CN114037346A - Generation method and device of intelligent flight unit group ring - Google Patents

Generation method and device of intelligent flight unit group ring Download PDF

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CN114037346A
CN114037346A CN202111415694.1A CN202111415694A CN114037346A CN 114037346 A CN114037346 A CN 114037346A CN 202111415694 A CN202111415694 A CN 202111415694A CN 114037346 A CN114037346 A CN 114037346A
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郭斯琪
肖璠
谢可欣
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Hangzhou Youmaikesi Information Technology Co ltd
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Abstract

The method comprises the steps that all duty days meeting rule conditions are searched according to basic data of the intelligent flight unit, and a duty day set is obtained; constructing a flight group ring network diagram according to the attendance day set; constructing a flight group ring model based on the to-be-scheduled flight set and the initial task ring set; using a branch pricing method to solve a main problem of the flight group ring model to obtain a feasible task ring; and searching an optimized path solved by the main problem of the flight group ring model by using a multi-label shortest path algorithm to obtain an optimized task ring, solving the flight group ring model according to the feasible task ring and the optimized task ring of each flight, and determining a group ring scheme of the intelligent flight unit. Therefore, the quality and robustness of the scheme can be ensured in limited solving time, and the method has higher research significance and application value.

Description

Generation method and device of intelligent flight unit group ring
Technical Field
The application relates to the field of computers, in particular to a method and equipment for generating an intelligent flight unit group ring.
Background
The aviation industry develops to the present, the resource allocation of each airline company in China still adopts a manual allocation form, and the quality of the scheduling scheme mainly depends on the rich experience of a responsible person. With the improvement of the living standard of people, the requirement for the trip of the airplane is rapidly increased, the size of the airplane fleet is rapidly expanded, and the air line network is increasingly complex. The 2020-year civil aviation industry development statistical bulletin issued by the China civil aviation administration in 2021 shows that in 2020, the nationwide passenger and air company executes 352.06 ten thousand flights, wherein 311.64 ten thousand flights are normal, and the average flight normal rate is 88.52%. Although the number of operating flights is influenced by the COID-2019 new crown epidemic situation, the development of the flight lines and the expansion of the size of the fleet continue, and as far as the end of 2020, China has 64 transport airlines, 3903 transport airplanes and 5581 regular flight lines.
An aircraft crew typically refers to all pilots participating in driving a flight, configured as a minimum of two, captain and copilot. When the flight time or the duty time is longer, the aircraft crew is selected to be expanded, namely the number of the aircraft crew members exceeds the minimum value required by the aircraft model for operating the aircraft, so that one aircraft crew member can be replaced by other qualified aircraft crew members, and the replaced aircraft crew member can rest in the flight.
According to the regulations of the civil aviation bureau, any crew member must arrange a continuous 48-hour rest period within 144 hours before executing a flight task or performing primary backup, and in order to reduce the problem solving difficulty and ensure that the crew member takes a 48-hour rest in the base to which the crew member belongs, the crew scheduling problem is generally divided into a crew ring and two sub-problems assigned. The group ring stage is to complete the series connection of all the tasks of scheduled flights, backups and the like in the planning period to obtain a plurality of task strings which start from the base and finally return to the base, wherein the duration time is not more than 96 hours, namely, generally not more than 5 calendar days. The flight hour cost of the crew, the overnight patch of the crew, the cost of taking a car or a plane, and the like, mainly depend on the construction process of the mission loop, and in addition, the flight time margin, the flight attendance time margin, the rest time margin, and the like related to the planning robustness also need to be adjusted in the loop formation stage.
For the problem of the unit group ring, besides the problem scale is increased due to the increase of the service volume, the complexity of problem solution is also increased due to the fact that the refined working rules are continuously updated by the 121-part regulation of the civil aviation bureau and the personalized service requirements supplemented by each aviation department. At present, the main implementation scheme is manual loop formation, which is mainly based on flight plans and airline structures, and takes meeting task loop compliance as the first premise, adds necessary lift or lift setting, and connects all flights to be scheduled in a planning period in series to form a task loop set. Under such a large and complicated aviation network, in the face of complicated scheduling rules, the scheduling and allocation of resource scheduling personnel are gradually unconscious, and the importance of informatization and automation is increasingly prominent. The quality of the loop-forming scheme reflects the utilization efficiency of unit resources on the whole, and on the other hand, the robustness of the loop-forming scheme also reflects the possibility of flight chain delay caused by unit reasons in the actual operation process to a certain extent.
Disclosure of Invention
An object of the application is to provide a method and equipment for generating an intelligent flight unit group ring, and the problems that in the prior art, the group ring service is completely developed manually, time and labor are wasted, more errors are easily caused by manual completion, the unit group ring cannot be optimized globally, and the limitation is obvious are solved.
According to one aspect of the application, a method for generating an intelligent aircraft crew loop is provided, and the method comprises the following steps:
searching all the attendance days meeting rule conditions according to basic data of the intelligent flight set to obtain an attendance day set, wherein the rule conditions comprise rules of civil aviation bureau regulation limits and group ring scene configuration;
constructing a flight group ring network diagram according to the attendance day set;
constructing a flight group ring model based on a to-be-scheduled flight set and an initial task ring set, wherein the flight group ring model comprises a model objective function and a constraint condition;
using a branch pricing method to solve a main problem of the flight group ring model to obtain a feasible task ring of each flight;
and searching an optimized path solved by the main problem of the flight group ring model by using a multi-label shortest path algorithm to obtain an optimized task ring, solving the flight group ring model according to the feasible task ring and the optimized task ring of each flight, and determining a group ring scheme of the intelligent flight unit.
