CN112465402A - Resource allocation method and related device - Google Patents
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Abstract
The embodiment of the application provides a resource allocation method and a related device, and the method can uniformly convert the business workload of a bank outlet into standard time for use through a workload standardization method, and is convenient for subsequently allocating the labor resources of the bank outlet. On the basis, the labor force resource combination optimization algorithm based on the queuing theory realizes the automatic calculation of the labor force combination scheme of the bank outlets, not only meets the requirements of the workload of the to-be-processed business of the bank outlets, but also ensures that the waiting time of customers is appropriate. Compared with a manual resource allocation mode, the method has stronger objectivity and improves the utilization rate of the labor resources of the bank outlets.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a resource allocation method and a related apparatus.
Background
How to reasonably distribute the limited labor resources of the bank outlets, the customer requirements under different passenger flow volumes can be fully met, the efficiency of the outlets for serving customers is improved, and the problem of value solving is solved.
In the management process of the network, the management personnel generally distribute the labor resources of the banking network according to subjective experience. Because the manual estimation method depends on the personal experience of the rule making personnel, the subjective factors are obvious, the standardability and the accuracy are low, and the distribution of network resources is uneven due to the lack of accurate estimation of network traffic, thereby wasting labor resources and influencing the service quality of customers.
Disclosure of Invention
In order to solve the technical problems in the prior art, the application provides a resource allocation method and a related device, which realize the automatic calculation of a labor force combination scheme of a bank outlet, not only meet the requirements of the pending service workload of the bank outlet, but also enable the waiting time of a client to be appropriate.
In one aspect, an embodiment of the present application provides a resource allocation method, where the method includes:
acquiring the total workload of the to-be-processed service of a target bank outlet in target time; the total workload of the service to be processed comprises the workload of the service to be processed corresponding to n time periods;
determining whether the workload provided by the number N of the pending people of the target bank network point in the current time period can meet the customer waiting condition according to the workload of the pending business of the target bank network point in the current time period; the traffic to be processed in the current time period is the sum of the remaining traffic to be processed in the ith-1 time period and the traffic to be processed in the ith time period; the initial value of i is 1; the initial value of N is 1;
if not, adjusting the undetermined number N to be N + k, and re-executing the to-be-processed service workload according to the target bank website in the current time period based on the adjusted undetermined number N to determine whether the workload provided by the undetermined number N of the target bank website in the current time period can meet the customer waiting condition; k is greater than or equal to 1;
if yes, determining whether the i is smaller than n;
if not, adjusting i to be i +1, re-executing the workload of the service to be processed in the current time period according to the target bank website, and determining whether the workload provided by the number N of the people to be determined in the current time period by the target bank website can meet the customer waiting condition;
if so, determining the number of the target people required by the target bank branch to process the total workload of the business to be processed in the target time.
In a possible implementation manner, the determining, according to the workload of the service to be processed in the current time period by the target banking outlet, whether the workload provided by the number N of people to be determined in the current time period by the target banking outlet can satisfy a customer waiting condition includes:
according to a first ratio of the workload of the service to be processed of the target bank outlet in the current time period to the workload provided by the number N of the people to be determined of the target bank outlet in the current time period;
determining a second ratio of the maximum waiting time of the client to the corresponding time length of the current time period;
determining whether the first ratio is less than or equal to the second ratio.
In one possible implementation, the method further includes:
acquiring the total workload of historical business processing of the target bank network point in historical time;
the acquiring the total workload of the to-be-processed service of the target banking outlet in the target time comprises the following steps:
dividing the historical time to obtain n time periods;
and acquiring the respective corresponding to-be-processed business workload of the target banking outlet in n time periods included in the target time according to the historical business processing total workload.
In one possible implementation, the method further includes:
acquiring sample service processing data corresponding to the target bank outlet sample service; the sample service has a first identity;
determining the service processing time corresponding to the sample service according to the sample service processing data;
determining a second identifier of the sample service based on the service processing time;
the acquiring, according to the historical service processing data, the to-be-processed service workload corresponding to each of the target banking outlets in the n time periods of the target time includes:
and acquiring the respective corresponding to-be-processed service workload of the target banking outlet in n time periods of the target time according to the historical service processing data and the second identifier of the historical service.
