Marine aircraft support operation scheduling method based on variable operation process

Abstract

The invention discloses a marine aircraft guarantee operation scheduling method based on a variable operation process, and relates to the technical field of marine aircraft scheduling, and the method comprises the following steps: 1, problem description; 2, a deck support-ammunition transfer integrated scheduling model is established; and 3, designing a scheduling optimization algorithm based on a differential evolution (DE) algorithm. According to the method, by describing a maritime aircraft maintenance service guarantee operation process, classifying operations needing to be guaranteed in the process, abstracting a problem into a resource-limited multi-project scheduling problem model based on a variable operation process, and by taking guarantee operation completion time as an optimization index, a resource-limited multi-project scheduling problem model is obtained; and finally, compared with a fixed operation flow-based aircraft service guarantee operation scheduling method, the advantages of aircraft service guarantee operation scheduling based on a variable flow mode are verified, and a scientific marine aircraft deck operation flow and an efficient and feasible aircraft service guarantee operation scheduling scheme are realized.

Description

Technical Field

[0001] The invention relates to the technical field of offshore aircraft scheduling, and in particular to an offshore aircraft support operation scheduling method based on a variable operation process. Background Art

[0002] As the main combat force of offshore platforms, the ability of seaplanes to deploy and recover directly affects the combat effectiveness of offshore platforms, and deck maintenance and service support operations are the key link that restricts the ability of seaplanes to deploy and recover. Therefore, how to plan a scientific deck operation process for seaplanes and formulate an efficient and feasible maintenance and service support operation scheduling plan has always been a core topic in the study of the combat effectiveness of offshore platforms. Compared with the aircraft support operations at land airports, the deck support operations of seaplanes have more complex resource constraints and stricter time constraints. At the same time, in order to maintain a high-intensity dispatch rate, the maintenance and service support operations of seaplanes are required to be completed within the deck cycle, and a deck cycle is limited to a specified time, 1+15 (1 hour and 15 minutes), 1+45. Therefore, any delay in the maintenance and service support operations may affect the completion time of the operations under this strict time scheduling. In order to ensure that the aircraft at sea can complete the maintenance and service support operations within the deck cycle, researchers have conducted a lot of research on the scheduling of maintenance and service support operations and ammunition transfer scheduling. For the scheduling of maintenance and service support operations, they have designed a multi-station support model, a centralized support model, and an integrated support model; for ammunition transfer scheduling, as a branch of the maintenance and service support operation process, researchers have established an independent scheduling model for optimization and solution. The existing technology has the following problems: Because the existing research on the optimization problem of scheduling of maritime aircraft maintenance service support operations has undergone a process of continuous refinement from HFSP to FJSP to RCMPSP in terms of model abstraction, the granularity of the model has gradually become finer and closer to the actual support operation environment and needs. However, when the existing research abstracts the optimization problem model of maritime aircraft maintenance service support scheduling, the operation process in RCMPSP is often fixed. In the process of maritime aircraft maintenance service support operations, the various processes in the operation process are highly flexible, and many support operations do not have a close sequence. Abstracting it as a fixed operation process RCMPSP will increase the critical path length of the maritime aircraft support operation process, resulting in an increase in the time required to complete the support operation. Summary of the invention

[0003] The present invention provides a method for scheduling offshore aircraft support operations based on a variable operation process to solve the problems raised in the above-mentioned background technology.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is: The following steps are involved: Step 1: Problem description; Step 2: Deck support-ammunition transfer integrated scheduling model; Step 3: Design of scheduling optimization algorithm based on differential evolution algorithm (DE); In the step 1, during the operation execution process, Kp types of maintenance personnel with different professions are required to perform inspection and maintenance and various resource replenishment operations before the sea aircraft is dispatched in a complex deck environment, and Kq types of service support equipment provide maintenance personnel with Kr types of supply resources required for maintenance support operations, so that the sea aircraft has the ability to be dispatched again; the step 2 refers to establishing a sea aircraft deck support-ammunition transfer integrated scheduling model under a variable process mode, and reducing it to a resource-constrained multi-project-resource distribution integrated scheduling problem based on a variable operation process; the step 3 refers to that from the problem description and optimization model, compared with the general RCPSP problem, the resource-constrained multi-project-resource distribution integrated scheduling problem has the following characteristics: the resources involved in the maintenance service support operation include maintenance support manpower, service support equipment, support resources, and resource transport vehicles. These resources are special. The resource distribution process and aircraft refueling operations have special requirements on the demand and use of resources. With the increase in the number of aircraft in the dispatch mission, the scale of the problem increases sharply. It is necessary to consider the transfer of various service support equipment and maintenance support personnel between different process positions, and use the DE algorithm to solve the problem.

