Method, device, medium and electronic equipment for generating crew scheduling plan

Abstract

Embodiments of the present application provide a method and device for generating a crew scheduling plan, a computer readable medium and an electronic device. The method comprises: obtaining a daily operation timetable of a train line to be arranged for scheduling, the daily operation timetable comprising at least train numbers of trains, stations passed by the trains and arrival times of the trains at the stations; splitting the daily operation timetable into a plurality of sub-tasks according to the stations passed by each train and the arrival times of the trains at the stations; determining business rules of rail transit for crew members; generating a plurality of constraint conditions according to the business rules; inputting the plurality of sub-tasks and the plurality of constraint conditions into a target model to output a crew scheduling plan table with the least number of required crew members by the target model, the crew scheduling plan table comprising value-riding task data of each crew member. The above technical solution can quickly generate a crew scheduling plan table corresponding to train numbers to achieve optimal configuration of people and train numbers.

Description

Technical Field

[0001] This application relates to the field of computer and data processing technology, and more specifically, to a method, apparatus, computer-readable medium, and electronic device for generating a flight attendant scheduling plan. Background Technology

[0002] Optimization methods for urban rail transit crew scheduling play a crucial role in improving the operational efficiency of urban rail transit and are also a research direction in the optimization of urban rail transit transportation organization. Crew scheduling plans specify the work arrangements for crew members within a shift cycle. Typically, crew scheduling plans are created by combining several consecutive crew segments into crew work sections, which in turn form crew shifts. Crew members then perform their duties according to the train numbers specified in the shifts. A crew segment is the smallest segment that allows for continuous completion of the duty task, obtained by dividing all the operating lines in a given timetable using a departure station, depot, or parking lot as dividing points. A rationally designed crew scheduling plan, arranging suitable work and rest times for crew members, is of great significance for improving the transportation organization efficiency, service level, and safety of operating companies.

[0003] The train crew scheduling plan refers to the process of dividing and reorganizing the train lines according to the conditions of the train lines and the crew system, based on a given train timetable, to obtain a set of feasible task numbers. In existing technologies, the task-balanced optimization method for train crew scheduling fully considers the current piece-rate salary system for urban rail transit crew members, aiming to minimize the cost of the generated crew scheduling plan. It constructs a set-partitioning master programming model and a crew task generation sub-programming model, and designs a labeling method based on shadow price selection for iterative solution. This scheme uses a set-covering model and a set-partitioning model to establish the crew problem model. To solve this problem and obtain its dual variables, the master problem can be linearly relaxed to obtain a linear programming problem. After iteration, the master problem is pruned using a branch-and-price method to obtain a 0-1 integer solution.

[0004] However, the existing technology only considers the full coverage of the flight attendant tasks for the flight attendant segments. Furthermore, the main planning problem and the sub-planning problem require solving the sub-problems once for each iteration. In real-world business scenarios, the large-scale data will lead to slow solution speeds and low scheduling efficiency. Summary of the Invention

[0005] The embodiments of this application provide a method, apparatus, computer program product or computer program, computer-readable medium and electronic device for generating a flight attendant schedule, which can at least improve the efficiency of generating the schedule to a certain extent.

[0006] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0007] According to one aspect of the embodiments of this application, a method for generating a train attendant shift schedule is provided. The method includes: obtaining a daily timetable of a train line for which a shift schedule needs to be arranged, the daily timetable including at least the train numbers of the trains running on the train line, the stations the trains pass through, and the arrival time at each station; dividing the daily timetable into multiple sub-tasks based on the stations each train passes through and the arrival time at each station; determining the business rules for train attendants in rail transit; generating multiple constraints based on the business rules; and inputting the multiple sub-tasks and the multiple constraints into a target model to output a train attendant shift schedule with the minimum number of attendants required, the train attendant shift schedule including the duty data of each attendant.

