CN112862260A - Airport ferry service scheduling method and system - Google Patents
Airport ferry service scheduling method and system Download PDFInfo
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Abstract
The invention discloses a method and a system for dispatching airport ferry service, and belongs to the technical field of airport personnel and vehicle dispatching. The method comprises the following steps: preprocessing the flight data according to the information completeness; decomposing the expected port entering and exiting task into corresponding subtasks; performing task chain combination on the subtasks based on the candidate conditions and the preference rules to form a task chain; on the basis of the task chain, respectively distributing the task chain to the staff and the ferry vehicle to obtain a ferry vehicle task package and a staff task package; and (4) integrating the assignment results of the ferry vehicle task packages and the staff task packages to obtain a complete scheduling scheme. According to the ferry vehicle personnel cooperation method, through the two-stage structure of the task chain and the task package, the personnel rest time constraint and the single maximum working time constraint are solved through the candidate set screening condition and the optimal selection rule of the task chain and the task package, and the ferry vehicle personnel cooperation effect is achieved through the ferry vehicle task package and the staff task package.
Description
Technical Field
The invention belongs to the technical field of airport personnel and vehicle scheduling, and particularly relates to an airport ferry service scheduling method and system.
Background
Airport ferry service is an important work content in airport ground service, and is represented by airport ferry vehicle scheduling and personnel scheduling corresponding to the airport ferry vehicle scheduling. The ferry vehicle is a transportation tool for transporting passengers between an airport terminal and a flight parking apron, and when a flight enters or exits a port, the ferry vehicle needs to safely, conveniently and quickly deliver the passengers to the airport terminal or the flight parking apron. In the actual scheduling process, the ferry vehicle scheduling process mostly depends on the experience of related personnel, and unified and scientific scheduling and deployment are lacked. How to rapidly and efficiently schedule the ferry vehicle to solve the traffic problem of passengers going out of a port and entering the port and meet the requirement of fair and reasonable workload of corresponding staff is the key research point of the scheduling problem.
In the existing research on the ferry scheduling problem, the problem is mostly regarded as a VRPTW (vehicular routing schemes with time windows ferry route) problem or a derivative problem, that is, the ferry route problem of carrying out the delivery and transportation of personnel and goods to multiple points from one point under the time window limit, and the research content is also mostly based on the VRPTW problem and neglects some practical constraints. Such as the problem of scheduling of personnel, the problem of rest time of personnel, the problem of single maximum working time and the like which are matched with the ferry vehicle.
Disclosure of Invention
Aiming at the defects and improvement requirements of the prior art, the invention provides an airport ferry service scheduling method and system, and aims to solve the personnel rest time constraint and the single maximum working time constraint through a two-stage structure of a task chain and a task package and through candidate set screening conditions and an optimal selection rule of the task chain and the task package, and achieve the effect of the personnel cooperation of the ferry vehicle through the ferry vehicle task package and the staff task package.
To achieve the above object, according to a first aspect of the present invention, there is provided an airport ferry service scheduling method, including the steps of:
s1, taking each flight data in a scheduling period as a task, and decomposing each task into subtasks of the number of ferry vehicles corresponding to the model according to the number of ferry vehicles required by passengers for receiving and delivering in different models;
s2, for each subtask, constructing all subtasks which are not in conflict with the subtask time and are consistent with the type of the ferry vehicle required as a candidate set of the subtask; constructing a new task chain by taking the earliest started subtask which is not combined into the task chain as an initial node, selecting the next subtask in the same task chain from the candidate set of the adjacent previous subtask, finishing the construction of the task chain until the candidate set of the last subtask in the task chain is empty, and repeating the operation until all subtasks are combined into the task chain;
s3, for each task chain, constructing all task chains which are not in conflict with the task chain time and are consistent with the type of the ferry vehicle required as a candidate set of the task chain; constructing a new ferry vehicle task package by taking the earliest starting task chain which is not combined into the ferry vehicle task package as an initial item, wherein the later task chain in the same ferry vehicle task package is selected from the candidate set of the adjacent previous task chain, and the construction of the task package is finished until the candidate set of the last task chain in the ferry vehicle task package is empty, and the operation is repeated until all the task chains are combined into the ferry vehicle task package;
s4, for each task chain, constructing all task chains which are not in conflict with the task chain time and the total duration of all subtasks in the task chain including the task chain does not exceed the legal working duration of the staff as a candidate set of the task chain; constructing a new employee task package by taking the earliest started task chain which is not combined into the employee task package as an initial item, wherein the next task chain in the same employee task package is selected from the candidate set of the adjacent previous task chain, the construction of the task package is finished until the candidate set of the last task chain in the employee task package is empty, and the operation is repeated until all task chains are combined into the employee task package;
s5, obtaining the mapping relation of the airport staff task package and the ferry vehicle task package to the subtasks respectively, and obtaining the complete scheduling scheme of the ferry vehicles and the staff required by all the subtasks.
