CN113570178A

CN113570178A - Scheduling method, equipment, device and storage medium

Info

Publication number: CN113570178A
Application number: CN202010350904.2A
Authority: CN
Inventors: 张理远; 王磊
Original assignee: Alibaba Group Holding Ltd
Current assignee: Alibaba Group Holding Ltd
Priority date: 2020-04-28
Filing date: 2020-04-28
Publication date: 2021-10-29

Abstract

The embodiment of the application provides a scheduling method, equipment, a device and a storage medium. In the embodiment of the application, in a multi-person multi-task scene, target information of a person to be scheduled and target information of a task to be allocated, which correspond to a plurality of scheduling information items respectively, are selected; respectively calculating the contents of the plurality of scheduling information items according to the target information of the personnel to be scheduled and the target information of the tasks to be allocated, which correspond to the plurality of scheduling information items; and generating a scheduling result according to the contents of the plurality of scheduling information items. The content of the plurality of scheduling information items is respectively calculated according to the target information of the person to be scheduled and the target information of the task to be allocated, which correspond to the plurality of scheduling information items, so that the grouping solution of the plurality of scheduling information items is realized, the calculation complexity and the calculation workload can be reduced, the data processing efficiency can be improved, and the scheduling efficiency can be improved.

Description

Scheduling method, equipment, device and storage medium

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a scheduling method, a scheduling apparatus, a scheduling device, and a storage medium.

Background

In order to better provide all-round service for users and improve user experience, most service industries are provided with various positions, and workers respectively perform their functions to ensure the normal and orderly operation of the industries. In some industries, various tasks require employees to have corresponding qualifications and skills, and meanwhile various humanized and fairness scheduling quality requirements must be considered, so that the scheduling problem becomes a complex technical problem.

In order to solve the complex scheduling problem, a complex model is often required to be constructed for solving, but the scheduling efficiency is low due to the large workload of model solving, and even the scheduling result cannot be obtained.

Disclosure of Invention

Aspects of the present application provide a scheduling method, device, apparatus, and storage medium to reduce the workload of scheduling and improve the efficiency of scheduling.

The embodiment of the application provides a scheduling method, which comprises the following steps:

acquiring information of staff to be scheduled and information of tasks to be allocated in a multi-person multi-task scene;

selecting target information of the staff to be scheduled and target information of the task to be allocated, which correspond to a plurality of scheduling information items respectively, from the information of the staff to be scheduled and the information of the task to be allocated;

respectively calculating the contents of the plurality of scheduling information items according to the target information of the personnel to be scheduled and the target information of the tasks to be allocated, which correspond to the plurality of scheduling information items;

and generating a scheduling result according to the contents of the plurality of scheduling information items.

The embodiment of the application further provides a scheduling method, which comprises the following steps:

acquiring information of tasks to be distributed in a multi-task scene;

selecting target information of the tasks to be allocated corresponding to a plurality of scheduling information items from the information of the tasks to be allocated;

respectively calculating the contents of the plurality of scheduling information items according to the target information of the tasks to be distributed corresponding to the plurality of scheduling information items;

An embodiment of the present application further provides a computer device, including: a memory and a processor; wherein the memory is used for storing a computer program;

the processor is coupled to the memory for executing the computer program for performing the steps of the above-described methods.

The embodiment of the present application further provides a shift scheduling device, including: the device comprises an acquisition module, a selection module, a calculation module and a generation module; wherein the content of the first and second substances,

the acquisition module is used for acquiring information of staff to be scheduled and information of tasks to be allocated in a multi-person multi-task scene;

the selection module is used for selecting target information of the staff to be scheduled and target information of the tasks to be allocated, which correspond to a plurality of scheduling information items respectively, from the information of the staff to be scheduled and the information of the tasks to be allocated;

the calculation module is used for respectively calculating the contents of the plurality of scheduling information items according to the target information of the personnel to be scheduled and the target information of the tasks to be allocated, which correspond to the plurality of scheduling information items;

and the generating module is used for generating a scheduling result according to the contents of the plurality of scheduling information items.

the acquisition module is used for acquiring information of tasks to be allocated in a multi-task scene;

the selection module is used for selecting target information of the tasks to be distributed corresponding to the plurality of scheduling information items from the information of the tasks to be distributed;

the calculation module is used for calculating the contents of the plurality of scheduling information items according to the target information of the tasks to be distributed corresponding to the plurality of scheduling information items;

Embodiments of the present application also provide a computer-readable storage medium storing computer instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the above-described methods.

In the embodiment of the application, in a multi-person multi-task scene, target information of a person to be scheduled and target information of a task to be allocated, which correspond to a plurality of scheduling information items, are selected from information of the person to be scheduled and information of the task to be allocated; respectively calculating the contents of the plurality of scheduling information items according to the target information of the personnel to be scheduled and the target information of the tasks to be allocated, which correspond to the plurality of scheduling information items; and generating a scheduling result according to the contents of the plurality of scheduling information items. The content of the plurality of scheduling information items is respectively calculated according to the target information of the person to be scheduled and the target information of the task to be allocated, which correspond to the plurality of scheduling information items, so that the grouping solution of the plurality of scheduling information items is realized, the calculation complexity and the calculation workload can be reduced, the data processing efficiency can be improved, and the scheduling efficiency can be improved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:

fig. 1a and fig. 1b are schematic flow charts of a scheduling method provided in an embodiment of the present application;

fig. 2 is a schematic flow chart of another scheduling method provided in the embodiment of the present application;

fig. 3 and fig. 4 are schematic structural diagrams of a computer device provided in an embodiment of the present application;

fig. 5 and 6 are schematic structural diagrams of a scheduling device provided in an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

Aiming at the technical problem that the scheduling efficiency is low due to large scheduling workload in the existing multi-task scene, in some embodiments of the application, target information of a person to be scheduled and target information of a task to be allocated, which correspond to a plurality of scheduling information items respectively, are selected in a multi-person multi-task scene; respectively calculating the contents of the plurality of scheduling information items according to the target information of the personnel to be scheduled and the target information of the tasks to be allocated, which correspond to the plurality of scheduling information items; and generating a scheduling result according to the contents of the plurality of scheduling information items. The content of the plurality of scheduling information items is respectively calculated according to the target information of the person to be scheduled and the target information of the task to be allocated, which correspond to the plurality of scheduling information items, so that the grouping solution of the plurality of scheduling information items is realized, the calculation complexity and the calculation workload can be reduced, the data processing efficiency can be improved, and the scheduling efficiency can be improved.

The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.