Optionally, searching out all dates before the duty meeting the rule condition according to the basic data of the intelligent flight unit includes:
acquiring basic data related to scheduling of the intelligent flight unit;
and determining the solving preference of the group ring scheme according to the basic data and configuring the rule of the group ring scene.
Optionally, constructing a flight group ring network map according to the collection of attendance days includes the following steps:
determining a plan starting date and a plan ending date of each personnel base, each personnel task according to the duty day set;
for any personnel base, according to the maximum continuous calendar day number of the task ring set in the scene configuration, respectively constructing a space-time network graph with the duration of one to the maximum continuous calendar day number of the task ring for each day from the plan starting date to the plan ending date;
and screening out target attendance days which need to be added into the space-time network diagram in the attendance day set according to a screening rule, and setting a connecting arc between the attendance days which meet the rules of place connection, rest rules and scene configuration in the civil aviation bureau regulation limit so as to complete the construction of the flight group ring network diagram.
Optionally, the screening rule comprises the following steps:
if the date corresponding to the starting moment of the attendance day is equal to the starting date of the space-time network diagram, continuously judging whether the starting airport of the attendance day is the corresponding personnel base or not, and if so, adding the space-time network diagram;
if the date of the attendance day is equal to any date in the middle of the spatio-temporal network diagram, directly joining;
if the date corresponding to the ending time of the attendance day is equal to the ending date of the space-time network diagram, whether the arrival airport of the attendance day is the corresponding personnel base or not is continuously judged, and if yes, the arrival airport of the attendance day is added.
Optionally, constructing a flight group ring model based on the to-be-scheduled flight set and the initial task ring set to construct a flight group ring model, including:
determining a flight set to be scheduled and an initial task ring set, and setting a threshold value of a fixed integer variable;
constructing a model objective function of the flight group ring model according to the cost of each task ring in the initial task ring set, the decision variable selected by the group ring scheme of the task ring and the set of all generated task rings in the planning period;
and determining the constraint conditions of the flight group ring model according to the constraints on set division and the constraints on variable values.
Optionally, the model objective function represents a total cost of minimizing a group ring solution, the model objective function satisfying the following condition:
Figure BDA0003375175510000041
wherein p represents a task ring, cpCost, x, of the representation task ring ppA decision variable of 0 or 1 indicates whether the task ring P is selected in the final group ring solution, P representing the set of all generated task rings during the planning period.
Optionally, the constraint condition satisfies the following condition:
Figure BDA0003375175510000042
Figure BDA0003375175510000043
wherein, L represents the set of scheduled flights and L represents the planned flight segment.
Optionally, the flight group ring model is solved by using a branch pricing method, wherein the main problem solving comprises the following steps:
step 1, judging whether the current solution is an integer solution, if not, executing step 2, otherwise, exiting to obtain a new flight group ring scheme;
step 2, set
Figure BDA0003375175510000044
Representing the resulting group ring scheme; when x is satisfiedp≥κ1Then, corresponding xpJoining collections
Figure BDA0003375175510000045
Wherein, κ1A threshold value representing a fixed integer variable;
and step 3: for the
Figure BDA0003375175510000046
Setting xpLower bound LB (x)p) If there is another task ring p' containing the same flight l as the task ring p, the variable value x corresponding to the task ring is setp′Upper bound UB (x)p′) 0, indicating that task ring p' is eliminated;
and 4, step 4: and solving the linear relaxation solution of the main problem of the flight group ring model.
Optionally, finding an optimized path of the solution of the main problem of the flight group ring model by using a multi-label shortest-path algorithm to obtain an optimized task ring, including:
searching an optimized path of the main problem solution of the flight group ring model based on the constructed flight group ring network diagram by using a multi-label shortest path algorithm;
if a group of task rings beneficial to the main problem solution optimization is found, adding the group of task rings into a task ring set, and skipping to the step 1;
and when a task ring beneficial to the optimization of the main problem solution cannot be found, jumping to the following steps: and constructing a flight group ring model corresponding to the flight group ring network diagram.
Optionally, finding an optimized path of a main problem solution of the flight group ring model based on the constructed flight group ring network diagram by using a multi-label short-circuit algorithm includes the following steps:
step S1, initializing labels of all nodes in the flight group ring network, wherein the labels comprise a value day set and a total check number contained in the current partial path;
step S2, traversing each node in turn according to the topological order, and obtaining the set of the subsequent nodes, if the traversal is finished, executing step S5, otherwise executing step S3;
step S3, for any label in the node and any node in the subsequent node set, rule checking is carried out according to the rule condition, if the check is that the rule condition is satisfied, the step S4 is skipped, and if the check is that the rule condition is not satisfied, the step S3 is executed again;
step S4, generating a new label according to the label meeting the rule condition and the content of the target node in the subsequent node set successfully verified, performing dominance judgment on the new label and all labels existing in the target node, if the verification number of any label existing in the target node is smaller than the new label, not reserving the new label, otherwise, deleting the label dominated by the new label in the labels existing in the target node, and adding the new label into the label set of the target node;
step S5, traversing all tags on the task ring end nodes in the flight group ring network, and if the check number recorded in the tags is less than 0, taking the task ring corresponding to the path recorded by the tags as an optimized path for solving the main problem of the flight group ring model.
Optionally, the method comprises:
and counting evaluation indexes according to the loop combination scheme, wherein the evaluation indexes comprise average flight hours on duty day, total set times, total airplane change times, total times of long flights and station passing, total loop combination for continuously executing early shifts, total loop combination for continuously executing late shifts, unit cost and temporary overnight station number of the flight units.