[0008] According to one aspect of the embodiments of this application, an apparatus for generating a crew member shift schedule is provided. The apparatus includes: a timetable acquisition unit, configured to acquire a daily operating timetable for a train line for which a shift schedule is to be arranged, the daily operating timetable including at least the train numbers of the trains running on the train line, the stations the trains pass through, and the arrival time at each station; a task splitting unit, configured to split the daily operating timetable into multiple sub-tasks according to the stations each train passes through and the arrival time at each station; and a shift schedule generation unit, configured to determine the business rules for crew members in rail transit, generate multiple constraints according to the business rules, input the multiple sub-tasks and the multiple constraints into a target model, and output a crew member shift schedule with the minimum number of crew members required through the target model, the crew member shift schedule including the duty task data of each crew member.

[0009] In some embodiments of this application, based on the foregoing scheme, the task splitting unit is further configured to: add a type identifier to the train number when the train number is a special train number type; input the multiple sub-tasks, the multiple constraints, and the type identifier into the target model, so as to output a crew scheduling plan table with the minimum number of crew members required for all trains running on the train line through the target model, and output a shift table for additional crew members for special train numbers through the target model according to the special operating rules corresponding to the type identifier, wherein the shift table for additional crew members includes the shift task data of each crew member.

[0010] In some embodiments of this application, based on the aforementioned scheme, the special train type includes at least one of the following: first train, last train, commuter train, outbound train, and reverse train from the depot.

[0011] In some embodiments of this application, based on the foregoing scheme, the task splitting unit is further configured to: input the plurality of sub-tasks and the plurality of constraints into a target model, so as to form a task chain by the target model of the plurality of sub-tasks that meet the plurality of constraints, and the target model determines the minimum number of crew members required for all trains running on the train line and the crew member shift schedule based on the number of task chains; wherein, each task chain corresponds to one crew member on duty.

[0012] In some embodiments of this application, based on the aforementioned scheme, the constraints include at least the following conditions: the mileage of each task chain does not exceed the upper limit of the mileage of the task period to which the task chain belongs; the cumulative working hours of each task chain do not exceed the upper limit of the working hours of the task period to which the task chain belongs, and are not lower than the lower limit of the working hours of the task period to which the task chain belongs; the working hours without meals for each task chain are lower than the upper limit of the working hours with meals; the ride time at stations with convenient rides is greater than the lower limit of the ride time, and less than or equal to the upper limit of the ride time; the number of attendants using each station as their departure point is lower than the upper limit of the number of attendants on duty; the number of attendants who finish their duty in any preset task period is lower than the upper limit of the number of attendants who leave duty; for any task chain, the mileage of the task chain belongs to the same task period.

[0013] In some embodiments of this application, based on the foregoing scheme, for any task chain, when the task chain consists of at least two sub-tasks, the following conditions are met: the departure location of the task chain is the departure location of the sub-task with the earliest shift time, and the departure location of the task chain is the departure location of the sub-task with the latest shift time; the shift mileage of the task chain is the sum of the shift mileage of the multiple sub-tasks that make up the task chain; the cumulative working hours of the task chain is the sum of the cumulative working hours of the multiple sub-tasks that make up the task chain and the shift preparation time of the task period to which it belongs; the attendants on duty in the task chain are assumed to be in a state of not having eaten; the departure location of the task chain is also the pick-up location of the task chain.

[0014] In some embodiments of this application, based on the foregoing scheme, the business rules include at least the pick-up and drop-off rules for the train, transfer constraint rules, meal rules, rest rules, and shift operation rules.

[0015] According to one aspect of the embodiments of this application, a computer program product or computer program is provided, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method for generating a flight attendant scheduling plan as described in the above embodiments.

[0016] According to one aspect of the embodiments of this application, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method for generating a flight attendant scheduling plan as described in the above embodiments.

[0017] According to one aspect of the embodiments of this application, an electronic device is provided, including: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the method for generating a flight attendant scheduling plan as described in the above embodiments.