It should be noted that: like reference numerals refer to like objects in the following figures and embodiments, and thus, once an object is defined in one figure or embodiment, further discussion thereof is not required in subsequent figures and embodiments.

Fig. 1a is a schematic flow chart of a scheduling method according to an embodiment of the present application. As shown in fig. 1a, the method comprises:

101. and acquiring information of the staff to be scheduled and information of the tasks to be allocated in the multi-person multi-task scene.

102. And selecting target information of the staff to be scheduled and target information of the task to be allocated, which correspond to the plurality of scheduling information items respectively, from the information of the staff to be scheduled and the information of the task to be allocated.

103. And respectively calculating the contents of the plurality of scheduling information items according to the target information of the personnel to be scheduled and the target information of the tasks to be allocated, which correspond to the plurality of scheduling information items.

104. And generating a scheduling result according to the contents of the plurality of scheduling information items.

In this embodiment, the multi-person multitasking means that there are multiple persons for the person to be scheduled, and there are multiple types of tasks to be allocated. Wherein, a plurality of people means 2 or more than 2 people, and a plurality means 2 or more than 2. The scheduling method provided by the embodiment is suitable for various multi-person multi-task application scenes, especially for application scenes of a large number of workers and a large number of operation tasks. For example, the crew of an application scenario such as an airport, train station, passenger station, port, dock, parking lot, warehouse, factory, agriculture, mall, etc.

Wherein, in the scene of airport staff scheduling, airport personnel include: flight crew and ground crew. The flight crew is a person who serves on the plane and mainly comprises a flight group and a crew group. The flight crew mainly comprises a pilot (captain), flight crew, flight communication staff and the like, and the crew member mainly comprises crew members, security officers (or part-time crew members), police and the like. The ground service personnel refer to personnel who serve on the ground at an airport and mainly comprise two parts of personnel of the airport and an airline company. Such as, but not limited to, post workers for check-in, security check-in, customer service, deployment, ticketing, boarding, and financial department personnel. Of course, the scheduling method provided by the embodiment of the application can also be used for respectively scheduling the flight crew and the ground crew.

In this embodiment, the person to be scheduled is a plurality of persons, and the information of the person to be scheduled includes: the user identification, skill information, rest rules, personal recommended shift and the like of the staff to be scheduled. The user identifier of the person to be scheduled refers to information uniquely identifying the person to be scheduled, and may be a job number of the person to be scheduled. The skill information of the person to be scheduled comprises: the post of the person to be scheduled, the skill proficiency, the qualification and other skill information. The work and rest rules of the staff to be scheduled comprise: the number of hours of work, the number of weeks, the number of days, the number of hours of work, the pattern of vacation, and the like required by the staff to be scheduled. The rest mode refers to the mode of doing two-five rests, doing one-six rests, and whether night shifts are available or not every week. The personal recommended shift is: work shift to be personal to the schdule.

The information of the tasks to be distributed comprises: and the task scheduling method includes one or more of time distribution information of the tasks to be distributed, skill requirement information, a rest mode required by the tasks to be distributed and the like, but is not limited to the above.

The number of the staff to be scheduled is large, and the staff information is complicated; the tasks to be allocated are various, the task information is various, and various humanized and fairness scheduling quality requirements must be considered, so that the scheduling problem becomes a complex technical problem. In order to solve the complex scheduling problem, reduce the workload of scheduling and improve the scheduling efficiency, the target information of the personnel to be scheduled and the target information of the task to be allocated, which correspond to a plurality of scheduling information items respectively, can be selected from the information of the personnel to be scheduled and the information of the task to be allocated; and respectively calculating the contents of the plurality of scheduling information items according to the target information of the personnel to be scheduled and the target information of the tasks to be allocated, which correspond to the plurality of scheduling information items. Therefore, the scheduling task can be split into a plurality of subtasks for processing, the calculation complexity and the calculation amount are reduced, the data processing efficiency is favorably improved, and the scheduling efficiency is favorably improved.

The scheduling information items calculated by each subtask can be partially overlapped or different. The scheduling information item refers to an information item contained in the scheduling result, and may include: the working time of the staff to be scheduled, the type of the assigned task, the place where the task is executed, etc., but not limited thereto.

Further, after the plurality of shift information items are calculated, a shift result may be generated according to the contents of the plurality of shift information items. Further, a shift arrangement result can be output.

In the present embodiment, the output mode of the shift result is not limited. For example, the shift result may be provided to a display device, which displays the shift result. Thus, the user can check the shift result. The display device can be a display screen of a computer device for performing scheduling or an independent physical machine. Alternatively, the display device may be a client device on the user side. Such as a user-side computer, a smart phone, or a wearable device, etc. For another example, the scheduling method provided in this embodiment may be used as a SaaS service, and the server device carrying the service may send the scheduling result to the client device on the user side, and the client device displays the scheduling result, but is not limited thereto.

Alternatively, the computer device may provide the shift result to the display device in a document or table, may also provide a link to a web page on which the shift result is located to the display device, and so on.

In the embodiment, in a multi-person multi-task scene, target information of a person to be scheduled and target information of a task to be allocated, which correspond to a plurality of scheduling information items, are selected from information of the person to be scheduled and information of the task to be allocated; respectively calculating the contents of the plurality of scheduling information items according to the target information of the personnel to be scheduled and the target information of the tasks to be allocated, which correspond to the plurality of scheduling information items; and generating a scheduling result according to the contents of the plurality of scheduling information items. The content of the plurality of scheduling information items is respectively calculated according to the target information of the person to be scheduled and the target information of the task to be allocated, which correspond to the plurality of scheduling information items, so that the grouping solution of the plurality of scheduling information items is realized, the calculation complexity and the calculation workload can be reduced, the data processing efficiency can be improved, and the scheduling efficiency can be improved.

In the embodiment of the present application, a specific implementation manner of calculating the contents of the plurality of shift information items according to the target information of the person to be shifted and the target information of the task to be assigned, which correspond to the plurality of shift information items, is not limited. In some embodiments, a plurality of mathematical solution models may be established according to target information of the person to be scheduled and target information of the task to be allocated, which correspond to the plurality of scheduling information items, respectively. Wherein, a plurality of mathematical solution models can decide the plurality of scheduling information items. Each mathematical solution model decides part of the scheduling information items in the plurality of scheduling information items. The scheduling information items decided by each mathematical solving model can be partially overlapped or different.