In one possible implementation, the method further includes:
and determining the labor force saturation of the target bank outlets in the target time according to the target number of people.
On the other hand, an embodiment of the present application provides a resource allocation apparatus, where the apparatus includes an obtaining unit, a determining unit, and an adjusting unit:
the acquisition unit is used for acquiring the total workload of the to-be-processed business of the target bank branch in the target time; the total workload of the service to be processed comprises the workload of the service to be processed corresponding to n time periods;
the determining unit is used for determining whether the workload provided by the number N of the undetermined persons of the target bank website in the current time period can meet the customer waiting condition according to the workload of the service to be processed of the target bank website in the current time period; the traffic to be processed in the current time period is the sum of the remaining traffic to be processed in the ith-1 time period and the traffic to be processed in the ith time period; the initial value of i is 1; the initial value of N is 1; if not, triggering the adjusting unit; if yes, determining whether the i is smaller than n; if yes, triggering the adjusting unit, and if not, determining that the number of people to be determined is the target number of people required by the target bank branch for processing the total workload of the business to be processed in the target time;
the adjusting unit is used for adjusting the number N of undetermined persons to be N + k if the customer waiting condition is not met, and triggering the determining unit based on the adjusted number N of undetermined persons; k is greater than or equal to 1;
and the adjusting unit is further configured to adjust i to i +1 and trigger the determining unit if i is smaller than n.
In a possible implementation manner, the determining unit is configured to:
according to a first ratio of the workload of the service to be processed of the target bank outlet in the current time period to the workload provided by the number N of the people to be determined of the target bank outlet in the current time period;
determining a second ratio of the maximum waiting time of the client to the corresponding time length of the current time period;
determining whether the first ratio is less than or equal to the second ratio.
In a possible implementation manner, the obtaining unit is further configured to obtain a total historical business processing workload of the target banking site in a historical time;
the acquisition unit is used for dividing the historical time to obtain n time periods;
and acquiring the respective corresponding to-be-processed business workload of the target banking outlet in n time periods included in the target time according to the historical business processing total workload.
In a possible implementation manner, the obtaining unit is further configured to:
acquiring sample service processing data corresponding to the target bank outlet sample service; the sample service has a first identity;
determining the service processing time corresponding to the sample service according to the sample service processing data;
determining a second identifier of the sample service based on the service processing time;
and the acquisition unit is used for acquiring the to-be-processed service workload of the target banking outlet within n time periods of the target time according to the historical service processing data and the second identifier of the historical service.
In a possible implementation manner, the determining unit is further configured to determine, according to the target number of people, a labor saturation of the target banking outlet in the target time.
According to the technical scheme, the workload of the banking outlets is uniformly converted into standard time through the workload standardization method, and the labor resources of the banking outlets are conveniently distributed subsequently. On the basis, the labor force resource combination optimization algorithm based on the queuing theory realizes the automatic calculation of the labor force combination scheme of the bank outlets, not only meets the requirements of the workload of the to-be-processed business of the bank outlets, but also ensures that the waiting time of customers is appropriate. Compared with a manual resource allocation mode, the method has stronger objectivity and improves the utilization rate of the labor resources of the bank outlets.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic flowchart of a resource allocation method according to an embodiment of the present application;
fig. 2 is a schematic view of time-share service distribution at a banking outlet according to an embodiment of the present application;
fig. 3 is a schematic diagram of a banking outlet labor intensity according to an embodiment of the present disclosure;
fig. 4 is a diagram illustrating a customer waiting time proportion distribution diagram of a banking outlet according to an embodiment of the present application;
fig. 5 is a schematic flowchart of another resource allocation method according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a resource allocation apparatus according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In the related technology, the labor resources of the bank outlets are distributed mainly in a manual estimation mode, so that the subjectivity is high, the situations that the staff of the bank outlets are uneven in busy and idle states and uneven in busy and off seasons are easy to occur, the resource waste of the bank outlets is caused, or the waiting time of customers is too long, and the customer experience is influenced. In view of this, the embodiments of the present application provide a resource allocation method and a related apparatus, which ensure reasonable allocation of labor resources at banking outlets while avoiding long waiting time of customers, and improve resource utilization.