[0018] In some embodiments of this application, the technical solutions involve obtaining the daily timetable of the train line to be scheduled, breaking down the daily timetable into multiple sub-tasks based on the stations each train passes through and its arrival time at each station, and determining the operational rules for train attendants to generate corresponding constraints. These sub-tasks and constraints are then input into a target model to output a train attendant scheduling plan that minimizes the number of attendants required for all trains. The train attendant scheduling plan includes the duty data for each attendant. This technical solution, by constructing a mixed-integer programming target model, overcomes the limitations of manual scheduling. While ensuring stable operation of the rail transit system, it comprehensively considers various operational rules and personnel capabilities, optimizing the scheduling plan from a global perspective, rationally and evenly allocating tasks, and quickly generating a train attendant scheduling plan corresponding to all trains running on the line. This achieves optimal personnel and train number configuration, comprehensively improving productivity and the efficiency of train attendant scheduling.

[0019] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0020] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0021] Figure 1 A schematic diagram of an exemplary system architecture to which the technical solutions of the embodiments of this application can be applied is shown;

[0022] Figure 2 A flowchart illustrating a method for generating a flight attendant shift schedule according to an embodiment of this application is shown;

[0023] Figure 3 A block diagram of a flight attendant scheduling apparatus according to one embodiment of this application is shown;

[0024] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown. Detailed Implementation

[0025] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0026] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0027] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0028] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0029] It should be noted that "multiple" in this article refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0030] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such uses of these terms can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described.

[0031] Figure 1 A schematic diagram of an exemplary system architecture to which the technical solutions of the embodiments of this application can be applied is shown.

[0032] like Figure 1 As shown, the system architecture may include a server 101 (which may also include one or more of smartphones, tablets, and laptops), a terminal 102, and a network 103. The network 103 serves as the medium for providing a communication link between the server 101 and the terminal 102. The network 103 may include various connection types, such as wired communication links, wireless communication links, etc.

[0033] In one embodiment of this application, the method for generating the flight attendant scheduling plan can be executed by server 101, or further, by terminal 102 in cooperation with server 101.

[0034] Specifically, server 101 can obtain the daily timetable of the train lines for which a scheduling plan needs to be arranged. The daily timetable includes at least the train numbers running on the lines, the stations the trains pass through, and the arrival time at each station. Users can select the train lines for each scheduling plan through terminal 102 and send them to server 101. Server 101 can obtain the daily timetable for that train line and then break it down into multiple sub-tasks based on the stations the trains pass through and the arrival time at each station. Users can also input the rail transit's business rules for train attendants through terminal 102 and send them to server 101. After determining the business rules, server 101 can generate multiple constraints based on the business rules and input the resulting sub-tasks and constraints into a mixed-integer programming target model to output a train attendant scheduling plan with the minimum number of attendants required. Specifically, the train attendant scheduling plan includes the duty assignment data for each attendant.

[0035] This application overcomes the limitations of manual scheduling by constructing a target model of mixed integer programming. Under the premise of ensuring stable operation of rail transit, it comprehensively considers various business rules and personnel capabilities, optimizes the scheduling plan from a global perspective, allocates tasks reasonably and evenly, and quickly generates a crew scheduling plan table corresponding to all trains running on the line, so as to achieve the optimal configuration of personnel and trains, and comprehensively improve productivity and crew scheduling efficiency.

[0036] The implementation details of the technical solutions in the embodiments of this application are described in detail below:

[0037] Figure 2 A flowchart illustrating a method for generating a flight attendant shift schedule according to an embodiment of this application is shown. This method can be executed by a device with computational processing capabilities, such as a [device name missing]. Figure 1 The server and terminal shown cooperate to execute the command. (Refer to...) Figure 2 As shown, the method for generating the flight attendant shift schedule includes at least steps 210 to 250, which are detailed below:

[0038] In step 210, the daily timetable of the train line to be scheduled is obtained. The daily timetable includes at least the train numbers of the trains running on the line, the stations the trains pass through, and the arrival time at each station.

[0039] In this application, the method for generating a crew scheduling schedule can be applied to scenarios requiring scheduling. For example, it can be used to schedule crew members for subway trains, high-speed rail or bullet trains, or intercity trains. Specifically, a single train line can include multiple operating trains, each corresponding to a train number. The daily timetable includes at least the train number of the train running on the line, the stations the train passes through, and the arrival time at each station. For example, train number A1 runs from Shanghai South Station to Jinhua, passing through Jiaxing, Haining, Hangzhou South, and Yiwu. The timetable for train number A1 includes the departure time from Shanghai South Station, the arrival time in Jinhua, the stations it passes through, the arrival time at each station, and the departure time from each station. Furthermore, the daily timetable also includes special stations, such as turnaround stations, terminal stations, and depots, and may also include timestamps corresponding to virtual platforms in the signaling system.

