involved in the field of carrier-based aircraft dynamic scheduling mainly include multi-agent method, proactive robust scheduling method, rolling time domain reactive scheduling method, fully reactive scheduling method based on heuristic rules, reinforcement learning real-time scheduling method, etc.

[0041] In summary, although the existing research has achieved some results, there are still three deficiencies: on the one hand, most of the current research formulates the flight plan through artificial experience, and regards the plan as a known condition as input, and has not yet realized the integrated planning and scheduling decision of the flight plan and the maintenance task; on the other hand, the current theoretical research on the scheduling of carrier-based aircraft sortie recovery operations focuses on the single-platform core ships under the traditional centralized combat mode, and has not yet considered the platform linkage of the distributed platform fleet allocation and the allocation and transfer of the maintenance task of the faulty carrier-based aircraft; on the other hand, the current research only considers static maintenance with a known maintenance plan, and has not yet considered the dynamic correction and adjustment of the maintenance plan under the conditions of urgent demand for the number of available carrier-based aircraft, continuous addition of faulty carrier-based aircraft, concentrated hangar maintenance load, and interference with the rhythm of the maintenance scheduling process.

[0042] In view of the above-mentioned technical problem of how to effectively realize the integrated scheduling of flight and maintenance of distributed platform fleets, this application takes the flight plan and maintenance scheduling of wave sorties of distributed platform fleets at sea as the research object, systematically analyzes the flight timing planning, cyclic sortie operation rules and maintenance constraint characteristics of carrier-based aircraft, and introduces a cross-platform maintenance linkage mechanism based on the heuristic rules of distributed maintenance task allocation based on the traditional single-platform independent maintenance form. The distributed platform fleet sortie and repair integrated scheduling (Aircraft fleet Sortie and Repair Integrated Scheduling of Distributed Platforms, DP-ASRS) optimization model is established. Aiming at indicators such as the comprehensive effectiveness of distributed platform tasks, single platform effectiveness, task wave completion rate, maintenance load dispersion and wave rotation continuity, the scientific allocation of carrier-based aircraft fleets, maintenance timing and maintenance tasks is realized, and the evaluation indicators such as the task wave completion rate and maintenance load dispersion are effectively improved, and the comprehensive effectiveness of combat and training tasks is further improved. Provide a reliable and realistic basis for the integrated planning and scheduling decision-making of flight plans and maintenance tasks for future distributed maritime combat carrier-based aircraft fleets.

[0043] The following will describe the implementation of the present invention in detail with reference to the accompanying drawings in the embodiments of the present invention.

[0044] Cyclic sortie operation: The sortie and recovery operation style of carrier-based aircraft can be divided into two modes: wave operation and continuous operation. The wave operation mode is to dispatch and recover waves according to the flight cycle (take-off-landing), and there is a preparation cycle between adjacent flight cycles. The flight cycle of the continuous operation mode is continuous, and adjacent flight cycles are staggered and overlapped. The most commonly used form for the continuous operation mode is the single-cycle double-wave cyclic formation, that is, "double-shift cyclic continuous sortie". With one flight cycle as the cycle unit, two formations are selected from the available carrier-based aircraft on the platform, and they are alternately dispatched and recovered in the order of waves, and the cycle is carried out (such as the first wave, the third wave, the fifth wave... The first formation of carrier-based aircraft group is dispatched, the second wave, the fourth wave, the sixth wave... The second formation of carrier-based aircraft group is dispatched), until the set number of continuous rotation waves is reached, the two formations are released, and two formations are selected again to continue the cycle to achieve continuous operation. The whole process has the characteristics of cyclic cycle and rhythmic law. The alternating cycle operation pattern can be flexibly formulated according to the deck operation cycle, the number of continuous rotation waves, the number of carrier-based aircraft in a single wave, the total number of waves, etc. Figure 1 shown.

[0045] Service support refers to a series of activities such as taxiing to the support parking position after the carrier-based aircraft completes its mission and lands, recharging "oil, liquid, gas and electricity", and adding weapons and ammunition, etc., in order to prepare for the next mission of the carrier-based aircraft and provide necessary guarantees for aviation operation safety and normal operation of the system. Service support preparation before flight needs to be carried out within a deck operation cycle, and the duration of a deck cycle is usually limited to a specified time, such as 1+30 (1 hour and 30 minutes) and 2+00, etc.

[0046] Flight schedule: The flight schedule of the fleet is to determine the status of each carrier-based aircraft through the ADMACS system under the task requirements determined by the basic operation cycle, the operation mode of the deployment and the single wave flight duration. At the beginning of each wave, the number of carrier-based aircraft required for the wave mission is selected from the available fleet, and the following is formulated: Figure 2 The platform dispatch flight plan shown in the figure. It can be seen that the flight plan diagram not only includes the timing planning such as the number of carrier-based aircraft performing flight missions, but also includes information such as service support, maintenance mode, and maintenance start and end time. The maintenance-related information reflects the actual maintenance time required, which is related to the process scheduling results of the maintenance tasks in the hangar, and is the difficulty in flight plan formulation.

[0047] On the one hand, the selection of the fleet for each wave of missions in the flight plan affects the timing of each carrier-based aircraft entering maintenance; on the other hand, entering the maintenance sequence under the condition of an uncertain number of maintenance tasks being carried out in the hangar will affect the maintenance scheduling plan (baseline scheduling plan) currently being executed, requiring reactive rescheduling of the baseline scheduling plan (such as Figure 2 At the same time, the subsequent time may still cause new carrier-based aircraft to enter the maintenance state due to the flight plan, causing the baseline scheduling plan to be adjusted again. Therefore, affected by the dynamic characteristics, the maintenance time of each aircraft is uncertain and difficult to predict in advance. It is necessary to conduct actual maintenance dynamic scheduling according to the specific situation to obtain the final scheduling plan, and feedback to the ADMACS system for the update of the available fleet set, which in turn affects the selection of the flight plan wave mission fleet. It can be seen that the wave-based flight sequence planning and maintenance scheduling are intertwined and coupled, and integrated scheduling optimization is required.

[0048] Carrier-based aircraft inspection and repair: The offshore platform hangar is responsible for the maintenance and repair of carrier-based aircraft. Maintenance refers to the regular preventive maintenance of carrier-based aircraft, which usually includes periodic inspections of 25 flight hours, 50 flight hours, 100 flight hours, 7 days, 3 months and 6 months. Maintenance is a corrective fault repair work, which refers to repairing faults and damage within a certain limit to restore its original function and availability. Carry out regular maintenance of carrier-based aircraft, troubleshooting and repair of airborne equipment, repair of airframe structure damage and aircraft engine repair to maintain or restore the good technical condition of carrier-based aircraft during their stay on board, maintain a high level of integrity of the fleet, and prepare for wave-based combat training tasks (maintenance and repair are collectively referred to as "inspection" in this article).

[0049] For the maintenance process of carrier-based aircraft: The maintenance tasks of carrier-based aircraft have simple serial relationships among the processes, which are divided into three processes: fault location, fault repair, and re-inspection. For the maintenance tasks of carrier-based aircraft, the processes are networked in sequence, and the immediate predecessor of any process may not be unique. The activity on node (AoN) is used to represent the networked relationship between the processes.

