CN110929966A - Customer service real-time scheduling method, computer-readable storage medium and electronic device - Google Patents
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Abstract
The invention discloses a customer service real-time scheduling method, a nonvolatile computer readable storage medium and electronic equipment, comprising: partitioning the customer service queue according to the pressure state of the customer service; determining a pressure sequencing value of the customer service in the customer service queue according to the pressure value of the customer service, and inserting the customer service into the customer service queue according to the pressure sequencing value; dividing each subarea in the customer service queue into a first subarea and a second subarea, putting all the customer services which are not allocated to the customers under the subarea into the second subarea, and transferring the customer services which are allocated to the customers in the second subarea and hope to be continuously allocated to the customers from the second subarea to the first subarea. Based on the same online customer service queue, the invention adopts two-stage partition strategies of pressure partition sequencing, first sub-partition sequencing, second sub-partition sequencing, concurrent sequencing in the same partition and the like, and an offset sequencing value under concurrent sequencing in the same partition, thereby improving the customer service quality, the service efficiency and the data consistency, and improving the capability of processing concurrent scheduling.
Description
Technical Field
The invention relates to the technical field of computers and internet, in particular to a customer service real-time scheduling method, a computer readable storage medium and electronic equipment.
Background
At present, in the customer service under the internet environment, the online customer service is one of the important links. Various schedules between customer services are often required for a better experience for the user. The common method of customer service scheduling is that the customer services under the same group are usually placed in the same scheduling queue, when the customer arrives, an appropriate customer service is selected from the scheduling queue and allocated to the customer, and this process is the scheduling of the customer service.
FIG. 1 illustrates a general real-time dispatch diagram of customer service pressure status. As shown in FIG. 1, the customer service events are generally divided into: the system comprises customer service behaviors such as login, logout, state change, heartbeat, seat change and the like, wherein a seat is a seat unit for serving a customer. The real-time pressure scheduling algorithm adjusts the operations of adding, changing and deleting the order of the customer service in the customer service queue (namely the scheduling queue) according to the customer service events.
In order to bring better experience to customers and improve the efficiency of customer service, the scheduling performance becomes more and more refined and intelligent. The long-term online customer service online data analysis shows that the performance behaviors of customer service under different pressure states are different. Generally, traditional customer service scheduling only performs scheduling according to the number of customers to be served, and generally, fewer customers to be served are allocated preferentially; the scheduling is an evenly distributed scheduling strategy, and no matter in which pressure state the customer service is, the scheduling strategy is adopted, which is not suitable in many scenes, and the situation of wasting customer service resources exists. For example: one merchant has 10 customer services, the capacity of receiving the customers simultaneously is 10 customers, and in the service valley period, 10 customers visit the merchant totally, under the strategy of average dispatching, each customer service can be distributed to only one customer, thus causing waste of customer service resources. It is also unreasonable if other customer services log off by manually hanging up or waiting for the customer to be served, because in many cases the customer service does not know whether the subsequent customer traffic will rise, and once a large number of customers are suddenly flooded, a bad situation will result in no customer service. Therefore, there is a need for a scheduling policy to assign customers to a portion of customer services and to ensure that other customer services remain online, which can engage in mail tracking, business promotion learning, and other tasks until the customers are reassigned.
The above scenario shows that it is very necessary to adopt different real-time scheduling strategies for different customer service pressure states. For example: when the customer service is in the idle state, a plurality of customers can be continuously distributed, so that the customer service can quickly enter the service state; when the customer service is in a saturated state, the customers are only intermittently distributed to the customer service one by one, so that the service quality and the pressure born by the customer service are better choices; when the customer service is in the explosive state, the customer is not distributed to the customer service, but other operations such as leaving a message or queuing can be carried out, otherwise, the service quality of the customer service is difficult to guarantee.
Different scheduling strategies are adopted for different customer service pressure states, so that the service quality of customers can be improved better, and the service of customer services can be more efficient, but more challenges are faced on the aspects of performance and data consistency under the condition of online distribution under high concurrency originally. And the pressure state of the customer service itself is dynamically changed, which also makes the real-time scheduling scenario more complicated.
The existing customer service real-time scheduling mechanism generally has two types: aggregate screening methods and multiple order queuing methods. (1) Collective screening method
The set screening method does not process customer service events and directly puts customer service in an unordered set.