[0005] A further improvement of the technical solution of the present invention is that the step 1 includes the following contents: A1: Deck operating environment. Compared with land airports, the deck area is particularly small. A series of complex operations such as recovery, parking, maintenance and departure of offshore aircraft need to be completed in a limited space. At the same time, the island, deck boundary and deployed offshore aircraft on the deck together form a complex obstacle network. A2: Classification of support operations. After outbound transfer or recovery to the support parking position, support operations need to be performed. Among them, operations 0 and 24 are virtual start and end processes. They do not consume support resources and take 0 time when executed. For the remaining operations, they can be divided into three categories according to their execution location requirements, support resource requirements and support process requirements: Operations that have no sequence and can be performed simultaneously: A large number of operations that need to be performed during the support process have no strict execution sequence constraints, resource demand conflicts and space constraints, and various professional maintenance personnel perform appearance inspection operations; Operations that have no sequence but cannot be performed simultaneously: mainly include operations that conflict with each other in operation space and operations that conflict with power demand. The ammunition mounting process cannot be powered on, while the fuel replenishment process needs to be powered on, so these two types of support operations cannot be performed; Operations with a sequence: Some support operations can only be performed after other operations are completed, and have strict process constraints. The ammunition mounting operation of the corresponding hanging point can only be performed after the wings are unfolded; According to the above classification of operation types, it is concluded that the operation process in the maintenance service support operation process can be changed, so it is necessary to optimize the scheduling of maintenance service support operations under the variable process mode; A3: Maintenance personnel can be divided into Kp different professions. They perform a series of maintenance procedures during the maintenance and service of maritime aircraft, including inspection and maintenance, replenishment of various required gases, replenishment of fuel, power supply, and ammunition mounting at the hanging point, to ensure that the maritime aircraft has the ability to be dispatched to perform missions. When performing different procedures, maintenance personnel of different professions are required. It takes time for personnel to transfer between different maintenance positions in the deck obstacle network; A4: Service support equipment. The service support equipment required in the process of maritime aircraft support can be divided into Ke types. Each type of support equipment carries a type of service support resource to supply the resource consumption during the execution of the support operation, including fuel, hydraulic, oxygen and nitrogen. According to whether the resource location is fixed, each type of support equipment can be divided into fixed support equipment station and mobile support vehicle. The fixed equipment station can provide the maritime aircraft within its coverage with the resources required to perform the corresponding support operation. The mobile support vehicle moves in the deck environment and can provide support for maritime aircraft parked at any location. A5: The space for the maintenance work station is required when executing the maintenance work process. Only the limitation of the work station space on the number of maintenance support personnel is considered. The cockpit of the offshore aircraft can only accommodate one person working at the same time, while there is work station space for operations outside the cockpit.

[0006] A further improvement of the technical solution of the present invention is that the step 2 includes the following steps: B1: Model assumptions. To establish the scheduling optimization model, the following assumptions are made: ① Assuming that a one-stop support parking position is set up on the deck of the offshore platform, one-stop support operations can be achieved at this parking position, and assuming that the service support resources at each parking position are sufficient for non-one-stop support parking positions, centralized support can be achieved at the parking position for offshore aircraft; ② Assume that the support range of maintenance personnel and service support vehicles can cover all support parking positions on the deck; ③ Ensure that the operation cannot be interrupted during execution; ④ There are sufficient support resources stored on the offshore platform to fully meet the needs of various support tasks; ⑤ The speed of the ammunition transport vehicle is only related to the type of vehicle, but has nothing to do with its carrying capacity; B2: Constraints. According to the characteristics and workflow of maintenance operations, the conditions under which the current process Oij can be started can be expressed as an AND gate logic. The current process can only be started when the four prerequisites are met at the same time. B3: Objective function. The purpose of optimizing the scheduling of maritime aircraft maintenance support operations is to complete the support operations as early as possible. Therefore, the objective function is set to minimize the support completion time.

[0007] The further improvement of the technical solution of the present invention is that the constraints for executing the maintenance service support operation in B2 are divided into three categories: support personnel constraints, support resource constraints and operation process constraints. At the same time, when the operation process involves resources, the ammunition distribution process constraints need to be considered. The support personnel constraints refer to the support personnel Kp corresponding to 4 professional categories, namely: I, II, III, IV, is the set of support personnel of the kth (k∈Kp) professional category, The number of k-th type of support personnel required for process Oij is recorded as The personnel constraints mainly include the constraints on the number of personnel required for the operation process and the time constraints for personnel to transfer between different workstations. in, is a 0-1 decision variable, satisfying formula (3); To ensure the connection variables between personnel in the processes, equation (4) is satisfied; is the variable for matching the support personnel between processes, satisfying formula (5); S eg is the guaranteed start time of process Oeg; is the guaranteed completion time of process Oij; B is a large real number that makes the inequality always hold; J is the set of all the operation processes in the guarantee task that satisfies equation (6); S ij , F ij They are the start guarantee time and the completion guarantee time of the process respectively;

[0008] Among them, i, e are the numbers of the seaplanes; j, g are the corresponding operation process numbers of the seaplanes i, e; The support resource constraint means that the support resources have corresponding support equipment to carry, and its constraint is reflected by the support equipment. There are 6 types of support equipment Ke on the deck, namely: fuel station / car, power station / car, oxygen station / car, nitrogen station / car, hydraulic station / car, and ammunition transporter. This part mainly considers the constraints related to the first 5 types of support equipment. is the mth (m∈Ke) type of security equipment set, is the number of type m support equipment required for process Oij. For exclusive support equipment, the constraints mainly consider the constraints on the number of personnel required for the operation process, the coverage constraints of the support equipment, and the transfer time constraints of the support equipment between process locations. in, is a 0-1 decision variable, satisfying formula (10); To ensure the connection variables between personnel in the processes, equation (11) is satisfied; is the guarantee equipment matching variable between processes, satisfying formula (12); Indicates the protection equipment The transfer process between two adjacent process locations is time-consuming; The operation process constraints refer to the operation process of the maintenance service of the maritime aircraft. The process constraints mainly include the preceding process constraints, the conflicting process constraints caused by the space constraints and the power supply usage matching constraints, the priority sequence constraints of the completion time, and the task start condition constraints. Among them, Y ijeg is a 0-1 decision variable, satisfying formula (19); P re (O eg ) is process O eg The set of immediate predecessor processes is shown in Figure 3 Processes connected by arrow lines; C on (O eg ) is the same as process O eg For a set of processes that cannot be executed simultaneously due to space constraint conflicts or power matching constraint conflicts, formula (16) ensures that the execution time periods of the conflicting processes have no intersection; d ijFor process O ij Working hours; Complete mooring time for seaplane i,

[0009] A further improvement of the technical solution of the present invention is that the step three comprises the following steps: C1: DE algorithm, DE is a population-based adaptive global optimization algorithm, its main process includes: ① Mutation: Mutation mainly updates the position of the current individual through the difference between vectors. The following mutation method is used here: Where t is the current iteration number; V h (t) is the individual after mutation; is the individual with the best fitness value in the current iterative population; A random number selected by the crowd that is different from X h (t) 3 random individuals; F is the scaling factor, which is used to control the scaling ratio of the difference vector; ② Crossover: The new individual V h (t+1) and the corresponding individual X in the contemporary population h (t) Perform a crossover operation to generate new offspring individuals. Among them, CR is the crossover probability; randh is a random integer between 1 and individual length N; ③Selection: In the parent individual X h (t) and the offspring individual U h (t) to select individuals with higher fitness and save them to the next generation. Among them, f(·) calculates the objective function corresponding to the individual; C2: DE algorithm flow.