The resource allocation method provided by the embodiment of the application can be applied to resource allocation equipment with data processing capacity, such as terminal equipment or a server, and the method can be independently executed through the terminal equipment, can also be independently executed through the server, can also be applied to a network scene of communication between the terminal equipment and the server, and can be executed through the cooperation between the terminal equipment and the server. The terminal equipment can be a mobile phone, a desktop computer, a portable computer and the like; the server may be understood as an application server or a Web server, and in actual deployment, the server may be an independent server or a cluster server. The following describes an embodiment of the present application with a server as a resource allocation device.
Referring to fig. 1, fig. 1 is a schematic flowchart of a resource allocation method according to an embodiment of the present disclosure. As shown in fig. 1, the resource allocation method includes the following steps:
s101: and acquiring the total workload of the to-be-processed service of the target banking outlet in the target time.
In the process of processing business at a bank outlet, the business is generally measured in a quantitative mode, and the waiting time of a client is measured by taking time as a unit. Due to the inconsistency of the two metering modes, the relation between the workload of the bank outlets and the waiting time of the customers cannot be directly measured in the process of distributing the labor resources of the bank outlets, namely the business processing capacity of the bank outlets cannot be directly measured.
Therefore, the embodiment of the application provides a workload measurement standardization method, which includes the steps of firstly obtaining sample service processing data corresponding to a sample service of a target bank outlet, wherein the sample service has a first identifier. And then, determining the service processing time corresponding to the sample service according to the sample service processing data. Then, based on the service processing time, a second identifier of the sample service is determined. The first identification is used for identifying the mode that the sample traffic is measured in number, and the second identification is used for identifying the mode that the sample traffic is measured in time.
In the implementation process, sampling the historical service of a target bank outlet, taking the sampled historical service as a sample service, and acquiring sample service processing data corresponding to the sample service. Then, according to the sample service processing data, the service processing time of the sample service is counted, and the service processing time is used as a second identifier of the sample service. Where the traffic processing time identifies the time required to process the sample traffic, otherwise known as the standard workload time. For example, the standard workload time for transacting one-time card opening service is reduced to 10 minutes, and the standard workload time for transacting one-time card selling service is reduced to 5 minutes.
It should be noted that, in practical application, the service may also be classified first, a plurality of sample services of the same type are extracted, and an average value of service processing times of the plurality of sample services is taken as the second identifier of the service, which is not limited herein. Based on the above, the standard labor capacity and time consumption conversion table of all types of services of the target bank outlets can be obtained.
The above-mentioned method of sampling and averaging by defining the minimum timing unit (such as hour/minute/second, etc.) unifies the services with number (such as times/pieces/pens, etc.) as a unit into a plurality of timing units, thus realizing the unification of timing and counting measurement.
The pending service workload refers to the workload that is required to be spent on processing the pending service. On the basis of the uniform measurement, the to-be-processed service workload refers to the time spent on processing the to-be-processed service, for example, a teller needs 10 minutes for processing a card-opening service.
It will be appreciated that the allocation of banking outlet labour resources is generally arranged to schedule work at a future time, and the volume of traffic or the situation of business transactions at the future time cannot be directly determined. In view of the fact that the target bank outlets have certain regularity in the passenger flow volume and the business handling condition, the passenger flow volume and the business handling condition at the historical time are adopted to simulate the passenger flow volume and the business handling condition at the future time in the embodiment of the application.
In the application process, the historical service processing workload of the target banking outlet in the historical time is firstly acquired, then the historical time is divided to obtain n time periods, and the to-be-processed service workload corresponding to the target banking outlet in the n time periods included in the target time is acquired according to the total historical service processing workload and the n time periods. The historical time and the target time may be a time period before the target time, such as the day before, week before, etc. the target time. The duration of the time period may be set in advance, for example, T ═ 30 minutes, 1 hour, and the like.
Taking a scenario in which the target time is the business time of the bank outlet 9:00-16:00 as an example, the terminal device may first obtain the total workload of the to-be-processed business in the bank outlet 9:00-16:00, and if the duration T of the time period is 30 minutes, divide the target time and the total workload of the to-be-processed business according to the duration T of 30 minutes, to obtain 16 time periods with a duration of 30 minutes and the respective corresponding workload of the to-be-processed business, for example, the workload of the to-be-processed business corresponding to the 4 th time period 10:30-11:00 is 300 minutes.
