CN114202258A - Intelligent cloud scheduling method and device, computer equipment and storage medium - Google Patents
Intelligent cloud scheduling method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses an intelligent cloud scheduling method, an intelligent cloud scheduling device, computer equipment and a storage medium, wherein expected access flow data are determined according to historical access flow data; dividing the expected access flow data into a plurality of interval flow data according to a preset time interval; determining the manpower requirement of the time period to be scheduled according to the flow data of each interval; and generating a customer service scheduling plan corresponding to the time period to be scheduled according to the customer service constraint condition, the customer service personnel constraint condition and the manpower requirement. Firstly, determining the manpower requirement from the dimension of access flow, then considering the constraint condition requirement of the customer service and the constraint condition of each customer service person, combining multiple factors to jointly determine a customer service scheduling plan, more reasonably arranging the working time of the customer service person, meeting the individual requirement of the customer service person, and better meeting the customer service requirement accessed by a user.
Description
Technical Field
The invention relates to the technical field of internet, in particular to an intelligent cloud scheduling method and device, computer equipment and a storage medium.
Background
Many large enterprises at present generally provide manual 24-hour customer service online service for better serving users, customer service staff provide services for customers in an online voice or chat mode, the working time of the customer service staff is not fixed, and people need to watch the customers in turn for 24 hours.
With the development of economy, the traffic of a customer service center is also increased sharply, and the current automatic scheduling technology still has many unreasonable places and cannot give consideration to both the customer service efficiency and the individual special requirements of customer service personnel. Therefore, how to let the customer service staff better meet the service requirements of the user access, and simultaneously, how to more reasonably arrange the working hours of the customer service staff is a problem that enterprises need to solve urgently at present.
Disclosure of Invention
The application provides an intelligent cloud scheduling method, an intelligent cloud scheduling device, computer equipment and a storage medium, which can better meet the service requirements of user access and can more reasonably arrange the working time of customer service personnel.
In a first aspect, the present application provides an intelligent cloud shift scheduling method, including:
determining expected access flow data according to historical access flow data;
dividing the expected access flow data into a plurality of interval flow data according to a preset time interval;
determining the manpower requirement of the time period to be scheduled according to the flow data of each interval;
and generating a customer service scheduling plan corresponding to the time period to be scheduled according to the customer service business attribute, the customer service personnel constraint condition and the manpower requirement.
Optionally, the historical access flow data includes a plurality of sub-access flow data of a preset data recording period, and each sub-access flow data is access flow data corresponding to each recording sub-time period of the preset data recording period;
the determining expected access traffic data from historical access traffic data includes:
determining a service weighting factor of the time period to be scheduled according to the historical access flow data;
determining a target sub-recording time period corresponding to the time period to be scheduled from a plurality of recording sub-time periods;
determining target sub-access traffic data corresponding to the target sub-recording time period from the plurality of sub-access traffic data;
and determining the expected access flow data corresponding to the time period to be scheduled according to the target sub-access flow data and the service weighting factor.
Optionally, the determining the manpower requirement of the time period to be scheduled according to the traffic data of each interval includes:
determining a flow peak value of the time period to be scheduled according to the flow data of each interval, wherein the flow peak value is the flow peak value of each interval to be scheduled of a plurality of intervals to be scheduled corresponding to the time period to be scheduled;
determining the service capacity requirement corresponding to the time period to be scheduled according to the flow peak value of each interval to be scheduled;
and determining the manpower requirement according to the service capacity requirement and the per-capita service capacity.
Optionally, the generating a customer service shift schedule plan corresponding to the time period to be shifted according to the customer service attribute, the customer service staff constraint condition, and the human demand includes:
determining candidate customer service personnel according to the customer service business attribute, the customer service personnel constraint condition and the manpower requirement;
selecting customer service scheduling personnel from the customer service candidate personnel according to the flow peak value of each to-be-scheduled interval, wherein the sum of the service capacities of the customer service scheduling personnel of each to-be-scheduled interval is not less than the flow peak value of each to-be-scheduled interval;
and generating the customer service shift scheduling plan according to the customer service shift scheduling personnel.
