CN115689144A - Flight operation guarantee task intelligent adjustment method, system, equipment and storage medium - Google Patents
Flight operation guarantee task intelligent adjustment method, system, equipment and storage medium Download PDFInfo
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- CN115689144A CN115689144A CN202210582630.9A CN202210582630A CN115689144A CN 115689144 A CN115689144 A CN 115689144A CN 202210582630 A CN202210582630 A CN 202210582630A CN 115689144 A CN115689144 A CN 115689144A
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Abstract
The invention relates to a method, a system, equipment and a storage medium for intelligently adjusting a guarantee task of a flight operation situation, which comprises the following steps: s1, acquiring related data, wherein the data relates to flight schedule information, flight information, airport area information, support personnel information, machine position information and support vehicle information; s2, acquiring a scheduling plan, and confirming a short-term scheduling plan and a long-term scheduling plan according to personnel conditions; s3, carrying out intelligent staff dispatching according to the flight task data and the scheduling plan; and S4, evaluating the guarantee capability, and performing statistical analysis on key indexes on the dispatching effect. The invention has the advantages that: the airport support system has the advantages that the integral promotion of airport support capability is realized, the working efficiency of support personnel is improved, and the utilization rate of airports and aircrafts is improved. By establishing the airport ground guarantee capability assessment and adjustment method, reasonable and optimal guarantee task arrangement of airport guarantee personnel is realized, and the utilization rate of airport fields and aircrafts is improved.
Description
Technical Field
The invention relates to a guarantee task intelligent adjustment method, system and equipment based on flight operation situation and a storage medium, belonging to the field of aviation ground service guarantee.
Background
With the rapid development of civil aviation industry in China, the throughput of a civil aviation transportation system is gradually increased, and the ground guarantee capability and the requirement on an airport are higher and higher. How to guarantee reasonable and effective arrangement of ground support personnel and vehicle scheduling, not only can the minimum manpower meet airport support requirements, but also can shorten flight support time, and improve the utilization rate of airport fields and aircrafts is a problem which needs to be researched and paid attention to.
Chinese patent application No. 202111505270.4 discloses an intelligent scheduling method for airport ground service. By integrating flight task information, flight position information, distance information, employee information and shift information and combining a pre-constructed shift scheduling planning model and constraint conditions, matrix analysis is carried out, the task completion rate is ensured to be as high as possible, the variance of the labor hour utilization rate of employees is small, and the employees are ensured to contribute to the shift scheduling working time as averagely as possible.
With the diversification and humanization of airport services, the constraint conditions of scheduling arrangement are gradually increased, different work positions of different airports have different scheduling, main and auxiliary scheduling, rotation mode, regional operation mode and the like due to the difference of working modes, meanwhile, the particularity of specific personnel needs to be considered, and the scheduling workload requirement under the premise of the constraint of the diversification services cannot be ensured by the algorithm. And the resource guarantee capability cannot be evaluated from the whole, and the highest utilization rate is achieved under the condition of the minimum resource. And the guarantee resource scheduling of the work dispatching link at the downstream of the shift arrangement can not be ensured.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides an intelligent guarantee task adjusting method based on flight operation situation, and the technical scheme of the invention is as follows:
an intelligent adjusting method for flight operation support tasks comprises the following steps:
s1, acquiring related data, wherein the data relates to flight schedule information, flight information, airport area information, support personnel information, machine position information and support vehicle information;
s2, acquiring a shift scheduling plan, and confirming a short-term shift scheduling plan and a long-term shift scheduling plan according to personnel conditions; s3, carrying out intelligent staff dispatching according to the flight task data and the scheduling plan;
and S4, evaluating the guarantee capability, and performing statistical analysis on key indexes on the dispatching effect.
The step S3 specifically includes:
s31, acquiring flight data, personnel scheduling data and basic data;
s32, setting a rule set;
s33, carrying out personnel difference matching to realize pre-dispatching;
and S34, performing batch scheduling or recommending dispatching as required.
The step S32 is specifically:
setting an objective function:
wherein: v i rule -all rule set sets that a person satisfies;
-rule weights;
RT ij -the cost spent by the guaranteed location corresponding to the safeguard i to the guaranteed location corresponding to the flight j; n- - -total number of flights; m-the total number of the security personnel, namely the total number of the squadrons aiming at the squadrons;
wherein x is ik The status is 1 on behalf of the support person k servicing flight i, and 0 otherwise.