[0010] The further improvement of the technical solution of the present invention is that: the C2 includes population initialization, fitness evaluation, support personnel allocation rules, and support equipment allocation rules. In the population initialization, Bigler compared and analyzed the random key encoding and task list encoding commonly used in the RCPSP problem. For the task list encoding, the mutation operation can be used, so the random key encoding method is adopted. The random key rij∈(0,1) represents the scheduling priority of the process Oij. It is defined that the smaller the rij value is, the higher the scheduling priority of the process Oij is. For the maintenance service support operation containing I number of sea aircraft, it can be encoded as, Since the Cubic mapping has good chaotic ergodicity, the Cubic mapping method is used to initialize the individuals in the population. Where xn is the n-th dimension code in x; ρ is a parameter, and takes x 1 ∈unifom(0.2,0.4), ρ=2.595: The decoding process in the fitness evaluation is to map the code into a scheduling plan, including the start time, end time, support personnel and equipment allocation of each operation process, and then calculate the fitness function value corresponding to the code, and use SSGS for decoding. According to the small proportion of the number of the preceding process pairs in the problem, the codes of the corresponding positions of the preceding process pairs in the single-machine operation process are sorted by size, so that when decoding is performed in ascending order according to the code value, the current process O ij The corresponding immediate predecessor process P re (O ij ) has completed the scheduling, that is, O ij Scheduleable, then define the scheduled process set Ab and the unscheduled process set Db, in the decoding process with a total of |J| stages, select the individual O with the highest priority in the set Dg in turn ij , and executes four decisions for it: ① Arrange maintenance support personnel and obtain the earliest start time t that satisfies the maintenance personnel constraints 1 ; ② Arrange the service support equipment and obtain the earliest start time t that meets the support equipment constraints 2 ; ③ According to the constraints of the immediate predecessor process, perform time scheduling to obtain the earliest guaranteed start time t that satisfies constraint (15) 3 ④ According to the conflicting process constraints, perform time scheduling to obtain the earliest guaranteed start time t that satisfies constraint (16) 4 ; Then, according to formula (26-27) calculate step O jj Start guarantee time S ij and end guarantee time F ij , and update the information of equipment and personnel; finally, let process O ij The code of the corresponding position is assigned with value B, which is added to the scheduled process set and transferred to the next scheduling stage. When all processes are scheduled, the scheduling plan is output and the objective function value f(X) is calculated. S ij =max{t 1 , t 2 , t 3 , t 4} ij ∈J (26); F ij =S ij +dij O j ∈J (27); The security personnel allocation rule can be set according to the objective function of the scheduling problem. The specific steps are as follows: ① Calculate the kth category (k∈Kp) of support personnel Complete the previous process O ij End time ② Find the time it takes for the support personnel to transfer from the previous process position Oij to the current process Oeg ③ According to formula (28), the process support personnel are calculated have, Then we can calculate Figure 6 The earliest possible start time t that satisfies the support personnel constraints 1 , The support equipment allocation rule means that the support equipment on the deck includes gas stations / cars, hydraulic stations / cars, nitrogen stations / cars, oxygen stations / cars, power stations / cars and ammunition transport vehicles. According to the assumptions, the resources carried by the support equipment other than the ammunition transport vehicle can meet the resource usage requirements of the current support mission. For this type of support equipment, the specific resource number to be allocated can be calculated using similar rules in the support personnel allocation rule. And calculate the earliest start time t that satisfies the guarantee equipment constraints 2 .

[0011] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art: 1. The present invention provides a method for scheduling maritime aircraft maintenance operations based on a variable operation process. The method describes the operation process of maintenance service support for maritime aircraft, classifies the operations that need to be performed in the process, and then abstracts the problem into a resource-constrained multi-project scheduling problem model based on a variable operation process, taking the completion time of the operation as the optimization index. Finally, the method is compared with the maintenance service support operation scheduling method based on a fixed operation process, and the advantages of the maintenance service support operation scheduling based on the variable process mode are verified, so as to realize a scientific operation process of the deck of maritime aircraft and an efficient and feasible maintenance service support operation scheduling plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A schematic diagram of the operating environment of an offshore aircraft deck of the present invention; Figure 2 It is a schematic diagram of a variable operation flow of a single-machine maintenance service support operation of the present invention; Figure 3 A schematic diagram of the coverage range of the security equipment station of the present invention; Figure 4 A schematic diagram of the conditions for starting the execution of the current process of the present invention; Figure 5 A schematic diagram of the use of a shared device according to the present invention; Figure 6 Provide a Gantt chart of the completion time for the sea aircraft in the task of the present invention; Figure 7 It is a schematic diagram of the maintenance service support operation of a single machine based on a fixed operation process of the present invention. DETAILED DESCRIPTION

[0013] The present invention is further described in detail below in conjunction with embodiments:

[0014] Example 1 Figure 1-7 The present invention provides a method for scheduling marine aircraft support operations based on a variable operation process, comprising the following steps: Step 1: Problem description; Step 2: Deck support-ammunition transfer integrated scheduling model; Step 3: Design of scheduling optimization algorithm based on differential evolution algorithm (DE); In the process of executing the operation in step 1, Kp types of maintenance personnel with different specialties are required to perform inspection and maintenance and various resource replenishment operations before the seaplane is dispatched in a complex deck environment, and Kq types of service support equipment provide the maintenance personnel with Kr types of supply resources required for maintenance operations, so that the seaplane has the ability to be dispatched again; Step 2 refers to establishing an integrated scheduling model for marine aircraft deck support and ammunition transfer under a variable process mode, and reducing it to a resource-constrained multi-project-resource distribution integrated scheduling problem based on a variable operation process; Step 3 refers to the following characteristics of the problem description and optimization model compared to the RCPSP problem: the resources involved in the maintenance service support operation include maintenance support manpower, service support equipment, support resources, and resource transport vehicles. These resources are special. The resource distribution process and aircraft refueling operations have special requirements for the demand and use of resources. With the increase in the number of aircraft in the dispatch mission, the scale of the problem increases sharply. It is necessary to consider the transfer of various types of service support equipment and maintenance support personnel between different process positions, and use the DE algorithm to solve the problem. Step 1 includes the following contents: A1: Deck operating environment. Compared with land airports, the deck area is particularly small. A series of complex operations such as recovery, parking, maintenance and departure of offshore aircraft need to be completed in a limited space. At the same time, the island, deck boundary and deployed offshore aircraft on the deck together form a complex obstacle network. A2: Classification of support operations. After outbound transfer or recovery to the support parking position, support operations need to be performed. Among them, operations 0 and 24 are virtual start and end processes. They do not consume support resources and take 0 time when executed. For the remaining operations, they can be divided into three categories according to their execution location requirements, support resource requirements and support process requirements: Operations that have no sequence and can be performed simultaneously: A large number of operations that need to be performed during the support process have no strict execution sequence constraints, resource demand conflicts and space constraints, and various professional maintenance personnel perform appearance inspection operations; Operations that have no sequence but cannot be performed simultaneously: mainly include operations that conflict with each other in operation space and operations that conflict with power demand. The ammunition mounting process cannot be powered on, while the fuel replenishment process needs to be powered on, so these two types of support operations cannot be performed; Operations with a sequence: Some support operations can only be performed after other operations are completed, and have strict process constraints. The ammunition mounting operation of the corresponding hanging point can only be performed after the wings are unfolded; According to the above classification of operation types, it is concluded that the operation process in the maintenance service support operation process can be changed, so it is necessary to optimize the scheduling of maintenance service support operations under the variable process mode; A3: Maintenance personnel can be divided into Kp different professions. They perform a series of maintenance procedures during the maintenance and service of maritime aircraft, including inspection and maintenance, replenishment of various required gases, replenishment of fuel, power supply, and ammunition mounting at the hanging point, to ensure that the maritime aircraft has the ability to be dispatched to perform tasks. When performing different procedures, maintenance personnel of different professions are required. It takes a certain amount of time for personnel to transfer between different maintenance positions in the deck obstacle network; A4: Service support equipment. The service support equipment required in the process of maritime aircraft support can be divided into Ke types. Each type of support equipment carries a type of service support resource to supply the resource consumption during the execution of the support operation, including fuel, hydraulic, oxygen and nitrogen. According to whether the resource location is fixed, each type of support equipment can be divided into fixed support equipment station and mobile support vehicle. The fixed equipment station can provide the maritime aircraft within its coverage with the resources required to perform the corresponding support operation. The mobile support vehicle moves in the deck environment and can provide support for maritime aircraft parked at any location. A5: To ensure the operation workstation space, a certain amount of space resources are required when executing the maintenance operation process. Only the limitation of the workstation space on the number of maintenance support personnel is considered. The cockpit of the offshore aircraft can only accommodate one person working at the same time, while there is workstation space for operations outside the cockpit.

[0015] In this embodiment, the support equipment can be divided into shared support equipment and exclusive support equipment according to the number of processes that can be supported at the same time. Shared support equipment can meet the support of multiple processes at the same time. The power supply provided by the power station (car) can simultaneously support multiple processes such as avionics appearance inspection, cockpit inspection and fuel replenishment; exclusive equipment can only support one corresponding process at any time. Hydraulic equipment stations (cars), gas stations (cars), etc. are all exclusive equipment.

[0016] Example 2 like Figure 1-7 As shown, based on Example 1, the present invention provides a technical solution: preferably, step 2 includes the following steps: B1: Model assumptions. To establish the scheduling optimization model, the following assumptions are made: ① Assuming that a certain number of one-stop support parking stands are set up on the deck of the offshore platform, one-stop support operations can be achieved at the parking stands. Assuming that the service support resources at each parking stand are sufficient for non-one-stop support parking stands, centralized support can be achieved for offshore aircraft at the parking stands. ② Assume that the support range of maintenance personnel and service support vehicles can cover all support parking positions on the deck; ③ Ensure that the operation cannot be interrupted during execution; ④ There are sufficient support resources stored on the offshore platform to fully meet the needs of various support tasks; ⑤ The speed of the ammunition transport vehicle is only related to the type of vehicle, but has nothing to do with its carrying capacity; B2: Constraints. According to the characteristics and workflow of maintenance operations, the conditions under which the current process Oij can be started can be expressed as an AND gate logic. The current process can only be started when the four prerequisites are met at the same time. B3: Objective function. The purpose of optimizing the scheduling of maritime aircraft maintenance support operations is to complete the support operations as early as possible. Therefore, the objective function is set to minimize the support completion time. The constraints for executing maintenance support operations in B2 are divided into three categories: support personnel constraints, support resource constraints, and operation process constraints. At the same time, when the operation process involves resources, the constraints of the ammunition distribution process need to be considered. The support personnel constraint means that the support personnel Kp corresponds to 4 professional categories, namely: I, II, III, IV, is the set of support personnel of the kth (k∈Kp) professional category, The number of k-th type of support personnel required for process Oij is recorded as The personnel constraints mainly include the constraints on the number of personnel required for the operation process and the time constraints for personnel to transfer between different workstations. in, is a 0-1 decision variable, satisfying formula (3); To ensure the connection variables between personnel in the processes, equation (4) is satisfied; is the variable for matching the support personnel between processes, satisfying formula (5); S eg is the guaranteed start time of process Oeg; is the guaranteed completion time of process Oij; B is a large real number that makes the inequality always hold; J is the set of all the operation processes in the guarantee task that satisfies equation (6); S ij , F ij They are the start guarantee time and the completion guarantee time of the process respectively;