In practical application, the n time periods may be numbered sequentially according to a time sequence, an ith time period is denoted as Ti, and a to-be-processed service workload corresponding to the ith time period Ti is denoted as Li. And obtaining a time consumption curve (Ti-Li) of the time-interval traffic of the bank outlets according to the ith time interval Ti and the corresponding to-be-processed traffic workload. Referring to fig. 2, fig. 2 shows the distribution of the to-be-processed service workload corresponding to 19 time periods with the target time of 8:00-17:30 and the time duration of 30 minutes.
The service handling condition in the historical time of the bank branch is used as the service handling condition in the target time, the service handling condition is converted into standard workload for use through a workload standardization method, and the service workload to be processed in each time period in the target time of the bank branch is used as basic data for subsequently distributing the labor resources of the bank branch.
S102: and determining whether the workload provided by the number N of the pending people of the target bank network point in the current time period can meet the waiting condition of a client or not according to the workload of the pending service of the target bank network point in the current time period.
In practical application, the time-consumption curve of the time-sharing standard service workload of the network point obtained in the step S101 is used as the passenger flow and service traversal condition of the network point within the target time, and the queuing theory in operation research is combined to serve first, and different labor resource combinations are calculated, that is, the meeting condition of the time-consumption curve of the time-sharing standard service workload of the network point when the number of undetermined persons (the number of the staffs waiting for working on duty) is N is calculated.
The queuing theory is a mathematical theory and a method for researching the random accumulation phenomenon of the system and the working process of a random service system, is also called a random service system theory, and is a branch of operational research in the field of data analysis. The queuing theory is to obtain statistical rules of data indexes (waiting time, queuing length, busy period length and the like) through statistical research on arrival and service time of service objects, and then to improve the structure of a service system or reorganize the served objects according to the rules, so that the service system can meet the requirements of the service objects, and the cost of an organization can be the most economic or certain indexes are the best. In the embodiment of the application, the bank outlets are required to ensure that the waiting time of customers is short and the labor resources of banks are fully utilized.
In a specific application process, initializing the number N of currently pending persons to be 1, wherein the service workload TB to be processed in the current time period is the residual service workload TB to be processed in the i-1 time period(i-1)And the sum of the traffic to be processed Li in the ith time period, namely TB ═ TB(i-1)+ Li. The value range of i is 1,2, …, and n, values are sequentially taken from i-1, when i-1, the traffic to be processed TB in the current time period is the traffic to be processed in the 1 st time period, that is, TB-L1.
The workload B of the undetermined number N provided in the current time period is N Ti, that is, the N tellers of the target bank network can provide service with the time of N Ti in the current time, or the workload that the N tellers can process in the time period Ti is N Ti. The customer waiting condition can be preset according to the actual service condition and is used for judging whether the current labor resource allocation scheme can meet the service quantity requirement or not and enabling the customer waiting time to be appropriate.
In one possible implementation manner, a first ratio R, that is, R ═ TB/B, between the pending business workload TB of the target banking outlet in the current time period and the workload B provided by the pending number N of people of the target banking outlet in the current time period may be used. And determining a second ratio Ra of the maximum waiting time t of the client to the corresponding time duration Ti of the current time period, namely Ra is t/Ti. It is thus possible to determine whether R > Ra is established by determining whether the first ratio is less than or equal to the second ratio. If not, the following S103 is executed, and if so, the following S104 is executed.
S103: if not, adjusting the undetermined number N to be N + k, and re-executing the step of determining whether the workload provided by the undetermined number N of the target bank website in the current time period can meet the customer waiting condition according to the workload of the service to be processed of the target bank website in the current time period based on the adjusted undetermined number N.
If the number of the undetermined people is N, the work capacity provided in the current time period cannot meet the customer waiting condition, and the customer waiting time is longer when only N teller numbers are distributed in the current time period, so that the labor resource cost and the customer satisfaction of the bank outlets cannot be considered. Therefore, the number of undetermined persons N needs to be adjusted. In the actual process of adjusting N, the number of undetermined persons N can be adjusted to be N + k, wherein k is an integer greater than or equal to 1. After the number N of undetermined persons is adjusted, the above S102 is executed again based on the adjusted number N of undetermined persons.