[0050] The maintenance scheduling of carrier-based aircraft is to plan the time sequence of the process and assign maintenance personnel or equipment and other resources. The offshore platform hangar usually sets up maintenance personnel according to professional categories. The maintenance process corresponds to a specific profession, and the personnel are divided into categories according to the profession they master. After the carrier-based aircraft to be repaired enters the hangar maintenance task sequence, a time sequence scheduling plan for the process and personnel that meets the model constraints is planned to generate the following: Figure 3 The schematic diagram of the aircraft carrier maintenance plan shown in the figure also needs to consider the reactive rescheduling mentioned in the previous section (respectively as Figure 2 , Figure 3 and Figure 4 (as shown at time t3 in the figure): based on the baseline scheduling plan before adding the task sequence, the process sets that have been completed, are in progress, and have not yet started scheduling are screened out, the occupied resource status is initialized, the baseline scheduling plan for the completed and in progress scheduling process sets is kept unchanged, and the process sets that have not yet started scheduling (including the newly added maintenance task process) are rescheduled according to the "first come, first served" rule under resource constraints.

[0051] Allocation and maintenance linkage mechanism: The DP-ASRS problem involves two aspects of allocation: one is the allocation of the platform for the fleet; the other is the allocation of cross-platform carrier-based aircraft maintenance tasks during the mission. The allocation of the platform for the fleet refers to the assignment of the carrier-based aircraft to the platform one by one based on the cumulative flight time of the carrier-based aircraft, under the condition that the number of carrier-based aircraft carried by the distributed platform is constrained. The accumulated flight time is the flight status attribute of the carrier-based aircraft. When the flight time of the carrier-based aircraft reaches a certain time, the carrier-based aircraft needs to be transferred to the platform hangar for regular maintenance. The accumulated flight time of the carrier-based aircraft directly affects the timing of the aircraft entering regular maintenance, and indirectly affects the available status during the subsequent mission sortie, that is, it affects the formulation of the wave sortie flight plan. Allocation is the basic premise for formulating the flight plan. The results of the fleet allocation will directly affect the effect of the subsequent wave sortie timing planning stage, and even affect the completion of the combat training mission.

[0052] Random failures or combat damages that occur during the mission of carrier-based aircraft will be transferred to the platform hangar for maintenance after the recovery phase. When the battle is fierce, the concentration of a large number of failed carrier-based aircraft will cause a backlog of maintenance tasks, which will lead to a decrease in the availability of the fleet for a period of time, and the recovery is slow, which will seriously affect the generation of subsequent combat effectiveness. In order to avoid the concentration of maintenance tasks in a single platform hangar, under the concept of distributed maritime operations, a cross-platform maintenance linkage mechanism based on distributed maintenance task allocation heuristic rules is proposed: relying on the powerful heterogeneous network convergence communication of the distributed system to achieve accurate and real-time data sharing of distributed platforms, and realize "ship-aircraft-ship maintenance linkage". Carrier-based aircraft that fail or are damaged during the flight mission receive load status data from the mother ship and other platform hangars before entering the wave recovery phase, and make a comprehensive judgment on the recovery platform according to the distributed maintenance task allocation heuristic rules. When the maintenance task is judged to be transferred to other platforms for maintenance, the faulty carrier-based aircraft will be added to the target platform recovery formation during the recovery phase for cross-platform recovery, thereby achieving the dispersion of platform maintenance load pressure. At the same time, a corresponding number of carrier-based aircraft are selected from the target platform recovery formation and transferred to the faulty aircraft carrier platform for recovery, so that the loss difference of the mother ship can be supplemented.

[0053] See also Figure 5 In one embodiment, the present invention provides a distributed platform fleet flight and maintenance integrated scheduling method, comprising the following steps S12 to S18:

[0054] S12, obtaining the current mission flight plan parameters and maintenance mission parameters; the mission flight plan parameters include the number of mission waves, the number of distributed platforms, the number of carrier-based aircraft on board the platform, the number of continuous rotation waves of cyclic operations, the number of wave formations for cyclic sorties, the number of carrier-based aircraft required for a single wave, the flight cycle duration, the deck operation cycle duration, the single-wave deck service support duration, the platform impact weight, and the performance evaluation index impact weight; the maintenance mission parameters include the number of maintenance skills, the number of platform maintenance personnel, and the maintenance mode.

[0055] It can be understood that for a given distributed platform in the current actual application scenario (which may include multiple carrier-based aircraft platforms at sea), its mission flight plan parameters and maintenance mission parameters are mission-determined or known data, which can be directly input or directly obtained from the aviation data management and control system ADMACS.

[0056] S14, calling the constructed DP-ASRS dynamic model; the objective functions of the DP-ASRS dynamic model include: distributed platform task comprehensive effectiveness optimization objective function and single platform effectiveness optimization objective function, and the constraints of the DP-ASRS dynamic model include distributed platform carrier-based aircraft fleet allocation constraints, flight timing planning constraints, maintenance scheduling constraints and distributed maintenance task platform transfer constraints.

[0057] It can be understood that the DP-ASRS dynamic model is a model specially constructed for the integrated dispatching and maintenance scheduling requirements of distributed platforms. It is composed of the distributed platform task comprehensive efficiency optimization objective function, the single platform efficiency optimization objective function, and the determined constraints. The DP-ASRS dynamic model can be pre-installed in the data system used for command and dispatch so that it can be quickly called in actual application.

[0058] S16, optimizing and solving the DP-ASRS dynamic model according to the mission flight plan parameters and the maintenance mission parameters, and outputting the current integrated scheduling plan.

[0059] It can be understood that the DP-ASRS dynamic model is optimized and solved according to the mission flight plan parameters and the maintenance task parameters, that is, using the currently obtained mission flight plan parameters and the maintenance task parameters, under the constraints of the model, the distributed platform mission comprehensive efficiency optimization objective function and the single platform efficiency optimization objective function are maximized and calculated and solved to obtain the optimal scheduling plan. The optimal scheduling plan is the current integrated scheduling plan, under which the distributed platform mission comprehensive efficiency is maximized and the single platform efficiency is maximized, and the distributed platform fleet wave dispatch planning and maintenance scheduling plan are correspondingly given. The specific calculation method for optimizing and solving the DP-ASRS dynamic model can be implemented using various optimization algorithms already available in the art, and is not limited in this specification, as long as the above-mentioned integrated scheduling plan can be calculated and solved.

[0060] S18, use the integrated scheduling solution to carry out integrated scheduling of flight and maintenance of distributed platform fleets.

[0061] It can be understood that after using the current mission flight plan parameters and maintenance mission parameters and calling the DP-ASRS dynamic model to quickly output the current integrated scheduling plan, the commander can use the integrated scheduling plan through the system used to carry out command and dispatch to perform integrated scheduling of distributed platform fleet flight and maintenance for the current distributed platform, so as to maximize the comprehensive effectiveness of combat and training tasks based on distributed platforms.