Preferably, prior to task decomposition, the raw flight data is pre-processed, including checking for data consistency, clearing out-of-range data, processing invalid data, and missing data.
Preferably, in step S1, the sub-tasks obtained by decomposition include: the type of the ferry vehicle required, the type of entering/exiting port, the starting point apron, the ending point apron, the starting time of the subtask, the execution time of the subtask and the ending time of the subtask.
Preferably, in step S2, the rule for constructing the candidate set is as follows:
(1) the demand ferry vehicle of each task chain is of the same type, starts from the starting apron and finally returns to the starting apron, and the in-situ waiting time between the subtasks cannot exceed the maximum waiting time;
(2) the waiting time for the front item subtask to finish, the transfer time of the front item and the back item are less than or equal to the time for the front item to return to the initial apron and the time for transferring the back item from the initial apron to the final apron;
(3) the planned end time of the next subtask + (the end time of the previous subtask + the end waiting time of the previous subtask + the transfer time of the previous and next subtask-the planned in-place time of the next subtask) + the next time + the time of returning to the starting apron-the time when the task chain starts is less than or equal to the maximum duration working time;
(4) the planned end time of the next subtask + (the end time of the previous subtask + the end waiting time of the previous subtask + the transfer time of the previous and next items-the planned in-place time of the next subtask) + the next time + the time of returning to the starting apron is less than or equal to the time of the shift limit + the allowed overtime;
(5) the plan in-place time-maximum allowable lead time of the next subtask is less than or equal to the end time of the previous subtask, the end waiting time of the previous subtask, the transfer time of the previous and next subtasks and the plan in-place time of the next subtask;
(6) the planned in-place time of the next subtask is less than or equal to the ending time of the previous subtask, the ending waiting time of the previous subtask, the transfer time of the previous and next subtasks, the planned in-place time of the next subtask and the maximum allowable delay time;
wherein, the conditions (1) to (4) are the conditions which must be satisfied, and the conditions (5) and (6) are the conditions which are satisfied by either one of them.
Preferably, in step S2, the selection rule is any one of the following:
(1) time priority rules: after the previous subtask is finished, selecting the subtask with the earliest starting time in the subtask candidate set to add into the task chain;
(2) saving priority rules: and after the previous subtask is finished, selecting a subtask candidate set, and adding the subtask with the largest difference between the (time for returning the previous item to the starting apron + time for transferring from the starting apron to the next item end apron) and the (waiting time for finishing the previous item subtask + time for transferring the previous item and the next item) into the task chain.
Preferably, in step S3, the ferry vehicle task package can receive the task chain and the following screening conditions are satisfied:
(1) each ferry vehicle can only complete one task chain at the same time;
(2) each ferry vehicle task package comprises a task chain time length and the total time length of the next task chain is less than the scheduling period;
(3) the type of the ferry vehicle is consistent with the type of the ferry vehicle required by the task chain.
Preferably, in step S3, the task chain to be executed is preferentially allocated to the feasible ferry vehicle task package with the least total working time when selecting.
Preferably, in step S4, the task chain receivable by the employee task package satisfies the following conditions:
(1) each employee can only complete one task chain at the same time;
(2) the total time of each employee task package is less than the legal working time of the employee;
(3) the continuous working time between task chains does not exceed the maximum allowed continuous working time.
Preferably, in step S4, the task chain to be executed is preferentially allocated to the feasible employee task package with the least total working time during picking.
To achieve the above object, according to a second aspect of the present invention, there is provided an airport ferry service scheduling system, comprising: a computer-readable storage medium and a processor;
the computer-readable storage medium is used for storing executable instructions;
the processor is configured to read executable instructions stored in the computer-readable storage medium, and execute the airport ferry service scheduling method according to the first aspect.