S104: if yes, determining whether the i is smaller than n.
If the workload provided by the number N of the pending people in the current time period can meet the customer waiting condition, the number N of the pending people can finish processing the workload of the service to be processed corresponding to the current time period in the current time period on the premise that the customer waiting time is appropriate. At this time, whether i is smaller than N in such a case is judged, that is, whether the currently pending number N can process the total workload of the pending business within the target time under the condition that the customer waiting condition is satisfied is determined. If so, the following S105 is performed. If not, the following S106 is executed.
S105: if yes, adjusting i to be i +1, re-executing the workload of the service to be processed in the current time period according to the target bank website, and determining whether the workload provided by the number N of the people to be determined in the current time period by the target bank website can meet the customer waiting condition.
If i is less than N, it indicates that the workload of the service to be processed corresponding to N time periods in the target time period has not been completely determined, so that i is adjusted to i +1, that is, whether the workload provided by the current number N of people to be determined can meet the workload of the service to be processed corresponding to the next time period is continuously determined.
S106: if not, determining that the number of the target people is the number of the target people required by the target bank outlets for processing the workload of the service to be processed in the target time.
If i is not less than N, that is, when i is equal to N, it indicates that the total workload of the service to be processed corresponding to the target time period is sequentially judged and completed according to the time period, and the currently number of people to be processed N can process the total workload of the service to be processed within the target time, so that it can be determined that the currently number of people to be processed N is the target number of people required by the target bank website to process the total workload of the service to be processed within the target time.
In practical application, the labor saturation and the customer waiting time proportion of the target bank outlets in the target time can be determined according to the determined target number. Wherein the labor saturation identifies a labor resource utilization rate of the target banking outlet for distributing the target number of people for the target time. As shown in fig. 3 and fig. 4, fig. 3 is a schematic diagram of a banking outlet labor intensity according to an embodiment of the present disclosure, and fig. 4 is a distribution diagram of a customer waiting time ratio of a banking outlet according to an embodiment of the present disclosure.
The above-mentioned customer waiting condition according to business settlement, judge whether the present undetermined person can already meet the traffic demand, can make the customer wait time suitable again. If the demand is met, the next time period is continuously considered, if the demand cannot be met, the undetermined number N needs to be increased, namely the labor resource distribution scheme needs to be adjusted until the optimal labor resource distribution scheme, namely the target number N, is found, the demand of the business volume of the bank outlets in the target time can be met, the waiting time of customers is shortest, the labor intensity can be saturated relatively, and the balance between the labor cost and the customer satisfaction degree is strived to be achieved.
For better understanding, the resource allocation method provided in the embodiment of the present application is described below with reference to fig. 5, and the resource allocation method includes the following steps:
s501: and generating a time consumption conversion table of the standard workload of the banking outlet.
As shown in Step1_1-Step1_4 in FIG. 5, historical business processing data of historical business of banking outlets is obtained, and a business workload meter time unit (hour/minute/second) is determined. And counting the time-counting units consumed by processing the piece counting service by sampling the piece counting service, and defining the average value of the sampling result as the conversion rate of the workload standard time of the piece counting service. Based on the calculation, the conversion rate of each type of piece-counting service is calculated, and a standard workload time consumption conversion table is generated.
S502: and generating a standard traffic time consumption curve (Ti-Li) of the banking outlet in the time period.
As shown in Step2 in fig. 5, historical service processing data of the previous working time of the banking outlet one day is obtained and divided into n time periods, the service processing condition of each time period Ti is converted into standard workload time Li through a standard workload time conversion table, and a time-sharing standard workload time curve of the banking outlet is generated.
S503: and outputting the number N of the teller persons at the bank outlets and the corresponding labor intensity.