[0062] The above-mentioned distributed platform fleet flight and maintenance integrated scheduling method, for the currently required distributed platform fleet flight and maintenance integrated scheduling, first obtains the current mission flight plan parameters and maintenance mission parameters, then calls the constructed DP-ASRS dynamic model, and uses the acquired known parameter data to optimize and solve the DP-ASRS dynamic model, outputs the distributed platform task comprehensive efficiency optimization objective function and the single platform efficiency optimization objective function to maximize the optimal scheduling plan that meets the constraints of the model, that is, the current integrated scheduling plan is obtained, and finally the integrated scheduling plan is used to carry out the distributed platform fleet flight and maintenance integrated scheduling, thereby achieving the purpose of effectively realizing the distributed platform fleet flight and maintenance integrated scheduling, and has strong real-time and applicability.

[0063] In one embodiment, the construction process of the DP-ASRS dynamic model may be as follows:

[0064] Before the model is established, reasonable assumptions are made based on the objective conditions of the distributed platform: 1) The wave dispatch mission plan is known; 2) The cost of transferring maintenance tasks across platforms is not considered; 3) The task allocation transfer time within the hangar and between platforms is ignored; 4) The maintenance process cannot be interrupted after it starts; 5) The platform can perform maintenance and repair on all types of carrier-based aircraft.

[0065] Regarding the definition of model parameters and variables, specifically, the parameter definition of the distributed platform fleet wave dispatch and periodic maintenance integrated static scheduling model is as follows:

[0066] I: The set of carrier-based aircraft to be allocated, I = {1, 2, ..., Ni}, where Ni is the number of carrier-based aircraft to be allocated. p : The set of carrier-based aircraft carried by the pth platform, I = {1, 2, ..., Ni p},Ni p is the number of carrier-based aircraft carried by the pth platform. P: the set of the number of carrier-based aircraft carrying platforms, P = {1, 2, ..., Np}, Np is the number of carrier-based aircraft carrying platforms. W p : The p-th platform mission dispatch wave set, Wp ={1,2,…,Nw p},Nw p represents the number of mission sorties of the p-th platform. n: the number of times the i-th carrier-based aircraft on the p-th platform is repaired, Indicates the number of times the i-th carrier-based aircraft on the p-th platform is repaired. The available time for the i-th carrier-based aircraft on the p-th platform before performing the n-th scheduled maintenance. The theoretical maintenance time between the i-th carrier-based aircraft on the p-th platform and the n-th scheduled maintenance. Tl: Maintenance timing offset time, allowing flexible entry into maintenance status within the Tl interval before and after the maintenance flight hour. Tw p : The duration of the pth platform flight cycle. Td p : The duration of the pth platform deck operation cycle. p : The duration of deck service support for a single wave of the pth platform. Nc p Ng: The number of continuous rotation waves of the p-th platform cycle operation. p Nd: The number of sub-wave groups dispatched by the p-th platform cycle. p : The number of carrier-based aircraft required for the single-wave flight mission of the p-th platform. Rt p : The p-th platform carrier-based aircraft assembles for maintenance. The set of available carrier-based aircraft at the pth platform at time t, is the number of available carrier-based aircraft on the p-th platform at time t. The carrier-based aircraft waiting for maintenance gather at the p-th platform at time t. The aircraft carriers waiting for repair gather at the pth platform at time t. is the number of carrier-based aircraft waiting for maintenance on the p-th platform at time t. The number of carrier-based aircraft to be repaired after the maintenance tasks are assigned to the p-th platform at time t. The p-th platform has a collection of carrier-based aircraft waiting for maintenance at time t. The i-th carrier-based aircraft on the p-th platform is about to perform the n-th maintenance process set, J: The total maintenance process set of the fleet, The set of all maintenance procedures that are in execution state at time t for the p-th platform cluster. The set of maintenance procedures that are in execution at time t for the i-th carrier-based aircraft on the p-th platform. The maximum completion time required to complete the nth maintenance process of the i-th carrier-based aircraft on the p-th platform. The set of immediate predecessor processes of the jth maintenance process (i, j) of the nth maintenance of the i-th carrier-based aircraft on the p-th platform. ij: The maintenance work hours of the jth maintenance process (i, j) of the i-th carrier-based aircraft on the p-th platform. BM: A sufficiently large positive number. Kc: The maintenance skill set, Kc = {1, 2, ..., |Kc|}. The p-th platform is a collection of maintenance support personnel with the k-th type of maintenance skills. The demand for the kth (k∈Kc)th type of maintenance skill during the jth maintenance process (i, j) of the i-th carrier-based aircraft on the p-th platform during the n-th maintenance.

[0067] The static decision variables are defined as follows:

[0068] The start time of the jth maintenance process (i, j) for the nth maintenance of the i-th carrier-based aircraft on the p-th platform.

[0069] The time when the support ends for the jth maintenance procedure (i, j) of the nth maintenance of the i-th carrier-based aircraft on the p-th platform.

[0070]

[0071]

[0072]

[0073]

[0074]

[0075] In one embodiment, the distributed platform task comprehensive performance optimization objective function is maxF:

[0076]

[0077] Among them, f p represents the performance evaluation value of platform p, v p It represents the influence weight of each platform. The commander can set the weight according to the mission and platform. P represents the number of distributed platforms.

[0078] It can be understood that in the distributed combat training mission at sea, multiple platforms jointly form a combat system, and each platform cooperates with each other, has its own division of labor, and completes the task together. With the performance of each single platform as the support, the comprehensive performance optimization target F of the integrated scheduling of the distributed platform fleet wave dispatch and maintenance is constructed as shown in the previous formula (1).

[0079] In one embodiment, the single platform performance optimization objective function is max f p :

[0080]

[0081] Among them, f p represents the performance evaluation value of platform p, γ1, γ2 and γ3 represent the influence weights of the performance indicators at three levels, P represents the number of distributed platforms, WR represents the task wave completion rate, MR represents the maintenance load dispersion, and CR represents the wave rotation continuity.

[0082] It can be understood that the single-platform performance optimization target is defined as shown in the above formula (2), which is reflected in three aspects: task wave completion rate, maintenance load dispersion, and wave rotation continuity.

[0083] Furthermore, the task wave completion rate is:

[0084]

[0085] in, is a task-complete wave variable if and only if hour, Indicates that the wth wave is the task-completed wave; otherwise Indicates that the wth wave is a missing wave, I p represents the set of carrier-based aircraft carried by the pth platform, Nd represents the number of carrier-based aircraft required for a single wave flight mission of the platform, and W p represents the set of waves of missions dispatched by the pth platform, Nw p Indicates the number of mission waves dispatched for the p-th platform.

[0086] Specifically, as the flight mission is executed, the available carrier aircraft on the platform will successively reach the scheduled maintenance time or fail, resulting in the number of available carrier aircraft failing to meet the number requirement of a single wave of carrier aircraft. This wave is called a shortfall wave. The proportion of the number of complete waves has a significant impact on the completion of combat and training missions. The evaluation index of the mission wave completion rate is defined as shown in the above formula (3). The greater the mission wave completion rate, the better the optimization effect of the sortie flight plan.

[0087] Furthermore, the load distribution is:

[0088] max MR p =std(Rt p ) (4)

[0089] Among them, std(·) is the standard deviation calculation function, Rt p Indicates the time set for the carrier-based aircraft on the p-th platform to enter maintenance.