[0017] Among them, i, e are the numbers of the seaplanes; j, g are the corresponding operation process numbers of the seaplanes i, e; Support resource constraints refer to the support resources that have corresponding support equipment to carry. The constraints are reflected by the support equipment. There are 6 types of support equipment Ke on the deck, namely: fuel station / cart, power station / cart, oxygen station / cart, nitrogen station / cart, hydraulic station / cart, and ammunition transporter. This part mainly considers the constraints related to the first 5 types of support equipment. is the mth (m∈Ke) type of security equipment set, is the number of type m support equipment required for process Oij. For exclusive support equipment, the constraints mainly consider the constraints on the number of personnel required for the operation process, the coverage constraints of the support equipment, and the transfer time constraints of the support equipment between process locations. in, is a 0-1 decision variable, satisfying formula (10); To ensure the connection variables between personnel in the processes, equation (11) is satisfied; is the guarantee equipment matching variable between processes, satisfying formula (12); Indicates the protection equipment The transfer process between two adjacent process locations is time-consuming; The operation process constraints refer to the operation process of the maintenance service of the maritime aircraft. The process constraints mainly include the constraints of the preceding process, the conflicting process constraints caused by the space constraints and the power supply usage matching constraints, the priority sequence constraints of the completion time, and the constraints of the start conditions of the guarantee task. Among them, Y ijeg is a 0-1 decision variable, satisfying formula (19); P re (O eg ) is process O eg The set of immediate predecessor processes is shown in Figure 3 Processes connected by arrow lines; C on (O eg ) is the same as process O eg For a set of processes that cannot be executed simultaneously due to space constraint conflicts or power matching constraint conflicts, formula (16) ensures that the execution time periods of the conflicting processes have no intersection; d ij For process O ij Working hours; Complete tethered time for seaplane i.

[0018]

[0019] In this embodiment, for shared support equipment, constraint (9) needs to be supplemented. For the current process Oeg, first determine whether its maintenance personnel meet the constraint time t1. Figure 5 If the requirement is met, replace constraint (9) with equation (13). Otherwise, execute constraint (13). Figure 5 As shown, for shared equipment, it is determined whether there is a process Oej that requires this type of shared equipment being executed on the same seaplane e. When the possible start time S(Oeg) of the process Oeg satisfies formula (14) (yellow rectangular block), the shared equipment that executes the process Oej can be directly selected.

[0020]

[0021] Example 3 like Figure 1-7 As shown, based on Example 1, the present invention provides a technical solution: Preferably, step three includes the following steps: C1: DE algorithm, DE is a population-based adaptive global optimization algorithm, its main process includes: ① Mutation: Mutation mainly updates the position of the current individual through the difference between vectors. The following mutation method is used here: Where t is the current iteration number; V h (t) is the individual after mutation; is the individual with the best fitness value in the current iterative population; A random number selected by the crowd that is different from Xh (t) 3 random individuals; F is the scaling factor, which is used to control the scaling ratio of the difference vector; ② Crossover: The new individual V h (t+1) and the corresponding individual X in the contemporary population h (t) Perform a crossover operation to generate new offspring individuals. Among them, CR is the crossover probability; randh is a random integer between 1 and individual length N; ③Selection: In the parent individual X h (t) and the offspring individual U h (t) to select individuals with higher fitness and save them to the next generation. Among them, f(·) calculates the objective function corresponding to the individual; C2: DE algorithm process; C2 includes population initialization, fitness evaluation, support personnel allocation rules, and support equipment allocation rules. In population initialization, Bigler compared and analyzed the random key encoding and task list encoding commonly used in RCPSP problems. For task list encoding, mutation operations can be used, so random key encoding is adopted. The random key rij∈(0,1) represents the scheduling priority of process Oij. The smaller the rij value is, the higher the scheduling priority of process Oij is. For the maintenance service support operation containing I number of maritime aircraft, it can be encoded as, Since the Cubic mapping has good chaotic ergodicity, the Cubic mapping method is used to initialize the individuals in the population. Where xn is the n-th dimension code in X; ρ is a parameter, and takes x 1 ∈uniform(0.2,0.4), ρ=2.595; The decoding process in fitness evaluation is to map the code into a scheduling plan, including the start time, end time, support personnel and equipment allocation of each operation process, and then calculate the fitness function value corresponding to the code. SSGS is used for decoding. According to the small proportion of the number of the preceding process pairs in the problem, the codes of the corresponding positions of the preceding process pairs in the single-machine operation process are sorted by size, so that when the code values ​​are decoded in ascending order, the current process O ij The corresponding immediate predecessor process P re (O ij ) has completed the scheduling, that is, O ijis schedulable, and then define the scheduled process set Ab and the unscheduled process set Db. In the decoding process with a total of |J| stages, select the individual O with the highest priority in the set Dg in turn. ij , and executes four decisions for it: ① Arrange maintenance support personnel and obtain the earliest start time t that satisfies the maintenance personnel constraints 1 ; ② Arrange the service support equipment and obtain the earliest start time t that meets the support equipment constraints 2 ; ③ According to the constraints of the immediate predecessor process, perform time scheduling to obtain the earliest guaranteed start time t that satisfies constraint (15) 3 ④ According to the conflicting process constraints, perform time scheduling to obtain the earliest guaranteed start time t that satisfies constraint (16) 4 ; Then, according to formula (26-27) calculate step O ij Start guarantee time S ij and end guarantee time F ij , and update the information of equipment and personnel; finally, let process O ij The code of the corresponding position is assigned with value B, which is added to the scheduled process set and transferred to the next scheduling stage. When all processes are scheduled, the scheduling plan is output and the objective function value f(X) is calculated. S ij =max{t 1 , t 2 , t 3 , t 4} j ∈J (26); F ij =S ij +d ij O ij ∈J (27); The allocation rule of support personnel can be set according to the objective function of the scheduling problem. The specific steps are as follows: ① Calculate the k-th category (k∈Kp) support personnel Complete the previous process O ij End time ② Find the time it takes for the support personnel to transfer from the previous process position Oij to the current process Oeg ③ According to formula (28), the process support personnel are calculated have, Then we can calculate Figure 6 The earliest possible start time t that satisfies the support personnel constraints 1 , The support equipment allocation rule means that the support equipment on the deck includes fuel stations / carts, hydraulic stations / carts, nitrogen stations / carts, oxygen stations / carts, power stations / carts and ammunition handling vehicles. According to the assumptions, the resources carried by the support equipment other than the ammunition handling vehicle can generally meet the resource usage requirements of the current support mission. For this type of support equipment, the specific resource number allocated can be calculated using similar rules in the support personnel allocation rule. And calculate the earliest start time t that satisfies the guarantee equipment constraints 2 .