As shown in STEP3_1-STEP3_6 in fig. 5, the current teller number N is initialized to 1, the pending service standard workload time TB is 0, and the current ith time period i is 1, which is N time periods. And then, calculating the total time consumption TB of the to-be-processed service standard workload in the current time period i as TB + Li according to the time consumption curve of the network point time-sharing standard service workload. And when the number of the tellers is calculated to be N, the maximum traffic B which can be completed in each time period Ti is N Ti. And calculating the total amount of the to-be-processed service in the current time period Ti and the maximum ratio R of the to-be-processed service to the maximum service which can be processed, which is TB/B. And judging whether R meets the customer waiting condition, namely judging whether R is larger than Ra, wherein Ra is the ratio of the maximum waiting time of the customer to each time period Ti. If not, update N to N +1, and execute STEP3_1 again. If yes, calculating the total TB of the rest to-be-processed service as TB-B, and judging whether i is smaller than n at the moment. If yes, i +1 is updated, and STEP3_1 is executed again. And if not, outputting the number N of the current tellers, the corresponding labor intensity, the customer waiting time distribution and the like.
The resource allocation method provided by the embodiment uniformly converts the service workload of the banking outlet into standard service workload by the workload standardization method, and facilitates subsequent allocation of the labor resources of the banking outlet. On the basis, the labor force resource combination optimization algorithm based on the queuing theory realizes the automatic calculation of the labor force combination scheme of the bank outlets, not only meets the requirements of the workload of the to-be-processed business of the bank outlets, but also ensures that the waiting time of customers is appropriate. Compared with a manual resource allocation mode, the method has the advantages of stronger objectivity, higher speed and better effect, and can accurately estimate the business volume of the bank outlets, thereby estimating the combined allocation of the labor resources more accurately.
For the resource allocation method provided in the foregoing embodiment, an embodiment of the present application further provides a resource allocation apparatus.
Referring to fig. 6, fig. 6 is a schematic structural diagram of a resource allocation apparatus according to an embodiment of the present application. As shown in fig. 6, the resource allocation apparatus 600 includes an obtaining unit 601, a determining unit 602, and an adjusting unit 603:
the acquiring unit 601 is configured to acquire a total workload of a to-be-processed service of a target banking outlet in a target time; the total workload of the service to be processed comprises the workload of the service to be processed corresponding to n time periods;
the determining unit 602 is configured to determine, according to the workload of the service to be processed in the current time period at the target banking outlet, whether the workload provided by the number N of people to be determined at the target banking outlet in the current time period can meet a customer waiting condition; the traffic to be processed in the current time period is the sum of the remaining traffic to be processed in the ith-1 time period and the traffic to be processed in the ith time period; the initial value of i is 1; the initial value of N is 1; if not, triggering the adjusting unit 603; if yes, determining whether the i is smaller than n; if yes, triggering the adjusting unit 603, and if not, determining that the number of people to be determined is a target number of people required by the target bank branch for processing the total workload of the business to be processed in the target time;
the adjusting unit 603 is configured to adjust the undetermined number N to be N + k if the customer waiting condition is not satisfied, and trigger the determining unit based on the adjusted undetermined number N; k is greater than or equal to 1;
the adjusting unit 603 is further configured to adjust i to i +1 and trigger the determining unit if i is smaller than n.
In a possible implementation manner, the determining unit 602 is configured to:
according to a first ratio of the workload of the service to be processed of the target bank outlet in the current time period to the workload provided by the number N of the people to be determined of the target bank outlet in the current time period;
determining a second ratio of the maximum waiting time of the client to the corresponding time length of the current time period;
determining whether the first ratio is less than or equal to the second ratio.
In a possible implementation manner, the obtaining unit 601 is further configured to obtain a total historical business processing workload of the target banking outlet in a historical time;
the obtaining unit 601 is configured to divide the historical time to obtain n time periods;
and acquiring the respective corresponding to-be-processed business workload of the target banking outlet in n time periods included in the target time according to the historical business processing total workload.
In a possible implementation manner, the obtaining unit 601 is further configured to:
acquiring sample service processing data corresponding to the target bank outlet sample service; the sample service has a first identity;
determining the service processing time corresponding to the sample service according to the sample service processing data;
determining a second identifier of the sample service based on the service processing time;
the obtaining unit 601 is configured to obtain, according to the historical service processing data and the second identifier of the historical service, to-be-processed service workloads corresponding to the target banking node in n time periods of the target time.
In a possible implementation manner, the determining unit 602 is further configured to determine, according to the target number of people, a labor saturation of the target banking outlet in the target time.