Alternatively, the mathematical solution model may be a mathematical model consisting of constraints and objective functions, or a mathematical model consisting of only constraints or only objective functions. Among them, a mathematical model having only constraint conditions may also be referred to as a constraint optimization model. Alternatively, the plurality of mathematical solution models may be integer programming models. The integer programming model can be an integer linear programming model, an integer constraint optimization model and the like.

In the embodiment of the application, the scheduling information items decided by the mathematical solution model are different, the corresponding target information of the staff to be scheduled and the task to be distributed is different, and the constraint conditions and the target function of the mathematical solution model are also different.

For example, in some embodiments, the scheduling information items decided by the mathematical solution model are the work-break time of the person to be scheduled, and the work-break time of the person to be scheduled may include the date, the shift number, and the like of the person to be scheduled on work and at rest. Correspondingly, the target information of the staff to be scheduled can be the rest rule of the staff to be scheduled; the target information of the task to be allocated may be time distribution information of the task to be allocated. Furthermore, constraint conditions can be constructed according to the time distribution information of the tasks to be distributed and the working rules of the staff to be scheduled. Optionally, the rest time of the person to be scheduled to make a decision may be set as an independent variable, and the constraint condition may be constructed by combining the rest rule of the person to be scheduled and the time distribution information of the task to be allocated. For example, the daily working time of a worker at a certain position is not more than N hours, etc., but is not limited thereto.

Further, a mathematical solution model can be established by combining the constructed constraint conditions with the aim of maximizing the task coverage rate or enabling the task coverage rate not to be smaller than a set coverage rate threshold value. The mathematical solution model is used for deciding the working time of the staff to be scheduled. Wherein, the task coverage rate means: the percentage of the completed task volume to the total task volume is assigned.

For another example, the shift information item is a task type assigned to the person to be assigned. Accordingly, the target information of the staff to be scheduled includes: the skill information of the staff to be scheduled; the target information of the task to be distributed is as follows: skill requirements of the task to be assigned.

Further, calculating the matching degree of the to-be-scheduled workers and the to-be-assigned tasks according to the skill requirements of the to-be-assigned tasks and the skill information of the to-be-scheduled workers; and establishing a mathematical solution model by taking the personnel to be scheduled as a target with the highest matching degree or the matching degree not less than the threshold of the matching degree. The mathematical solution model is used for deciding the task type distributed by the personnel to be distributed.

The above description only takes the scheduling information item as the working time of the task to be allocated and the type of the allocated task as an example. In other embodiments, but not limited thereto, staff satisfaction maximization, fairness maximization, human cost minimization, etc. may also be targeted for the mathematical solution model. The employee satisfaction can be measured as the percentage of the individual needs of the employee that are met. The employee personalized requirements can be leave requests, rest requests in special time periods and the like. Fairness can be measured as the variance of the total task time allocated to each person. The human cost can be measured by the number of the input personnel.

In this embodiment, after the plurality of mathematical solution models are constructed, the plurality of mathematical solution models may be subjected to associated solution to obtain the contents of the plurality of shift scheduling information items. When a plurality of mathematical solving models are subjected to associated solving, a heuristic algorithm can be adopted for solving in the solving process of each mathematical solving model to obtain the content of the scheduling information item decided by the mathematical solving model. Wherein, the heuristic algorithm may be: one or more of a particle swarm algorithm, an ant colony algorithm, a bee colony algorithm, a simulated annealing algorithm, and a genetic algorithm.

Optionally, for a first solved mathematical solution model in the plurality of mathematical solution models, a heuristic algorithm may be used to solve, and content of the scheduling information item decided by the mathematical solution model is obtained.

For any target mathematical solving model solved after the first solved mathematical solving model, the contents of the scheduling information items decided by the mathematical solving model solved before the target mathematical solving model can be added into the constraint conditions of the target mathematical solving model to obtain new constraint conditions. Thus, for the objective solution model, the new constraint condition includes the content of the shift information item decided by the mathematical solution model solved before the objective mathematical solution model, in addition to the original constraint condition. And then, for the target mathematical solution model, solving the target mathematical solution model according to the new constraint condition so as to obtain the content of the target scheduling information item decided by the target mathematical solution model.

For example, for the mathematical solution model for deciding the working time of the person to be scheduled and the assigned task type, for convenience of description and distinction, the mathematical solution model for deciding the working time of the person to be scheduled is defined as a first mathematical solution model; and defining a mathematical solution model for deciding the task type allocated to the staff to be scheduled as a second mathematical solution model. Assuming that the first mathematical solution model is a first solution model and the second mathematical solution model is a model which is solved after the first mathematical solution model, the working time of the staff to be scheduled, which is decided by the first mathematical solution model, can be used as a constraint condition of the second mathematical solution model. For the second mathematical solution model, the constraint conditions are: the first mathematical solution model decides the working time of the staff to be scheduled, and the target is that the matching degree of the staff to be scheduled and the task to be allocated is the highest or not less than the threshold value of the matching degree; and then, solving the second mathematical solution model to obtain the task type distributed by the personnel to be distributed.

After the plurality of mathematical solving models are solved to obtain the contents of the plurality of scheduling information items, the scheduling result can be generated according to the contents of the plurality of scheduling information items. Optionally, the content of the plurality of shift information items may be optimized to generate a shift result.

In the embodiment of the present application, a specific implementation manner of optimizing the contents of the plurality of shift information items is not limited. In one embodiment, the content of the plurality of shift information items may be optimized according to the task coverage. The specific implementation mode is as follows: and calculating the task coverage rate in each set time period according to the contents of the plurality of scheduling information items and the time distribution information of the tasks to be distributed. Optionally, according to the content of the plurality of scheduling information items, counting the amount of tasks allocated within each set time period, and according to the time distribution information of the tasks to be allocated, counting the total amount of the tasks to be allocated within each set time period; and then, calculating the percentage of the distributed task quantity in each set time period to the total quantity of the tasks to be distributed in the time period as the task coverage rate in the time period.

Further, selecting a target time period with the task coverage rate smaller than or equal to a set coverage rate threshold value from the task coverage rates in each time period; and recalculating the contents of the plurality of scheduling information items in the target time period to obtain a scheduling result.

Optionally, the target task to be allocated in the target time period may be determined according to the time distribution information of the task to be allocated; constructing constraint conditions according to the information of the target tasks to be distributed and the information of the staff to be scheduled; taking the targets of the plurality of mathematical solution models as targets, and establishing a global planning model by combining the constructed constraint conditions; and solving the global planning model to obtain the contents of the plurality of scheduling information items in the target time period again. Alternatively, the global planning model may be an integer planning model.

