CN116843140A - Operation center scheduling method, device, equipment and medium - Google Patents
Operation center scheduling method, device, equipment and medium Download PDFInfo
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The application discloses an operation center scheduling method, device, equipment and medium, which can be applied to the field of big data or the field of finance. Inputting the first service link distribution information into an operation center service prediction model, and predicting second service link distribution information in a second time period; inputting the first working time length and the first saturation of each first worker into a worker working time length and labor cost evaluation model, and predicting the first labor cost of each first worker; and for each business link in each second time period, selecting second workers with the number of second workers from the first worker set according to the low-to-high cost of the first workers and the corresponding relation between the business links and the first workers to form a second worker set, and generating a first scheduling plan. So as to select the second staff with lower manpower cost to carry out duty, thereby reducing the manpower cost of the staff as a whole and arranging the proper staff number to carry out duty.
Description
Technical Field
The present application relates to the field of big data, and in particular, to a method, an apparatus, a device, and a medium for scheduling an operation center.
Background
With the construction and development of intensive operation of banks, intensive business scenes of an operation center are gradually increased. The bank can handle various business types, and for each business type, the bank can have a plurality of processing links in the processing process, for example, for transfer transaction, the bank can comprise a plurality of processing links such as information input, password verification and the like, and for different processing links, corresponding staff needs to be arranged for duty. Especially when the traffic is huge, not only each worker needs to be arranged at a proper post for duty, but also the problem of personnel cost needs to be considered. Therefore, providing a suitable scheduling method for an operation center is a technical problem that needs to be solved at present.
Disclosure of Invention
Therefore, the application aims to provide an operation center scheduling method, an operation center scheduling device and an operation center scheduling medium, so that second staff with lower labor cost can be selected for duty, the labor cost of the staff is reduced as a whole, and the proper staff quantity can be arranged for duty. The specific scheme is as follows:
in one aspect, the present application provides an operation center scheduling method, including:
Acquiring first business link distribution information in a first time period; the first time period comprises a plurality of first sub-time periods, and the first business link distribution information comprises first business volume of each business link in each first sub-time period;
inputting the first service link distribution information into an operation center service prediction model, and predicting second service link distribution information in a second time period; the second time period is after the first time period, the second time period comprises a plurality of second sub-time periods, and the second business link distribution information comprises second business volume of each business link in each second sub-time period;
obtaining the first personnel number of each business link in each second sub-time period according to the second business link distribution information and the personnel average handling capacity of each business link;
acquiring a first staff set; the first staff member set comprises a plurality of first staff members;
inputting the first working time length and the first saturation of each first worker into a worker working time length and labor cost evaluation model, and predicting the first labor cost of each first worker;
For each business link in each second time period, selecting second staff members with second staff members from the first staff member set according to the first staff member cost from small to large and the corresponding relation between the business link and the first staff member to form a second staff member set, and generating a first scheduling plan according to the corresponding relation among the second time period, the business link and the second staff member set; the second staff member is the same as the first staff member.
On the other hand, the embodiment of the application also provides an operation center scheduling device, which comprises:
the first acquisition unit is used for acquiring first service link distribution information in a first time period; the first time period comprises a plurality of first sub-time periods, and the first business link distribution information comprises first business volume of each business link in each first sub-time period;
the first prediction unit is used for inputting the first service link distribution information into an operation center service prediction model and predicting second service link distribution information in a second time period; the second time period is after the first time period, the second time period comprises a plurality of second sub-time periods, and the second business link distribution information comprises second business volume of each business link in each second sub-time period;
The first determining unit is used for obtaining the first personnel number of each business link in each second sub-time period according to the second business link distribution information and the per-person processing capacity of each business link;
the second acquisition unit is used for acquiring the first staff set; the first staff member set comprises a plurality of first staff members;
the second prediction unit is used for inputting the first working time length and the first saturation of each first worker into a worker working time length and labor cost evaluation model and predicting the first labor cost of each first worker;
the second determining unit is used for selecting second staff members with second staff members from the first staff member set according to the first staff member cost from small to large and the corresponding relation between the service links and the first staff members in each second time period to form a second staff member set, and generating a first scheduling plan according to the corresponding relation between the second time period, the service links and the second staff member set; the second staff member is the same as the first staff member.
In another aspect, an embodiment of the present application further provides a computer device, including a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is used for executing the operation center scheduling method according to the instructions in the program codes.
In another aspect, an embodiment of the present application further provides a computer readable storage medium, where the computer readable storage medium is used to store a computer program, and the computer program is used to execute the operation center scheduling method.