[0090] Specifically, reasonably assigning the task sequence of each platform's carrier-based aircraft, dispersing the time for each carrier-based aircraft to enter maintenance, and forming a staggered use interval can avoid the concentration of maintenance load in the platform hangar and the reduction of the number of available carrier-based aircraft, which affects the normal execution of combat training tasks. The maintenance load dispersion index of the defined sortie flight plan is used to calculate the distribution standard deviation of the time when the platform's carrier-based aircraft enters maintenance as shown in the above formula (4). Rt p The larger the standard deviation, the greater the discreteness of the timing of the carrier-based aircraft on the pth platform entering maintenance, and the better the optimization effect of the sortie flight plan.

[0091] Furthermore, the wave rotation continuity is:

[0092]

[0093] in, is a continuous rotating wave variable if and only if When established, Indicates that the i-th carrier aircraft is in [w,w+Ng p ·Nc p -1] Complete continuous rotation within the wave interval, otherwise Indicates that in [w,w+Ng p ·Nc p -1] The continuous rotation is not completed within the wave interval; I p represents the set of carrier-based aircraft carried by the pth platform, Nd represents the number of carrier-based aircraft required for a single wave flight mission of the platform, and W p represents the p-th platform mission dispatch wave set, Nw p represents the number of mission waves of the pth platform, P represents the number of distributed platforms, Nc p Ng represents the number of continuous rotation waves of the p-th platform cycle operation, p Indicates the number of sub-wave groups dispatched by the p-th platform cycle;

[0094] Specifically, in the cyclic continuous sortie operation mode, the carrier-based aircraft group carried by the platform is divided into several groups, which are dispatched and recovered alternately in wave order. The reason is: on the one hand, considering the continuity of the pilot's dispatch mission, it is required to fly the same aircraft for several waves in succession to maintain the driving habit; on the other hand, it avoids the storage and deck transportation costs involved in the frequent replacement of dispatched aircraft, which is in line with the actual dispatch and recovery operation practices. Maintaining the wave rotation plan is the basis for maintaining the efficiency of support and is of great significance to the combat effectiveness of the fleet. The evaluation index of the wave rotation continuity of the cyclic operation is defined as shown in the above formula (5). The greater the continuity of the wave rotation of the cyclic operation, the better the optimization effect of the dispatch flight plan.

[0095] In the formulation of the actual integrated scheduling plan for fleet wave dispatch and maintenance, the performance indicators at the above three levels have certain priorities. γ1, γ2 and γ3 are defined as the influence weights of the performance evaluation indicators. Commanders can formulate numerical values ​​according to the importance of the indicators.

[0096] Regarding the constraints of the above model, in one embodiment, the distributed platform carrier-based aircraft fleet allocation constraints include that the number of carrier-based aircraft allocated to the platform matches the number of carrier-based aircraft required for the platform mission and each carrier-based aircraft can only be allocated to one platform in the same allocation.

[0097] Specifically, the allocation constraints of the distributed platform carrier-based aircraft fleet can be expressed as follows:

[0098]

[0099]

[0100] Formula (6) indicates that the number of carrier-based aircraft assigned to the platform matches the number of carrier-based aircraft required for the platform mission; Formula (7) indicates that each carrier-based aircraft can only be assigned to one platform in the same allocation.

[0101] In one embodiment, the flight sequence planning constraints include selection constraints of carrier aircraft wave rotation into adjacent wave formations, mutual exclusion constraints between carrier aircraft mission execution and maintenance / residence, constraints on the number of carrier aircraft dispatched for a single wave flight mission, constraints on the timing of carrier aircraft performing regular maintenance, and constraints on the association of flight sequence planning with maintenance scheduling.

[0102] Specifically, the flight timing planning constraints can be expressed as follows:

[0103]

[0104]

[0105]

[0106]

[0107]

[0108] Formula (8) represents the selection constraint of the wave rotation of carrier-based aircraft, the adjacent wave formation and the wave rotation. The formation and wave rotation requires that any carrier-based aircraft adjacent to the wave selection is mutually exclusive, and the mutual exclusion range is related to the number of cyclic sortie wave formations Ng p Related, such as Ng p =3, w=1 means the first wave and the second and third waves Mutually exclusive (the values ​​cannot be 1 at the same time). Formula (9) represents the mutually exclusive constraint between the execution of missions and maintenance / residence of carrier-based aircraft. Formula (10) represents the constraint on the number of carrier-based aircraft dispatched for a single wave flight mission, where represents the number of carrier-based aircraft occupied by the (w-1)th wave mission of the pth platform, It indicates the number of carrier-based aircrafts that perform regular maintenance in the wth wave on the pth platform, = represents the number of available carrier-based aircraft in the wth wave of the pth platform. Formula (11) represents the timing constraint for the periodic maintenance of carrier-based aircraft. The available time for the i-th carrier-based aircraft on the pth platform to perform tasks decreases to the interval Tl before and after the nth periodic maintenance flight hour. Formula (12) represents the associated constraint between flight sequence planning and maintenance scheduling. The maintenance / residence decision variable of the i-th carrier-based aircraft on the pth platform coincides with the wave span of the nth periodic maintenance.

[0109] In one embodiment, the maintenance scheduling constraints include: each maintenance process is carried out in sequence according to the established maintenance process, and the subsequent maintenance task must start after the completion of its immediate predecessor process; each maintenance process has guaranteed start time and guaranteed end time constraints; the skill demand of each maintenance process matches the number of maintenance personnel assigned to each maintenance process and who select this skill; any maintenance personnel can use at most one skill when performing maintenance work on any maintenance process; and priority constraints for maintenance personnel conflicts.

[0110] The distributed maintenance task platform transfer constraints include: the number of repairs to be transferred is less than or equal to the total number of carrier-based aircraft to be repaired; the total number of global transfers is equal to the total number of supplements.

[0111] Specifically, the above constraints can be expressed as follows:

[0112]

[0113]

[0114]

[0115]

[0116]

[0117] Formula (13) indicates that each maintenance process is carried out in sequence according to the established maintenance process, and the subsequent maintenance task must start after the completion of its immediate predecessor process. Formula (14) indicates the guaranteed start time and guaranteed end time constraints for each maintenance process. Formula (15) indicates that the demand for skills in each maintenance process matches the number of maintenance personnel assigned to the process and who choose this skill. Formula (16) indicates that any maintenance personnel can use at most one skill when performing maintenance work on any maintenance process. Formula (17) indicates the priority constraint for maintenance personnel conflicts. When different processes have a demand for the same maintenance personnel, the order of maintenance must be distinguished according to priority.

[0118] The static model of integrated dispatching and maintenance of distributed platform fleet constructed above is shown in formula (18):

[0119]

[0120] When considering the dynamic maintenance of random failures or combat damage, a dynamic scheduling model integrating the wave dispatch and maintenance of distributed platform fleets is constructed, and the decision variables are introduced and defined as follows:

[0121]

[0122]

[0123] The distributed maintenance task platform transfer constraints are introduced as follows:

[0124]

[0125]

[0126] Formula (19) indicates that the number of aircraft to be transferred for repair is less than or equal to the total number of aircraft to be repaired; Formula (20) indicates that the total number of global transfers is equal to the total number of supplements.