Optionally, when the calculation time reaches a set time threshold, the optimization of the contents of the plurality of scheduling information items according to the task coverage rate is stopped; or, when the recalculation times reach the set times threshold, stopping optimizing the contents of the plurality of scheduling information items according to the task coverage rate; alternatively, when the calculation time reaches the set time threshold and the recalculation times reaches the set time threshold, the optimization of the contents of the plurality of scheduling information items according to the task coverage rate may be stopped.

Further, the shift arrangement result can be generated according to the contents of the shift arrangement information items in the target time period and the contents of the shift arrangement information items in other time periods. For example, shifts of the persons to be scheduled may be linked together, forming a shift list for the corresponding time period, and so on.

In another embodiment, the content of the plurality of shift information items may be randomly optimized. The specific implementation mode is as follows: randomly selecting a time period in the time period corresponding to the task to be distributed, and recalculating the contents of the plurality of scheduling information items in the randomly selected time period to obtain a scheduling result. Optionally, determining a target task to be allocated within a randomly selected time period according to the time distribution information of the task to be allocated; constructing constraint conditions according to the information of the target tasks to be distributed and the information of the staff to be scheduled; taking the targets of the multiple mathematical solution models as targets, and establishing a global planning model by combining the constructed constraint conditions; solving the global planning model to retrieve the contents of the plurality of shift information items within the randomly selected time period. Further, a scheduling result is generated according to the contents of the plurality of scheduling information items in the time period selected randomly and the contents of the plurality of scheduling information items at other times. Optionally, the contents of the plurality of shift scheduling information items in the randomly selected time period and the contents of the plurality of shift scheduling information items at other times may be merged to generate a shift scheduling result.

Optionally, when the calculation time reaches a set time threshold, stopping performing random optimization on the contents of the plurality of shift information items; or, when the recalculation times reach the set times threshold, stopping the random optimization of the contents of the plurality of scheduling information items; or when the calculation time reaches the set time threshold and the recalculation times reaches the set time threshold, stopping randomly optimizing the contents of the plurality of scheduling information items.

In still other embodiments, the content of the plurality of shift information items may be analyzed to determine whether the use of personnel can be reduced without changing the task coverage rate, thereby saving the labor cost.

It should be noted that the task coverage optimization and the random optimization can be combined to optimize the contents of the plurality of scheduling information items, so that the task coverage is continuously increased, and the task coverage can be prevented from falling into a trap. Therefore, in the process of optimizing the contents of a plurality of scheduling information items, if only the task coverage rate is concerned, in the process of solving the global planning model corresponding to the time period with the lower task coverage rate, the time period with the lower coverage rate may be involved, but no better solution exists, and the time period is always before the delay, so that the time period falls into the trap.

For the sake of facilitating understanding of the above-mentioned embodiment of the scheduling method, the following description is given by way of example with reference to the specific example shown in fig. 1 b. As shown in fig. 1b, the main steps of the method include:

and S1, acquiring information of all staff to be scheduled and information of all tasks to be allocated under the multi-person multi-task scene.

And S2, selecting target information of the staff to be scheduled and target information of the tasks to be allocated, which correspond to the plurality of scheduling information items respectively, from the information of the staff to be scheduled and the information of the tasks to be scheduled.

And S3, establishing a plurality of mathematical solving models according to the target information of the personnel to be scheduled and the target information of the tasks to be allocated, which correspond to the plurality of scheduling information items respectively. Wherein, a plurality of mathematical solution models can decide the plurality of scheduling information items.

For a specific implementation process of building the mathematical solution model and the constraint conditions and objectives of the multiple mathematical solution models, reference may be made to the relevant contents of the above embodiments, which are not described herein again.

And S4, performing associated solution on the plurality of mathematical solution models by adopting a heuristic algorithm to obtain the contents of the plurality of scheduling information items.

And S5, analyzing the contents of the plurality of shift information items, and reducing the use of personnel under the condition of not reducing the task coverage rate.

And S6, randomly optimizing the contents of the plurality of scheduling information items to obtain first contents of the plurality of scheduling information items.

And S7, optimizing the task coverage rate of the first contents of the plurality of scheduling information items to obtain second contents of the plurality of scheduling information items.

And S8, generating a scheduling result according to the second content of the plurality of scheduling information items.

And S9, outputting a shift arrangement result.

In the present embodiment, steps S5, S6, and S7 may be performed in series or in parallel. When the steps S5, S6 and S7 are executed in series, the execution order of the steps S5, S6 and S7 is not limited, and the steps S5, S6 and S7 are executed in sequence as shown in fig. 1b, but the execution order of the steps S5, S6 and S7 is not limited.

Accordingly, embodiments of the present application also provide a computer-readable storage medium storing computer instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the shift scheduling method.

The scheduling method provided by the embodiment of the application is not only suitable for the information of the known staff to be scheduled, but also suitable for the application scene of allocating the tasks to be allocated to the staff to be scheduled, and is also suitable for the application scene of allocating the staff for the tasks to be allocated, namely allocating the staff meeting the requirements for the tasks to be allocated. The following description is given by way of example with reference to specific embodiments.

Fig. 2 is a schematic diagram illustrating results of another scheduling method provided in an embodiment of the present application. As shown in fig. 2, the method includes:

201. and acquiring information of the tasks to be distributed in the multi-task scene.

202. And selecting target information of the tasks to be distributed corresponding to the plurality of scheduling information items from the information of the tasks to be distributed.

203. And respectively calculating the contents of the plurality of scheduling information items according to the target information of the tasks to be distributed corresponding to the plurality of scheduling information items.

204. And generating a scheduling result according to the contents of the plurality of scheduling information items.

The scheduling method provided by the embodiment is suitable for a multi-task scene, and can configure corresponding personnel for the tasks to be allocated. For example, the number of persons required for each of the tasks to be distributed, the skill information of the persons, the resting mode, and the like are calculated, but not limited thereto. Accordingly, the plurality of shift information items include: the number of persons required for the task to be distributed, the skill information of the persons, the resting mode and the like.

In this embodiment, target information of a task to be allocated corresponding to each of a plurality of scheduling information items may be selected from information of the task to be allocated; and respectively calculating the contents of the plurality of scheduling information items according to the target information of the personnel to be scheduled and the target information of the tasks to be allocated, which correspond to the plurality of scheduling information items. Therefore, the scheduling task can be split into a plurality of subtasks for processing, the calculation complexity and the calculation amount are reduced, the data processing efficiency is favorably improved, and the scheduling efficiency is favorably improved. The scheduling information items calculated by each subtask can be partially overlapped or different.