[0040] In step 220, the daily timetable is broken down into multiple sub-tasks based on the stations each train passes through and the arrival time at each station.

[0041] In this application, after obtaining the daily timetable for the train line, the server can break down the daily timetable into multiple sub-tasks based on the stations each train passes through and its arrival time at each station. This step aims to break down each train into the smallest decision granularity (i.e., sub-task) in the crew scheduling model, that is, to break down the daily timetable based on the platforms and times where crew members can transfer, thereby obtaining multiple crew duty tasks, i.e., multiple sub-tasks, to complete all trains on that train line.

[0042] Continue to refer to Figure 2 In step 220, the task set TASK includes driving tasks, passenger tasks, and / or standby tasks. The aforementioned sub-tasks are tasks included in the task set TASK.

[0043] In step 230, the operational rules for train attendants are determined.

[0044] Different types of rail transit have different operational rules for conductors. Furthermore, the operational rules for conductors may also differ between different train types.

[0045] In one embodiment, the business rules include at least the pick-up and drop-off rules for each train, transfer constraint rules, meal rules, rest rules, and shift operation rules.

[0046] Pick-up and drop-off rules can specify which stations can be used as pick-up and drop-off points, and which stations cannot. Transfer constraint rules can specify which stations can be used as transfer points and the maximum transfer time. Meal rules can include meal times and the maximum time crew members can be without meals. Rest rules can include crew member rest times, the maximum number of crew members resting at the same time, and the maximum rest time. Shift operation rules can include the number of shifts, such as four shifts in three rotations, and the task time slots for each shift, which can include morning shifts, day shifts, night shifts, etc. The specific time corresponding to each task time slot can be determined according to specific business needs.

[0047] In step 240, multiple constraints are generated based on business rules.

[0048] Once the business rules are defined, they can be quantified to generate multiple constraints. For example, for any flight attendant's shift, it can only belong to one shift period, as expressed below:

[0049]

[0050] Among them, Shift_Type i,a The variable, either 0 or 1, indicates whether the value of task i belongs to task time period a, where a ∈ 0, 1, 2. Here, a = 0 represents the morning shift, a = 1 represents the day shift, and a = 2 represents the night shift. Therefore, the task time period constraints generated according to the shift operation rules can be as follows:

[0051]

[0052]

[0053]

[0054]

[0055]

[0056]

[0057] In one embodiment, the method further includes: inputting multiple subtasks and multiple constraints into a target model, so as to form a task chain from the multiple subtasks that meet multiple constraints through the target model, and the target model determines the minimum number of crew members required for all trains running on the train line and the crew member shift schedule based on the number of task chains; wherein, each task chain corresponds to one crew member on duty.

[0058] The primary objective of the target model is to identify interconnected subtasks based on the input data, forming a task chain from these interconnected subtasks. This allows for the creation of N task chains from the initial M subtasks, where M and N are both positive natural numbers, and M is less than or equal to N. Each task chain includes a head and a tail. One flight attendant executes one task chain.

[0059] Head i A variable of 0 or 1 indicates whether subtask i is the head of its task chain, i.e., whether subtask i is the first subtask in the task chain. If yes, then Head... i =1. Tail i A variable of 0 or 1 indicates whether subtask i is the tail of its task chain, i.e., whether subtask i is the last subtask in the task chain. If yes, then Tail i =1. For any subtasks i and j, if i and j meet the connection condition, then i and j belong to the same task chain. In this case, subtasks i and j belong to the same task time period, and its expression is as follows:

[0060]

[0061]

[0062] Where M represents a sufficiently large constant, the specific value of which depends on the magnitude of other constants in the model, Shift_Type j,a The variable is either 0 or 1, used to indicate whether the value multiplied by task j belongs to task time period a, where a∈{0,1,2}. Here, a=0 represents the morning shift, a=1 represents the day shift, and a=2 represents the night shift. ij For variables that are 0 or 1, when i is connected to j, Arc ij=1; conversely, if i and j are not connected, Arc ij =0. For any subtask i, if it is the head of some task chain, Head i =1, then the cumulative mileage Head of subtask i i For its own mileage m i The expression is as follows:

[0063]

[0064] For any subtasks i and j, if i and j are connected, then the cumulative mileage of the task chain formed by i and j is the sum of the cumulative mileages of i and j.