[0022]

[0023] Example 4 like Figure 1-7 As shown, based on Example 1, the present invention provides a technical solution: preferably, Figure 1 The Ford offshore platform deck shown in the figure is used as an experimental platform for the maintenance and service support operations of the offshore aircraft fleet. In order to facilitate the simulation comparison of the maintenance and service support operation scenarios under different support task scales, the offshore aircraft deck support operation scheduling based on the variable process mode is set to include the execution of two types of combat tasks (XI, XII). The task scale is 6 aircraft. For the single aircraft support operation, the following is constructed Figure 2 The coverage of the deck fixed support equipment station is shown in the following table.

[0024] The ammunition transporter can cover all parking spaces, so it is not listed in the table. In addition, a certain number of mobile support equipment vehicles are equipped to cover all parking spaces on the deck. The configuration of support personnel is set according to the experience of the dispatcher: 3 people for professional I, 8 people for professional II, 18 people for professional III, and 12 people for professional IV. Each process requires 1 corresponding professional number. According to the above description, the simulation case is set as shown in the following table.

[0025] Figure 2 In the operation process shown, the types of support personnel and equipment required for each operation process, as well as the time consumption of each support operation process of the sea aircraft performing different combat missions, are simulated for support task 1. The IPSO algorithm parameters are set as follows: population size 50, maximum decoding times 15000, inertia weight 0.72984, cognitive factor and social factor are both taken as 0.49618, the particle speed value range of each dimension is [-0.2, 0.2], the boundary processing measure is random initialization within the interval, and the configuration is Core TMThe IPSO algorithm was implemented using Python 3.9.13 Spyder 5.2.2 on a laptop with an i7 processor and 16GB RAM. The Gantt chart of the completion time of each sea aircraft support corresponding to the algorithm results was obtained. Figure 6 As shown, the guaranteed task completion time is 39.93 minutes.

[0026] In this embodiment, in the following table,

[0027] “-” indicates that the corresponding personnel or equipment are not needed. When the ammunition retrieval operation is not required in the support mission, the operation time is set to 0. Since the number of support equipment required is sufficient and can meet the demand at any time, it is equivalent to not requiring support equipment. The results generated by the algorithm can meet the support personnel, equipment and process constraints proposed in the scheduling of maritime aircraft support operations under the variable operation process mode, as well as the shared equipment constraints, which shows that the established model and algorithm can effectively solve the scheduling problem of maritime aircraft support operations based on the variable process mode. In order to verify the advantages of the variable operation process proposed in this paper over the original operation process, according to the constraint model established in step 2 and the mission field parameters established above, the IPSO algorithm proposed above is used to achieve the following Figure 7 The fixed operation process maintenance support operation scheduling optimization problem shown in the figure is solved, and it is found that under the same task scenario, the completion time of the support operation in the fixed operation process mode is 53.60 minutes, and the reduction ratio r of the completion time of the support task is calculated by the following formula: Among them, f fixed Ensure scene completion time for fixed work process; var The variable operation process guarantees the completion time of the task scenario. It is calculated that under the same operation scenario, the guaranteed completion time under the variable operation process mode can be shortened by 25.5% compared with the fixed operation process, which illustrates the advantages of the variable operation process.

[0028] The working principle of the method for scheduling maritime aircraft support operations based on variable operation processes will be described in detail below.

[0029] like Figure 1-7As shown in the figure, the operation process of aircraft maintenance service support at sea is described, and the operations that need to be supported in the process are classified, including a set of operations that can be supported at the same time without sequence, a set of operations that cannot be supported at the same time, and a set of operations with a guaranteed sequence; secondly, the problem is abstracted into a resource-constrained multi-project scheduling problem model based on a variable operation process, and the guaranteed operation completion time is used as the optimization indicator. The differential evolution algorithm DE is used to ensure that the algorithm is effective and verify the superiority and robustness of the algorithm performance; finally, by comparing it with the maintenance service support operation scheduling method based on a fixed operation process, the advantages of the maintenance service support operation scheduling based on the variable process mode are verified.

[0030] The present invention has been generally described in detail above, but it is obvious to those skilled in the art that some modifications or improvements may be made to the present invention. Therefore, modifications or improvements that do not depart from the spirit of the present invention are within the scope of protection of the present invention.