By adopting the set screening method, the performance of customer service entering the set is very high. When the customer comes, the customer service meeting the customer is screened out from the set, the problem of efficiency reduction can not occur under the condition that the number of the customer service persons is small, but the efficiency is low under the condition that the number of the customer service persons is large, and the customer service meeting the corresponding customer can be screened out only through comparing the customer service persons one by one.
Therefore, there is a certain improvement to the set filtering method, and the improved set filtering method is to put customer service into a plurality of sets according to different states, which can bring partial improvement of performance, but essentially needs to compare in classified subsets, so the improved set filtering method still has poor performance.
(2) Multi-order queue method
The main idea of the multi-order queue method is to classify the pressure state of customer service and place the customer service in several different order queues when the customer service event is triggered. Thus, when a customer arrives, the customer goes through several sequence queues according to a certain priority to find the customer service suitable for the customer. Meanwhile, aiming at different pressure state queues, the multi-sequence queue method can adopt different scheduling algorithm strategies. This mechanism is temporary at a customer service event: the customer service calculates the ordering value of the customer service in the sequence queue well under a scheduling algorithm and then inserts the customer service into the proper position in the sequence queue, which is slightly time-consuming, but the performance is still good under a storage structure of a distributed cache such as SortedSet of Redis.
The problem with the multiple order queue approach is that: if the customer service events are more densely concurrent, the customer service needs to be switched in different sequence queues, so that the consistency and the concurrency performance of data are difficult to ensure, the complexity is increased, and the continuity and the reliability are difficult to ensure in a continuous iterative production environment.
Disclosure of Invention
In view of this, the present invention provides a method, a computer-readable storage medium, and an electronic device for real-time customer service scheduling, so as to achieve efficient performance of real-time customer service scheduling, reduce complexity of a scheduling manner, and ensure consistency of state data.
The technical scheme of the invention is realized as follows:
a customer service real-time scheduling method comprises the following steps:
partitioning the customer service queue according to the pressure state of the customer service;
determining a pressure sorting value of the customer service in the customer service queue according to the pressure value of the customer service, and inserting the customer service into the customer service queue according to the pressure sorting value;
dividing each subarea in the customer service queue into a first subarea and a second subarea, putting all the customer services which are not allocated to the customers under the subarea into the second subarea, and transferring the customer services which are allocated to the customers in the second subarea and hope to be continuously allocated to the customers from the second subarea to the first subarea.
Further, the step of transferring customer service in the second sub-area, which is allocated to the customer and is desired to be continuously allocated to the customer, from the second sub-area to the first sub-area comprises:
adjusting a pressure ranking value of the customer service with a time-shift factor to shift the customer compliance with the second sub-zone into the first sub-zone.
Further, the pressure ranking values of customer service in the second sub-zone are:
score1＝Na+[(ci-ca)/(cb-ca)]×(Nb-Na)
wherein, score1A pressure ranking value, N, for customer service in the second subregionaA first boundary value, N, for the second subregion and the subregion to which the first subregion belongsbA second boundary value for the second subregion and the subregion to which the first subregion belongs, caTo correspond to NaPressure value of cbTo correspond to NbPressure value of ciA pressure value for any customer service in the second sub-zone, wherein Nb>Na，cb>ci>ca，cb、caAnd ciAre all integers.
Further, the pressure ranking values of customer service in the first sub-zone are:
score2＝Na+[offset/(cb-ca)]×(Nb-Na)
wherein, score2Is at the firstPressure ranking value, N, of customer service in sub-zoneaA first boundary value, N, for the second subregion and the subregion to which the first subregion belongsbA second boundary value for the second subregion and the subregion to which the first subregion belongs, caTo correspond to NaPressure value of cbTo correspond to NbIs the time offset factor, which is the ratio of the timestamp when the customer service was distributed to the customer to the maximum value of the long integer, where N isb>Na，cb>ca，cbAnd caAre integers.
Further, for a plurality of customer services with the same pressure ranking value in the second sub-area, the pressure ranking values among the customer services are finely adjusted by using a time offset factor, and the customer services are ranked according to the finely adjusted pressure ranking values.