Optionally, the group ring scene configuration includes a number of task ring maximum duration calendar days, a number of task ring continuous flight calendar days, a number of continuous setting times, a number of departure and departure times in a flight duty period, a first class definition setting, a second class definition setting, a flight connection type setting, an airport non-serializable group limit, and a base requirement.
According to another aspect of the present application, there is also provided an intelligent flight crew loop generation device, including:
one or more processors; and
a memory storing computer readable instructions that, when executed, cause the processor to perform the operations of the method as previously described.
According to yet another aspect of the present application, there is also provided a computer readable medium having computer readable instructions stored thereon, the computer readable instructions being executable by a processor to implement the method as described above.
Compared with the prior art, the method and the device have the advantages that all the duty days meeting the rule conditions are searched according to basic data of the intelligent flight unit, and the duty day set is obtained, wherein the rule conditions comprise rules of civil aviation bureau regulation limits and group ring scene configuration; constructing a flight group ring network diagram according to the attendance day set; constructing a flight group ring model based on a to-be-scheduled flight set and an initial task ring set, wherein the flight group ring model comprises a model objective function and a constraint condition; using a branch pricing method to solve a main problem of the flight group ring model to obtain a feasible task ring of each flight; and searching an optimized path solved by the main problem of the flight group ring model by using a multi-label shortest path algorithm to obtain an optimized task ring, solving the flight group ring model according to the feasible task ring and the optimized task ring of each flight, and determining a group ring scheme of the intelligent flight unit. . Therefore, the optimal solution or better solution of the unit group ring problem can be obtained in a short time, the quality and robustness of the scheme can be ensured in a limited solving time, and the method has higher research significance and application value.
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Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
fig. 1 illustrates a flow diagram of a method for generating an intelligent flight crew loop provided according to an aspect of the present application;
FIG. 2 is a diagram illustrating a format of a partial table for recording flight information in an embodiment of the present application;
FIG. 3 is a diagram illustrating a flight group ring network view of an attendance day in one embodiment of the present application;
FIG. 4 is a schematic diagram illustrating flight group ring branch pricing in an embodiment of the present application;
fig. 5 shows a schematic diagram of a flight path and a crew according to an embodiment of the present application.
The same or similar reference numbers in the drawings identify the same or similar elements.
Detailed Description
The present application is described in further detail below with reference to the attached figures.
In a typical configuration of the present application, the terminal, the device serving the network, and the trusted party each include one or more processors (e.g., Central Processing Units (CPUs)), input/output interfaces, network interfaces, and memory.
The Memory may include volatile Memory in a computer readable medium, Random Access Memory (RAM), and/or nonvolatile Memory such as Read Only Memory (ROM) or flash Memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, Phase-Change RAM (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), flash Memory or other Memory technology, Compact Disc Read-Only Memory (CD-ROM), Digital Versatile Disc (DVD) or other optical storage, magnetic cassette tape, magnetic tape storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory computer readable media (transient media), such as modulated data signals and carrier waves.
Fig. 1 shows a schematic flow diagram of a method for generating an intelligent flight crew loop according to an aspect of the present application, where the method includes: step S11 to step S15, wherein,
step S11, searching all duty days meeting rule conditions according to basic data of the intelligent flight unit to obtain a duty day set, wherein the rule conditions comprise rules of civil aviation bureau regulation restriction and group ring scene configuration; when the group ring of the intelligent flight unit is generated, firstly, the on-duty day is generated, and according to basic data such as flight, airplane, model and station passing time rule, all on-duty days meeting the civil aviation bureau regulation limit and the custom rule of group ring scene configuration are searched by using a depth-first search algorithm, so that an on-duty day set is obtained. The civil aviation bureau regulation limits are as follows: the upper limit of flight time, the upper limit of attendance day time, the lower limit of rest time and the like, and the rules of the configuration of the group ring scene are as follows: continuous setting is not allowed, the number of times of entering and exiting is not more than 2, certain two flights are not allowed to be connected in series, certain two airports are not allowed to appear in the same duty day, and the like; based on the characteristics of all flights, airports contained within the duty day, such as: the flight takes off and lands at the moment, the check-in time of the airport and the like, thereby calculating the characteristic data of the flight time, the check-in time, the check-out time and the like of each check-in day. If the scene is configured with early shift, late shift and the like, the corresponding attribute of each duty day can be judged according to the definition.
Step S12, constructing a flight group ring network diagram according to the attendance day set; and constructing the flight group ring network diagram according to the rest requirement and other rules according to the generated duty day set so as to convert the generation of the group ring into a subproblem to find the shortest path in the flight group ring network diagram.
Step S13, constructing a flight group ring model based on the to-be-scheduled flight set and the initial task ring set, wherein the flight group ring model comprises a model objective function and constraint conditions; when the group ring scheme is determined, a departure team ring model is constructed according to the initial task ring set and the to-be-scheduled flight set of the department, and the model is solved through conversion into the model so as to obtain a feasible group ring and an optimized group ring.
Step S14, using a branch pricing method to solve a main problem of the flight group ring model to obtain a feasible task ring; when the model is solved by using the branch pricing method, firstly, the flight group ring model is relaxed into a linear programming model, which is called as a main problem, so that the main problem is solved, dual variable values of each flight are obtained, and feasible task rings of each flight are obtained, namely, feasible task rings which can be judged to meet rule conditions are found out firstly.