Optionally, the obtaining of the personnel constraint condition includes:
acquiring personal forbidden information of each customer service staff;
and binding the customer service staff information with the personal forbidden information corresponding to the customer service staff to obtain the staff constraint condition corresponding to each customer service staff.
Optionally, the method further includes:
judging whether the scheduling plan of each customer service scheduling staff in the customer service scheduling plan meets preset scheduling constraints or not;
and if not, modifying the customer service shift scheduling plan according to the preset shift scheduling constraint.
In a second aspect, the present application provides an intelligent cloud scheduling device, the device includes:
the first determining module is used for determining expected access flow data according to historical access flow data;
the dividing module is used for dividing the expected access flow data into a plurality of interval flow data according to a preset time interval;
the second determining module is used for determining the manpower requirement of the time period to be scheduled according to the flow data of each interval;
and the generating module is used for generating a customer service scheduling plan corresponding to the time period to be scheduled according to the customer service business attribute, the customer service personnel constraint condition and the manpower requirement.
Optionally, the apparatus further comprises: the judging module is used for judging whether the scheduling plan of each customer service scheduling staff in the customer service scheduling plan meets preset scheduling constraints or not; and if not, modifying the shift schedule plan according to the preset shift schedule constraint.
In a third aspect, the present application provides a computer device, including a processor and a memory, where the memory stores a computer program, and the computer program executes the intelligent cloud scheduling method according to any one of the above items when the computer program runs on the processor.
In a fourth aspect, the present application provides a computer-readable storage medium storing a computer program which, when run on a processor, performs the intelligent cloud scheduling method of any one of the above.
According to the intelligent cloud scheduling method, the intelligent cloud scheduling device, the computer equipment and the storage medium, expected access flow data are determined according to historical access flow data; dividing the expected access flow data into a plurality of interval flow data according to a preset time interval; determining the manpower requirement of the time period to be scheduled according to the flow data of each interval; and generating a customer service scheduling plan corresponding to the time period to be scheduled according to the customer service constraint condition, the customer service personnel constraint condition and the manpower requirement. Therefore, the manpower requirement is determined from the dimension of the access flow, then the constraint condition requirement of the customer service and the constraint condition of each customer service person are considered, and multiple factors are combined to jointly determine the customer service scheduling plan, so that the working time of the customer service person is more reasonably arranged, the personalized requirement of the customer service person is met, and the service requirement of the customer service for the user to access can be better met.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings required to be used in the embodiments will be briefly described below, and it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the scope of the present invention. Like components are numbered similarly in the various figures.
FIG. 1 shows a flow diagram of a method for intelligent cloud scheduling;
fig. 2 shows a block diagram of a smart cloud shift device.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
Hereinafter, the terms "including", "having", and their derivatives, which may be used in various embodiments of the present invention, are only intended to indicate specific features, numbers, steps, operations, elements, components, or combinations of the foregoing, and should not be construed as first excluding the existence of, or adding to, one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing.
Furthermore, the terms "first," "second," "third," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which various embodiments of the present invention belong. The terms (such as those defined in commonly used dictionaries) should be interpreted as having a meaning that is consistent with their contextual meaning in the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein in various embodiments of the present invention.
Example 1
An embodiment of the application provides an intelligent cloud scheduling method, and as shown in fig. 1, the intelligent cloud scheduling method includes:
step S101, expected access flow data are determined according to historical access flow data;
the historical access flow data refers to data of historical access of the website to the customer service, and the selection of the historical access flow data needs to cover the whole year, including various holidays. Generally, data of one year to two years is selected as a reference, and in practical application, data with reference value can be selected according to the actual situation of a website.
According to the access traffic data of the past whole year, the annual access traffic variation trend of the past whole year can be known, and the access traffic variation trend of the current year, namely the expected access traffic data, can be estimated according to the annual access traffic variation trend of the past whole year.