Generally, by the above technical solution conceived by the present invention, the following beneficial effects can be obtained:
the ferry service scheduling problem is mainly characterized by the matching of personnel ferry vehicles and respective related constraints, and has the difficulty that thousands of flight tasks, dozens of ferry vehicles and dozens of employees are required to be uniformly scheduled, the data volume is large, the variables are large, the scheduling scheme is required to meet the constraints in various aspects such as the number of the personnel ferry vehicles, the time requirements of the personnel ferry vehicles and the like, and similar problems are difficult to solve even if heuristic algorithms such as heredity, ant colony and the like are adopted. The method comprises the steps of preprocessing original flight data; decomposing the original inbound and outbound flight tasks of the airport into corresponding subtasks; performing task chain combination on the subtasks based on the screening condition and the optimization rule (the optimization rule refers to the greedy idea) to form a task chain; on the basis of the task chain, distributing the task chain to the staff to form a staff task package; on the basis of the task chain, distributing the task chain to the vehicles to form a ferry vehicle task package; and integrating the staff task package and the ferry vehicle task package distribution scheme to form a complete airport ferry service scheduling scheme. The constraint conditions are graded layer by layer through a method of a task chain and a task packet, the constraint conditions are graded into the processes of subtask combination, task chain combination and task packet distribution, and a better and feasible scheme is obtained through the cooperation of step combination, greedy thought and rule limitation.
Drawings
Fig. 1 is a flowchart of an airport ferry service scheduling method provided in an embodiment of the present invention;
FIG. 2 is a schematic diagram of data processing according to an embodiment of the present invention;
FIG. 3 is a sub-task decomposition diagram provided by an embodiment of the invention;
FIG. 4 is a diagram illustrating a merging pattern of multiple subtasks according to an embodiment of the present invention;
FIG. 5 is a schematic diagram illustrating task chain candidate set screening provided by an embodiment of the present invention;
FIG. 6 is a task chain assembly flow diagram provided by an embodiment of the invention;
FIG. 7 is a schematic diagram of a worker task package assembly process provided by an embodiment of the invention;
FIG. 8 is a schematic diagram of an analysis of idle and real time of a vehicle according to an embodiment of the present invention;
FIG. 9 is a schematic diagram of the overall task balance of a vehicle provided by an embodiment of the present invention;
fig. 10 is a schematic diagram of an overall scheduling scheme according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in fig. 1, the present invention provides an airport ferry service scheduling method, which includes the following steps:
s1: preprocessing original flight data;
recognizable errors in the data file are discovered and corrected, including checking data for consistency, clearing out-of-range data, handling invalid data, and missing data. For the outbound flight, the starting airport apron is not determined or the departure information is lacked, so that the flight can not participate in scheduling; for inbound flights, no landing apron is determined or no passenger exit is available to participate in the dispatch; for all flights, flights lacking the necessary information of time to enter, time to exit, number, model, etc. cannot participate in the scheduling. As shown in fig. 2, since the departure flight gate information (origin apron, gate, landing apron, departure gate, arrival time, departure time, serial number, model, etc.) is missing, these flight data are deleted.
S2: decomposing the original inbound and outbound flight tasks of the airport into corresponding subtasks;
specifically, each departure flight task or each arrival flight task is decomposed into different subtasks of the same service object, and the departure subtask and the arrival subtask have corresponding time attributes, which mainly include planned arrival time, planned departure time, planned arrival time, and planned ending time. The waiting time is set between the planned arrival time and the planned departure time, the real load transfer time is set between the planned departure time and the planned arrival time, and the waiting time is set between the planned arrival time and the planned ending time.
The departure subtask has two basic modes, and the entry subtask has one basic mode:
(1) and in the departure mode 1, the vehicle is departed from the airport apron to the airport apron where the takeoff airplane is located.
(2) And in the departure mode 2, the airplane departs from the apron where the gate is located to reach the apron where the takeoff airplane is located.
(3) The airport-entering mode, from the arrival at the apron where the airplane is located to the departure at the apron.
Subtasks are defined as a single vehicle that completes one passenger departure from the gate to the airport where the flight departs, or return to the airport where the flight arrives.