[0127] The DP-ASRS dynamic model constructed in combination with the above is shown in formula (21):

[0128]

[0129] In one embodiment, in order to more intuitively and comprehensively illustrate the above-mentioned distributed platform fleet flight and maintenance integrated scheduling method, the following is a simulation experiment example of the distributed platform fleet flight and maintenance integrated scheduling method. It should be noted that the examples given in this specification are only illustrative and are not the only limitation of the specific implementation cases of the present invention. Those skilled in the art can, under the illustration of the implementation cases provided by the present invention, similarly adopt the above-mentioned distributed platform fleet flight and maintenance integrated scheduling method to realize the integrated scheduling of fleet wave sorties and maintenance of different distributed platforms.

[0130] Experimental case design: A simulation experiment case was constructed based on three large surface ship platforms distributed at sea performing a high-intensity continuous combat training mission. The simulation was based on MATLAB 2020a software programming and a personal computer (Windows 7 64-bit operating system, Intel(R)Xeon(R)Gold 5122 CPU@3.60GHz, 32G memory) was used for calculation. Each algorithm was run independently 20 times and the data was recorded.

[0131] Mission flight plan parameters are set as follows: Mission wave number Nw 1 =Nw 2 =Nw 3 =36, the number of distributed platforms Np = 3, the number of carrier-based aircraft carried by the platform Ni 1 =30,Ni 2 =28,Ni 3 =20, the number of continuous rotation waves of cyclic operation Nc 1 =4,Nc 2 =3,Nc 3 =2, the number of wave groups to be dispatched in a cycle Ng 1 =Ng 2 =Ng 3 =2, the number of carrier-based aircraft required for a single wave Nd 1 =8,Nd 2 =5,Nd 3 =4, flight cycle duration Tw 1 =Tw 2 =Tw 3 =2, deck operation cycle duration Td 1 =Td 2 =Td 3 =1.5, single wave deck service support time To 1 =To 2 =To 3 =1, platform influence weight v 1 =0.5,v 2 =0.3,v 3 =0.2, the influence weights of performance evaluation indexes are γ1=0.5, γ2=0.3, and γ3=0.2.

[0132] The maintenance task parameters are set as follows: Maintenance skill quantity Kc = {1,2,3,4}, set four types of maintenance professional skills: ad hoc, avionics, ordnance and machinery, and the number of maintenance personnel on the three platforms The maintenance modes M1-M6 correspond to 25h maintenance, 50h maintenance, 100h maintenance, mechanical failure, avionics system failure and special system failure. The maintenance network process is as follows: Figure 6 As shown, Figure 6 Processes 1 and 20 are virtual start and end processes, the purpose of which is to integrate and connect all processes. The operation time of the carrier-based aircraft maintenance process is shown in Table 1.

[0133] Table 1

[0134]

[0135] The simulation experiment sets three groups of cases with different initial values ​​of the accumulated flight time of the fleet. Figure 7 As shown in the figure, "+" represents the median and "×" represents the average. (a) is the distribution of the initial value of the cumulative flight time, and (b) is the distribution of the available time before the next scheduled maintenance. The distribution of the available time before the next scheduled maintenance in Case 3, Case 1 and Case 2 is successively concentrated to the small value, indicating that more and earlier carrier-based aircraft will enter scheduled maintenance in the subsequent cases, and the maintenance task load pressure of the platform hangar increases in sequence. Case 2 can verify the adaptive solution performance of the proposed method for large-scale reactive rescheduling of fleet maintenance tasks and integrated scheduling of fleet wave dispatch and maintenance under the condition of highly reduced fleet availability, which is the focus of this experimental case study.

[0136] Without considering the random failure of carrier-based aircraft and the cross-platform maintenance linkage mechanism, the baseline scheduling scheme for the integrated wave dispatch and scheduled maintenance of distributed carrier-based aircraft groups is obtained based on the optimization solution within the static model range of equation (18). Taking Case 2 Platform 3 as an example, the scheduling results are as follows: Figure 8 As shown in the figure, (a) is the Gantt chart of the flight sequence of the wave sortie, and (b) is the Gantt chart of the maintenance plan. Figure 8 The Gantt chart of the optimization results shows that the optimization solution has good continuity in the distribution of maintenance load and wave rotation. During the maintenance plan scheduling process, there were 4 reactive reschedulings, which were at the start of the 4th, 6th, 7th and 9th maintenance. After inspection, the scheduling scheme shown in the Gantt chart meets the constraints of the model, verifying the correctness of the model and the effectiveness of the optimization method.

[0137] The results of cluster allocation on platform 3 are as follows: Fig. 9 As shown, (a) is the cumulative flight time distribution result, and (b) is the available time distribution result before the next scheduled maintenance. Fig. 9 (a) Comparison Figure 8(a) It can be seen that the flight time distribution results of platform 3 in the three groups of cases are roughly the same as the overall distribution of the initial value, and there is no obvious regularity between the actual value and distribution of the cumulative flight time. Fig. 9 (b) Contrast Figure 8 (b) Obvious regular characteristics are obtained: the median and average values ​​of the available time before the next scheduled maintenance of the fleet assigned to platform 3 in the three groups of cases are all lower than the initial values, and case 3 is more significant. Analysis of Table 2 shows that the fitness function f is the largest in case 3 and the smallest in case 2 among the three groups of cases. Based on the above results, the reason is analyzed: the optimization of the allocation of the fleet's carrying platforms is not the actual value of the fleet's flight time, but the available time before the next scheduled maintenance of each carrier-based aircraft in the fleet. The larger it is, the better the performance of the performance evaluation indicators F and f. Platform 3 has low pressure on flight mission dispatch, sufficient number of maintenance personnel, and no significant demand for the available time before scheduled maintenance, which makes the distribution result value lower than the overall level. At the same time, the distribution of the available time before the next scheduled maintenance is roughly uniform, and the distribution is hierarchical, which is in line with the expected law.

[0138] Table 2

[0139]

[0140] Cross-platform maintenance linkage mechanism comparison experiment:

[0141] Taking Case 2 as an example, considering the random failure of carrier-based aircraft and the cross-platform maintenance linkage mechanism, firstly, based on the static model of formula (18), the baseline scheduling scheme of the integrated flight timing planning and scheduled maintenance of the distributed carrier-based aircraft group is optimized. Taking platform 2 as an example, the baseline scheduling results are as follows: Fig.10 As shown, (a) is the Gantt chart of the wave flight sequence, and (b) is the Gantt chart of the maintenance plan. Secondly, on the basis of the baseline scheduling plan, random failures or damage based on probability triggering are added to simulate the maritime engagement state of the distributed platform. Dynamic uncertainty disturbances such as failures or damage will affect the execution of the subsequent baseline flight sequence planning. The plan needs to be adjusted reactively after the disturbance. The flight sequence planning after the disturbance adjustment will change locally from the baseline scheduling.