[0065] In one embodiment, the constraint includes at least the following conditions:

[0066] The value multiplied by the mileage for each task chain shall not exceed the mileage limit for the time period to which the task chain belongs;

[0067] The cumulative working hours of each task chain shall not exceed the upper limit of the working hours of the task time period to which the task chain belongs, and shall not be lower than the lower limit of the working hours of the task time period to which the task chain belongs;

[0068] The uneaten working hours of each task chain are lower than the upper limit of the eating working hours. If subtask i is the head of the task chain, the flight attendant executing subtask i is in an uneaten state by default.

[0069] For stations with convenient access, the travel time is greater than the lower limit of the convenient travel time, but less than or equal to the upper limit of the convenient travel time.

[0070] The number of flight attendants using each station as their departure point is less than the maximum number of attendees, which can be determined based on the number of lockers at each station.

[0071] If the number of flight attendants who finish their shifts during any preset task period is less than the maximum number of crew members who leave the duty, the maximum number of crew members who leave the duty can be determined based on the capacity of the apartment where the flight attendants are located.

[0072] For any task chain, the value multiplied by the time of the task chain belongs to the same task time period.

[0073] In step 250, multiple sub-tasks and multiple constraints are input into the target model to output a flight attendant scheduling plan with the minimum number of flight attendants required. The flight attendant scheduling plan includes the duty data of each flight attendant.

[0074] Specifically, the expression for the objective function of the target model is: Minimize∑ i Head i +ω·Deadhead iMinimize refers to the minimum number of crew members required for all trains operating on the line. ω is the penalty coefficient for the passenger transport task; its specific value can be customized according to requirements. Deadhead i This refers to whether subtask i needs to be taken off duty. If so, then Deadhead. i =1, if not, then Deadhead i =0. Therefore, the target model can be used to group subtasks that meet multiple constraints into a single task chain, and the minimum number of crew members required for all trains operating on the line can be determined based on the number of task chains, along with the crew member scheduling plan. Each task chain corresponds to one crew member on duty. The crew member scheduling plan includes the total number of crew members required for all trains, as well as the duty data for each crew member. For example, each row in the crew member scheduling plan represents a task, including key information such as the train number, arrival time, arrival location, disembarkation time, and disembarkation location, as well as derivative information such as flow direction and whether it involves leaving or entering the depot.

[0075] In one embodiment, for any task chain, when the task chain consists of at least two subtasks, the following condition is met:

[0076] The start point of a task chain is the start point of the sub-task with the earliest duty time, and the end point of a task chain is the end point of the sub-task with the latest duty time.

[0077] The value multiplied by the mileage of a task chain is the sum of the value multiplied by the mileage of the multiple subtasks that make up the task chain;

[0078] The cumulative working hours of a task chain are the sum of the cumulative working hours of the multiple sub-tasks that make up the task chain, and the preparation time for the task's time period.

[0079] Flight attendants in the duty task chain are assumed to be in a state of not having eaten;

[0080] The departure point of the task chain is also the pick-up point of the task chain.

[0081] In one embodiment, the method further includes: adding a type identifier to the train number when the train number is a special train number type; inputting multiple sub-tasks, multiple constraints, and the type identifier into the target model to output a crew scheduling plan that minimizes the number of crew members required for all trains running on the train line through the target model; and outputting a shift schedule for additional crew members for the special train number through the target model according to the special operating rules corresponding to the type identifier, wherein the shift schedule for additional crew members includes the shift task data of each crew member.

[0082] Among them, special train types include at least one of the following: first train, last train, commuter train, outbound train, and train departing from the depot in the opposite direction.