The embodiment of the application provides an operation center scheduling method, an operation center scheduling device, operation center scheduling equipment and an operation center scheduling medium, wherein first service link distribution information in a first time period is acquired; the first time period comprises a plurality of first sub-time periods, and the first business link distribution information comprises first business volume of each business link in each first sub-time period; inputting the first service link distribution information into an operation center service prediction model, and predicting second service link distribution information in a second time period; the second time period is after the first time period, the second time period comprises a plurality of second sub-time periods, and the second business link distribution information comprises second business volume of each business link in each second sub-time period; obtaining the first personnel number of each business link in each second sub-time period according to the second business link distribution information and the personnel average handling capacity of each business link; acquiring a first staff set; the first staff member set comprises a plurality of first staff members; inputting the first working time length and the first saturation of each first worker into a worker working time length and labor cost evaluation model, and predicting the first labor cost of each first worker; for each business link in each second time period, selecting second staff members with second staff members from the first staff member set according to the first staff member cost from small to large and the corresponding relation between the business link and the first staff member to form a second staff member set, and generating a first scheduling plan according to the corresponding relation among the second time period, the business link and the second staff member set; the second staff member is the same as the first staff member.
In the embodiment of the application, the second service link distribution information in the second time period in the future can be predicted through the operation center service prediction model, and the first personnel cost can be output through the personnel working time length and the personnel cost evaluation model so as to select the second personnel with lower personnel cost for duty, thereby reducing the personnel cost of the personnel on the whole and arranging the proper personnel quantity for duty.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are some embodiments of the application and that other drawings may be obtained from these drawings without inventive effort for a person skilled in the art.
Fig. 1 shows a schematic flow chart of an operation center scheduling method according to an embodiment of the present application;
fig. 2 is a schematic flow chart of another scheduling method of an operation center according to an embodiment of the present application;
fig. 3 is a structural diagram of an operation center shift arrangement system according to an embodiment of the present application;
Fig. 4 is a block diagram of an operation center scheduling device according to an embodiment of the present application;
fig. 5 is a block diagram of a computer device according to an embodiment of the present application.
Detailed Description
In order that the above objects, features and advantages of the application will be readily understood, a more particular description of the application will be rendered by reference to the appended drawings.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, but the present application may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present application is not limited to the specific embodiments disclosed below.
For easy understanding, the following describes in detail an operation center scheduling method, an apparatus, a device and a medium provided in the embodiments of the present application with reference to the accompanying drawings.
Referring to fig. 1, a flow chart of an operation center scheduling method according to an embodiment of the present application is shown, and the method may include the following steps.
S101, acquiring first business link distribution information in a first time period.
In the embodiment of the present application, the first period may be a past period, the first period may include a plurality of first sub-periods, and the service link distribution information in the first period may be acquired and recorded as first service link distribution information, where the first service link distribution information may include a first traffic volume of each service link in each first sub-period.
Specifically, at least one service link is being processed in each first sub-period, and different service links have corresponding first traffic. For example, in the first sub-period 9:00-10:00, the traffic link a and the traffic link B are being processed, the first traffic volume of the traffic link a is 100, and the first traffic volume of the traffic link B is 200; in the second sub-time period 10:00-11:00, the service link A and the service link C are being processed, the first traffic of the service link A is 300, and the first traffic of the service link C is 50.
Specifically, the traffic of each traffic segment in the whole first time period may also be obtained, for example, in the first time period 9:00-11:00, the traffic of the traffic segment a is 400, the traffic of the traffic segment B is 200, and the traffic of the traffic segment C is 50.
Specifically, the service type in the first time period and the service volume corresponding to each service type can be obtained, and the distribution condition of each service type in each sub-time period, such as the service volume of each service type in each first sub-time period, can be obtained more carefully. One service type specifically includes a plurality of service links, that is, a plurality of service links need to be processed in turn to process a certain service type.
S102, inputting the first service link distribution information into an operation center service prediction model, and predicting second service link distribution information in a second time period.
In the embodiment of the application, the operation center business prediction model can predict business link distribution information of a future period, the first business link distribution information can be input into the operation center business prediction model, and the business link distribution information in a second period can be predicted and recorded as second business link distribution information.
Specifically, the second period of time may be a future period of time, the second period of time may include a plurality of second sub-periods of time after the first period of time, and the second traffic distribution information may include a second traffic of each traffic in each second sub-period of time, that is, a second traffic of each traffic in a different second period of time may be obtained, so as to grasp a specific distribution of traffic in the future period of time.