Step S102, dividing the expected access flow data into a plurality of interval flow data according to a preset time interval;
specifically, the expected access traffic data is divided into a plurality of intervals according to a preset time interval by a time period division method, the preset time interval can be set to 10min, 15min and the like, and the preset time interval is set by referring to factors such as the time length of each normal call of actual customer service work, the actual situation of customer service business and the like.
Step S103, determining the manpower requirement of the time period to be scheduled according to the flow data of each interval;
each interval flow corresponds to the access flow data of each preset time interval in the above S102, and the manpower requirement scheduled in the period to be scheduled can be adapted to the access flow of each preset time interval. In this embodiment, each interval flow in the time period to be scheduled is mapped to the manpower required by the time period to be scheduled according to the corresponding principle. Various conversion principles are adopted, such as the principle of minimum manpower, the principle of not allowing flow overflow and the like.
The minimum manpower is the minimum manpower used at the flow peak within the preset time interval. For example, the peak value of the flow rate is 100 within the preset time interval, if 100 persons can just complete the work with the peak value of the flow rate being 100, then 100 persons are just scheduled, but when 200 persons are scheduled to go to work, serious manpower waste is caused. The manpower requirement is more accurately determined, and the manpower waste is avoided.
And step S104, generating a customer service scheduling plan corresponding to the time period to be scheduled according to the customer service business attribute, the customer service personnel constraint condition and the manpower requirement.
The customer service attributes refer to the working time, working duration, intermediate rest duration, and personnel capacity requirements of one class, and the personnel capacity requirements refer to the capacity required for completing a certain customer service. For example, the person selected for customer service A has a capability requirement to be able to complete customer service A. The customer service attributes can be set in advance according to actual regulations, requirements and job site requirements of different customer service services.
The customer service staff constraint condition refers to a constraint condition bound to each staff, for example, the staff A requires no night shift, the staff B requests for leave at No. 10/30, and the like, and when the shift is scheduled, the staff A is not scheduled at night, and the staff B is at No. 10/30, considering some special conditions of staff individuals. The individual needs of each customer service person are considered.
On the premise of manpower demand, the multi-dimensional factors are comprehensively considered, so that the customer service scheduling is more reasonable, and the service requirements and the individual requirements of customer service personnel are met to the maximum extent.
In a specific embodiment, the historical access flow data includes a plurality of sub-access flow data of a preset data recording period, and each sub-access flow data is access flow data corresponding to each recording sub-time period of the preset data recording period;
the determining expected access traffic data from historical access traffic data includes:
determining a service weighting factor of the time period to be scheduled according to the historical access flow data;
determining a target sub-recording time period corresponding to the time period to be scheduled from a plurality of recording sub-time periods;
determining target sub-access traffic data corresponding to the target sub-recording time period from the plurality of sub-access traffic data;
and determining the expected access flow data corresponding to the time period to be scheduled according to the target sub-access flow data and the service weighting factor.
Specifically, historical access traffic data of the past whole year can be used as a reference, the performance of the current website and the performance of the past contemporaneous website are compared with a weighting factor, and the contemporaneous access traffic of the current year is finally calculated to serve as expected access traffic data. For example, if the current year's current period traffic is 50 and the current year's traffic is increased by 100%, the weighting factor may be considered as 2, and the current year's expected access traffic data may be considered as 100. The specific computational means of accessing traffic data is expected to vary but in principle for customer service jobs of different traffic types.
In a specific embodiment, the determining the manpower requirement of the time period to be scheduled according to the traffic data of each interval includes:
determining a flow peak value of the time period to be scheduled according to the flow data of each interval, wherein the flow peak value is the flow peak value of each interval to be scheduled of a plurality of intervals to be scheduled corresponding to the time period to be scheduled;
determining the service capacity requirement corresponding to the time period to be scheduled according to the flow peak value of each interval to be scheduled;
and determining the manpower requirement according to the service capacity requirement and the per-capita service capacity.