In the embodiment of the present application, a specific implementation manner of calculating the contents of the plurality of shift information items according to the target information of the person to be shifted and the target information of the task to be assigned, which correspond to the plurality of shift information items, is not limited. In some embodiments, a plurality of mathematical solution models may be established according to target information of tasks to be allocated respectively corresponding to the plurality of scheduling information items. Wherein, a plurality of mathematical solution models can decide the plurality of scheduling information items. Each mathematical solution model decides part of the scheduling information items of the plurality of scheduling information items. The scheduling information items decided by each mathematical solving model can be partially overlapped or different. For the implementation form of the mathematical solution model, reference may be made to the relevant contents of the above embodiments, and details are not described herein again.

Further, after the plurality of shift information items are calculated, a shift result may be generated according to the contents of the plurality of shift information items. For a specific embodiment of generating a shift scheduling result according to the contents of a plurality of shift scheduling information items, reference may be made to the related contents in fig. 1a and its optional embodiment, which are not described herein again.

Further, a shift arrangement result can be output. In the present embodiment, the output mode of the shift result is not limited. For example, the shift result may be provided to a display device, which displays the shift result. Thus, the user can check the shift result. The display device can be a display screen of a computer device for performing scheduling or an independent physical machine. Alternatively, the display device may be a client device on the user side. Such as a user-side computer, a smart phone, or a wearable device, etc. For another example, the scheduling method provided in this embodiment may also be used as a SaaS service, and the server device carrying the service may send the scheduling result to the client device on the user side, and the client device displays the scheduling result, but is not limited thereto.

It should be noted that, in some embodiments, the scheduling methods provided in fig. 1a and fig. 2 may also be used to form two scheduling modes, and the two scheduling modes are provided to the user for the user to select autonomously according to the scheduling requirement. Optionally, an interactive interface may be presented to the user. Two shift mode selection controls are displayed on the interactive interface and are selected by a user independently.

It should be noted that the execution subjects of the steps of the methods provided in the above embodiments may be the same device, or different devices may be used as the execution subjects of the methods. For example, the execution subject of

steps

101 and 102 may be device a; for another example, the execution subject of step 101 may be device a, and the execution subject of step 102 may be device B; and so on.

In addition, in some of the flows described in the above embodiments and the drawings, a plurality of operations are included in a specific order, but it should be clearly understood that the operations may be executed out of the order presented herein or in parallel, and the sequence numbers of the operations, such as 201, 202, etc., are merely used for distinguishing different operations, and the sequence numbers do not represent any execution order per se. Additionally, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel.

Fig. 3 is a schematic diagram illustrating a result of a computer device according to an embodiment of the present application. The computer device may be a terminal device such as a smart phone, a tablet computer, a personal computer, a wearable device, or a single server device, or a cloud server array, or a Virtual Machine (VM) running in the cloud server array. As shown in fig. 3, the computer apparatus includes: a memory 30a and a processor 30 b.

In the present embodiment, the memory 30a is used for storing a computer program.

The processor 30b is coupled to the memory 30a for executing a computer program for: acquiring information of staff to be scheduled and information of tasks to be allocated in a multi-person multi-task scene; selecting target information of the staff to be scheduled and target information of the task to be allocated, which correspond to the plurality of scheduling information items respectively, from the information of the staff to be scheduled and the information of the task to be allocated; respectively calculating the contents of the plurality of scheduling information items according to the target information of the personnel to be scheduled and the target information of the tasks to be allocated, which correspond to the plurality of scheduling information items; and generating a scheduling result according to the contents of the plurality of scheduling information items.

Optionally, the processor 30b may be further configured to: after the shift arrangement result is generated, the shift arrangement result is provided for the display device, so that the display device can display the shift arrangement result.

Optionally, the display device is a client device on the user side. The computer device may include: a communication component 30 c. Accordingly, the processor 30b, when providing the shift result to the display device, is specifically configured to: the shift scheduling result is provided to the client device through the communication component 30c for the client device to display the shift scheduling result.

Optionally, the computer device comprises: and a display screen 30 d. The display device is a display screen 30d of a computer device. Accordingly, the processor 30b, when providing the shift result to the display device, is specifically configured to: the shift arrangement result is output to the display screen 30d to display the shift arrangement result on the display screen 30 d.

In some embodiments, the processor 30b, when calculating the contents of the plurality of shift information items, is specifically configured to: establishing a plurality of mathematical solving models according to target information of the personnel to be scheduled and target information of the tasks to be allocated, which correspond to the plurality of scheduling information items respectively; and performing associated solution on the plurality of mathematical solution models to obtain the contents of a plurality of scheduling information items.

Alternatively, the plurality of mathematical solution models may be integer programming models.

Further, when performing the association solution on the multiple data solution models, the processor 30b is specifically configured to: aiming at the target mathematical solution model, adding the contents of the scheduling information items decided by the mathematical solution model solved before the target mathematical solution model into the constraint conditions of the target mathematical solution model to obtain new constraint conditions; solving the target mathematical solution model according to the new constraint condition to obtain the content of the target scheduling information item decided by the target mathematical solution model; the target mathematical solution model is any one of a plurality of mathematical solution models except for the first mathematical solution model to be solved.

Optionally, when performing the correlation solution on the multiple mathematical solution models, the processor 30b is specifically configured to: and performing correlation solving on the plurality of mathematic solving models by adopting a heuristic algorithm to obtain the contents of a plurality of scheduling information items.

In some embodiments, the scheduling information item is a work time of the person to be scheduled, and the target information of the person to be scheduled includes: making a rest rule for the staff to be scheduled; the target information of the task to be distributed is as follows: time distribution information of the tasks to be distributed. Accordingly, the processor 30b, when establishing the plurality of mathematical solution models, is specifically configured to: constructing a first constraint condition according to the time distribution information of the tasks to be distributed and the working rules of the staff to be scheduled; establishing a first mathematical solution model by taking the maximized task coverage rate or the task coverage rate not less than the coverage rate threshold value as a target and combining a first constraint condition; the first mathematical solution model is used for deciding the working time of the staff to be scheduled.

In other embodiments, the shift information item is a task type assigned to the person to be assigned, and the target information of the person to be assigned includes: the skill information of the staff to be scheduled; the target information of the task to be distributed is as follows: skill requirements of the task to be assigned. Accordingly, the processor 30b, when establishing the plurality of mathematical solution models, is specifically configured to: calculating the matching degree of the to-be-scheduled workers and the to-be-assigned tasks according to the skill requirements of the to-be-assigned tasks and the skill information of the to-be-scheduled workers; and establishing a second mathematical solution model for deciding the task type allocated to the staff to be allocated by taking the staff to be scheduled and the task to be allocated with the highest matching degree or the matching degree not less than the threshold of the matching degree as a target.