If the airport requires that the passenger capacity of the vehicle is used as a division standard, the number of the subtasks can be determined by dividing the number of the passengers carried by the flight by the upward integer of the maximum passenger capacity of the vehicle. If the airport requires a fixed number of service vehicles per flight service, then the number of subtasks is based on the fixed number. When a plurality of vehicles serve the same flight, the planned in-place time and the planned end time of the subtasks generated after the decomposition should be changed according to the relevant regulations of the airport.
Take the airport as an example that requires a fixed number of service vehicles per flight service, and the fixed number is taken as the number of subtasks. When a plurality of vehicles serve the same flight, the planned in-place time and the planned end time of the subtasks generated after the decomposition are changed according to the relevant regulations of the airport.
S2 relates to the following parameters:
Tpp,qthe transfer time of apron p and apron q,
outspmthe position corresponding to the gate of the departure task m,
outfpmthe apron corresponding to the position of the departure task m,
STDmflight departure time of the departure task m;
STAnthe flight arrival time of the inbound task n.
When there are different kinds of vehicles serving the same flight, the flight decomposition subtask time attribute is as follows, wherein the related constant is set according to the airport, and can be set differently according to different airports.
1 st vehicle A
Planning the in-place time: STA (station)n-5；
Planning end time:
2 nd vehicle A
Planning the in-place time: STA (station)n；
Planning end time:
vehicle 3A
Planning the in-place time: STA (station)n+5；
Planning end time:
1 st vehicle B
Planning the in-place time: STA (station)n-5；
Planning end time:
after the outbound flight and the inbound flight are subjected to subtask decomposition, the outbound flight generates two basic modes, namely an outbound mode 1 (departure from a vehicle apron to an apron where a takeoff airplane is located) and an outbound mode 2 (departure from the apron where a gate is located to the apron where the takeoff airplane is located). Inbound flights will create an inbound pattern from arriving at the airport where the aircraft is located to arriving at the departure airport.
The subtask decomposition results are shown in FIG. 3.
S3: and performing task chain combination on the subtasks based on the screening condition and the preference rule to form a task chain.
After the inbound and outbound tasks are decomposed, the merging mode of two subtasks is researched, and then the subtasks are tried to be merged into a task chain according to the merging mode of the plurality of subtasks. Before trying to combine, screening a candidate set, and distributing subtasks in the screened candidate set to different task chains according to a set priority rule.
Three merging modes based on two subtasks:
(1) the continuous departure mode 1 is a series connection of two departure modes 1.
(2) The continuous departure mode 2 is a series connection of a departure mode 1 and a departure mode 2.
(3) The mixed entry and exit modes are a series connection of an exit mode 1 and an entry mode.
The task chain merging mode has four types as follows, and the related diagram is shown in fig. 4:
(1) merging of several departure modes 2.
(2) A combination of several egress modes 2 and one ingress mode.
(3) A combination of one departure mode 1 and several departure modes 2.
(4) A combination of one departure mode 1 and several departure modes 2 and a combination of one arrival mode.
In S3, after the task chain merging mode is established, candidate set screening is performed on the subtasks, where 1, 2, 3, and 4 are conditions that must be satisfied, 5 and 6 are conditions that must be satisfied by either of two, and a schematic diagram of the screening conditions is shown in fig. 5:
(1) the required vehicles of each task chain are of the same type, start from the initial apron and finally return to the initial apron, and the on-site waiting time between the subtasks cannot exceed the maximum waiting time.
(2) The waiting time for the front item subtask to finish, the time for the front item to transfer back to the initial apron, and the time for transferring the back item from the initial apron to the apron.
(3) The planned end time of the next subtask + (the end time of the previous subtask + the end waiting time of the previous subtask + the transfer time of the previous and next subtask-the planned in-place time of the next subtask) + the next time + the time of returning to the original apron-the time when the task chain start time is less than or equal to the maximum continuous working time.
(4) The planned end time of the next subtask + (the end time of the previous subtask + the end waiting time of the previous subtask + the transfer time of the previous item-the planned in-place time of the next subtask) + the next time + the time of returning to the initial apron is less than or equal to the shift limit time + the allowed overtime (the shift limit time is the time of stopping work of all vehicles).
(5) The plan in-place time-maximum allowable lead time of the next subtask is less than or equal to the end time of the previous subtask, the end waiting time of the previous subtask, the transfer time of the previous and next subtasks and the plan in-place time of the next subtask.