In this embodiment, the time period to be scheduled is divided into a plurality of intervals to be scheduled, each interval to be scheduled is regarded as a shift, and the access flow peak value of the corresponding interval to be scheduled is taken as the service capacity requirement of the corresponding interval to be scheduled according to the fluctuation of the access flow in one shift, for example, if the access flow peak value of the interval to be scheduled is 500, the total value of the manpower service capacity arranged for the interval to be scheduled C reaches 500 but exceeds as little as possible. Avoiding excessive manpower waste. And determining the number of the personnel to be selected and arranging a scheduling plan after determining the service capacity requirement corresponding to each interval to be scheduled.
The average service capability value of the workplace is used as a calculation basis, for example, if one customer service can simultaneously receive access of two users, the capability value of the customer service is recorded as 2, the average value of the service capability values of all the customer service staff is recorded as the average service capability value, and the average service capability value is the manpower required by the time period to be scheduled.
In a specific embodiment, the generating a customer service shift schedule plan corresponding to the time period to be shifted according to the customer service business attribute, the customer service staff constraint condition, and the human demand includes:
determining candidate customer service personnel according to the customer service business attribute, the customer service personnel constraint condition and the manpower requirement;
selecting customer service scheduling personnel from the customer service candidate personnel according to the flow peak value of each to-be-scheduled interval, wherein the sum of the service capacities of the customer service scheduling personnel of each to-be-scheduled interval is not less than the flow peak value of each to-be-scheduled interval;
and generating the customer service shift scheduling plan according to the customer service shift scheduling personnel.
Specifically, on the premise of human demand, the attribute of the customer service and the constraint condition of customer service staff are comprehensively considered, staff which do not meet the condition are removed, the staff which meet the condition are candidate customer service staff, then the staff are selected from the candidate customer service staff, and meanwhile the service capability value of each selected staff in the interval to be scheduled can be guaranteed to reach the peak value of the flow of the interval to be scheduled, namely the scheduled staff can be guaranteed to complete the customer service, and the phenomenon that no person is doing and the staff is insufficient in work can be avoided. And the selected customer service staff arrange the scheduling plan in the scheduling, so that a final customer service scheduling plan is generated.
In a specific embodiment, the obtaining of the personnel constraint condition includes:
acquiring personal forbidden information of each customer service staff;
and binding the customer service staff information with the personal forbidden information corresponding to the customer service staff to obtain the staff constraint condition corresponding to each customer service staff.
Specifically, before the shift is performed, each customer service staff may set some personal disabling information according to its own needs, for example, not going to work at night, double-break, etc. Personal forbidden information is bound with each customer service person to form a person constraint condition of each customer service person, and during scheduling, the individual setting of the customer service person is comprehensively considered, the individual requirement of each customer service person is respected, and a more reasonable scheduling plan is formed.
In a specific embodiment, the method further comprises:
judging whether the scheduling plan of each customer service scheduling staff in the customer service scheduling plan meets preset scheduling constraints or not;
and if not, modifying the customer service shift scheduling plan according to the preset shift scheduling constraint.
In addition, since the shift arrangement is a continuous process, for example, the shift arrangement on monday affects the shift arrangement result on tuesday, and the staff is required to rest and can not arrange for D customers to serve the shift from monday to sunday in consideration of the reasonability and fairness of the arrangement.
Therefore, the generated customer service shift schedule plan also needs to consider whether the shift schedule plan in a phase is unreasonable, and preset the shift schedule constraint as the shift schedule constraint conditions in a preset phase or period, for example, the constraint conditions that the shift schedule plan in a week has a rest for three days, and the shift schedule plan cannot continuously go to work for more than five days. If only one day of logic is considered, it may result in the end that all people are resting on weekends, when no people are working and the shift fails. The unreasonable situation in the continuous scheduling plan is avoided, and the scheduling plan requirement of customer service is better met.