In the embodiment of the application, the traffic of each traffic link in the first time period, the traffic corresponding to each traffic type and the traffic of each traffic type in each first sub-time period can be input into the model, so that the traffic of each traffic link in the second time period, the traffic corresponding to each traffic type and the traffic of each traffic type in each second sub-time period can be predicted, and the traffic handling situation of the future time period can be mastered from multiple aspects, thereby facilitating the follow-up arrangement of suitable staff for duty.
And S103, obtaining the first personnel number of each business link in each second sub-time period according to the second business link distribution information and the per-person processing capacity of each business link.
In the embodiment of the application, the per-person processing capacity of each business link can be the processing capacity of each business link worker per hour, for example, the per-person processing capacity of the business link A can be 20 pieces per hour, and the per-person processing capacity of the business link B can be 35 pieces per hour.
Specifically, the first personnel number of each business link in each second sub-time period can be obtained according to the second business link distribution information and the per-person processing amount of each business link. That is, for each second sub-period, the number of people required by each business link can be obtained through the second traffic volume and the per-person throughput of each business link and recorded as the first number of people, so that the workers with the first number of people can finish the second traffic volume, the situation that the workers arrange less clients to handle poor experiences is avoided, and the situation that the workers arrange more people to cause the increase of the labor cost of the bank is avoided.
S104, acquiring a first staff set.
In the embodiment of the application, the first staff member set can be obtained, and the first staff member set can comprise a plurality of first staff members so as to select a proper staff member from the plurality of first staff members to carry out duty. The on-job personnel list of the operation center can be directly acquired and used as the first staff set.
In one possible implementation, the first set of staff members may be determined in conjunction with the staff member's vacation information. Specifically, a fifth set of staff members may be obtained; the fifth set of staff members includes a plurality of fifth staff members, for example, all of the incumbent staff members of the bank may constitute the fifth set of staff members. The person requesting rest information may include information such as a name of a person requesting rest and a period of time requesting rest, and the first person set may be determined according to the fifth person set and the person requesting rest information.
That is, the staff requesting the holiday in the second time period can be removed from the fifth staff set, and the rest is the staff which can normally work in the second time period, so that the first staff set is formed, the unattended situation is avoided due to the fact that the staff requesting the holiday is arranged to carry out the duty, and the accuracy of staff scheduling is improved.
S105, inputting the first working time length and the first saturation of each first staff member into a staff working time length and labor cost evaluation model, and predicting the first labor cost of each first staff member.
In the embodiment of the application, the personnel working time length and labor cost evaluation model can predict the labor cost of the personnel, the labor cost can be understood as payroll compensation of the personnel, and the like, and for each first personnel, the first working time length can be obtained, and can be the working time length in the same day or the working time length in a previous period, and the first saturation can be the ratio of the first working time length to the upper limit of the working time length, for example, the ratio of the working time length in the same day to the upper limit of the working time length in the same day.
Specifically, the first working time length and the first saturation of each first worker can be input into the worker working time length and labor cost evaluation model, so that the first labor cost of each first worker is predicted, the labor cost of each worker is mastered on the whole, and follow-up labor cost saving is facilitated.
S106, for each business link in each second time period, selecting second workers with the second personnel number from the first worker set according to the first labor cost from small to large and the corresponding relation between the business link and the first workers to form a second worker set, and generating a first scheduling plan according to the corresponding relation among the second time period, the business link and the second worker set.
In the embodiment of the application, for each service link in each second time period, the first staff capable of processing the service link can be found through the corresponding relation between the service link and the first staff, for example, the first staff capable of processing the service link A has the first staff, the second staff and the third staff, the number of the staff required by the service link A is 2, and the second staff with the second staff number can be selected from the first staff set according to the fact that the first staff cost is from small to large to form the second staff set so as to arrange the second staff to process the service link, wherein the number of the second staff is the same as that of the first staff.
For example, among the first staff member a, the second staff member and the third staff member capable of processing the service link a, the first staff member b and the third staff member are sequentially ranked from the low cost to the high cost, and the first two staff member b and the third staff member c can be selected to process the service link a.
Specifically, according to the corresponding relation among the second time period, the service links and the second staff sets, namely, in each second sub-time period of the second time period, a first scheduling plan is generated according to the combination of each service link and the corresponding second staff for processing the service link. The first scheduling plan includes a set of staff members for each business segment during each second sub-period. For example, in the second sub-period 10:00-11:00, the staff members for processing the business link A are collected into B and C.