(6) The planned in-place time of the next subtask is less than or equal to the ending time of the previous subtask, the ending waiting time of the previous subtask, the transfer time of the previous and next subtasks, the planned in-place time of the next subtask and the maximum allowable delay time.
In S3, after the subtasks are screened, the following two merging rules may be used when merging the subtasks:
(1) time precedence rule (by time): and after the previous subtask is finished, selecting the subtask with the earliest starting time in the subtask candidate set and adding the subtask into the task chain.
(2) Saving priority rule (by max): and after the previous subtask is finished, selecting a subtask candidate set, and adding the subtask with the largest difference between the (time for returning the previous item to the initial apron + time for transferring the previous item from the initial apron to the next item to the apron) and the (time for waiting for finishing the previous item subtask + time for transferring the previous item and the next item) into the task chain.
The idea of subtask merging is as follows: and taking the subtask executed earliest in the same shift as the first subtask of the first task chain, after the first subtask is completed, screening a candidate set, and selecting the next subtask in the candidate set according to a priority rule. And continuously repeating the candidate set screening and the priority rule selection. And when the candidate set is an empty set, the task chain is bound, and the next task chain is screened until all subtasks are combined. The task chain assembly flow is shown in fig. 6.
The task chain assembly flow is as follows:
step 1: initializing, and arranging a subtask list in a time sequence;
step 2: taking the subtask to be executed earliest in the same shift as the first subtask of the task chain, and going to step 6 when the subtask to be executed does not exist;
and step 3: and (5) screening a candidate set. When the candidate set is an empty set, go to step 5;
and 4, step 4: selecting subtasks from the candidate set according to a priority rule, adding the subtasks into the task chain, and going to step 3;
and 5: the task chain is finished to step 2;
step 6: and ending, and outputting the existing task chain list.
S4: on the basis of the task chain, distributing the task chain to the staff to form a staff task package;
and under the condition that human resources are mainly limited, the employees can receive and distribute all task chains through screening of the candidate set according to the priority rule to form employee task packages. An employee task package is defined as a combination of task chains assigned to an employee. In the example, the main limiting conditions are that the total working time of the staff is less than a certain time, the longest continuous working time of the staff is less than a certain time, the working time of the staff is balanced with the number of tasks, and the working time period of the staff is limited (early, middle and late).
After combining subtasks to obtain different task chains, the staff will receive and distribute all task chains,
a set of task chains is represented that is,
representing a set of employees. Q se1 denotes the e-th bitAnd the employee completes the s-th task chain, otherwise, the task chain is not completed.
On the principle that the working time and the working amount of the staff are relatively balanced and reasonable, when the staff task packages receive the task chain, the working time and the number of the tasks in each staff task package are relatively average to the greatest extent.
To ensure that the workload is relatively even, the following data should be calculated at the time of allocation:
average work time of staff: total duration/number of people for all task chains;
average working time of early employees: the total length of the task chain/number of people in the morning shift from the beginning;
average working time of middle-class employees: starting from the total duration of the task chain/the number of people in middle class;
average working time of night shift employees: starting from the total time of the task chain of the night class/the number of the night class people;
the minimum required employee number N in a time period: the total duration of the task chain in the time interval is 8 hours (rounded up);
when the task chain candidate set is screened, the task chain receivable by the employee task package meets the following conditions:
(1) each employee can only complete one task chain at the same time;
(2) the total time of each employee task package is less than the maximum working time;
(3) the continuous working time between task chains does not exceed the maximum continuous working time;
when the task chain combination is carried out, the task balance principle is used as a priority rule, namely in the task package candidate set, the task chain to be executed is preferentially distributed to the feasible staff task package with the minimum total working time.
The task chain combination method is characterized in that N worker task packages are established according to the minimum required number of workers in a time period, and a task chain list is arranged according to the work starting time sequence. Directly distributing N task chains with the earliest starting time to N worker task packages, screening a candidate set when the residual task chains exist, selecting the worker task packages of the received task chains in the candidate set according to a priority rule, and adding new worker task packages when the candidate set is an empty set. Until all task chains are allocated.