Further, the pressure ranking values after customer service fine adjustment with the same pressure ranking value in the second sub-area are as follows:
score3＝Na+[(ci-ca+offset)/(cb-ca)]×(Nb-Na)
wherein, score3For said fine-tuned pressure sequencing value, NaA first boundary value, N, for the second subregion and the subregion to which the first subregion belongsbA second boundary value for the second subregion and the subregion to which the first subregion belongs, caTo correspond to NaPressure value of cbTo correspond to NbPressure value of ciThe offset is the time offset factor which is the ratio of the timestamp of any customer service inserted into the customer service queue to the maximum value of the long integer, wherein N is the pressure value of any customer service in the second subareab>Na，cb>ci>ca，cb、caAnd ciAre all integers.
Further, the partitions include a free partition, an active partition, a saturated partition, and a burst partition.
Further, when any customer service event comes, the customer service pressure is evaluated to obtain the pressure value, the pressure ranking value is further determined, and the customer service is inserted into the customer service queue according to the pressure ranking value.
A non-transitory computer readable storage medium storing instructions that, when executed by a processor, cause the processor to perform the steps in the customer service real-time scheduling method of any one of the above.
An electronic device, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to cause the at least one processor to perform steps in a real-time customer service dispatch method as described in any one of the above.
According to the scheme, the customer service real-time scheduling method, the nonvolatile computer readable storage medium and the electronic device have the advantages that two-stage partition strategies such as pressure partition sequencing, first sub-area sequencing, second sub-area sequencing, same-area concurrent sequencing and the like are adopted on the basis of the same online customer service queue, the customer service quality and the service efficiency are improved, and the consistency of the states of dispatches is improved. Meanwhile, the invention also provides an offset sorting value under the condition of concurrent in the same region, thereby improving the capability of processing concurrent scheduling. In addition, the invention has no redundant hypothesis and constraint condition, thereby having strong expandability, being capable of adapting to various scheduling scenes, and being capable of greatly improving the performance by applying the technical scheme of the invention to the distributed cache queue.
Drawings
FIG. 1 is a schematic diagram of a real-time dispatch of a customer service pressure status;
FIG. 2 is a schematic diagram illustrating steps of a method for real-time scheduling of customer services according to an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating a pressure partition ordering in a real-time customer service scheduling method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a head allocation subregion in an embodiment of the present invention;
FIG. 5 is a diagram illustrating concurrent sorting of zones according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device in an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and examples.
Fig. 1 shows a real-time scheduling process of a customer service pressure state, as shown in fig. 1, as long as there is a customer service event, a real-time pressure scheduling algorithm is triggered, and a result of the real-time pressure scheduling algorithm determines one of adding, changing and deleting a customer service in a customer service queue. In order to obtain better experience for customers, customer service needs to be sorted according to pressure from weak (free side) to strong (explosion side), and the distribution principle is generally distributed from weak to strong in sequence. In order to improve the efficiency of customer service, it is necessary to classify the pressure states of customer service, for example, in fig. 1, the pressure states of customer service are divided into four states, i.e., idle, saturated, and explosive states. When a customer enters, directly taking out a customer service from the head (the free side) of the queue for distribution, if the distribution condition is not met, updating the pressure state of the customer service by adopting a pressure scheduling algorithm again, so that the customer service with the pressure state updated is placed at a proper position of the online queue, and taking out a new customer service from the head of the queue again for distribution, and circulating until the distribution is successful. When the customer service distribution is successful, the pressure state of the customer service also needs to be updated and put in a proper position of an online queue.
From the above process, it can be seen that the real-time pressure scheduling mechanism is very critical. Determines the quality and efficiency of customer distribution. The classification sorting-based customer service real-time scheduling method provided by the following embodiments of the invention mainly comprises three key parts, namely pressure logic partition sorting, head seat allocation sub-partition sorting and same-partition concurrent sorting, and the embodiments of the invention are explained in detail below.
As shown in fig. 2, the method for real-time customer service scheduling provided in the embodiment of the present invention mainly includes:
and 3, splitting each partition in the customer service queue into a first sub-partition and a second sub-partition, putting all the customer services which are not distributed to the customers under the partition into the second sub-partition, and transferring the customer services which are distributed to the customers in the second sub-partition and hope to be continuously distributed to the customers from the second sub-partition to the first sub-partition.
Although the above steps are denoted by reference numerals, the above steps are not necessarily divided into the order of execution before and after the steps.
In a specific embodiment, the step of transferring the customer service in the second sub-area, which is allocated to the customer and is desired to be continuously allocated to the customer, from the second sub-area to the first sub-area in step 3 comprises:
and adjusting the pressure sequencing value of the customer service by using the time offset factor so as to transfer the customer compliance second sub-area into the first sub-area.