Therefore, the second business link distribution information in the second time period in the future can be predicted through the operation center business prediction model, and the first personnel cost can be output through the personnel working time length and the labor cost evaluation model, so that second personnel with lower labor cost can be selected for duty, the labor cost of the personnel is reduced on the whole, and the appropriate personnel quantity can be arranged for duty.
In one possible implementation manner, S106 may consider determining a staff list for the service link with the largest number of staff requirements, and then selecting the staff on duty that can be the other service links of the other second sub-time periods from the staff list, so as to improve the multiplexing rate of the staff on duty and reduce the switching times of the staff.
Specifically, for each business link in each second sub-period, there is a first number of people that need to process the business link in the second sub-period, the first number of people with the maximum value can be determined from the plurality of first numbers of people to be used as a third number of people, and the business link corresponding to the third number of people is used as the first business link. For example, in the second sub-period 9:00-10:00, the first number of people in the service link a is 30 people, the first number of people in the service link B is 20 people, in the second sub-period 10:00-11:00, the first number of people in the service link a is 50 people, and the first number of people in the service link C is 40 people, the first number of people in the service link a can be recorded as the third number of people in the second sub-period 10:00-11:00, and the service link a can be recorded as the first service link in the second sub-period 10:00-11:00.
Specifically, for the first business link, according to the corresponding relation between the first business link and the third staff, a list of staff capable of processing the first business link can be obtained, for example, the third staff capable of processing the business link A has a first staff, a second staff and a third staff, and according to the first staff cost from small to large, the third staff with the third staff number is selected from the first staff set to form a third staff set, so that the third staff in the third staff set can be determined to process the first business link, for example, the third staff set comprises the first staff and the third staff.
Specifically, other types of traffic links other than the first traffic link or traffic links that are the same as the first traffic link but in a second sub-period of time different from the first traffic link may be denoted as second traffic links. For each second business link except the first business link, whether the third worker set has fourth workers capable of processing the fourth number of the second business links can be judged to form the fourth worker set, so that people which can be on duty for the second business link are preferentially selected from the list of people on duty, and the multiplexing rate of the people can be improved.
If the third staff set has fourth staff capable of processing the fourth staff of the second business link, for example, the third staff set includes b and c, both b and c can process the second business link, and b and c can be combined into the fourth staff set, the first scheduling plan is generated according to the corresponding relation between the first business link, the second time period where the first business link is located, and the third staff set, and the corresponding relation between the second business link, the second time period where the second business link is located, and the fourth staff set.
Otherwise, the fourth staff member of the fourth staff member number is selected from the first staff member set according to the first staff member cost from small to large and the corresponding relation between the second service link and the fourth staff member, and the fourth staff member is used as the staff member for processing the second service link, and the first scheduling plan is generated according to the corresponding relation between the first service link, the second time period where the first service link is located, the third staff member set, the second service link, the second time period where the second service link is located, and the fourth staff member set.
In the embodiment of the application, before the model is applied, the model can be trained by collecting the historical data, so that a trained model is obtained. Specifically, a first training set and a second training set may be acquired; the first training set may include third traffic link distribution information in a third time period, traffic volume of each traffic link, traffic volume corresponding to each traffic type, and traffic volume of each traffic type in each third sub-time period; the third time period includes a plurality of the third sub-time periods.
The third service link distribution information may be a service volume of each service link in each third sub-period, where the service volume of each service link is a respective service volume of different service links in the whole third period. Training the first preset model by using the first training set to obtain an operation center business prediction model;
specifically, the second training set may include a second working duration, a second saturation, and a second labor cost for each staff member over a period of time; and training a second preset model by using a second training set to obtain a personnel working time length and labor cost evaluation model.
In the embodiment of the present application, referring to fig. 2, a schematic flow chart of another scheduling method of an operation center according to the embodiment of the present application is shown.