The employee task package assembly process is as follows, and the employee task package assembly process is shown in fig. 7:
step 1: initializing, and arranging a task chain list in a starting time sequence;
step 2: establishing N employee task packages according to the minimum required employee number N in a time period, and directly distributing N task chains to be executed earliest to the N employee task packages;
and step 3: when the residual task chain exists, going to step 4; if no task chain to be completed exists, going to step 7;
and 4, step 4: screening a candidate set, and carrying out step 6 when the candidate set is an empty set;
and 5: selecting a priority rule, and receiving a task chain until a step 3 is performed;
step 6: adding a new employee task package to the step 4;
and 7: and finishing, finishing all task chains and outputting a task package list of the staff.
S5: and on the basis of the task chain, distributing the task chain to the vehicles to form a ferry vehicle task package.
Specifically, under the condition that vehicle resources are mainly limited, the vehicles receive and distribute all task chains through candidate set screening according to a priority rule to form a ferry vehicle task package. A ferry car mission package is defined as a combination of a plurality of mission chains assigned to a car (each of which starts at the original level of the car, passes through a number of nodes, and returns to the original level). The main limitations in the examples are: the vehicle is always in operation for less than a certain time, and the vehicle type is consistent with the vehicle type required by the task chain.
Since the vehicles have no limit conditions such as rest time and maximum working time, task chain receiving distribution is carried out on the vehicles according to different combination rules.
A set of task chains is represented that is,
representing a collection of vehicles. QscThe result is 1 when the c-th vehicle completes the s-th task chain, otherwise the task chain is not completed.
Because the types of vehicles are different, preparation is simultaneously made for analyzing and comparing scheduling results, the average working time of various vehicles needs to be calculated, and the calculation method comprises the following steps:
vehicle average operating time: the total duration/number of vehicles of the task chain;
average working time of the cart: the total duration of the task chain of the A-type vehicles/A vehicle number;
average working time of the trolley: the total duration of the task chain of the type B vehicles/the number of the vehicles B;
when the task chain candidate set is screened, the ferry vehicle task package can receive the task chain and needs to meet the following screening conditions:
(1) each vehicle can only complete one task chain at the same time;
(2) the total time of each ferry vehicle task package is less than 24 hours;
(3) the vehicle type is consistent with the demanded vehicle type of the task chain.
When the task chains are combined, the task balance principle is used as a priority rule, and in the task package candidate set, the task chains to be executed are preferentially distributed to the feasible ferry vehicle task packages with the minimum total working time.
The distribution process of S5 is basically the same as the distribution process of S4, and the difference is that different task chains correspond to different types of vehicles.
The ferry vehicle task package combination process is as follows:
step 1: initializing, and arranging a task chain list in a starting time sequence;
step 2: when the residual task chain exists, going to step 3; if no task chain to be completed exists, going to step 6;
and step 3: screening a candidate set, and carrying out step 5 when the candidate set is an empty set;
and 4, step 4: selecting a priority rule, and receiving a task chain until step 2;
and 5: adding a new ferry vehicle task package to the step 2;
step 6: and (5) finishing the distribution of all task chains, and outputting a ferry vehicle task package list.
S6: a complete airport ferry service scheduling scheme is formed by integrating the ferry vehicle task package and the staff task package distribution scheme;
and integrating the staff task package distribution scheme in the S4 and the ferry vehicle task package distribution scheme in the S5 to obtain a total airport ferry service scheduling scheme.
S7: and establishing an evaluation system according to each index, and evaluating the airport ferry service scheduling scheme.
And establishing an evaluation system for each index, evaluating the airport ferry service scheduling scheme, and adopting the evaluation indexes to perform total task time comparison analysis, no-load and real-load time analysis, working hour utilization rate analysis and total task balance analysis.
The invention adopts more evaluation indexes in the aspect of scheduling scheme evaluation, such as total task time comparison analysis, no-load and real-load time analysis, man-hour utilization rate analysis, total task balance analysis and the like. Therefore, a decision maker can obtain more comprehensive overall ferry scheduling scheme evaluation and select a scheme according to personal preference. The scheme indexes mainly aim at the problem established by a scheduling scheme evaluation system, relate to scheme data processing and implementation effect prediction, and can reversely adjust program parameters through the scheme indexes so that the overall scheme meets different principle requirements such as an economic principle or a fairness principle.
In the example, the basic scheduling is used as a reference, and the basic scheduling means that for each subtask, an assigned vehicle departs from the initial apron, and returns to the initial apron directly after the subtask is completed.