Step S15, an optimized path of the main problem solution of the flight group ring model is found in the flight group ring network diagram by using a multi-label shortest path algorithm to obtain an optimized task ring, the flight group ring model is solved according to the feasible task ring of each flight and the optimized task ring, and a group ring scheme of the intelligent flight unit is determined. Searching an optimized path solved by the main problem of the flight group ring model by using a multi-label shortest path algorithm to obtain an optimized task ring, and continuously repeating the step until the optimized path cannot be obtained; in addition to solving the main problem of the model, a group of task rings beneficial to the main problem solution optimization are found based on the constructed flight group ring network diagram by using a multi-label shortest path algorithm, so that variables corresponding to the optimized task rings are added to the main problem model, the main problem model is the linear programming model, when the optimized task rings cannot be found, all variables contained in the main problem are subjected to rule judgment, the task rings meeting rule conditions are added into a feasible task ring set, and the group ring scheme of the intelligent flight unit is determined according to the finally obtained task ring set. Therefore, the optimal solution or better solution of the unit group ring problem can be obtained in a short time, the obtained group ring scheme is not only in compliance and meets the requirements of civil aviation bureau regulations and aviation department actual business, but also has actual availability, the fatigue level of the whole running unit and the balance of various tasks are controlled, the scientificity of unit resource arrangement is improved, and a good foundation is laid for the assignment of subsequent unit members.
In some embodiments of the present application, basic data related to the shift arrangement of the intelligent flight crew is obtained; and determining the solving preference of the group ring scheme according to the basic data and configuring the rule of the group ring scene. Here, data of basic elements related to the crew scheduling is acquired and converted into csv table data for use in subsequent models and algorithms, where the basic data includes airplane information (machine number, machine type, rest level, etc.), machine type information (machine type, sub-machine type, long and short machine type, etc.), airport information (airport four-code, airport three-code, city name, airport name, international and domestic attributes, etc.), flight information (planned departure and end airport, planned departure and end time, flight-taking airplane, flight attributes, etc.), set information (flight information of other transportation modes or other departments), and the like, and a format of a partial table in which the flight information is recorded is as shown in fig. 2. The method for adjusting the solution preference of the unit group ring scheme to be obtained by configuring the relevant parameters in the algorithm model can be divided into two types, namely a penalty classification and a limitation classification, wherein the penalty classification comprises penalty points of the unit group ring scheme, which cause the increase of the operating cost of the airline operator, for example: the number of days of the outer station overnight, the number of times of adding the unit by the driver, the number of times of trains and the like; penalties for the characteristics that cause the degree of fatigue of the units to rise, such as: the number of times of secondary entering and exiting, the number of times of continuous early and late shifts, the number of times of jumping in the morning and evening, and the like; penalties that cause the scheme robustness-reducing features, such as: the number of times of changing the airplane, the number of times of insufficient rest time margin, the number of times of too late continuous fourth flight sunset time and the like. The restriction classes include airport minimum time to cross the station requirement, on-duty time of flight and flight on-duty time restrictions, rest period requirements, and the like. And configuring rules of the group ring scene for converting the rule requirements and the personalized requirements in the actual group ring service scene of the unit into settings in a specific model and an algorithm logic and the like.
Continuing with the above embodiment, the configuration of the group ring scenario includes the maximum number of task ring duration calendar days, the number of task ring continuous flight calendar days, the number of continuous setting times, the number of times of entering and exiting within the flight duty period, the setting of the definition of early shift, the setting of definition of late shift, the setting of flight connection type, the limitation of non-cluster of airport, and the requirement of base. Here, the maximum number of the task ring continuous calendar days sets the maximum number of the allowed continuous calendar days including tasks such as setting, flight, backup and the like; the setting of the number of the continuous flight calendar days of the task ring is to set the maximum number of the allowed continuous calendar days with the flight tasks; the continuous setting times are set as the times of allowing the unit members to continuously take the setting in an attendance period, and when the continuous setting is not allowed, the setting times are set to be 1; the setting of the number of the entering and exiting fields in the flight attendance period is to set whether the pilot is allowed to leave the field for rest in the flight attendance period, and the allowed number of the entering and exiting fields can be further respectively set according to the actual situation of the airport; the early shift definition setting can define the early shift by limiting the time period of the attendance starting time, the time period of the attendance ending time and the like, so that the work and rest regularity can be met to a certain extent when the ring is formed; the night class definition setting can define the night class by limiting the time period of the attendance starting time, the time period of the attendance ending time and the like, so that the work and rest regularity can be met to a certain extent when a ring is formed; the flight fixed connection/connection forbidding/breakthrough connection setting can set the flight combination which must be connected in series or the flight combination which forbids to be connected in series according to the experience of business personnel or the actual operation requirement, and can break through the flight combination of the set scheduling rule; the limitation that the airport non-cluster groups are restricted is that certain airport cluster groups are prohibited from being in the same duty day; the base requirements are to limit the number of task rings that certain bases go out per day, etc.