[0142] In order to verify the superiority of the cross-platform maintenance linkage mechanism under the condition of dynamic uncertainty maintenance tasks, a comparison experiment between the cross-platform maintenance linkage mechanism and the independent maintenance of a single platform was conducted. The probability of random failure of the distributed platform carrier-based aircraft is set to 0.1, and the probability of battle damage failure of the platform 1 carrier-based aircraft is set to 0.3. The flight plan and the integrated scheduling scheme of independent maintenance of Case 2 Platform 2 under the condition of independent maintenance of a single platform are calculated. The flight sequence planning results are shown in Figure 2. Fig.11 (a) shows that compared with Fig.10(a) Baseline flight sequence planning: At the beginning of the 11th overhaul, the 7th and 1st carrier-based aircraft had avionics system failure and mechanical failure respectively. The subsequent sortie algorithm affected by the failure selected the 28th carrier-based aircraft for a small-scale supplementary adjustment to meet the mission requirements. At the same time, Fig.10 (b) The impact of the maintenance plan Gantt chart is adjusted reactively at the same time. The adjustment results are as follows: Fig.11 (b) as shown.

[0143] Based on the DP-ASRS dynamic model of formula (21), the baseline scheduling scheme is calculated for the reactive scheduling adjustment of the cross-platform maintenance linkage mechanism. The maintenance task transfer results are shown in Table 3. Taking the first column of data as an example, it means that at the 24.5h of the mission time, the 26th carrier-based aircraft of platform 1 has an M5 avionics system failure, and the maintenance task is transferred to platform 2. At the same time, the 25th carrier-based aircraft of platform 2 is supplemented to platform 1 to maintain the number of carrier-based aircraft on the platform. Taking platform 2 as an example, the scheduling Gantt chart results of the wave sortie flight sequence are shown in Fig.12 As shown in (a), the dashed box in the figure is marked as the carrier-based aircraft transferred into platform 2, and the solid box is marked as the carrier-based aircraft transferred out of platform 2. It can be seen from the figure that the 26th, 1st (originally carried as platform 3), and 2nd carrier-based aircraft of platform 1 are transferred to platform 2 as maintenance tasks. At the same time, the 25th, 3rd, and 5th carrier-based aircraft of platform 2 are transferred out as supplements of platform 1. The 23rd carrier-based aircraft on platform 2 had a special system failure and was not judged as a maintenance task transferred to other platforms, which is consistent with the data in Table 3. The results of the maintenance plan Gantt chart are shown in the figure. Fig.12 As shown in (b), combined with the analysis, it can be seen that the complexity of scheduling scale increases greatly after adding random failures or battle damage. During the maintenance plan scheduling process, 13 reactive reschedulings were experienced, which were located at the start time of the 2nd, 3rd, 4th, 5th, 7th, 8th, 9th, 11th, 12th, 13th, 14th, 15th and 16th maintenance. At the start time of the 9th, 15th and 16th maintenance, maintenance tasks from other platforms were carried out respectively. After inspection, the scheduling scheme shown in the Gantt chart meets the constraints of the model, verifying the correctness of the cross-platform maintenance linkage mechanism in the model.

[0144] Table 3

[0145] Transfer time / h 24.5 35 47 48.5 Failure Mode M5 M5 M6 M6 Transfer out of the platform 1 1 1(3) 1 Fault number 26 25 1 2 Transfer to platform 2 3 2 2 Supplementary No. 25 1 3 5

[0146] The complete calculation results of the cross-platform maintenance linkage mechanism and the independent maintenance scheduling of a single platform are shown in Table 4. The following conclusions are drawn based on the comparative analysis of the calculation results: 1. The cross-platform maintenance linkage mechanism transfers the maintenance task of the faulty carrier-based aircraft to the small maintenance load platform based on the distributed maintenance task allocation heuristic rule, which realizes the dispersion of the maintenance load, which is manifested as an advantage in the MR indicator. 2. For platform 1 with a high probability of failure, under the conditions of case 1 and case 2 with high overall task intensity and high theoretical maintenance times, thanks to the distributed maintenance task allocation heuristic rule, the allocation and transfer of fault maintenance tasks and the replenishment of available carrier-based aircraft are realized, so that the platform can always meet the fleet availability required by the task and ensure the stable and full completion of the task wave, which is manifested as an advantage in the WR indicator. 3. The stable task completion and wave rotation continuity indicators brought by the advantages of the cross-platform maintenance linkage mechanism in the CR indicator ensure the overall stability of combat training tasks and deck operations. 4. Thanks to the advantages of the sub-indicators, the cross-platform maintenance linkage mechanism has improved the overall index f compared with the single-platform independent maintenance, which is in line with the expected law. However, due to the high complexity and strong uncertainty of the scheduling process of the cross-platform transfer of carrier-based aircraft, the discreteness of the solution results under some case platforms is greater than that of the single-platform independent maintenance, and the overall stability of the solution results is slightly weaker, which is manifested as the suboptimal f variance index in some cases. 5. Under the condition of heavy maintenance tasks, the independent maintenance of a single platform causes the maintenance load of the platform hangar to be concentrated, the maintenance tasks to be backlogged, and the task timeliness is poor, which is manifested as the lack of task waves, that is, the WR index is less than 1, which makes the index f and MR show disadvantages compared with the cross-platform maintenance linkage mechanism. However, since the maintenance of a single platform avoids breaking the cumbersome and complex process of breaking the dispatch cycle operation process of the original platform of some carrier-based aircraft and the transfer of maintenance tasks, the scheduling results are slightly more stable, which is manifested as the advantages of f variance and CR indicators in some cases.

[0147] Table 4

[0148]

[0149] Table 4 (continued)

[0150]

[0151] Experimental conclusion:

[0152] 1) Aiming at the problem of integrated flight and maintenance scheduling of distributed platform fleets, this paper systematically analyzes theoretical research on aircraft task assignment and maintenance planning, carrier-based aircraft sortie recovery operation scheduling, carrier-based aircraft maintenance scheduling, and dynamic scheduling in the field of civil aviation at home and abroad. Taking the task wave completion rate, maintenance load dispersion and wave rotation continuity as optimization goals, and comprehensively considering various processes and constraints, an integrated flight and maintenance scheduling model for distributed platform fleets at sea that takes into account the transfer of maintenance tasks is established. This model can provide theoretical support for commanders to formulate fleet allocation, sortie flight plans and collaborative maintenance scheduling plans for future distributed maritime operations.

[0153] 2) The established model can meet the constraints of various processes, resources and time for the allocation of distributed platform carrier-based aircraft fleet, flight sequence planning, cyclic dispatch operations, deck service support, and maintenance. The Gantt chart scheduling results verify the correctness and effectiveness of the model.

[0154] 3) Compared with the independent maintenance of a single platform, the cross-platform maintenance linkage mechanism shows advantages in all indicators set by the model, especially under the conditions of high mission intensity, high probability of failure and high theoretical maintenance times. Therefore, the cross-platform maintenance linkage mechanism can be applied to actual combat and training tasks.