[0083] To meet specific capacity demands (such as asymmetrical passenger flow between different directions during special operating periods), depots are typically established in the middle of the train line during linear train route planning, and reverse departure trains are scheduled during timetable compilation. This special departure method requires additional crew members to be arranged from the depot to assist in the reverse departure during the crew scheduling plan. Therefore, the target model can output the duty roster for this special train service, which includes the duty assignment data for each crew member.

[0084] Furthermore, in real-world business scenarios, the hardware infrastructure at certain train line transfer stations does not support crew departures and arrivals. Therefore, the target model will not treat tasks involving receiving passengers at such stations as the beginning of a task chain, nor will it treat tasks involving disembarking passengers at such stations as the end of a task chain. Adding this specific business rule for special train routes to the basic business rules can effectively reduce the model size and improve the solution speed. It also allows for pre-connection of tasks involving receiving passengers and disembarking passengers at such stations.

[0085] Furthermore, based on data analysis of the operation diagrams and shift tables in actual business scenarios, if the morning return segment and afternoon exit segment tasks are executed by the same task card, it will result in a 4-6 hour idle time. This portion of the ineffective working hours of the day shift tasks reduces productivity. To address this issue, the target model can, based on a preset upper limit for idle time, perform pre-edge matching for the morning return segment tasks and afternoon exit segment tasks of each segment and field, using the idle time as a weight, through minimum weight maximum cardinality matching. For tasks that are not matched, corresponding value-multiplication exit and entry segment tasks are generated, allowing them to return to the positive line after entering and exiting the segment and continue executing the value-multiplication task. This improves productivity and the effective utilization of manpower.

[0086] In some embodiments of the technical solutions provided in this application,

[0087] By obtaining the daily timetable of the train lines to be scheduled, the daily timetable is broken down into multiple sub-tasks based on the stations each train passes through and its arrival time at each station. The operational rules for train attendants are then determined to generate corresponding constraints. These sub-tasks and constraints are then input into a target model, which outputs a train attendant scheduling plan that minimizes the number of attendants required for all trains. The schedule includes the duty data for each attendant. This technical solution overcomes the limitations of manual scheduling by constructing a mixed-integer programming target model. While ensuring stable operation of the rail transit system, it comprehensively considers various operational rules and personnel capabilities to optimize the scheduling plan from a global perspective, rationally and evenly allocating tasks and quickly generating a train attendant scheduling plan corresponding to all trains operating on the lines. This achieves optimal personnel and train schedule configuration, comprehensively improving productivity and the efficiency of train attendant scheduling.

[0088] The following describes an embodiment of the apparatus described in this application, which can be used to execute the method for generating a flight attendant scheduling plan as described in the above embodiments of this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method for generating a flight attendant scheduling plan described above in this application.

[0089] Figure 3 A block diagram of an apparatus for generating a flight attendant scheduling plan according to one embodiment of the present application is shown.

[0090] Reference Figure 3 As shown, a flight attendant scheduling plan generation device 300 according to an embodiment of this application includes: a timetable acquisition unit 301, a task splitting unit 302, and a shift table generation unit 303.

[0091] The timetable acquisition unit 301 is used to acquire the daily operating timetable of the train line to be scheduled. The daily operating timetable includes at least the train number of the train running on the train line, the stations the train passes through, and the arrival time of each station.

[0092] Task splitting unit 302 is used to split the daily timetable into multiple sub-tasks based on the stations each train passes through and the arrival time at each station.

[0093] The shift schedule generation unit 303 is used to determine the business rules for train attendants in rail transit, generate multiple constraints based on the business rules, input multiple sub-tasks and multiple constraints into the target model, and output the train attendant shift schedule with the minimum number of attendants required through the target model. The train attendant shift schedule includes the shift task data of each attendant.

[0094] In some embodiments of this application, based on the aforementioned scheme, the task splitting unit 302 is further configured to: add a type identifier to the train number when the train number is a special train number type; input multiple sub-tasks, multiple constraints, and the type identifier into the target model, so as to output a crew scheduling plan table with the minimum number of crew members required for all trains running on the train line through the target model, and output a shift table for additional crew members for special train numbers through the target model according to the special operating rules corresponding to the type identifier, wherein the shift table for additional crew members includes the shift task data of each crew member.