The resource allocation device provided by the embodiment uniformly converts the service workload of the banking outlet into standard service workload by the workload standardization method, and is convenient for subsequently allocating the labor resources of the banking outlet. On the basis, the labor force resource combination optimization algorithm based on the queuing theory realizes the automatic calculation of the labor force combination scheme of the bank outlets, not only meets the requirements of the workload of the to-be-processed business of the bank outlets, but also ensures that the waiting time of customers is appropriate. Compared with a manual resource allocation mode, the method has stronger objectivity and improves the utilization rate of the labor resources of the bank outlets.
An embodiment of the present application further provides a computer device, where the computer device includes a memory and a processor:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute the resource allocation method according to the instruction in the program code.
The embodiment of the present application further provides a computer-readable storage medium, where the computer-readable storage medium is used for storing a computer program, and the computer program is used for executing the resource allocation method described in the foregoing embodiment.
It will be understood by those skilled in the art that all or part of the steps of implementing the above method embodiments may be implemented by hardware associated with program instructions, and that the program may be stored in a computer readable storage medium, and when executed, performs the steps including the above method embodiments; and the aforementioned storage medium may be at least one of the following media: various media that can store program codes, such as read-only memory (ROM), RAM, magnetic disk, or optical disk.
It should be noted that, in the present specification, all the embodiments are described in a progressive manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus and system embodiments, since they are substantially similar to the method embodiments, they are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for related points. The above-described embodiments of the apparatus and system are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
The above description is only one specific embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method for resource allocation, the method comprising:
acquiring the total workload of the to-be-processed service of a target bank outlet in target time; the total workload of the service to be processed comprises the workload of the service to be processed corresponding to n time periods;
determining whether the workload provided by the number N of the pending people of the target bank network point in the current time period can meet the customer waiting condition according to the workload of the pending business of the target bank network point in the current time period; the traffic to be processed in the current time period is the sum of the remaining traffic to be processed in the ith-1 time period and the traffic to be processed in the ith time period; the initial value of i is 1; the initial value of N is 1;
if not, adjusting the undetermined number N to be N + k, and re-executing the to-be-processed service workload according to the target bank website in the current time period based on the adjusted undetermined number N to determine whether the workload provided by the undetermined number N of the target bank website in the current time period can meet the customer waiting condition; k is greater than or equal to 1;
if yes, determining whether the i is smaller than n;
if not, adjusting i to be i +1, re-executing the workload of the service to be processed in the current time period according to the target bank website, and determining whether the workload provided by the number N of the people to be determined in the current time period by the target bank website can meet the customer waiting condition;
if so, determining the number of the target people required by the target bank branch to process the total workload of the business to be processed in the target time.
2. The method as claimed in claim 1, wherein said determining whether the workload provided by the pending number N of the target banking site in the current time period can satisfy the customer waiting condition according to the pending business workload of the target banking site in the current time period comprises:
according to a first ratio of the workload of the service to be processed of the target bank outlet in the current time period to the workload provided by the number N of the people to be determined of the target bank outlet in the current time period;
determining a second ratio of the maximum waiting time of the client to the corresponding time length of the current time period;
determining whether the first ratio is less than or equal to the second ratio.
3. The method of claim 1, further comprising:
acquiring the total workload of historical business processing of the target bank network point in historical time;
the acquiring the total workload of the to-be-processed service of the target banking outlet in the target time comprises the following steps:
dividing the historical time to obtain n time periods;
and acquiring the respective corresponding to-be-processed business workload of the target banking outlet in n time periods included in the target time according to the historical business processing total workload.
4. The method of claim 3, further comprising:
acquiring sample service processing data corresponding to the target bank outlet sample service; the sample service has a first identity;
determining the service processing time corresponding to the sample service according to the sample service processing data;
determining a second identifier of the sample service based on the service processing time;
the acquiring, according to the historical service processing data, the to-be-processed service workload corresponding to each of the target banking outlets in the n time periods of the target time includes:
and acquiring the respective corresponding to-be-processed service workload of the target banking outlet in n time periods of the target time according to the historical service processing data and the second identifier of the historical service.
5. The method of claim 1, further comprising:
and determining the labor force saturation of the target bank outlets in the target time according to the target number of people.