The method also comprises a step of carrying out weight optimization on the multi-objective function, wherein a plurality of objective functions are converted into one objective function in a linear conversion mode:
f＝f 1 +f 2 +f 3 (7)；
wherein:
-rule set precedence objective function weight coefficients; f. of 1 -target function target values for rule set precedence; β - - -weight coefficient of the shortest path objective function; f. of 2 -a path-shortest objective function target value; δ - - -weight coefficients of the task balancing objective function; f. of 3 -task balancing objective function target values; f- -single objective function value, f is the final bestAnd (5) aiming.
The step S32 further includes adjusting the rule set according to specific situations, where the defined rule constraint conditions are as follows:
(1) And (3) dispatching rule constraint conditions of the machine position area:
secured flight area F i nation Must be a station area P which can be secured by security personnel k nation Is selected from the group consisting of (a) a subset of,
(2) Dispatching rule constraint conditions of the boarding gate area: boarding gate area P for guaranteeing personnel security k gate Must be a subset of the set of locations P that can be secured,
(3) Extracting the constraint conditions of the dispatching rules of the turntable areas: extraction turntable area F for guaranteeing personnel security i luggage Must be a guaranteed set of extraction carousel areas P k luggage Is selected from the group consisting of (a) a subset of,
(4) And (3) airline dispatching rule constraint conditions: flight department F corresponding to flight i icao Navigation department P capable of ensuring personnel k icao Is selected from the group consisting of (a) a subset of,
a guarantee task intelligent adjustment system based on flight operation situation comprises:
the data acquisition module is used for acquiring related data, wherein the data relates to flight plan information, flight information, airport area information, support personnel information, machine position information and support vehicle information;
the scheduling plan obtaining module is used for obtaining a scheduling plan and confirming a short-term scheduling plan and a long-term scheduling plan according to the personnel condition;
the intelligent dispatching module is used for intelligently dispatching personnel according to the flight task data and the scheduling plan;
and the statistical analysis module is used for evaluating the guarantee capability and performing statistical analysis on key indexes on the dispatching effect.
A computer device, comprising:
at least one processor; and a memory storing computer instructions executable on the processor, the instructions when executed by the processor implementing the steps of the method of any one of claims 1 to 5.
A computer-readable storage medium, which stores a computer program, wherein the computer program is executed by a processor to perform the steps of the method for intelligently adjusting flight service provisioning tasks.
The invention has the advantages that: on one hand, the personnel required by each time period can be dynamically arranged according to the personnel requirements of each time period, and the requirement on the man-hour balance can be effectively met. Cost control and personnel working efficiency control are realized, fair and reasonable rest time is given to the personnel, and the enthusiasm of the personnel is improved; on the other hand, accurate matching of guarantee tasks and personnel is achieved, dispatching of various ground service guarantee posts is achieved, the walking path distance of the personnel is reduced, and the service time of each personnel is balanced. Finally, factors incompatible with ground support requirements can be found, evaluated and improved in time through an evaluation index system of airport ground support capability.
The airport security capacity is integrally improved, the working efficiency of security personnel is improved, and the utilization rate of the airport and the aircraft is improved. By establishing the airport ground guarantee capability evaluation and adjustment method, reasonable and optimal guarantee task arrangement of airport support personnel is realized, and the utilization rates of airport fields and aircrafts are improved.
Drawings
FIG. 1 is a schematic flow diagram of the present invention.
FIG. 2 is a flow chart illustrating intelligent staff dispatching according to the present invention.
Detailed Description
The invention will be further described with reference to specific embodiments, and the advantages and features of the invention will become apparent as the description proceeds. These examples are illustrative only and do not limit the scope of the present invention in any way. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention, and that such changes and modifications may be made without departing from the spirit and scope of the invention.
Referring to fig. 1 and fig. 2, the invention relates to an intelligent regulation method for a guarantee task of a flight operation situation, comprising the following steps:
s1, acquiring related data, wherein the data relates to flight schedule information, flight information, airport area information, support personnel information, machine position information and support vehicle information;
s2, acquiring a scheduling plan, and confirming a short-term scheduling plan and a long-term scheduling plan according to personnel conditions;
s3, carrying out intelligent staff dispatching according to the flight task data and the scheduling plan;
and S4, evaluating the guarantee capability, and performing statistical analysis on key indexes (mainly comprising the average working time of personnel, the utilization rate of the personnel, the task completion efficiency of the personnel and the like) on the dispatching effect.