Further, the processor 30b, when generating the shift scheduling result, is specifically configured to: and optimizing the contents of the plurality of scheduling information items to generate a scheduling result.

Optionally, when optimizing the content of the plurality of shift information items, the processor 30b is specifically configured to: calculating the task coverage rate in each set time period according to the contents of the scheduling information items and the time distribution information of the tasks to be distributed; selecting a target time period with the task coverage rate less than or equal to a set coverage rate threshold; recalculating the contents of the plurality of scheduling information items in the target time period to obtain a scheduling result; and/or randomly selecting a time period in the time period corresponding to the task to be distributed, and recalculating the contents of the plurality of scheduling information items in the randomly selected time period to obtain a scheduling result.

Further, the processor 30b, when recalculating the contents of the plurality of shift information items within the target time period, is specifically configured to: determining a target task to be allocated in a target time period according to the time distribution information of the task to be allocated; constructing a second constraint condition according to the information of the target task to be distributed and the information of the staff to be scheduled; taking the targets of the multiple mathematical solution models as targets, and establishing a global planning model by combining second constraint conditions; and solving the global planning model to obtain the contents of the plurality of scheduling information items in the target time period again.

Optionally, the global planning model is an integer planning model.

In some optional embodiments, as shown in fig. 3, the computer device may further include: power supply assembly 30e, etc. If the computer device can be a computer, a smart phone or other terminal devices, the method can further include: audio component 30f, and the like. Only some of the components shown in fig. 3 are schematically depicted, and it is not meant that the computer device must include all of the components shown in fig. 3, nor that the computer device only includes the components shown in fig. 3.

The computer device provided by the embodiment selects the target information of the person to be scheduled and the target information of the task to be allocated, which correspond to the plurality of scheduling information items respectively; respectively calculating the contents of the plurality of scheduling information items according to the target information of the personnel to be scheduled and the target information of the tasks to be allocated, which correspond to the plurality of scheduling information items; and generating a scheduling result according to the contents of the plurality of scheduling information items. The content of the plurality of scheduling information items is respectively calculated according to the target information of the person to be scheduled and the target information of the task to be allocated, which correspond to the plurality of scheduling information items, so that the grouping solution of the plurality of scheduling information items is realized, the calculation complexity and the calculation workload can be reduced, the data processing efficiency can be improved, and the scheduling efficiency can be improved.

Fig. 4 is a schematic structural diagram of another computer device according to an embodiment of the present application. The implementation form of the computer device can refer to the relevant contents of the above embodiments, and is not described herein again. As shown in fig. 4, the computer apparatus includes: a memory 40a and a processor 40 b.

In the present embodiment, the memory 40a is used for storing a computer program.

The processor 40b is coupled to the memory 40a for executing a computer program for: acquiring information of tasks to be distributed in a multi-task scene; selecting target information of the tasks to be allocated corresponding to a plurality of scheduling information items from the information of the tasks to be allocated; respectively calculating the contents of the plurality of scheduling information items according to the target information of the tasks to be distributed corresponding to the plurality of scheduling information items; and generating a scheduling result according to the contents of the plurality of scheduling information items.

Optionally, the processor 40b may be further configured to: after the shift arrangement result is generated, the shift arrangement result is provided for the display device, so that the display device can display the shift arrangement result.

Optionally, the display device is a client device on the user side. The computer device may include: a communication component 40 c. Accordingly, when providing the shift result to the display device, the processor 40b is specifically configured to: the shift result is provided to the client device through the communication component 40c for the client device to display the shift result.

Optionally, the computer device comprises: and a display screen 40 d. The display device is a display screen 40d of a computer device. Accordingly, when providing the shift result to the display device, the processor 40b is specifically configured to: and outputting the scheduling result to the display screen 40d so as to display the scheduling result on the display screen 40 d.

Optionally, the plurality of shift information items include: the number of people required for the task to be assigned, the skill information of the people, and the resting mode.

For a specific embodiment of how to calculate the contents of the shift information items in groups, reference may be made to the related contents in fig. 3, which is not described herein again.

In some optional embodiments, as shown in fig. 4, the computer device may further include: power supply assembly 40e, etc. If the computer device can be a computer, a smart phone or other terminal devices, the method can further include: audio component 40f, and the like. Only some of the components shown in fig. 4 are schematically shown, and it is not meant that the computer device must include all of the components shown in fig. 4, nor that the computer device only includes the components shown in fig. 4.

In a multitasking scenario, the computer device provided in this embodiment may select, from information of tasks to be allocated, target information of the tasks to be allocated, which corresponds to each of the plurality of scheduling information items; respectively calculating the contents of the plurality of scheduling information items according to the target information of the tasks to be distributed corresponding to the plurality of scheduling information items; and generating a scheduling result according to the contents of the plurality of scheduling information items. The content of the plurality of scheduling information items is respectively calculated according to the target information of the tasks to be distributed corresponding to the plurality of scheduling information items, the scheduling tasks can be divided into a plurality of subtasks for processing, the complexity of calculation and the calculation workload can be reduced, the data processing efficiency can be improved, and the scheduling efficiency can be improved.

In embodiments of the present application, the memory is used to store computer programs and may be configured to store other various data to support operations on the device on which it is located. Wherein the processor may execute a computer program stored in the memory to implement the corresponding control logic. The memory may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.

In the embodiments of the present application, the processor may be any hardware processing device that can execute the above described method logic. Alternatively, the processor may be a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), or a Micro Controller Unit (MCU); programmable devices such as Field-Programmable Gate arrays (FPGAs), Programmable Array Logic devices (PALs), General Array Logic devices (GAL), Complex Programmable Logic Devices (CPLDs), etc. may also be used; or Advanced Reduced Instruction Set (RISC) processors (ARM), or System On Chips (SOC), etc., but is not limited thereto.

In embodiments of the present application, the communication component is configured to facilitate wired or wireless communication between the device in which it is located and other devices. The device in which the communication component is located can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, 4G, 5G or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component may also be implemented based on Near Field Communication (NFC) technology, Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, or other technologies.

In the embodiment of the present application, the display screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the display screen includes a touch panel, the display screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

In embodiments of the present application, a power supply component is configured to provide power to various components of the device in which it is located. The power components may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device in which the power component is located.