In some embodiments of the present application, in step S12, determining a schedule start date and a schedule end date for each personnel base, each personnel task from the set of attendance days; for any personnel base, according to the maximum continuous calendar day number of the task ring set in the scene configuration, respectively constructing a space-time network graph with the duration of one to the maximum continuous calendar day number of the task ring for each day from the plan starting date to the plan ending date; and screening out target attendance days which need to be added into the space-time network diagram in the attendance day set according to a screening rule, and setting a connecting arc between the attendance days which meet the rules of place connection, rest rules and scene configuration in the civil aviation bureau regulation limit so as to complete the construction of the flight group ring network diagram. Here, the construction steps of the spatio-temporal network map of the duty day are as follows: step 1, let B be a personnel base set, index B, StartDate be a plan start date, EndDate be a plan end date; step 2, for any personnel base, according to the maximum continuous calendar day number of the task ring set in the scene configuration, respectively constructing a space-time network graph with the duration of one to the maximum continuous calendar day number of the task ring for each day from the plan starting date to the plan ending date; step 3, judging whether the attendance date d needs to be added into the network diagram according to a screening rule; and 4, setting connection arcs between the duty days meeting the place connection, rest rules and the user-defined rules in the scene configuration, wherein each duty day network comprises three types of nodes including a task ring start type, a task ring end type and a connection point type, and two types of arcs including a duty day arc and a connection arc type, as shown in fig. 3.
Following the above embodiment, the screening rule includes the following steps: if the date corresponding to the starting moment of the attendance day is equal to the starting date of the space-time network diagram, continuously judging whether the starting airport of the attendance day is the corresponding personnel base or not, and if so, adding the space-time network diagram; if the date of the attendance day is equal to any date in the middle of the spatio-temporal network diagram, directly joining; if the date corresponding to the ending time of the attendance day is equal to the ending date of the space-time network diagram, whether the arrival airport of the attendance day is the corresponding personnel base or not is continuously judged, and if yes, the arrival airport of the attendance day is added. When judging whether the attendance date d needs to be added into the network map according to the screening rule, if the date corresponding to the starting time of the attendance date is equal to the starting date of the network map, judging whether the starting airport is a corresponding personnel base, and if the dates are the same, adding the personnel base; if the date of the attendance day is equal to a certain date in the middle of the network diagram, directly joining; if the date corresponding to the ending time of the attendance date is equal to the ending date of the network map, whether the arrival airport of the attendance date is the corresponding personnel base or not needs to be judged, and if the arrival airport of the attendance date is the same, the attendance is added.
In some embodiments of the present application, in step S13, a to-be-scheduled flight set and an initial task ring set are determined, and a threshold value of a fixed integer variable is set; constructing a model objective function of the flight group ring model according to the cost of each task ring in the initial task ring set, the decision variable selected by the group ring scheme of the task ring and the set of all generated task rings in the planning period; and determining the constraint conditions of the flight group ring model according to the constraints on set division and the constraints on variable values. The method comprises the steps of determining an objective function and a constraint condition of a model by using a branch pricing method, specifically, obtaining an initial task ring set by using a heuristic algorithm, setting a threshold value of a fixed integer variable, determining the objective function according to the cost of each task ring, the set of all generated task rings in a planning period and a decision variable (0-1 variable) of whether the task rings are selected in a final group ring scheme, determining a flight set needing to be scheduled, and using the set of flights to be scheduled as a set of planned flight segments to perform the constraint condition of the model by using the set of the planned flight segments.
Following the above embodiment, the model objective function represents the total cost of minimizing the group ring solution, and the model objective function satisfies the following condition:
Figure BDA0003375175510000121
wherein p represents a task ring, cpCost, x, of the representation task ring ppA decision variable of 0 or 1 indicates whether the task ring P is selected in the final group ring solution, P representing the set of all generated task rings during the planning period. Here, cpThe cost of the task ring p is represented by two parts, one part and the task ringThe flight task components contained in the mission ring are related and represent the salary cost that the driver needs to pay for the pilot carrying out the mission ring, and the other part represents the reflection of the mission ring quality and is related to the penalty classes in the parameter configuration, and when the mission ring has a characteristic corresponding to a certain penalty, the corresponding penalty needs to be added to the cost of the mission ring. And xpA 0-1 variable is set, the 0 variable indicating that the task ring p is not selected in the final group ring scheme, and the 1 variable indicating that the task ring p is selected in the final group ring scheme. The objective function represents the total cost of minimizing the group loop solution, including the pilot salaries that the flight crew needs to pay in order to secure the flight mission for all flights, as well as the extra costs of out-station overnight, set up, etc.
Continuing with the above embodiment, the constraint satisfies the following condition:
Figure BDA0003375175510000131
Figure BDA0003375175510000132
wherein, L represents a set of flights to be scheduled, and L represents a planned flight segment in the set of flights to be scheduled. Here, the first set partitioning constraint ensures that each planned leg is covered exactly once, and the second variable value constraint determines the value range of each decision variable.
In some embodiments of the present application, as shown in fig. 4, a main problem solution is performed on the flight group ring model by using a branch pricing method, wherein the main problem solution comprises the following steps: step 1, judging whether the current solution is an integer solution, if not, executing step 2, otherwise, exiting to obtain a new flight group ring scheme; step 2, set
Figure BDA0003375175510000133
Representing the resulting group ring scheme; when x is satisfiedp≥κ1Then, corresponding xpJoining collections
Figure BDA0003375175510000134
Wherein, κ1A threshold value representing a fixed integer variable; and step 3: for the
Figure BDA0003375175510000135
Setting xpLower bound LB (x)p) If there is another task ring p' containing the same flight l as the task ring p, the variable value x corresponding to the task ring is setp′Upper bound UB (x)p′) 0, indicating that task ring p' is eliminated; and 4, step 4: and solving the linear relaxation solution of the main problem of the flight group ring model.