[0155] It should be understood that although Figure 5 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Figure 5 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequentially, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0156] See also Fig.13, a distributed platform fleet flight and maintenance integrated scheduling device 100 is also provided, comprising a data acquisition module 11, a model calling module 12, an optimization output module 13 and a scheduling execution module 14. Among them, the data acquisition module 11 is used to obtain the current mission flight plan parameters and maintenance task parameters; the mission flight plan parameters include the number of mission waves, the number of distributed platforms, the number of carrier-based aircraft on the platform, the number of continuous rotation waves of cyclic operations, the number of wave formations of cyclic sorties, the number of carrier-based aircraft required for a single wave, the flight cycle duration, the deck operation cycle duration, the single wave deck service support duration, the platform influence weight and the efficiency evaluation index influence weight, and the maintenance task parameters include the number of maintenance skills, the number of platform maintenance personnel and the maintenance mode. The model calling module 12 is used to call the constructed DP-ASRS dynamic model; the objective function of the DP-ASRS dynamic model includes: the distributed platform task comprehensive efficiency optimization objective function and the single platform efficiency optimization objective function, and the constraints of the DP-ASRS dynamic model include the distributed platform carrier-based aircraft fleet allocation constraints, the flight timing planning constraints, the maintenance scheduling constraints and the distributed maintenance task platform transfer constraints. The optimization output module 13 is used to optimize and solve the DP-ASRS dynamic model according to the mission flight plan parameters and the maintenance mission parameters, and output the current integrated scheduling plan. The scheduling execution module 14 is used to use the integrated scheduling plan to perform integrated scheduling of distributed platform fleet flight and maintenance.

[0157] The above-mentioned distributed platform fleet flight and maintenance integrated scheduling device 100, through the collaboration of various modules, for the currently required distributed platform fleet flight and maintenance integrated scheduling, first obtains the current mission flight plan parameters and maintenance task parameters, and then calls the constructed DP-ASRS dynamic model, and uses the acquired known parameter data to optimize and solve the DP-ASRS dynamic model, and outputs the distributed platform task comprehensive efficiency optimization objective function and the single platform efficiency optimization objective function to maximize the optimal scheduling plan that meets the constraints of the model, that is, the current integrated scheduling plan is obtained, and finally the integrated scheduling plan is used to carry out the distributed platform fleet flight and maintenance integrated scheduling, thereby achieving the purpose of effectively realizing the distributed platform fleet flight and maintenance integrated scheduling, and having strong real-time and applicability.

[0158] In one embodiment, each module of the above-mentioned distributed platform fleet flight and maintenance integrated scheduling device 100 can also be used to implement the corresponding sub-steps in each embodiment of the above-mentioned distributed platform fleet flight and maintenance integrated scheduling method.

[0159] Regarding the specific limitations of the distributed platform fleet flight and maintenance integrated scheduling device 100, please refer to the corresponding limitations of the distributed platform fleet flight and maintenance integrated scheduling method above, which will not be repeated here. Each module in the above-mentioned distributed platform fleet flight and maintenance integrated scheduling device 100 can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of a device with a specific data processing function in the form of hardware, or can be stored in the memory of the aforementioned device in the form of software, so that the processor can call and execute the operations corresponding to the above modules. The aforementioned device can be, but is not limited to, a data management / command device or a computing system for an offshore distributed platform.

[0160] On the other hand, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor can implement the following steps when executing the computer program: obtaining current mission flight plan parameters and maintenance task parameters; calling the constructed DP-ASRS dynamic model; optimizing and solving the DP-ASRS dynamic model according to the mission flight plan parameters and maintenance task parameters, and outputting the current integrated scheduling plan; and using the integrated scheduling plan to perform integrated scheduling of distributed platform fleet flight and maintenance. Among them, the mission flight plan parameters include the number of mission waves, the number of distributed platforms, the number of carrier-based aircraft carried by the platform, the number of continuous rotation waves of cyclic operations, the number of wave formations for cyclic sorties, the number of carrier-based aircraft required for a single wave, the flight cycle duration, the deck operation cycle duration, the single wave deck service support duration, the platform influence weight and the efficiency evaluation index influence weight; the maintenance task parameters include the number of maintenance skills, the number of platform maintenance personnel and the maintenance mode; the objective function of the DP-ASRS dynamic model includes: the distributed platform task comprehensive efficiency optimization objective function and the single platform efficiency optimization objective function; the constraints of the DP-ASRS dynamic model include the distributed platform carrier-based aircraft fleet allocation constraints, the flight timing planning constraints, the maintenance scheduling constraints and the distributed maintenance task platform transfer constraints.

[0161] In one embodiment, when the processor executes the computer program, it can also implement the steps or sub-steps added in each embodiment of the above-mentioned distributed platform fleet flight and maintenance integrated scheduling method.

[0162] On the other hand, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: obtaining current mission flight plan parameters and maintenance task parameters; calling the constructed DP-ASRS dynamic model; optimizing and solving the DP-ASRS dynamic model according to the mission flight plan parameters and maintenance task parameters, and outputting the current integrated scheduling plan; and using the integrated scheduling plan to perform integrated scheduling of distributed platform fleet flight and maintenance. Among them, the mission flight plan parameters include the number of mission waves, the number of distributed platforms, the number of carrier-based aircraft carried by the platform, the number of continuous rotation waves of cyclic operations, the number of wave formations for cyclic sorties, the number of carrier-based aircraft required for a single wave, the flight cycle duration, the deck operation cycle duration, the single wave deck service support duration, the platform influence weight and the efficiency evaluation index influence weight; the maintenance task parameters include the number of maintenance skills, the number of platform maintenance personnel and the maintenance mode; the objective function of the DP-ASRS dynamic model includes: the distributed platform task comprehensive efficiency optimization objective function and the single platform efficiency optimization objective function; the constraints of the DP-ASRS dynamic model include the distributed platform carrier-based aircraft fleet allocation constraints, the flight timing planning constraints, the maintenance scheduling constraints and the distributed maintenance task platform transfer constraints.

[0163] In one embodiment, when the computer program is executed by a processor, it can also implement the steps or sub-steps added in each embodiment of the above-mentioned distributed platform fleet flight and maintenance integrated scheduling method.

[0164] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and 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 embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus dynamic random access memory (Rambus DRAM, referred to as RDRAM) and interface dynamic random access memory (DRDRAM).

[0165] The technical features of the above embodiments may be combined arbitrarily. 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.