Determining expected access traffic data from historical access traffic data in the present embodiment; dividing the expected access flow data into a plurality of interval flow data according to a preset time interval; determining the manpower requirement of the time period to be scheduled according to the flow data of each interval; and generating a customer service scheduling plan corresponding to the time period to be scheduled according to the customer service constraint condition, the customer service personnel constraint condition and the manpower requirement. The method comprises the steps of determining manpower requirements from the dimension of access flow, then considering the constraint condition requirements of customer service and the constraint conditions of each customer service person, combining multiple factors to jointly determine a customer service scheduling plan, more reasonably arranging the working time of the customer service person, meeting the individual requirements of the customer service person, better meeting the service requirements of the customer service for user access, providing a cloud scheduling method capable of adding reasonability and intellectualization, and improving scheduling efficiency and reasonability.
Example 2
The embodiment of the application provides an intelligence cloud scheduling device, as shown in fig. 2, an intelligence cloud scheduling device 200 includes:
a first determining module 201, configured to determine expected access traffic data according to historical access traffic data;
a dividing module 202, configured to divide the expected access traffic data into multiple interval traffic data according to a preset time interval;
the second determining module 203 is used for determining the manpower requirement of the time period to be scheduled according to the flow data of each interval;
and the generating module 204 is configured to generate a customer service scheduling plan corresponding to the time period to be scheduled according to the customer service business attribute, the customer service personnel constraint condition, and the human demand.
In this embodiment, the first determining module 201 is configured to determine a service weighting factor of the time period to be scheduled according to the historical access traffic data; determining a target sub-recording time period corresponding to the time period to be scheduled from a plurality of recording sub-time periods; determining target sub-access traffic data corresponding to the target sub-recording time period from the plurality of sub-access traffic data; and determining the expected access flow data corresponding to the time period to be scheduled according to the target sub-access flow data and the service weighting factor.
In this embodiment, the second determining module 203 is configured to determine a flow peak value of the to-be-scheduled time period according to the flow data of each interval, where the flow peak value is a flow peak value of each to-be-scheduled interval of a plurality of to-be-scheduled intervals corresponding to the to-be-scheduled time period; determining the service capacity requirement corresponding to the time period to be scheduled according to the flow peak value of each interval to be scheduled; and determining the manpower requirement according to the service capacity requirement and the per-capita service capacity.
In this embodiment, the generating module 204 is further configured to determine candidate customer service staff according to the customer service attribute, the customer service staff constraint condition, and the human demand; selecting customer service scheduling personnel from the customer service candidate personnel according to the flow peak value of each to-be-scheduled interval, wherein the sum of the service capacities of the customer service scheduling personnel of each to-be-scheduled interval is not less than the flow peak value of each to-be-scheduled interval; and generating the customer service shift scheduling plan according to the customer service shift scheduling personnel.
In this embodiment, the system further comprises an obtaining module, configured to obtain personal disabling information of each customer service person; and binding the customer service staff information with the personal forbidden information corresponding to the customer service staff to obtain the staff constraint condition corresponding to each customer service staff.
In this embodiment, the apparatus further includes: the judging module is used for judging whether the scheduling plan of each customer service scheduling staff in the customer service scheduling plan meets preset scheduling constraints or not; and if not, modifying the shift schedule plan according to the preset shift schedule constraint.
Through the intelligent cloud scheduling device of the embodiment, various factors can be combined to jointly determine a customer service scheduling plan, the working time of customer service personnel can be more reasonably arranged, the individualized requirements of the customer service personnel can be met, the business requirements of customer service services accessed by users can be better met, a cloud scheduling device capable of achieving reasonable and intelligent operation is provided, and the scheduling efficiency and the scheduling rationality are improved.
Example 3
An embodiment of the present application provides a computer device, which includes a processor and a memory, where the memory stores a computer program, and the computer program executes the intelligent cloud scheduling method described in any embodiment 1 when the processor runs.
For specific implementation steps, reference may be made to the description related to the intelligent cloud scheduling method provided in embodiment 1, and details are not repeated here to avoid repetition.
Example 4
An embodiment of the present application provides a computer-readable storage medium, which stores a computer program, and when the computer program runs on a processor, the computer program performs any one of the above-mentioned intelligent cloud scheduling methods.