Claims

1. A method for scheduling offshore aircraft support operations based on a variable operation process, characterized in that: The following steps are involved: Step 1: Problem description; Step 2: Deck support-ammunition transfer integrated scheduling model; Step 3: Design of scheduling optimization algorithm based on differential evolution algorithm DE; In the step 1, during the operation execution process, Kp types of maintenance personnel with different professions are required to perform inspection and maintenance and various resource replenishment operations before the sea aircraft is dispatched in a complex deck environment, and Kq types of service support equipment provide maintenance personnel with Kr types of supply resources required for maintenance support operations, so that the sea aircraft has the ability to be dispatched again; the step 2 refers to establishing a sea aircraft deck support-ammunition transfer integrated scheduling model under a variable process mode, and reducing it to a resource-constrained multi-project-resource distribution integrated scheduling problem based on a variable operation process; the step 3 refers to that from the problem description and optimization model, compared with the general RCPSP problem, the resource-constrained multi-project-resource distribution integrated scheduling problem has the following characteristics: the resources involved in the maintenance service support operation include maintenance support manpower, service support equipment, support resources, and resource transport vehicles. These resources are special. The resource distribution process and aircraft refueling operations have special requirements on the demand and use of resources. With the increase in the number of aircraft in the dispatch mission, the scale of the problem increases sharply. It is necessary to consider the transfer of various service support equipment and maintenance support personnel between different process positions, and use the DE algorithm to solve the problem.

2. The method for scheduling offshore aircraft support operations based on a variable operation process according to claim 1, characterized in that: The step 1 includes the following contents: A1: Deck operating environment. Compared with land airports, the deck area is particularly small. A series of complex operations such as recovery, parking, maintenance and departure of offshore aircraft need to be completed in a limited space. At the same time, the island, deck boundary and deployed offshore aircraft on the deck together form a complex obstacle network. A2: Classification of support operations. After outbound transfer or recovery to the support parking position, support operations need to be performed. Among them, operations 0 and 24 are virtual start and end processes. They do not consume support resources and take 0 time when executed. For the remaining operations, they can be divided into three categories according to their execution location requirements, support resource requirements and support process requirements: Operations that have no sequence and can be performed simultaneously: A large number of operations that need to be performed during the support process have no strict execution sequence constraints, resource demand conflicts and space constraints. Operations that have no sequence but cannot be performed simultaneously: mainly include operations with conflicting operation spaces and operations with conflicting power supply requirements. The ammunition mounting process cannot be powered on, while the fuel replenishment process needs to be powered on, so these two types of support operations cannot be performed; Operations with a sequence: Some support operations can only be performed after other operations are completed, and have strict process constraints. The ammunition mounting operation of the corresponding hanging point can only be performed after the wings are unfolded; According to the above classification of operation types, it is concluded that the operation process in the maintenance service support operation process can be changed, so it is necessary to optimize the scheduling of maintenance service support operations under the variable process mode; A3: Maintenance personnel can be divided into Kp different professions. They perform a series of maintenance procedures during the maintenance and service of maritime aircraft, including inspection and maintenance, replenishment of various required gases, replenishment of fuel, power supply, and ammunition mounting at the hanging point, to ensure that the maritime aircraft has the ability to be dispatched to perform missions. When performing different procedures, maintenance personnel of different professions are required. It takes time for personnel to transfer between different maintenance positions in the deck obstacle network; A4: Service support equipment. The service support equipment required in the process of maritime aircraft support can be divided into Ke types. Each type of support equipment carries a type of service support resource to supply the resource consumption during the execution of the support operation, including fuel, hydraulic, oxygen and nitrogen. According to whether the resource location is fixed, each type of support equipment can be divided into fixed support equipment station and mobile support vehicle. The fixed equipment station can provide the maritime aircraft within its coverage with the resources required to perform the corresponding support operation. The mobile support vehicle moves in the deck environment and can provide support for maritime aircraft parked at any location. A5: The space for maintenance workstations is the space resource usually needed to perform maintenance work procedures. Only the limitation of the workstation space on the number of maintenance personnel is considered. The cockpit of a seaplane can only accommodate one person at a time, while there is usually workstation space for operations outside the cockpit.