6. A resource allocation apparatus, characterized in that the apparatus comprises an obtaining unit, a determining unit and an adjusting unit:
the acquisition unit is used for acquiring the total workload of the to-be-processed business of the target bank branch in the target time; the total workload of the service to be processed comprises the workload of the service to be processed corresponding to n time periods;
the determining unit is used for determining whether the workload provided by the number N of the undetermined persons of the target bank website in the current time period can meet the customer waiting condition according to the workload of the service to be processed of the target bank website in the current time period; the traffic to be processed in the current time period is the sum of the remaining traffic to be processed in the ith-1 time period and the traffic to be processed in the ith time period; the initial value of i is 1; the initial value of N is 1; if not, triggering the adjusting unit; if yes, determining whether the i is smaller than n; if yes, triggering the adjusting unit, and if not, determining that the number of people to be determined is the target number of people required by the target bank branch for processing the total workload of the business to be processed in the target time;
the adjusting unit is used for adjusting the number N of undetermined persons to be N + k if the customer waiting condition is not met, and triggering the determining unit based on the adjusted number N of undetermined persons; k is greater than or equal to 1;
and the adjusting unit is further configured to adjust i to i +1 and trigger the determining unit if i is smaller than n.
7. The apparatus of claim 6, wherein the determining unit is configured to:
according to a first ratio of the workload of the service to be processed of the target bank outlet in the current time period to the workload provided by the number N of the people to be determined of the target bank outlet in the current time period;
determining a second ratio of the maximum waiting time of the client to the corresponding time length of the current time period;
determining whether the first ratio is less than or equal to the second ratio.
8. The apparatus according to claim 6, wherein the obtaining unit is further configured to obtain a historical total workload of the business process of the target banking site in a historical time;
the acquisition unit is used for dividing the historical time to obtain n time periods;
and acquiring the respective corresponding to-be-processed business workload of the target banking outlet in n time periods included in the target time according to the historical business processing total workload.
9. The apparatus of claim 8, wherein the obtaining unit is further configured to:
acquiring sample service processing data corresponding to the target bank outlet sample service; the sample service has a first identity;
determining the service processing time corresponding to the sample service according to the sample service processing data;
determining a second identifier of the sample service based on the service processing time;
and the acquisition unit is used for acquiring the to-be-processed service workload of the target banking outlet within n time periods of the target time according to the historical service processing data and the second identifier of the historical service.
10. The apparatus of claim 6, wherein the determining unit is further configured to determine the labor saturation of the target banking outlet at the target time according to the target number of people.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113222377A (en) * | 2021-04-29 | 2021-08-06 | 上海天好信息技术股份有限公司 | Online artificial seat resource dynamic scheduling method based on real-time audio and video technology |
| CN113469523A (en) * | 2021-06-30 | 2021-10-01 | 上海浦东发展银行股份有限公司 | Teller scheduling information acquisition method and device, electronic equipment and storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111967785A (en) * | 2020-08-26 | 2020-11-20 | 中国银行股份有限公司 | Optimization processing method and device for business handling of bank outlets |
| CN112052975A (en) * | 2020-09-29 | 2020-12-08 | 中国银行股份有限公司 | Bank outlet personnel scheduling method and device |
-
2020
- 2020-12-17 CN CN202011494856.0A patent/CN112465402A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111967785A (en) * | 2020-08-26 | 2020-11-20 | 中国银行股份有限公司 | Optimization processing method and device for business handling of bank outlets |
| CN112052975A (en) * | 2020-09-29 | 2020-12-08 | 中国银行股份有限公司 | Bank outlet personnel scheduling method and device |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113222377A (en) * | 2021-04-29 | 2021-08-06 | 上海天好信息技术股份有限公司 | Online artificial seat resource dynamic scheduling method based on real-time audio and video technology |
| CN113469523A (en) * | 2021-06-30 | 2021-10-01 | 上海浦东发展银行股份有限公司 | Teller scheduling information acquisition method and device, electronic equipment and storage medium |
| CN113469523B (en) * | 2021-06-30 | 2022-12-30 | 上海浦东发展银行股份有限公司 | Teller scheduling information acquisition method and device, electronic equipment and storage medium |
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