[0095] In some embodiments of this application, based on the aforementioned scheme, special train types include at least one of the following: first train, last train, commuter train, outbound train, and reverse train from the depot.

[0096] In some embodiments of this application, based on the aforementioned scheme, the task splitting unit 302 is further configured to: input multiple sub-tasks and multiple constraints into the target model, so as to form a task chain by combining the sub-tasks that meet multiple constraints among the multiple sub-tasks through the target model, and the target model determines the minimum number of crew members required for all trains running on the train line and the crew member shift schedule based on the number of task chains; wherein, each task chain corresponds to one crew member on duty.

[0097] In some embodiments of this application, based on the aforementioned scheme, the constraints include at least the following conditions: the mileage of each task chain does not exceed the upper limit of the mileage of the task period to which the task chain belongs; the cumulative working hours of each task chain do not exceed the upper limit of the working hours of the task period to which the task chain belongs, and are not lower than the lower limit of the working hours of the task period to which the task chain belongs; the working hours without meals for each task chain are lower than the upper limit of the working hours with meals; the ride time at stations with convenient rides is greater than the lower limit of the ride time, and less than or equal to the upper limit of the ride time; the number of attendants using each station as their departure point is lower than the upper limit of the number of attendants on duty; the number of attendants who finish their duty in any preset task period is lower than the upper limit of the number of attendants who leave duty; for any task chain, the mileage of the task chain belongs to the same task period.

[0098] In some embodiments of this application, based on the foregoing scheme, for any task chain, when the task chain consists of at least two sub-tasks, the following conditions are met: the departure location of the task chain is the departure location of the sub-task with the earliest shift time, and the departure location of the task chain is the departure location of the sub-task with the latest shift time; the shift mileage of the task chain is the sum of the shift mileage of the multiple sub-tasks that make up the task chain; the cumulative working hours of the task chain is the sum of the cumulative working hours of the multiple sub-tasks that make up the task chain and the shift preparation time of the task period to which it belongs; the attendants of the shift task chain are assumed to be in an uneaten state; the departure location of the task chain is also the pick-up location of the task chain.

[0099] In some embodiments of this application, based on the aforementioned scheme, the business rules include at least the pick-up and drop-off rules for train services, transfer constraint rules, meal rules, rest rules, and shift operation rules.

[0100] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown.

[0101] It should be noted that, Figure 4 The computer system 1000 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0102] like Figure 4 As shown, the computer system 1000 includes a Central Processing Unit (CPU) 1001, which can perform various appropriate actions and processes based on programs stored in Read-Only Memory (ROM) 1002 or programs loaded from storage portion 1008 into Random Access Memory (RAM) 1003, such as performing the methods described in the above embodiments. The RAM 1003 also stores various programs and data required for system operation. The CPU 1001, ROM 1002, and RAM 1003 are interconnected via a bus 1004. An Input / Output (I / O) interface 1005 is also connected to the bus 1004.

[0103] The following components are connected to I / O interface 1005: an input section 1006 including a keyboard, mouse, etc.; an output section 1007 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 1008 including a hard disk, etc.; and a communication section 1009 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to I / O interface 1005 as needed. Removable media 1011, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 1010 as needed so that computer programs read from them can be installed into storage section 1008 as needed.

[0104] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1009, and / or installed from removable medium 1011. When the computer program is executed by central processing unit (CPU) 1001, it performs various functions defined in the system of this application.

[0105] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such transmitted data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0106] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0107] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0108] In another aspect, this application also provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method for generating a flight attendant scheduling plan as described in the above embodiments.

[0109] In another aspect, this application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to implement the method for generating the flight attendant scheduling plan described in the above embodiments.

[0110] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0111] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the method according to the embodiments of this application.