The step S3 is specifically:
s31, acquiring flight data, personnel scheduling data and basic data;
s32, setting a rule set;
s33, carrying out personnel difference matching to realize pre-dispatching;
and S34, performing batch scheduling or recommending dispatching as required.
The step S32 is specifically: setting an objective function:
wherein: v i rule -all rule set sets satisfied by a person;
-rule weights;
RT ij -the cost spent by the guaranteed location corresponding to the safeguard i to the guaranteed location corresponding to the flight j; n- -total number of flights; m-the total number of the security personnel, namely the total number of the squadrons aiming at the squadrons;
wherein x is ik The state is 1 if the representative support person k serves the flight i, and is 0 if not.
The formula (1) realizes the effect of rule set priority configuration to the maximum extent.
Wherein, the formula (2) embodies the regional proximity principle. In the algorithm, the region of the airport where the gate is located is set, and a moving cost (time) matrix between the regions is established. When tasks are dispatched, the tasks of the staff in the same area are guaranteed to be arranged as much as possible, and the moving cost and feasibility among the cross-areas are considered.
The formula (3) balance reflects the fairness principle that the guarantee staff can dispatch the work, and the balance reflects that the variance is minimum between the time lengths of the work dispatching tasks of all the guarantee staff.
The method also comprises a step of carrying out weight optimization on the multi-objective function, wherein a plurality of objective functions are converted into one objective function in a linear conversion mode:
f＝f 1 +f 2 +f 3 (7)；
wherein:
-rule set precedence objective function weight coefficients; f. of 1 -target value of objective function with rule set precedence; β - - -weight coefficient of the shortest path objective function; f. of 2 -a path-shortest objective function target value; δ - - -weight coefficients of the task balancing objective function; f. of 3 -task balancing objective function target values; f- - -single objective function value, f is the final optimization objective.
The step S32 further includes adjusting the rule set according to specific conditions, where the defined rule constraint conditions are as follows:
(1) And (3) dispatching rule constraint conditions of the machine position area:
secured flight area F i nation Must be a position area P which can be ensured by the ensured personnel k nation Is determined by the number of sub-sets of,
(2) Dispatching rule constraint conditions of the boarding gate area are as follows: boarding gate area P for guaranteeing personnel security k gate Must be a subset of the guaranteed set of places P,
(3) Extracting the constraint conditions of the dispatching rules of the turntable areas: extraction turntable area F for guaranteeing personnel guarantee i luggage Must be provided withIs a secured set of extraction carousel areas P k luggage Is selected from the group consisting of (a) a subset of,
(4) And (3) airline dispatching rule constraint conditions: flight department F corresponding to flight i icao Navigation driver P which must be ensured by personnel k icao Is selected from the group consisting of (a) a subset of,
the invention can realize the recommendation and dispatch of personnel for the guarantee task of a certain flight. The candidate persons are prioritized according to the personal qualification, rule set, distance matrix, personal balance, etc., and the distance matrix is added
And the middle beta weight can be recommended to dispatch by an algorithm according to a distance priority principle. Similarly, when the weights of personnel qualification, historical tasks and the like in the rule set are increased, the recommended scheduling processing aiming at a certain single guarantee task can be realized. If a certain support personnel can not execute the support task due to an emergency, determining a specific required support personnel set according to task information by dispatching and recommending, and finally returning to an available personnel list according to the recommended matching degree.
The invention also relates to a flight operation situation-based guarantee task intelligent adjustment system, which comprises the following components:
the data acquisition module is used for acquiring related data, wherein the data relates to flight schedule information, flight information, airport area information, support personnel information, machine position information and support vehicle information;
the scheduling plan obtaining module is used for obtaining a scheduling plan and confirming a short-term scheduling plan and a long-term scheduling plan according to the personnel condition;
the intelligent dispatching module is used for intelligently dispatching personnel according to the flight task data and the scheduling plan;
and the statistical analysis module is used for evaluating the guarantee capability and performing statistical analysis on key indexes on the dispatching effect.
The invention also relates to a computer device comprising: at least one processor; and a memory storing computer instructions executable on the processor, the instructions when executed by the processor implementing the steps of the flight operations support task intelligent tuning method.
The invention also relates to a computer-readable storage medium, in which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the method for intelligently adjusting a flight operation assurance task.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered as the technical solutions and the inventive concepts of the present invention within the technical scope of the present invention.