[0166] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and all of them belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A distributed platform fleet flight and maintenance integrated scheduling method, characterized in that: Includes steps: Obtaining current mission flight plan parameters and maintenance mission parameters; the mission flight plan parameters include the number of mission waves, the number of distributed platforms, the number of carrier-based aircraft on the platform, the number of continuous rotation waves of cyclic operations, the number of wave formations for cyclic sorties, the number of carrier-based aircraft required for a single wave, the flight cycle duration, the deck operation cycle duration, the single-wave deck service support duration, the platform impact weight, and the performance evaluation index impact weight; the maintenance mission parameters include the number of maintenance skills, the number of platform maintenance personnel, and the maintenance mode; Call the constructed DP-ASRS dynamic model; The objective function of the DP-ASRS dynamic model includes: a distributed platform task comprehensive effectiveness optimization objective function and a single platform effectiveness optimization objective function, and the constraints of the DP-ASRS dynamic model include distributed platform carrier-based aircraft fleet allocation constraints, flight timing planning constraints, maintenance scheduling constraints, and distributed maintenance task platform transfer constraints; Optimizing and solving the DP-ASRS dynamic model according to the mission flight plan parameters and the maintenance mission parameters, and outputting the current integrated scheduling plan; The integrated scheduling scheme is used to perform integrated scheduling of flight and maintenance of distributed platform fleets; wherein the distributed platform task comprehensive efficiency optimization objective function is maxF: The single platform performance optimization objective function is maxf p : Among them, v p represents the influence weight of the p-th platform, f p represents the performance evaluation value of the pth platform, γ1, γ2 and γ3 represent the impact weights of the performance indicators at three levels, P represents the number of distributed platforms, and WR p represents the task wave completion rate of the pth platform, MR p represents the maintenance load dispersion of the pth platform, CR p Indicates the continuity of the wave rotation of the p-th platform; The completion rate of the task wave is: in, is a task-complete wave variable if and only if hour, Indicates that the wth wave is the task-completed wave; otherwise Indicates that the wth wave is a missing wave, I p represents the set of carrier-based aircraft carried by the pth platform, Nd represents the number of carrier-based aircraft required for a single wave flight mission of the platform, and W p represents the set of waves of missions dispatched by the pth platform, Nw p represents the number of mission waves dispatched by the p-th platform; The maintenance load dispersion is: maxMR p =std(Rt p ) Among them, std(·) is the standard deviation calculation function, Rt p Indicates the time set for the carrier-based aircraft on the pth platform to enter maintenance; The wave rotation continuity is: in, is a continuous rotating wave variable if and only if When established, Indicates that the i-th carrier aircraft is in [w,w+Ng p ·Nc p -1] Complete continuous rotation within the wave interval, otherwise Indicates that in [w,w+Ng p ·Nc p -1] The continuous rotation is not completed within the wave interval; I p Nd represents the set of carrier-based aircraft carried by the pth platform, p represents the number of carrier-based aircraft required for a single-wave flight mission of the p-th platform, W p represents the p-th platform mission dispatch wave set, Nw p represents the number of mission waves of the pth platform, P represents the number of distributed platforms, Nc p Ng represents the number of continuous rotation waves of the p-th platform cycle operation, p Indicates the number of sub-wave groups dispatched by the p-th platform cycle; 2. The method for integrated flight and maintenance scheduling of distributed platform fleets according to claim 1, characterized in that: The distributed platform carrier-based aircraft fleet allocation constraints include that the number of carrier-based aircraft allocated to the platform matches the number of carrier-based aircraft required for the platform mission and each carrier-based aircraft can only be allocated to one platform in the same allocation.

3. The method for integrated flight and maintenance scheduling of distributed platform fleets according to claim 1, characterized in that: The flight sequence planning constraints include selection constraints of carrier aircraft wave rotation and adjacent wave formation, mutual exclusion constraints of carrier aircraft execution mission and maintenance / residence, constraints on the number of carrier aircraft dispatched for a single wave flight mission, constraints on the timing of carrier aircraft performing regular maintenance, and constraints on the association of flight sequence planning with maintenance scheduling.

4. The method for integrated flight and maintenance scheduling of distributed platform fleets according to claim 1, characterized in that: The maintenance scheduling constraints include: Each maintenance process is carried out in sequence according to the established maintenance process, and the subsequent maintenance task must start after the completion of the immediately preceding process; each maintenance process is subject to guaranteed start time and guaranteed end time constraints; the demand for skills in each maintenance process matches the number of maintenance personnel assigned to each maintenance process and who choose this skill; any maintenance personnel can only use one skill when performing maintenance work on any maintenance process; maintenance personnel conflict priority constraints; The distributed maintenance task platform transfer constraints include: the number of maintenance to be transferred is less than or equal to the total number of carrier-based aircraft to be repaired; the total number of global transfers is equal to the total number of supplements.

5. A distributed platform fleet flight and maintenance integrated scheduling device, characterized in that: include: Data acquisition module, used to obtain the current mission flight plan parameters and maintenance mission parameters; The mission flight plan parameters include the number of mission waves, the number of distributed platforms, the number of carrier-based aircraft on the platform, the number of continuous rotation waves of cyclic operations, the number of wave formations for cyclic sorties, the number of carrier-based aircraft required for a single wave, the flight cycle duration, the deck operation cycle duration, the single-wave deck service support duration, the platform impact weight, and the performance evaluation index impact weight; the maintenance mission parameters include the number of maintenance skills, the number of platform maintenance personnel, and the maintenance mode; Model calling module, used to call the constructed DP-ASRS dynamic model; The objective function of the DP-ASRS dynamic model includes: a distributed platform task comprehensive effectiveness optimization objective function and a single platform effectiveness optimization objective function, and the constraints of the DP-ASRS dynamic model include distributed platform carrier-based aircraft fleet allocation constraints, flight timing planning constraints, maintenance scheduling constraints, and distributed maintenance task platform transfer constraints; An optimization output module, used to optimize and solve the DP-ASRS dynamic model according to the mission flight plan parameters and the maintenance mission parameters, and output the current integrated scheduling plan; The scheduling execution module is used to use the integrated scheduling scheme to perform integrated scheduling of flight and maintenance of distributed platform fleets; wherein the distributed platform task comprehensive efficiency optimization objective function is maxF: The single platform performance optimization objective function is maxf p : Among them, v p represents the influence weight of the p-th platform, f p represents the performance evaluation value of the pth platform, γ1, γ2 and γ3 represent the impact weights of the performance indicators at three levels, P represents the number of distributed platforms, and WR p represents the task wave completion rate of the pth platform, MR p represents the maintenance load dispersion of the pth platform, CR p Indicates the continuity of the wave rotation of the p-th platform; The completion rate of the task wave is: in, is a task-complete wave variable if and only if hour, Indicates that the wth wave is the task-completed wave; otherwise Indicates that the wth wave is a missing wave, I p represents the set of carrier-based aircraft carried by the pth platform, Nd represents the number of carrier-based aircraft required for a single wave flight mission of the platform, and W p represents the set of waves of missions dispatched by the pth platform, Nw p represents the number of mission waves dispatched by the p-th platform; The maintenance load dispersion is: maxMR p =std(Rt p ) Among them, std(·) is the standard deviation calculation function, Rt p Indicates the time set for the carrier-based aircraft on the pth platform to enter maintenance; The wave rotation continuity is: in, is a continuous rotating wave variable if and only if When established, Indicates that the i-th carrier aircraft is in [w,w+Ng p ·Nc p -1] Complete continuous rotation within the wave interval, otherwise Indicates that in [w,w+Ng p ·Nc p -1] The continuous rotation is not completed within the wave interval; Ip represents the set of carrier-based aircraft carried by the pth platform, Nd p represents the number of carrier-based aircraft required for a single-wave flight mission of the p-th platform, W p represents the p-th platform mission dispatch wave set, Nw p represents the number of mission waves of the pth platform, P represents the number of distributed platforms, Nc p Ng represents the number of continuous rotation waves of the p-th platform cycle operation, p Indicates the number of sub-wave groups dispatched by the p-th platform cycle;

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