Then, searching an optimized path of solving a main problem of the flight group ring model based on the constructed flight group ring network diagram by using a multi-label shortest path algorithm; if a group of task rings beneficial to the main problem solution optimization is found, adding the group of task rings into the task ring set, and skipping to the step 4; and (5) when the task ring beneficial to the optimization of the main problem can not be found, skipping to the step 1. Here, with continued reference to FIG. 4, the column generation algorithm finds a set of task rings p that facilitate optimization of the main problem solution based on the constructed flight group ring network graph for the on-duty day1,p2,...,pnAdded into task ring set, P ═ PU { P-1,p2,...,pnAnd 4, turning to the step 4, otherwise, when the task ring cannot be found, skipping to the step 1, and iteratively processing the solution of the flight group ring model, namely, finding a group of task rings which are beneficial to the main problem solution optimization by using a multi-label shortest-path algorithm based on the constructed flight group ring network diagram, so that variables corresponding to the optimized task rings are added into the main problem model, when the optimized task ring cannot be found, carrying out rule judgment on all variables contained in the main problem, and adding the task rings meeting rule conditions into a feasible task ring set.
Specifically, an optimized path for solving a main problem of the flight group ring model is found based on the constructed flight group ring network diagram by using a multi-label shortest path algorithm, and the method comprises the following steps: step S1, initializing labels of all nodes in the flight group ring network, where the labels include a duty day set and a total check number included in a current partial path, and sometimes it is necessary to add a label accordingly according to a scenario configuration, for example: when the maximum number of the allowed continuous calendar days of the flight tasks exists in the set task ring, adding a content to record the number of the continuous flight calendar days accumulated by the current partial path in the tag for rule judgment when the paths are connected in series; step S2, traversing each node in turn according to the topological sorting, and obtaining a set of subsequent nodes, if the traversal is finished, executing step S5, otherwise executing step S3, wherein each node i belongs to N, and the set of subsequent nodes is S (N); step S3, performing rule check on any label in the nodes and any node in the subsequent node set according to the rule condition, jumping to step S4 if the rule condition is met, and re-executing step S3 if the rule condition is not met, namely performing rule check on any label p in the point i and any node j in the subsequent set S (n), and judging whether the partial path continuous serial connection node j recorded in the label k violates the civil aviation bureau regulation or the custom rule set in the scene configuration; step S4, generating a new label according to the label meeting the rule condition and the content of the target node in the subsequent node set successfully checked, making a dominance judgment on the new label and all labels existing in the target node, if the check number of any label existing in the target node is less than the new label, not reserving the new label, otherwise, deleting the label dominated by the new label in the labels existing in the target node, and adding the new label into the label set of the target node, namely, generating a new label q according to the label p and the content of the node j, identifying the label q and all labels existing in the node j to make a dominance judgment, if the check number of any label n existing in the node j is less than the label q, considering the label q to be dominated without reserving, otherwise, deleting the label dominated by the label q in the labels existing in the node j, adding the label q into the label set of the node j; step S5, traversing all the labels on the task ring end nodes in the flight group ring network, and if the check number recorded in the label is less than 0, taking the task ring corresponding to the path recorded by the label as an optimized path for solving the main problem of the flight group ring model, that is, the task ring variable corresponding to the path recorded by the label is considered as being solved by the main problem capable of optimizing the model, and is therefore adopted.
In some embodiments of the present application, the method comprises: and counting evaluation indexes according to the loop combination scheme, wherein the evaluation indexes comprise average flight hours on duty day, total set times, total airplane change times, total times of long flights and station passing, total loop combination for continuously executing early shifts, total loop combination for continuously executing late shifts, unit cost and temporary overnight station number of the flight units. Determining task ring information according to the group ring scheme, wherein the task ring information comprises flight information, setting information and the like forming a task ring, and evaluating indexes (KPI statistics) are carried out on flight coverage, outstation overnight times, setting times, long station passing times, machine changing times, early and late shift times and the like; wherein, the average flight hour on duty day: the duty day comprises flight tasks, non-private units, duty, backup, setting and task arrangement (simulation machine training, simulation machine flying, training, official business, others, regular training, examination and daily training). The value of the average flight hour on duty day can directly reflect the utilization rate of the unit. Setting total times: excessive setting arrangement not only can directly influence the income of an airline company or increase the cost, but also can influence the work satisfaction degree of subsequent aircrews. Total number of airplane changes: too many times of changing the machines in the duty day not only can influence the unit experience, but also can reduce the robustness of the whole unit scheduling scheme to a certain extent. In the actual operation process, if the situation of flight plan interruption occurs, the action paths of the unit and the airplane are different, which often easily causes chain delay. For example: as shown in fig. 5, the aircraft 1: flight F1- > flight F2, airplane 2: flight F3- > flight F4, unit 1: flight F1- > F4, unit 2: flight F3- > F2, when flight F1 is delayed, flight F2 flown by airplane 1 may be delayed due to insufficient station passing time; and the station-passing time of the machine of the unit 1 is insufficient, and the flight F4 flown by the unit 1 cannot take off according to the original plan. Flight length over station total number: although the secondary entering and exiting field can enable the crew members to obtain better rest conditions in the interval of the flight, the secondary entering and exiting field means that in the middle of the duty day, sign-in and exit, taking vehicles to go back and forth between the airport and the rest place and then sign in a series of processes, the actual experience of the crew members is not good, and particularly, the crew members are not paid when the rest time in the rest place is not long. The total number of the group rings for continuously executing the early shift, the total number of the group rings for continuously executing the late shift: the human fatigue and the biological rhythm are closely related to the work and rest habits of the human body, and the fatigue feeling of the pilot is poor due to the fact that the pilot continuously executes the early shift or the late shift, so that the work satisfaction degree of the pilot is reduced. Overnight days, overnight subsidy expenses resulting from shift results, hotel accommodation costs: the overnight expense in the unit cost is directly related to the number of days of the outdoor overnight period, the number of overnight airports also needs to be controlled, fewer overnight airports are convenient to manage on the premise of meeting the scheduling requirement, and the crew members are easier to adjust when the situations such as flight delay occur. Number of flight crew temporary overnight stations: if an overnight station is allowed to be newly added, the possibility of the daily structure of the duty and the link connection of the group ring is effectively improved, so that the daily average flight time of a pilot is favorably improved, but the newly added overnight station needs an extra communication protocol hotel and the like for a navigation department, and the overnight cost can be increased. Therefore, while the existing KPIs such as the time of day flight should be increased as much as possible, the number of new temporary overnight points should be limited.