In embodiments of the present application, the audio component may be configured to output and/or input audio signals. For example, the audio component includes a Microphone (MIC) configured to receive an external audio signal when the device in which the audio component is located is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal may further be stored in a memory or transmitted via a communication component. In some embodiments, the audio assembly further comprises a speaker for outputting audio signals. For example, for devices with language interaction functionality, voice interaction with a user may be enabled through an audio component, and so forth.

Fig. 5 is a schematic structural diagram of a shift scheduling device according to an embodiment of the present application. As shown in fig. 5, the shift arrangement device includes: an acquisition module 50a, a selection module 50b, a calculation module 50c and a generation module 50 d.

In this embodiment, the obtaining module 50a is configured to obtain information of a person to be scheduled and information of a task to be allocated in a multi-person multi-task scene.

And the selecting module 50b is configured to select target information of the staff to be scheduled and target information of the task to be allocated, which correspond to the plurality of scheduling information items, from the information of the staff to be scheduled and the information of the task to be allocated.

And the calculating module 50c is configured to calculate the contents of the plurality of scheduling information items according to the target information of the person to be scheduled and the target information of the task to be allocated, which correspond to the plurality of scheduling information items, respectively.

And a generating module 50d, configured to generate a shift scheduling result according to the contents of the shift scheduling information items.

In some embodiments, the shift schedule apparatus further comprises: a module 50e is provided. The providing module 50e is configured to provide the scheduling result to the display device, so that the display device can display the scheduling result.

In some embodiments, the calculating module 50c is specifically configured to, when calculating the contents of the plurality of shift information items: establishing a plurality of mathematical solving models according to target information of the personnel to be scheduled and target information of the tasks to be allocated, which correspond to the plurality of scheduling information items respectively; and performing associated solution on the plurality of mathematical solution models to obtain the contents of a plurality of scheduling information items.

Further, when performing the association solution on the multiple data solution models, the calculating module 50c is specifically configured to: aiming at the target mathematical solution model, adding the contents of the scheduling information items decided by the mathematical solution model solved before the target mathematical solution model into the constraint conditions of the target mathematical solution model to obtain new constraint conditions; solving the target mathematical solution model according to the new constraint condition to obtain the content of the target scheduling information item decided by the target mathematical solution model; the target mathematical solution model is any one of a plurality of mathematical solution models except for the first mathematical solution model to be solved.

Optionally, when performing the correlation solution on the multiple mathematical solution models, the calculating module 50c is specifically configured to: and performing correlation solving on the plurality of mathematic solving models by adopting a heuristic algorithm to obtain the contents of a plurality of scheduling information items.

In some embodiments, the scheduling information item is a work time of the person to be scheduled, and the target information of the person to be scheduled includes: making a rest rule for the staff to be scheduled; the target information of the task to be distributed is as follows: time distribution information of the tasks to be distributed. Accordingly, the calculation module 50c is specifically configured to, when building a plurality of mathematical solution models: constructing a first constraint condition according to the time distribution information of the tasks to be distributed and the working rules of the staff to be scheduled; establishing a first mathematical solution model by taking the maximized task coverage rate or the task coverage rate not less than the coverage rate threshold value as a target and combining a first constraint condition; the first mathematical solution model is used for deciding the working time of the staff to be scheduled.

In other embodiments, the shift information item is a task type assigned to the person to be assigned, and the target information of the person to be assigned includes: the skill information of the staff to be scheduled; the target information of the task to be distributed is as follows: skill requirements of the task to be assigned. Accordingly, the calculation module 50c is specifically configured to, when building a plurality of mathematical solution models: calculating the matching degree of the to-be-scheduled workers and the to-be-assigned tasks according to the skill requirements of the to-be-assigned tasks and the skill information of the to-be-scheduled workers; and establishing a second mathematical solution model for deciding the task type allocated to the staff to be allocated by taking the staff to be scheduled and the task to be allocated with the highest matching degree or the matching degree not less than the threshold of the matching degree as a target.

Further, when the shift scheduling result is generated, the generating module 50d is specifically configured to: and optimizing the contents of the plurality of scheduling information items to generate a scheduling result.

Optionally, when optimizing the contents of the plurality of shift information items, the generating module 50d is specifically configured to: calculating the task coverage rate in each set time period according to the contents of the scheduling information items and the time distribution information of the tasks to be distributed; selecting a target time period with the task coverage rate less than or equal to a set coverage rate threshold; recalculating the contents of the plurality of scheduling information items in the target time period to obtain a scheduling result; and/or randomly selecting a time period in the time period corresponding to the task to be distributed, and recalculating the contents of the plurality of scheduling information items in the randomly selected time period to obtain a scheduling result.

Further, when the content of the plurality of shift scheduling information items in the target time period is recalculated, the generating module 50d is specifically configured to: determining a target task to be allocated in a target time period according to the time distribution information of the task to be allocated; constructing a second constraint condition according to the information of the target task to be distributed and the information of the staff to be scheduled; taking the targets of the multiple mathematical solution models as targets, and establishing a global planning model by combining second constraint conditions; and solving the global planning model to obtain the contents of the plurality of scheduling information items in the target time period again.

Optionally, the global planning model is an integer planning model.

In the scheduling device provided by the embodiment, in a multi-person multi-task scene, target information of a person to be scheduled and target information of a task to be allocated, which correspond to a plurality of scheduling information items respectively, are selected; respectively calculating the contents of the plurality of scheduling information items according to the target information of the personnel to be scheduled and the target information of the tasks to be allocated, which correspond to the plurality of scheduling information items; and generating a scheduling result according to the contents of the plurality of scheduling information items. The content of the plurality of scheduling information items is respectively calculated according to the target information of the person to be scheduled and the target information of the task to be allocated, which correspond to the plurality of scheduling information items, so that the grouping solution of the plurality of scheduling information items is realized, the calculation complexity and the calculation workload can be reduced, the data processing efficiency can be improved, and the scheduling efficiency can be improved.

Fig. 6 is a schematic structural diagram of another shift scheduling device according to an embodiment of the present application. As shown in fig. 6, the shift arrangement device includes: an acquisition module 60a, a selection module 60b, a calculation module 60c and a generation module 60 d.

The obtaining module 60a is configured to obtain information of a task to be allocated in a multitasking scenario.

And the selecting module 60b is configured to select target information of the task to be allocated, which corresponds to each of the plurality of scheduling information items, from the information of the task to be allocated.

And the calculating module 60c is configured to select target information of the task to be allocated, which corresponds to each of the plurality of scheduling information items, from the information of the task to be allocated.

And the generating module 60d is configured to generate a shift scheduling result according to the contents of the plurality of shift scheduling information items.