For basic scheduling, the total task time is the sum of the time from the initial apron of the corresponding car number of all subtasks to the initial apron of the car after the passenger is delivered. The optimal scheduling total time refers to the sum of the time of all task chains.
The vehicle empty and loaded time analysis is shown in fig. 8. The overall vehicle mission balance is shown in fig. 9. The final scheduling scheme is shown in fig. 10.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. An airport ferry service scheduling method is characterized by comprising the following steps:
s1, taking each flight data in a scheduling period as a task, and decomposing each task into subtasks of the number of ferry vehicles corresponding to the model according to the number of ferry vehicles required by passengers for receiving and delivering in different models;
s2, for each subtask, constructing all subtasks which are not in conflict with the subtask time and are consistent with the type of the ferry vehicle required as a candidate set of the subtask; constructing a new task chain by taking the earliest started subtask which is not combined into the task chain as an initial node, selecting the next subtask in the same task chain from the candidate set of the adjacent previous subtask, finishing the construction of the task chain until the candidate set of the last subtask in the task chain is empty, and repeating the operation until all subtasks are combined into the task chain;
s3, for each task chain, constructing all task chains which are not in conflict with the task chain time and are consistent with the type of the ferry vehicle required as a candidate set of the task chain; constructing a new ferry vehicle task package by taking the earliest starting task chain which is not combined into the ferry vehicle task package as an initial item, wherein the later task chain in the same ferry vehicle task package is selected from the candidate set of the adjacent previous task chain, and the construction of the task package is finished until the candidate set of the last task chain in the ferry vehicle task package is empty, and the operation is repeated until all the task chains are combined into the ferry vehicle task package;
s4, for each task chain, constructing all task chains which are not in conflict with the task chain time and the total duration of all subtasks in the task chain including the task chain does not exceed the legal working duration of the staff as a candidate set of the task chain; constructing a new employee task package by taking the earliest started task chain which is not combined into the employee task package as an initial item, wherein the next task chain in the same employee task package is selected from the candidate set of the adjacent previous task chain, the construction of the task package is finished until the candidate set of the last task chain in the employee task package is empty, and the operation is repeated until all task chains are combined into the employee task package;
s5, obtaining the mapping relation of the airport staff task package and the ferry vehicle task package to the subtasks respectively, and obtaining the complete scheduling scheme of the ferry vehicles and the staff required by all the subtasks.
2. The method of claim 1, wherein prior to task decomposition, pre-processing of raw flight data is performed, the pre-processing including checking data consistency, clearing out-of-range data, processing invalid data, and missing data.
3. The method of claim 1, wherein in step S1, the sub-tasks obtained by decomposition include: the type of the ferry vehicle required, the type of entering/exiting port, the starting point apron, the ending point apron, the starting time of the subtask, the execution time of the subtask and the ending time of the subtask.
4. The method of claim 3, wherein in step S2, the rules for constructing the candidate set are as follows:
(1) the demand ferry vehicle of each task chain is of the same type, starts from the starting apron and finally returns to the starting apron, and the in-situ waiting time between the subtasks cannot exceed the maximum waiting time;
(2) the waiting time for the front item subtask to finish, the transfer time of the front item and the back item are less than or equal to the time for the front item to return to the initial apron and the time for transferring the back item from the initial apron to the final apron;
(3) the planned end time of the next subtask + (the end time of the previous subtask + the end waiting time of the previous subtask + the transfer time of the previous and next subtask-the planned in-place time of the next subtask) + the next time + the time of returning to the starting apron-the time when the task chain starts is less than or equal to the maximum duration working time;
(4) the planned end time of the next subtask + (the end time of the previous subtask + the end waiting time of the previous subtask + the transfer time of the previous and next items-the planned in-place time of the next subtask) + the next time + the time of returning to the starting apron is less than or equal to the time of the shift limit + the allowed overtime;
(5) the plan in-place time-maximum allowable lead time of the next subtask is less than or equal to the end time of the previous subtask, the end waiting time of the previous subtask, the transfer time of the previous and next subtasks and the plan in-place time of the next subtask;
(6) the planned in-place time of the next subtask is less than or equal to the ending time of the previous subtask, the ending waiting time of the previous subtask, the transfer time of the previous and next subtasks, the planned in-place time of the next subtask and the maximum allowable delay time;
wherein, the conditions (1) to (4) are the conditions which must be satisfied, and the conditions (5) and (6) are the conditions which are satisfied by either one of them.