By the method for generating the intelligent flight unit group ring, the quality and the robustness of the scheme can be guaranteed in the limited solving time, and the method has high research significance and application value.
In addition, the embodiment of the application also provides a computer readable medium, on which computer readable instructions are stored, and the computer readable instructions can be executed by a processor to implement the foregoing method for generating the intelligent aircraft crew loop.
In an embodiment of the present application, a device for generating an intelligent flight crew group ring is further provided, where the device includes:
one or more processors; and
a memory storing computer readable instructions that, when executed, cause the processor to perform the operations of the method as previously described.
For example, the computer readable instructions, when executed, cause the one or more processors to:
searching all the attendance days meeting rule conditions according to basic data of the intelligent flight set to obtain an attendance day set, wherein the rule conditions comprise rules of civil aviation bureau regulation limits and group ring scene configuration;
constructing a flight group ring network diagram according to the attendance day set;
constructing a flight group ring model based on a to-be-scheduled flight set and an initial task ring set, wherein the flight group ring model comprises a model objective function and a constraint condition;
using a branch pricing method to solve a main problem of the flight group ring model to obtain a feasible task ring of each flight;
and searching an optimized path solved by the main problem of the flight group ring model by using a multi-label shortest path algorithm to obtain an optimized task ring, solving the flight group ring model according to the feasible task ring and the optimized task ring of each flight, and determining a group ring scheme of the intelligent flight unit.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
It should be noted that the present application may be implemented in software and/or a combination of software and hardware, for example, implemented using Application Specific Integrated Circuits (ASICs), general purpose computers or any other similar hardware devices. In one embodiment, the software programs of the present application may be executed by a processor to implement the steps or functions described above. Likewise, the software programs (including associated data structures) of the present application may be stored in a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like. Additionally, some of the steps or functions of the present application may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.
In addition, some of the present application may be implemented as a computer program product, such as computer program instructions, which when executed by a computer, may invoke or provide methods and/or techniques in accordance with the present application through the operation of the computer. Program instructions which invoke the methods of the present application may be stored on a fixed or removable recording medium and/or transmitted via a data stream on a broadcast or other signal-bearing medium and/or stored within a working memory of a computer device operating in accordance with the program instructions. An embodiment according to the present application comprises an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform a method and/or a solution according to the aforementioned embodiments of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. The terms first, second, etc. are used to denote names, but not any particular order.

Claims (14)

1. A method for generating an intelligent aircraft crew loop is characterized by comprising the following steps:
searching all the attendance days meeting rule conditions according to basic data of the intelligent flight set to obtain an attendance day set, wherein the rule conditions comprise rules of civil aviation bureau regulation limits and group ring scene configuration;
constructing a flight group ring network diagram according to the attendance day set;
constructing a flight group ring model based on a to-be-scheduled flight set and an initial task ring set, wherein the flight group ring model comprises a model objective function and a constraint condition;
using a branch pricing method to solve a main problem of the flight group ring model to obtain a feasible task ring of each flight;
and searching an optimized path solved by the main problem of the flight group ring model by using a multi-label shortest path algorithm to obtain an optimized task ring, solving the flight group ring model according to the feasible task ring and the optimized task ring of each flight, and determining a group ring scheme of the intelligent flight unit.
2. The method of claim 1, wherein searching for all dates of attendance that meet the rule condition based on the basic data of the intelligent flight crew comprises:
acquiring basic data related to scheduling of the intelligent flight unit;
and determining the solving preference of the group ring scheme according to the basic data and configuring the rule of the group ring scene.
3. The method of claim 1, wherein constructing a flight group ring network map from the set of attendance days comprises the steps of:
determining a plan starting date and a plan ending date of each personnel base, each personnel task according to the duty day set;
for any personnel base, according to the maximum continuous calendar day number of the task ring set in the scene configuration, respectively constructing a space-time network graph with the duration of one to the maximum continuous calendar day number of the task ring for each day from the plan starting date to the plan ending date;
and screening out target attendance days which need to be added into the space-time network diagram in the attendance day set according to a screening rule, and setting a connecting arc between the attendance days which meet the rules of place connection, rest rules and scene configuration in the civil aviation bureau regulation limit so as to complete the construction of the flight group ring network diagram.
4. The method according to claim 3, wherein the screening rule comprises the steps of:
if the date corresponding to the starting moment of the attendance day is equal to the starting date of the space-time network diagram, continuously judging whether the starting airport of the attendance day is the corresponding personnel base or not, and if so, adding the space-time network diagram;
if the date of the attendance day is equal to any date in the middle of the spatio-temporal network diagram, directly joining;
if the date corresponding to the ending time of the attendance day is equal to the ending date of the space-time network diagram, whether the arrival airport of the attendance day is the corresponding personnel base or not is continuously judged, and if yes, the arrival airport of the attendance day is added.