Step 1: the scheduling staff starts a service agent through the interaction module, inputs or maintains the feature and the learning algorithm model to the machine learning module through the interaction module, and executes the step 2;
step 2: the service agent acquires historical information of processing traffic of an operation center, personnel position role configuration, operation duration of personnel under each position role and labor cost and forwards the historical information to the calculation storage module; the computing and storing module is used for carrying out standard integration and summarization processing on the received historical information of the processing traffic volume of the operation center, the configuration of personnel post roles, the operation duration of the personnel under each post role and the labor cost, and forming integrated summarization information for the machine learning module to use;
step 3: the machine learning module reads the integrated and collected information extraction characteristic data in the calculation storage module, trains a learning algorithm model and forms analysis and identification capabilities of operation center traffic prediction capability, personnel role configuration and labor cost;
step 4: the scheduling staff inputs or maintains personnel information, post role configuration and holiday requesting information of the operation center to the intelligent scheduling module of the operation center through the interaction module; the intelligent scheduling module of the operation center synchronizes personnel information, post role configuration and holiday requesting information of the operation center to the machine learning module;
Step 5: the machine learning module is used for comprehensively analyzing and identifying the processing traffic of the current operation center by using the trained learning algorithm model, predicting the traffic of the operation center and the post role demand of each service period, and calculating the number of operation center personnel and role demands matched with the demand and the period role demand by combining the configuration of the post role of the current center personnel, the current working time and the working saturation of the personnel; screening available personnel by combining personnel information about holiday seeking personnel; calculating service cost of the screened available personnel, selecting an optimal cost, a personnel scheduling plan and a personnel role working period switching plan which meet the requirements of centralized operation business, producing personnel scheduling plans, personnel role working period switching plans and cost analysis results, and sending the personnel scheduling plans, the personnel role working period switching plans and the cost analysis results to an intelligent scheduling module of an operation center;
step 6: the intelligent scheduling module of the operation center receives and analyzes the personnel scheduling plan, the personnel role working period switching plan and the cost analysis result of the machine learning module, generates a final personnel scheduling plan (comprising personnel role working period and the like), generates scheduling notification information and transmits the scheduling notification information to the message service; generating a cost analysis report for subsequent review;
Step 7: the message service receives a scheduling message notice of an intelligent scheduling module of the operation center and forwards the scheduling message notice to an operator of the operation center;
step 8: and the scheduling staff checks the scheduling result and the cost analysis report through the interaction module.
In the embodiment of the application, the method can be executed by using a customer service scheduling system, and the structure diagram of the operation center scheduling system provided by the embodiment of the application is shown by referring to fig. 3, and comprises an interaction module, a message service module, a customer service intelligent scheduling module, a machine learning module, a calculation storage module, a service agent module intensive operation center module, an application system and a basic resource module.
Specifically, the interaction module provides an interaction access function, and comprises an enabling/stopping service agent, an inputting/maintaining machine learning library, management and maintenance operation center personnel information, post role configuration, holiday requesting information, analysis report consulting and the like; the message service module provides message notification capability and forwards the scheduling condition message notification to the operator of the operation center;
the intelligent scheduling module of the operation center provides the functions of personnel information management of the operation center, post role configuration, holiday requesting management, analysis and review of labor cost and the like, and comprises the steps of receiving and recording the personnel information of the operation center, post role configuration, holiday requesting information of the interaction module, synchronizing the personnel information of the operation center, post role configuration, holiday requesting information to the machine learning module, receiving the personnel scheduling plan and the labor cost analysis result of the machine learning module, forming a final personnel scheduling plan, sending a message notification to the operation personnel of the operation center through a message service, generating a cost analysis report, receiving an operation analysis query request of the interaction module and the like;
The machine learning module is used for performing model training on a machine learning algorithm by using historical information of operation center processing traffic volume, personnel post role configuration, operation time of personnel under each post role and labor cost collected by a service agent, forming analysis and identification capacity of operation center traffic volume prediction capacity, personnel role configuration and labor cost, and providing analysis results of concentrated operation personnel scheduling plans and labor cost by combining current operation center processing traffic volume, personnel post role configuration, personnel current working time and working saturation and personnel on holiday conditions; the method comprises the steps of receiving characteristic and learning algorithm models input and maintained by an interaction module, reading integrated summary information of a calculation storage module, performing characteristic extraction and learning algorithm model training, forming operation center traffic prediction capacity, personnel role configuration and analysis and recognition capacity of labor cost, performing comprehensive analysis and recognition on operation center processing traffic, predicting operation center traffic and post role demand of each service period, and calculating the number of operation center personnel and role demands matched with the demand and the period role demand by combining the current center personnel post role configuration, the current personnel working time and the working saturation; screening available personnel by combining personnel information about holiday seeking personnel; calculating service cost of the screened available personnel, selecting an optimal cost, a personnel scheduling plan and a personnel role working period switching plan which meet the requirements of centralized operation business, producing personnel scheduling plans, personnel role working period switching plans and cost analysis results, and sending the personnel scheduling plans, the personnel role working period switching plans and the cost analysis results to an intelligent scheduling module of an operation center;
The computing and storing module is used for providing a data information integration and summarization function, receiving historical information of the service agent, such as the processing traffic volume, the personnel position role configuration, the operation duration of personnel under each position role and the labor cost of the customer, collected and obtained by the service agent, and sending the integrated information to the machine learning module;
the service agent module provides information acquisition and acquisition functions of processing traffic volume of an operation center, configuration of personnel post roles, operation duration of personnel under each post role and labor cost, and comprises the steps of acquiring historical information of the processing traffic volume of the operation center, the configuration of the personnel post roles, the operation duration of the personnel under each post role and the labor cost, and transmitting the historical information to calculation and storage; collecting the current operation center traffic and sending the operation duration information of the personnel under each post role to a machine learning module;
specifically, the intensive operation center module provides an intensive operation service processing function. The application system provides a banking business processing function; and the basic resource module is used for providing basic resources required by the operation of the module and the system and comprises calculation, storage, network and the like.