5. The method according to any of claims 1 to 4, wherein in step S2, the selection rule is any of the following:
(1) time priority rules: after the previous subtask is finished, selecting the subtask with the earliest starting time in the subtask candidate set to add into the task chain;
(2) saving priority rules: and after the previous subtask is finished, selecting a subtask candidate set, and adding the subtask with the largest difference between the (time for returning the previous item to the starting apron + time for transferring from the starting apron to the next item end apron) and the (waiting time for finishing the previous item subtask + time for transferring the previous item and the next item) into the task chain.
6. The method of claim 1, wherein in step S3, the ferry vehicle task package can receive the task chain satisfying the following screening conditions:
(1) each ferry vehicle can only complete one task chain at the same time;
(2) each ferry vehicle task package comprises a task chain time length and the total time length of the next task chain is less than the scheduling period;
(3) the type of the ferry vehicle is consistent with the type of the ferry vehicle required by the task chain.
7. The method of claim 1 wherein in step S3, the task chain to be performed is preferably assigned to the feasible ferry vehicle task package with the least total operating time during the pick.
8. The method of claim 1, wherein in step S4, the employee task package receivable task chains satisfy the following condition:
(1) each employee can only complete one task chain at the same time;
(2) the total time of each employee task package is less than the legal working time of the employee;
(3) the continuous working time between task chains does not exceed the maximum allowed continuous working time.
9. The method of claim 1, wherein in step S4, the task chain to be performed is preferably assigned to the feasible employee task package with the least total work time when picking.
10. An airport ferry service dispatch system, comprising: a computer-readable storage medium and a processor;
the computer-readable storage medium is used for storing executable instructions;
the processor is configured to read executable instructions stored in the computer-readable storage medium and execute the airport ferry service scheduling method of any of claims 1 to 9.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117236473A (en) * | 2023-11-10 | 2023-12-15 | 华中科技大学 | Method and system for distributing paths of passenger co-riding vehicles in junction evacuation scene |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105336222A (en) * | 2015-10-27 | 2016-02-17 | 中国民用航空总局第二研究所 | Airport ground intelligent command and dispatching system and method |
| CN106652631A (en) * | 2016-12-12 | 2017-05-10 | 天津盛扬信远科技有限公司 | Airport operation control simulation training device |
| CN107301510A (en) * | 2017-06-26 | 2017-10-27 | 北京首都国际机场股份有限公司 | A kind of tank service truck and ferry bus coordinated dispatching method based on genetic algorithm |
| CN111291888A (en) * | 2020-01-21 | 2020-06-16 | 西安科技大学 | Scheduling optimization method for airport special vehicles |
| CN112036768A (en) * | 2020-09-14 | 2020-12-04 | 民航数据通信有限责任公司 | Intelligent scheduling system and method for airport scene vehicles |
-
2021
- 2021-01-18 CN CN202110062039.6A patent/CN112862260B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105336222A (en) * | 2015-10-27 | 2016-02-17 | 中国民用航空总局第二研究所 | Airport ground intelligent command and dispatching system and method |
| CN106652631A (en) * | 2016-12-12 | 2017-05-10 | 天津盛扬信远科技有限公司 | Airport operation control simulation training device |
| CN107301510A (en) * | 2017-06-26 | 2017-10-27 | 北京首都国际机场股份有限公司 | A kind of tank service truck and ferry bus coordinated dispatching method based on genetic algorithm |
| CN111291888A (en) * | 2020-01-21 | 2020-06-16 | 西安科技大学 | Scheduling optimization method for airport special vehicles |
| CN112036768A (en) * | 2020-09-14 | 2020-12-04 | 民航数据通信有限责任公司 | Intelligent scheduling system and method for airport scene vehicles |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117236473A (en) * | 2023-11-10 | 2023-12-15 | 华中科技大学 | Method and system for distributing paths of passenger co-riding vehicles in junction evacuation scene |
| CN117236473B (en) * | 2023-11-10 | 2024-01-30 | 华中科技大学 | Method and system for distributing paths of passenger co-riding vehicles in junction evacuation scene |
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