5. The method of claim 1, wherein constructing a flight group ring model based on the to-be-scheduled flight set and the initial task ring set comprises:
determining a flight set to be scheduled and an initial task ring set, and setting a threshold value of a fixed integer variable;
constructing a model objective function of the flight group ring model according to the cost of each task ring in the initial task ring set, the decision variable selected by the group ring scheme of the task ring and all generated task ring sets in the planning period;
and determining the constraint conditions of the flight group ring model according to the constraints on set division and the constraints on variable values.
6. The method of claim 5, wherein the model objective function represents a total cost of minimizing a group ring solution, the model objective function satisfying the following condition:
Figure FDA0003375175500000031
wherein p represents a task ring, cpCost, x, of the representation task ring ppA decision variable of 0 or 1 indicates whether the task ring P is selected in the final group ring solution, P indicating the set of all generated task rings during the planning period.
7. The method of claim 6, wherein the constraint satisfies the following condition:
Figure FDA0003375175500000032
Figure FDA0003375175500000033
wherein, L represents the set of scheduled flights and L represents the planned flight segment.
8. The method of claim 5, wherein the flight group ring model is subjected to a main problem solution using branch pricing, wherein main problem solution comprises the steps of:
step 1, judging whether the current solution is an integer solution, if not, executing step 2, otherwise, exiting to obtain a new flight group ring scheme;
step 2, set
Figure FDA0003375175500000034
Representing the resulting group ring scheme; when x is satisfiedp≥κ1Then, corresponding xpJoining collections
Figure FDA0003375175500000035
Wherein, κ1A threshold value representing a fixed integer variable;
and step 3: for the
Figure FDA0003375175500000036
Setting xpLower bound LB (x)p) If there is another task ring p' containing the same flight l as the task ring p, the variable value x corresponding to the task ring is setp′Upper bound UB (x)p′) 0, indicating that task ring p' is eliminated;
and 4, step 4: and solving the linear relaxation solution of the main problem of the flight group ring model.
9. The method of claim 8, wherein finding the optimal path of the main problem solution of the flight group ring model using a multi-label shortest-path algorithm to obtain an optimal task ring comprises:
searching an optimized path of the main problem solution of the flight group ring model based on the constructed flight group ring network diagram by using a multi-label shortest path algorithm;
if a group of task rings beneficial to the main problem solution optimization is found, adding the group of task rings into the task ring set, and skipping to the step 4;
and (5) when the task ring beneficial to the optimization of the main problem can not be found, skipping to the step 1.
10. The method of claim 9, wherein finding the optimized path of the main problem solution of the flight group ring model based on the constructed flight group ring network map using a multi-label shortest path algorithm comprises the following steps:
step S1, initializing labels of all nodes in the flight group ring network, wherein the labels comprise a value day set and a total check number contained in the current partial path;
step S2, traversing each node in turn according to the topological order, and obtaining the set of the subsequent nodes, if the traversal is finished, executing step S5, otherwise executing step S3;
step S3, for any label in the node and any node in the subsequent node set, rule checking is carried out according to the rule condition, if the check is that the rule condition is satisfied, the step S4 is skipped, and if the check is that the rule condition is not satisfied, the step S3 is executed again;
step S4, generating a new label according to the label meeting the rule condition and the content of the target node in the subsequent node set successfully verified, performing dominance judgment on the new label and all labels existing in the target node, if the verification number of any label existing in the target node is smaller than the new label, not reserving the new label, otherwise, deleting the label dominated by the new label in the labels existing in the target node, and adding the new label into the label set of the target node;
step S5, traversing all tags on the task ring end nodes in the flight group ring network, and if the check number recorded in the tags is less than 0, taking the task ring corresponding to the path recorded by the tags as an optimized path for solving the main problem of the flight group ring model.
11. The method according to claim 1, characterized in that it comprises:
and counting evaluation indexes according to the loop combination scheme, wherein the evaluation indexes comprise average flight hours on duty day, total set times, total airplane change times, total times of long flights and station passing, total loop combination for continuously executing early shifts, total loop combination for continuously executing late shifts, unit cost and temporary overnight station number of the flight units.
12. The method of claim 1, wherein the group ring scenario configuration comprises a task ring maximum duration calendar day number, a task ring consecutive flight calendar day number, a number of consecutive sets, a number of trips within a flight attendance period, an early class definition setting, a late class definition setting, a flight engagement type setting, an airport non-serializable group limit, and a base requirement.
13. An intelligent aircraft crew loop generation device, the device comprising:
one or more processors; and
a memory storing computer readable instructions that, when executed, cause the processor to perform the operations of the method of any of claims 1 to 12.
14. A computer readable medium having computer readable instructions stored thereon which are executable by a processor to implement the method of any one of claims 1 to 12.
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CN116644988A (en) * 2023-05-08 2023-08-25 中国民航科学技术研究院 Flight fatigue value calculation method and device, electronic equipment and storage medium
CN116777064A (en) * 2023-06-20 2023-09-19 广东工业大学 Two-dimensional boxing method based on non-primary cut constraint and branch pricing algorithm
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CN116644988A (en) * 2023-05-08 2023-08-25 中国民航科学技术研究院 Flight fatigue value calculation method and device, electronic equipment and storage medium
CN116644988B (en) * 2023-05-08 2023-10-17 中国民航科学技术研究院 Flight fatigue value calculation method and device, electronic equipment and storage medium
CN116777064A (en) * 2023-06-20 2023-09-19 广东工业大学 Two-dimensional boxing method based on non-primary cut constraint and branch pricing algorithm
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