The embodiment of the application provides an operation center scheduling method, which can predict second service link distribution information in a second time period in the future through an operation center service prediction model, and can output first personnel cost through a personnel working time and labor cost evaluation model so as to select second personnel with lower labor cost for duty, thereby reducing the labor cost of the personnel on the whole and arranging proper personnel quantity for duty.
Based on the above operation center scheduling method, the embodiment of the present application further provides an operation center scheduling device, and referring to fig. 4, a structural block diagram of the operation center scheduling device provided by the embodiment of the present application is shown, where the device may include:
a first obtaining unit 201, configured to obtain first service link distribution information in a first period; the first time period comprises a plurality of first sub-time periods, and the first business link distribution information comprises first business volume of each business link in each first sub-time period;
a first prediction unit 202, configured to input the first service link distribution information into an operation center service prediction model, and predict second service link distribution information in a second time period; the second time period is after the first time period, the second time period comprises a plurality of second sub-time periods, and the second business link distribution information comprises second business volume of each business link in each second sub-time period;
A first determining unit 203, configured to obtain, according to the second service link distribution information and the per-person throughput of each service link, a first number of people in each service link in each second sub-period;
a second acquiring unit 204, configured to acquire a first staff member set; the first staff member set comprises a plurality of first staff members;
a second prediction unit 205, configured to input a first working duration and a first saturation of each first worker into a worker working duration and a labor cost assessment model, and predict a first labor cost of each first worker;
a second determining unit 206, configured to pick, for each of the service links in each second time period, a second number of staff members from the first staff member set according to the first staff member cost from small to large and the correspondence between the service links and the first staff member, to form a second staff member set, and to generate a first scheduling plan according to the correspondence between the second time period, the service links and the second staff member set; the second staff member is the same as the first staff member.
Specifically, the second determining unit is configured to:
determining the maximum value from the first personnel numbers as a third personnel number, and taking a service link corresponding to the third personnel number as a first service link;
for the first business link, according to the first labor cost from small to large and the corresponding relation between the first business link and third staff, selecting the third staff of the third staff number from the first staff set to form a third staff set;
for each second business link except the first business link, judging whether the third worker set has fourth workers with the number of fourth workers capable of processing the second business link, and forming a fourth worker set;
if yes, generating the first scheduling plan according to the first service link, the corresponding relation between the second time period where the first service link is located and the third staff set, and the corresponding relation between the second service link, the second time period where the second service link is located and the fourth staff set;
Otherwise, according to the first labor cost from small to large and the corresponding relation between the second business link and the fourth staff, the fourth staff of the fourth staff number is selected from the first staff set, and the first scheduling plan is generated according to the corresponding relation between the first business link, the second time period where the first business link is located and the third staff set, and the corresponding relation between the second business link, the second time period where the second business link is located and the fourth staff set.
Specifically, the second acquisition unit is configured to:
acquiring a fifth staff set; the fifth staff member set comprises a plurality of fifth staff members;
and determining the first staff set according to the fifth staff set and the staff rest information.
Specifically, the device further comprises:
the third acquisition unit is used for acquiring the first training set and the second training set; the first training set comprises third service link distribution information in a third time period, service volume of each service link, service volume corresponding to each service type and service volume of each service type in each third sub-time period; the third time period includes a plurality of the third sub-time periods; the second training set comprises a second working time length, a second saturation and a second manpower cost;
The training unit is used for training a first preset model by using the first training set to obtain the operation center business prediction model; and training a second preset model by using the second training set to obtain the personnel working time length and labor cost evaluation model.