[0112] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0113] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for generating a flight attendant shift schedule, characterized in that, The method includes: Obtain the daily timetable of the train line to be scheduled, wherein the daily timetable includes at least the train number of the train running on the train line, the stations the train passes through, and the arrival time at each station; The daily timetable is divided into multiple sub-tasks based on the stations each train passes through and the arrival time at each station; Establish operational rules for rail transit attendants; Multiple constraints are generated based on the business rules; The multiple sub-tasks and multiple constraints are input into the target model to output a flight attendant scheduling plan with the minimum number of flight attendants required. The flight attendant scheduling plan includes the duty assignment data for each flight attendant. The method further includes: The multiple subtasks and multiple constraints are input into the target model so that the subtasks that meet the multiple constraints can be grouped into a task chain by the target model. The target model determines the minimum number of crew members required for all trains running on the train line and the crew member shift schedule based on the number of task chains. Each task chain corresponds to a flight attendant on duty; The constraints include at least the following conditions: The value multiplied by the mileage for each task chain shall not exceed the mileage limit for the time period to which the task chain belongs; The cumulative working hours of each task chain shall not exceed the upper limit of the working hours of the task time period to which the task chain belongs, and shall not be lower than the lower limit of the working hours of the task time period to which the task chain belongs; The uneaten working hours for each task chain are lower than the maximum working hours for meals; For stations with convenient access, the travel time is greater than the lower limit of the convenient travel time, but less than or equal to the upper limit of the convenient travel time. The number of flight attendants using each station as their departure point is lower than the maximum number of attendees allowed. The number of flight attendants who finish their shifts during any preset task period is less than the maximum number of crew members who leave duty. For any given task chain, the value multiplied by the time of the task chain belongs to the same task time period.

2. The method according to claim 1, characterized in that, The method further includes: If the train number is a special train number type, add a type identifier to the train number; The multiple sub-tasks, multiple constraints, and type identifiers are input into the target model to output a crew scheduling plan that minimizes the number of crew members required for all trains operating on the train line. The target model also outputs a shift schedule for additional crew members for special train services based on the special operating rules corresponding to the type identifiers. The shift schedule for additional crew members includes the shift task data for each crew member.

3. The method according to claim 2, characterized in that, The special train types include at least one of the following: first train, last train, commuter train, outbound train, and train departing from the depot in the opposite direction.

4. The method according to claim 1, characterized in that, For any task chain, when the task chain consists of at least two subtasks, the following condition is met: The start point of the task chain is the start point of the sub-task with the earliest shift time, and the end point of the task chain is the end point of the sub-task with the latest shift time. The value multiplied by the mileage of the task chain is the sum of the value multiplied by the mileage of the multiple sub-tasks that make up the task chain; The cumulative working hours of the task chain are the sum of the cumulative working hours of the multiple sub-tasks that make up the task chain, and the attendance preparation time of the task time period to which it belongs; Flight attendants in the aforementioned task chain are assumed to be in a state of not having eaten; The departure location of the task chain is also the pick-up location of the task chain.

5. The method according to claim 1, characterized in that, The business rules include at least the pick-up and drop-off rules for the train service, transfer constraints, meal rules, rest rules, and shift operation rules.

6. A device for generating a flight attendant shift schedule, the device being used to implement the method for generating a flight attendant shift schedule as described in any one of claims 1 to 5, characterized in that, The device includes: The timetable acquisition unit is used to acquire the daily operating timetable of the train line to be scheduled. The daily operating timetable includes at least the train number of the train running on the train line, the stations the train passes through, and the arrival time of each station. The task splitting unit is used to split the daily timetable into multiple sub-tasks based on the stations each train passes through and the arrival time at each station. The shift schedule generation unit is used to determine the business rules for train attendants in rail transit, generate multiple constraints based on the business rules, input the multiple sub-tasks and the multiple constraints into the target model, and output the train attendant shift schedule with the minimum number of attendants required through the target model. The train attendant shift schedule includes the shift task data of each attendant.

7. An electronic device, characterized in that, The electronic device includes one or more processors and one or more memories, wherein at least one piece of program code is stored in the one or more memories, and the at least one piece of program code is loaded and executed by the one or more processors to perform the operations performed by the method for generating a flight attendant scheduling plan as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one piece of program code, which is loaded and executed by a processor to perform the operations performed by the method for generating a flight attendant scheduling plan as described in any one of claims 1 to 5.

Images