For specific implementation steps, reference may be made to the description related to the intelligent cloud scheduling method provided in embodiment 1, and details are not repeated here to avoid repetition.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative and, for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, each functional module or unit in each embodiment of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention or a part of the technical solution that contributes to the prior art in essence can be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a smart phone, a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention.
Claims (10)
1. An intelligent cloud scheduling method is characterized by comprising the following steps:
determining expected access flow data according to historical access flow data;
dividing the expected access flow data into a plurality of interval flow data according to a preset time interval;
determining the manpower requirement of the time period to be scheduled according to the flow data of each interval;
and generating a customer service scheduling plan corresponding to the time period to be scheduled according to the customer service business attribute, the customer service personnel constraint condition and the manpower requirement.
2. The method according to claim 1, wherein the historical access traffic data includes a plurality of sub-access traffic data of a preset data recording period, and each sub-access traffic data is access traffic data corresponding to each recording sub-time period of the preset data recording period;
the determining expected access traffic data from historical access traffic data includes:
determining a service weighting factor of the time period to be scheduled according to the historical access flow data;
determining a target sub-recording time period corresponding to the time period to be scheduled from a plurality of recording sub-time periods;
determining target sub-access traffic data corresponding to the target sub-recording time period from the plurality of sub-access traffic data;
and determining the expected access flow data corresponding to the time period to be scheduled according to the target sub-access flow data and the service weighting factor.
3. The method of claim 1, wherein determining the manpower requirement for the period of time to be scheduled based on the interval traffic data comprises:
determining a flow peak value of the time period to be scheduled according to the flow data of each interval, wherein the flow peak value is the flow peak value of each interval to be scheduled of a plurality of intervals to be scheduled corresponding to the time period to be scheduled;
determining the service capacity requirement corresponding to the time period to be scheduled according to the flow peak value of each interval to be scheduled;
and determining the manpower requirement according to the service capacity requirement and the per-capita service capacity.
4. The method of claim 3, wherein generating the customer service shift schedule plan corresponding to the time period to be shifted according to the customer service business attributes, the customer service personnel constraint conditions and the human demand comprises:
determining candidate customer service personnel according to the customer service business attribute, the customer service personnel constraint condition and the manpower requirement;
selecting customer service scheduling personnel from the customer service candidate personnel according to the flow peak value of each to-be-scheduled interval, wherein the sum of the service capacities of the customer service scheduling personnel of each to-be-scheduled interval is not less than the flow peak value of each to-be-scheduled interval;
and generating the customer service shift scheduling plan according to the customer service shift scheduling personnel.
5. The method of claim 1, wherein the obtaining of the personnel constraint comprises:
acquiring personal forbidden information of each customer service staff;
and binding the customer service staff information with the personal forbidden information corresponding to the customer service staff to obtain the staff constraint condition corresponding to each customer service staff.
6. The method of claim 1, further comprising:
judging whether the scheduling plan of each customer service scheduling staff in the customer service scheduling plan meets preset scheduling constraints or not;
and if not, modifying the customer service shift scheduling plan according to the preset shift scheduling constraint.
7. The utility model provides an intelligence cloud scheduling device which characterized in that, the device includes:
the first determining module is used for determining expected access flow data according to historical access flow data;
the dividing module is used for dividing the expected access flow data into a plurality of interval flow data according to a preset time interval;
the second determining module is used for determining the manpower requirement of the time period to be scheduled according to the flow data of each interval;
and the generating module is used for generating a customer service scheduling plan corresponding to the time period to be scheduled according to the customer service business attribute, the customer service personnel constraint condition and the manpower requirement.
8. The apparatus of claim 7, further comprising: the judging module is used for judging whether the scheduling plan of each customer service scheduling staff in the customer service scheduling plan meets preset scheduling constraints or not; and if not, modifying the shift schedule plan according to the preset shift schedule constraint.
9. A computer device comprising a processor and a memory, the memory storing a computer program that when executed by the processor performs the intelligent cloud scheduling method of any one of claims 1 to 6.
10. A computer-readable storage medium, characterized in that it stores a computer program which, when run on a processor, performs the intelligent cloud scheduling method of any of claims 1 to 6.
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