In some embodiments, the shift schedule apparatus further comprises: a module 60e is provided. The providing module 60e is configured to provide the scheduling result to the display device, so that the display device can display the scheduling result.

For a specific embodiment of how to calculate the contents of the shift information items in groups, reference may be made to the related contents in fig. 5, which is not described herein again.

In a multitask scene, the scheduling device provided by the embodiment can select target information of tasks to be allocated, which corresponds to a plurality of scheduling information items respectively, from information of the tasks to be allocated; respectively calculating the contents of the plurality of scheduling information items according to the target information of the tasks to be distributed corresponding to the plurality of scheduling information items; and generating a scheduling result according to the contents of the plurality of scheduling information items. The content of the plurality of scheduling information items is respectively calculated according to the target information of the tasks to be distributed corresponding to the plurality of scheduling information items, the scheduling tasks can be divided into a plurality of subtasks for processing, the complexity of calculation and the calculation workload can be reduced, the data processing efficiency can be improved, and the scheduling efficiency can be improved.

It should be noted that, the descriptions of "first", "second", etc. in this document are used for distinguishing different messages, devices, modules, etc., and do not represent a sequential order, nor limit the types of "first" and "second" to be different.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A scheduling method, comprising:

2. The method according to claim 1, wherein the calculating the contents of the plurality of shift information items according to the target information of the person to be shifted and the target information of the task to be assigned, which correspond to the plurality of shift information items, respectively, comprises:

establishing a plurality of mathematical solving models according to the target information of the personnel to be scheduled and the target information of the tasks to be allocated, which correspond to the plurality of scheduling information items respectively; each data solving model is used for deciding the content of part of the scheduling information items in the plurality of scheduling information items;

and performing associated solution on the plurality of mathematical solution models to obtain the contents of the plurality of scheduling information items.

3. The method according to claim 2, wherein performing the associative solution on the plurality of data solution models to obtain the contents of the plurality of shift information items comprises:

aiming at a target mathematical solution model, adding the contents of scheduling information items decided by a mathematical solution model solved before the target mathematical solution model into the constraint conditions of the target mathematical solution model to obtain new constraint conditions;

solving the target mathematical solving model according to the new constraint condition to obtain the content of the target scheduling information item decided by the target mathematical solving model;

the target mathematical solution model is any one of the plurality of mathematical solution models except for the first solved mathematical solution model.

4. The method according to claim 2, wherein the performing the correlation solution on the plurality of mathematical solution models to obtain the contents of the plurality of shift information items comprises: and performing associated solution on the plurality of mathematical solution models by adopting a heuristic algorithm to obtain the contents of the plurality of scheduling information items.

5. The method according to claim 2, wherein if the scheduling information item is the work break time of the person to be scheduled, the target information of the person to be scheduled comprises: the working and rest rules of the staff to be scheduled; the target information of the task to be distributed is as follows: time distribution information of the tasks to be distributed;

the establishing of the plurality of mathematical solution models according to the target information of the staff to be scheduled and the target information of the tasks to be allocated, which are respectively corresponding to the plurality of scheduling information items, comprises the following steps:

constructing a first constraint condition according to the time distribution information of the tasks to be distributed and the working rules of the staff to be scheduled; and

establishing a first mathematical solution model by combining the first constraint condition with the aim of maximizing the task coverage rate or enabling the task coverage rate not to be smaller than a coverage rate threshold value; the first mathematical solution model is used for deciding the working time of the staff to be scheduled.

6. The method according to claim 2, wherein if a scheduling information item is a task type assigned to the person to be assigned, the target information of the person to be scheduled comprises: the skill information of the staff to be scheduled; the target information of the task to be distributed is as follows: skill requirements of the task to be assigned;

calculating the matching degree of the to-be-scheduled workers and the to-be-assigned tasks according to the skill requirements of the to-be-assigned tasks and the skill information of the to-be-scheduled workers;

and establishing a second mathematical solution model for deciding the task type allocated to the staff to be allocated by taking the staff to be scheduled and the task to be allocated with the highest matching degree or the matching degree not less than the threshold of the matching degree as a target.

7. The method of any one of claims 2-6, wherein the plurality of mathematical solution models are integer programming models.

8. The method according to any one of claims 2-6, wherein generating a shift result according to the contents of the plurality of shift information items comprises:

optimizing the content of the plurality of scheduling information items to generate the scheduling result.

9. The method of claim 8, wherein optimizing the content of the plurality of shift information items comprises:

calculating the task coverage rate in each set time period according to the contents of the plurality of scheduling information items and the time distribution information of the tasks to be distributed; selecting a target time period with the task coverage rate less than or equal to a set coverage rate threshold; recalculating the contents of the plurality of scheduling information items in the target time period to obtain the scheduling result;

and/or the presence of a gas in the gas,

and randomly selecting a time period in the time period corresponding to the task to be distributed, and recalculating the contents of the plurality of scheduling information items in the randomly selected time period to obtain the scheduling result.

10. The method of claim 9, wherein the recalculating the contents of the plurality of shift information items within the target time period comprises:

determining a target task to be allocated in the target time period according to the time distribution information of the task to be allocated;

constructing a second constraint condition according to the information of the target task to be distributed and the information of the staff to be scheduled;

establishing a global planning model by taking the targets of the plurality of mathematical solution models as targets and combining the second constraint conditions;

and solving the global planning model to obtain the contents of the plurality of scheduling information items in the target time period again.

11. The method of claim 10, wherein the global planning model is an integer planning model.

12. The method of any one of claims 1-6, after generating the shift schedule results, further comprising:

and providing the scheduling result to display equipment so that the display equipment can display the scheduling result.

13. A scheduling method, comprising:

acquiring information of tasks to be distributed in a multi-task scene;

14. The method of claim 13, wherein the plurality of shift information items comprise: the number of personnel required by the task to be distributed, personnel skill information and a rest mode.

15. The method of claim 13 or 14, after generating the shift result, further comprising:

16. A computer device, comprising: a memory and a processor; wherein the memory is used for storing a computer program;

the processor is coupled to the memory for executing the computer program for performing the steps in the method of any of claims 1-15.

17. A shift arrangement device, comprising: the device comprises an acquisition module, a selection module, a calculation module and a generation module; wherein the content of the first and second substances,

18. A shift arrangement device, comprising: the device comprises an acquisition module, a selection module, a calculation module and a generation module; wherein the content of the first and second substances,

19. A computer-readable storage medium having stored thereon computer instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the method of any one of claims 1-15.