The embodiment of the application provides an operation center scheduling device, which can predict second service link distribution information in a second time period in the future through an operation center service prediction model, and can output first personnel cost through a personnel working time and labor cost evaluation model so as to select second personnel with lower labor cost for duty, thereby reducing the labor cost of the personnel on the whole and arranging proper personnel quantity for duty.
In yet another aspect, an embodiment of the present application provides a computer device, referring to fig. 5, which shows a structural diagram of the computer device provided by the embodiment of the present application, where the device includes a processor 310 and a memory 320:
the memory 310 is used for storing program codes and transmitting the program codes to the processor;
the processor 320 is configured to execute the operation center scheduling method provided in the foregoing embodiment according to an instruction in the program code.
The computer device may comprise a terminal device or a server, in which the aforementioned operation center shift arrangement may be configured.
In still another aspect, an embodiment of the present application further provides a storage medium, where the storage medium is used to store a computer program, where the computer program is used to execute the method for scheduling an operation center provided in the foregoing embodiment.
Additionally, embodiments of the present application provide a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions to cause the computer device to perform the operations center scheduling method provided in various alternative implementations of the above aspects.
It should be noted that the method, the device, the equipment and the medium for scheduling the operation center provided by the application can be used in the big data field or the financial field. The foregoing is merely an example, and the application fields of the method, the device, the equipment and the medium for scheduling an operation center provided by the present application are not limited.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by program instruction hardware, and the above program may be stored in a computer readable storage medium, where the program when executed performs steps including the above method embodiments; and the aforementioned storage medium may be at least one of the following media: read-only Memory (ROM), RAM, magnetic disk or optical disk, etc.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented, for example, in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "includes" and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for the device embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments for relevant points.
The foregoing is merely a preferred embodiment of the present application, and the present application has been disclosed in the above description of the preferred embodiment, but is not limited thereto. Any person skilled in the art can make many possible variations and modifications to the technical solution of the present application or modifications to equivalent embodiments using the methods and technical contents disclosed above, without departing from the scope of the technical solution of the present application. Therefore, any simple modification, equivalent variation and modification of the above embodiments according to the technical substance of the present application still fall within the scope of the technical solution of the present application.
Claims (10)
1. An operation center shift arrangement method, comprising:
Acquiring first business link distribution information in a first time period; the first time period comprises a plurality of first sub-time periods, and the first business link distribution information comprises first business volume of each business link in each first sub-time period;
inputting the first service link distribution information into an operation center service prediction model, and predicting second service link distribution information in a second time period; the second time period is after the first time period, the second time period comprises a plurality of second sub-time periods, and the second business link distribution information comprises second business volume of each business link in each second sub-time period;
obtaining the first personnel number of each business link in each second sub-time period according to the second business link distribution information and the personnel average handling capacity of each business link;
acquiring a first staff set; the first staff member set comprises a plurality of first staff members;
inputting the first working time length and the first saturation of each first worker into a worker working time length and labor cost evaluation model, and predicting the first labor cost of each first worker;
For each business link in each second time period, selecting second staff members with second staff members from the first staff member set according to the first staff member cost from small to large and the corresponding relation between the business link and the first staff member to form a second staff member set, and generating a first scheduling plan according to the corresponding relation among the second time period, the business link and the second staff member set; the second staff member is the same as the first staff member.
2. The method of claim 1, wherein for each of the business links in each of the second time periods, selecting a second staff member of a second number of staff members from the first staff member set according to the first staff member cost from small to large and the correspondence between the business links and the first staff member, forming a second staff member set, and generating a first scheduling plan according to the correspondence between the second time period, the business links and the second staff member set, including:
determining the maximum value from the first personnel numbers as a third personnel number, and taking a service link corresponding to the third personnel number as a first service link;
For the first business link, according to the first labor cost from small to large and the corresponding relation between the first business link and third staff, selecting the third staff of the third staff number from the first staff set to form a third staff set;
for each second business link except the first business link, judging whether the third worker set has fourth workers with the number of fourth workers capable of processing the second business link, and forming a fourth worker set;
if yes, generating the first scheduling plan according to the first service link, the corresponding relation between the second time period where the first service link is located and the third staff set, and the corresponding relation between the second service link, the second time period where the second service link is located and the fourth staff set;
otherwise, according to the first labor cost from small to large and the corresponding relation between the second business link and the fourth staff, the fourth staff of the fourth staff number is selected from the first staff set, and the first scheduling plan is generated according to the corresponding relation between the first business link, the second time period where the first business link is located and the third staff set, and the corresponding relation between the second business link, the second time period where the second business link is located and the fourth staff set.