Claims (8)
1. An intelligent adjusting method for flight operation support tasks is characterized by comprising the following steps:
s1, acquiring related data, wherein the data relates to flight schedule information, flight information, airport area information, support personnel information, machine position information and support vehicle information;
s2, acquiring a scheduling plan, and confirming a short-term scheduling plan and a long-term scheduling plan according to personnel conditions;
s3, carrying out intelligent staff dispatching according to the flight task data and the scheduling plan;
and S4, evaluating the guarantee capability, and performing statistical analysis on key indexes on the dispatching effect.
2. The intelligent adjusting method for the flight operation support task according to claim 1, wherein the step S3 specifically comprises:
s31, acquiring flight data, personnel scheduling data and basic data;
s32, setting a rule set;
s33, carrying out personnel difference matching to realize pre-dispatching;
and S34, performing batch scheduling or recommending dispatching as required.
3. The intelligent adjusting method for the flight operation support task according to claim 2, wherein the step S32 is specifically:
setting an objective function:
wherein: v i rule -all rule set sets satisfied by a person;
-rule weights;
RT ij -the cost spent by the guaranteed location corresponding to the safeguard i to the guaranteed location corresponding to the flight j; n- -total number of flights; m-the total number of the security personnel, namely the total number of the squadrons aiming at the squadrons;
wherein x is ik The status is 1 on behalf of the support person k servicing flight i, and 0 otherwise.
4. The intelligent adjusting method for flight operation support tasks according to claim 3, further comprising a step of performing weight optimization on the multi-objective function, wherein the plurality of objective functions are converted into one objective function in a linear conversion manner:
f＝f 1 +f 2 +f 3 (7)；
wherein:
-rule set precedence objective function weight coefficients; f. of 1 -target value of objective function with rule set precedence; beta- - -weight coefficient of the shortest path objective function; f. of 2 -a path-shortest objective function target value; δ - - -weight coefficients of the task balancing objective function; f. of 3 -task balancing objective function target values; f- - -single objective function value, f is the final optimization objective.
5. The intelligent adjusting method for the flight operation support task according to claim 3, wherein the step S32 further comprises adjusting the rule set according to specific conditions, and the defined rule constraint conditions are as follows:
(1) And (3) dispatching rule constraint conditions of the machine position area:
secured flight area F i nation The personnel must be the area of the machine seat which can be protected by the security personnel
Is selected from the group consisting of (a) a subset of,
(2) Dispatching rule constraint conditions of the boarding gate area are as follows: boarding gate area P for guaranteeing personnel security k gate Must be a subset of the guaranteed set of places P,
(3) Extracting the constraint conditions of the dispatching rules of the turntable areas: extraction turntable area F for guaranteeing personnel security i luggage Must be guaranteed extraction carousel region set P k luggage Is selected from the group consisting of (a) a subset of,
(4) Airline dispatch rules constraints: airline department F corresponding to flight i icao Navigation department P capable of ensuring personnel k icao Is selected from the group consisting of (a) a subset of,
6. the utility model provides a guarantee task intelligence adjustment system based on flight operation situation which characterized in that includes:
the data acquisition module is used for acquiring related data, wherein the data relates to flight schedule information, flight information, airport area information, support personnel information, machine position information and support vehicle information;
the scheduling plan obtaining module is used for obtaining a scheduling plan and confirming a short-term scheduling plan and a long-term scheduling plan according to the personnel condition;
the intelligent dispatching module is used for intelligently dispatching personnel according to the flight task data and the scheduling plan;
and the statistical analysis module is used for evaluating the guarantee capability and carrying out statistical analysis on key indexes on the dispatching effect.
7. A computer device, comprising:
at least one processor; and a memory storing computer instructions executable on the processor, the instructions when executed by the processor implementing the steps of the method of any one of claims 1 to 5.
8. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116757554A (en) * | 2023-08-14 | 2023-09-15 | 青岛民航凯亚系统集成有限公司 | Airport flight area efficiency evaluation method and system |
| CN117910783A (en) * | 2024-03-19 | 2024-04-19 | 中国民用航空总局第二研究所 | Ground guarantee personnel scheduling method based on flight ground guarantee task |
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2022
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116757554A (en) * | 2023-08-14 | 2023-09-15 | 青岛民航凯亚系统集成有限公司 | Airport flight area efficiency evaluation method and system |
| CN117910783A (en) * | 2024-03-19 | 2024-04-19 | 中国民用航空总局第二研究所 | Ground guarantee personnel scheduling method based on flight ground guarantee task |
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