3. The method for scheduling offshore aircraft support operations based on a variable operation process according to claim 1 is characterized in that: The step 2 comprises the following steps: B1: Model assumptions. To establish the scheduling optimization model, the following assumptions are made: ① Assuming that a one-stop support parking position is set up on the deck of the offshore platform, one-stop support operations can be achieved at this parking position, and assuming that the service support resources at each parking position are sufficient for non-one-stop support parking positions, centralized support can be achieved at the parking position for offshore aircraft; ② Assume that the support range of maintenance personnel and service support vehicles can cover all support parking positions on the deck; ③ Ensure that the operation cannot be interrupted during execution; ④ There are sufficient support resources stored on the offshore platform to fully meet the needs of various support tasks; ⑤ The speed of the ammunition transport vehicle is only related to the type of vehicle, but has nothing to do with its carrying capacity; B2: Constraints. According to the characteristics and workflow of maintenance operations, the conditions for the current process Oij to start execution can be expressed as "AND" gate logic. Only when the four prerequisites are met at the same time can the current process start. B3: Objective function. The purpose of optimizing the scheduling of maritime aircraft maintenance support operations is to complete the support operations as early as possible. Therefore, the objective function is set to minimize the support completion time. （20）。 4. The method for scheduling offshore aircraft support operations based on a variable operation process according to claim 3 is characterized in that: The constraints for executing the maintenance support operation in B2 are divided into three categories: support personnel constraints, support resource constraints and operation process constraints. At the same time, when the operation process involves resources, the ammunition distribution process constraints need to be considered. The support personnel constraints refer to the support personnel Kp corresponding to 4 professional categories, namely: I, II, III, IV, For the A collection of professional security personnel. ; The number of k-th type of support personnel required for process Oij is recorded as ,The staff constraints mainly include the staff quantity constraints of the operation process and the ,transfer time constraints of staff between different work stations. （1）； （2）； in, is a 0-1 decision variable, satisfying formula (3); To ensure the connection variables between processes, equation (4) is satisfied; is the variable for matching the support personnel between processes, satisfying formula (5); is the guaranteed start time of process Oeg; is the guaranteed completion time of process Oij; B is a large real number that makes the inequality always hold; J is the set of all the operation processes in the guarantee task, satisfying equation (6); They are the start guarantee time and the completion guarantee time of the process respectively; （3）； （4）； （5）； （6）； Where i, e are the numbers of the seaplanes; j, g are the numbers of the corresponding operation procedures in seaplanes i, e; The support resource constraint means that the support resources are carried by the corresponding support equipment, and its constraint is also reflected by the support equipment. There are 6 types of support equipment Ke on the deck, namely: fuel station / car, power station / car, oxygen station / car, nitrogen station / car, hydraulic station / car, and ammunition transporter. This part mainly considers the constraints related to the first 5 types of support equipment. For the A collection of security equipment, ; is the number of type m support equipment required for process Oij. For exclusive support equipment, the constraints mainly consider the constraints on the number of personnel required for the operation process, the coverage constraints of the support equipment, and the transfer time constraints of the support equipment between process locations. （7）； （8）； （9）； in, is a 0-1 decision variable, satisfying formula (10); To ensure the connection variables between personnel in the processes, equation (11) is satisfied; is the guarantee equipment matching variable between processes, satisfying formula (12); Indicates the protection equipment The transfer process between two adjacent process locations is time-consuming; （10）； （11）； （12）； The operation process constraints refer to the operation process of the maintenance service of the maritime aircraft. The process constraints mainly include the preceding process constraints, the conflicting process constraints caused by the space constraints and the power supply usage matching constraints, the priority sequence constraints of the completion time, and the task start condition constraints. （15）； （16）； （17）； （18）； in, is a 0-1 decision variable, satisfying formula (19); For process The set of immediate predecessor processes, For the process For a set of processes that cannot be executed simultaneously due to space constraint conflicts or power matching constraint conflicts, formula (16) ensures that the execution time periods of the conflicting operations have no intersection; For process Working hours; Complete mooring time for seaplane i, （19）。 5. The method for scheduling offshore aircraft support operations based on a variable operation process according to claim 1, characterized in that: The step three comprises the following steps: C1: DE algorithm, DE is a population-based adaptive global optimization algorithm, its main process includes: ① Mutation: Mutation mainly updates the position of the current individual through the difference between vectors. The following mutation method is used here: （21）； Where t is the current iteration number; For the individual after mutation; is the individual with the best fitness value in the current iterative population; Randomly selected by the masses ; F is the scaling factor, which is used to control the scaling ratio of the difference vector; ② Crossover: New individuals Corresponding individuals in the contemporary population Perform a crossover operation to generate new offspring individuals. （22）； Among them, CR is the crossover probability; randh is a random integer between 1 and individual length N; ③Selection: In the parent individual and offspring individuals Select between them and save the individuals with higher fitness to the next generation. （23）； in, Calculate the objective function corresponding to the individual; C2: DE algorithm flow.

6. The method for scheduling offshore aircraft support operations based on a variable operation process according to claim 5, characterized in that: The C2 includes population initialization, fitness evaluation, support personnel allocation rules, and support equipment allocation rules. In the population initialization, Bigler compared and analyzed the random key encoding and task list encoding commonly used in the RCPSP problem. For the task list encoding, the mutation operation can be used, so the random key encoding method is adopted. The random key rij∈(0,1) represents the scheduling priority of the process Oij. It is defined that the smaller the rij value is, the higher the scheduling priority of the process Oij is. For the maintenance service support operation containing I number of maritime aircraft, it can be encoded as: （24）； Since the Cubic mapping has good chaotic ergodicity, the Cubic mapping method is used to initialize the individuals in the population. （25）； Where xn is the nth dimension code in X; As a parameter, and take , =2.595; The decoding process in the fitness evaluation is to map the code into a scheduling plan, including the start time, end time, support personnel and equipment allocation of each operation process, and then calculate the fitness function value corresponding to the code, and use SSGS for decoding. According to the small proportion of the number of the preceding process pairs in the problem, the codes of the corresponding positions of the preceding process pairs in the single-machine operation process are sorted by size, so that when the code values ​​are decoded in ascending order, the current process Corresponding preceding process The scheduling has been completed, that is is schedulable, and then define the scheduled process set Ab and the unscheduled process set Db. In the decoding process with a total of |J| stages, select the individuals with the highest priority in the set Dg in turn. , and executes four decisions for it: ① Arrange maintenance personnel and obtain the earliest possible maintenance start time that meets the maintenance personnel constraints ; ② Arrange service support equipment and obtain the earliest possible start time that meets the support equipment constraints ; ③ According to the constraints of the immediate predecessor process, perform time scheduling to obtain the earliest guaranteed start time that satisfies constraint (15) ④ According to the conflicting process constraints, perform time scheduling to obtain the earliest guaranteed start time that satisfies constraint (16) ; Then, according to formula (26-27) the process is calculated Start guarantee time and end of guarantee time , and update the support equipment and personnel information; finally, order the process The code of the corresponding position is assigned with value B, which is added to the scheduled process set and transferred to the next scheduling stage. When all processes are scheduled, the scheduling plan is output and the objective function value f(X) is calculated. （26）； （27）； The security personnel allocation rule can be set according to the objective function of the scheduling problem. The specific steps are as follows: ① Calculate the kth category Support staff Complete the previous process End time ; ② Find the time it takes for the support personnel to transfer from the previous process position Oij to the current process Oeg ; ③ According to formula (28), the process support personnel are calculated ,have, （28）； Then we can calculate the earliest possible start time of support that satisfies the support personnel constraints in Figure 6: , （29）； The support equipment allocation rule means that the support equipment on the deck includes gas stations / cars, hydraulic stations / cars, nitrogen stations / cars, oxygen stations / cars, power stations / cars and ammunition transport vehicles. According to the assumptions, the resources carried by the support equipment other than the ammunition transport vehicle can meet the resource usage requirements of the current support mission. For this type of support equipment, the specific resource number to be allocated can be calculated using similar rules in the support personnel allocation rule. , and calculate the earliest possible start time that satisfies the guarantee equipment constraints .

Images