3. The method of claim 1, wherein the obtaining a first set of staff members comprises:
acquiring a fifth staff set; the fifth staff member set comprises a plurality of fifth staff members;
and determining the first staff set according to the fifth staff set and the staff rest information.
4. A method according to any one of claims 1-3, characterized in that the method further comprises:
acquiring a first training set and a second training set; the first training set comprises third service link distribution information in a third time period, service volume of each service link, service volume corresponding to each service type and service volume of each service type in each third sub-time period; the third time period includes a plurality of the third sub-time periods; the second training set comprises a second working time length, a second saturation and a second manpower cost;
training a first preset model by using the first training set to obtain the operation center business prediction model; and training a second preset model by using the second training set to obtain the personnel working time length and labor cost evaluation model.
5. An operation center shift arrangement device, comprising:
the first acquisition unit is used for acquiring first service link distribution information in a first time period; the first time period comprises a plurality of first sub-time periods, and the first business link distribution information comprises first business volume of each business link in each first sub-time period;
the first prediction unit is used for inputting the first service link distribution information into an operation center service prediction model and predicting second service link distribution information in a second time period; the second time period is after the first time period, the second time period comprises a plurality of second sub-time periods, and the second business link distribution information comprises second business volume of each business link in each second sub-time period;
the first determining unit is used for obtaining the first personnel number of each business link in each second sub-time period according to the second business link distribution information and the per-person processing capacity of each business link;
the second acquisition unit is used for acquiring the first staff set; the first staff member set comprises a plurality of first staff members;
The second prediction unit is used for inputting the first working time length and the first saturation of each first worker into a worker working time length and labor cost evaluation model and predicting the first labor cost of each first worker;
the second determining unit is used for selecting second staff members with second staff members from the first staff member set according to the first staff member cost from small to large and the corresponding relation between the service links and the first staff members in each second time period to form a second staff member set, and generating a first scheduling plan according to the corresponding relation between the second time period, the service links and the second staff member set; the second staff member is the same as the first staff member.
6. The apparatus according to claim 5, wherein the second determining unit is configured to:
determining the maximum value from the first personnel numbers as a third personnel number, and taking a service link corresponding to the third personnel number as a first service link;
for the first business link, according to the first labor cost from small to large and the corresponding relation between the first business link and third staff, selecting the third staff of the third staff number from the first staff set to form a third staff set;
For each second business link except the first business link, judging whether the third worker set has fourth workers with the number of fourth workers capable of processing the second business link, and forming a fourth worker set;
if yes, generating the first scheduling plan according to the first service link, the corresponding relation between the second time period where the first service link is located and the third staff set, and the corresponding relation between the second service link, the second time period where the second service link is located and the fourth staff set;
otherwise, according to the first labor cost from small to large and the corresponding relation between the second business link and the fourth staff, the fourth staff of the fourth staff number is selected from the first staff set, and the first scheduling plan is generated according to the corresponding relation between the first business link, the second time period where the first business link is located and the third staff set, and the corresponding relation between the second business link, the second time period where the second business link is located and the fourth staff set.
7. The apparatus of claim 5, wherein the second acquisition unit is configured to:
acquiring a fifth staff set; the fifth staff member set comprises a plurality of fifth staff members;
and determining the first staff set according to the fifth staff set and the staff rest information.
8. The apparatus according to any one of claims 5-7, further comprising:
the third acquisition unit is used for acquiring the first training set and the second training set; the first training set comprises third service link distribution information in a third time period, service volume of each service link, service volume corresponding to each service type and service volume of each service type in each third sub-time period; the third time period includes a plurality of the third sub-time periods; the second training set comprises a second working time length, a second saturation and a second manpower cost;
the training unit is used for training a first preset model by using the first training set to obtain the operation center business prediction model; and training a second preset model by using the second training set to obtain the personnel working time length and labor cost evaluation model.
9. A computer device, the computer device comprising a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute the operation center scheduling method of any one of claims 1-4 according to instructions in the program code.
10. A computer readable storage medium for storing a computer program for executing the operation center scheduling method of any one of claims 1-4.
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| CN202310796682.0A CN116843140A (en) | 2023-06-30 | 2023-06-30 | Operation center scheduling method, device, equipment and medium |
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| CN202310796682.0A CN116843140A (en) | 2023-06-30 | 2023-06-30 | Operation center scheduling method, device, equipment and medium |
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