In one embodiment, the pressure ranking values for customer service in the second sub-zone are:
score1＝Na+[(ci-ca)/(cb-ca)]×(Nb-Na)
wherein, score1Pressure ranking value, N, for customer service in the second subregionaIs the first boundary value, N, of the second subregion and the subregion to which the first subregion belongsbA second boundary value for the second subregion and the subregion to which the first subregion belongs, caTo correspond to NaPressure value of cbTo correspond to NbPressure value of ciIs a secondPressure value of any customer service in the subarea, wherein Nb>Na，cb>ci>ca，cb、caAnd ciAre all integers.
In one embodiment, the pressure ranking values for customer service in the first sub-zone are:
score2＝Na+[offset/(cb-ca)]×(Nb-Na)
wherein, score2Ranking value of pressure for customer service in first subregion, NaIs the first boundary value, N, of the second subregion and the subregion to which the first subregion belongsbA second boundary value for the second subregion and the subregion to which the first subregion belongs, caTo correspond to NaPressure value of cbTo correspond to NbIs a time offset factor, which is the ratio of the time stamp of the service when it is distributed to the customer to the maximum value of the long integer, where N isb>Na，cb>ca，cbAnd caAre integers.
In a specific embodiment, for a plurality of customer services with the same pressure ranking value in the second sub-area, the pressure ranking value among the plurality of customer services is finely adjusted by using a time offset factor, and the plurality of customer services are ranked according to the finely adjusted pressure ranking value. Further, the plurality of customer service fine-tuned pressure ranking values with the same pressure ranking value in the second sub-zone are:
score3＝Na+[(ci-ca+offset)/(cb-ca)]×(Nb-Na)
wherein, score3For the fine-tuned pressure-sequencing value, NaIs the first boundary value, N, of the second subregion and the subregion to which the first subregion belongsbA second boundary value for the second subregion and the subregion to which the first subregion belongs, caTo correspond to NaPressure value of cbTo correspond to NbPressure value of ciThe pressure value of any customer service in the second sub-area, offset is a time offset factor, timeThe offset factor is the ratio of the timestamp of any service inserted into the service queue to the maximum value of the long integer, where N isb>Na，cb>ci>ca，cb、caAnd ciAre all integers.
In one particular embodiment, the partitioning of the customer service queue includes a free partition, an active partition, a saturated partition, and a burst partition.
In the method for real-time customer service scheduling of the embodiment of the invention, the evaluation and scheduling of the customer service pressure are carried out in real time, and specifically, the embodiment of the invention comprises the following steps: when any customer service event comes, the pressure of the customer service is evaluated to obtain the pressure value of the customer service, and then the pressure ranking value of the customer service is determined and the customer service is inserted into the customer service queue according to the pressure ranking value. Due to the real-time triggering of the customer service event, the method provided by the embodiment of the invention can evaluate and schedule the customer service pressure in real time.
The customer service real-time scheduling method provided by the embodiment of the invention is mainly embodied in three key parts of pressure logic partition sequencing, head seat allocation sub-partition sequencing and same-partition concurrent sequencing.
(1) Pressure logical partition ordering
In order to enable customer services in the same customer service queue to adopt different allocation strategies under different pressure states, the pressure value partitioning of the customer service queue is required, and the technical scheme of the invention provides a strategy for logically partitioning the pressure values, which comprises the following specific steps:
1) status partitioning
Partitioning the customer service state, comprising: free partition [0, N1) Active partition [ N1,N2) Saturated partition [ N ]2,N3) Burst wire partition [ N ]3-, in which N is1<N2<N3. The pressure ranking value placed in the customer service queue must belong to one of these partitions at the arrival of any customer service event. As shown in fig. 3.
2) And mapping the pressure value. When any customer service event comes, the pressure evaluation of the customer service is performed by using methods such as rules, AI algorithm classification and the like, wherein the method for performing the pressure evaluation on the customer service can be realized by using methods existing in the field, and is not described herein again.
The customer service pressure value is divided according to the number of customers to be served. In this example, the rules specify a relationship between customer number and pressure value as: idle [0, c1) Active [ c ]1,c2) Saturated [ c ]2,c3) Explosion wire [ c ]3-, in which c1、c2、c3Each represents a customer number, and c1<c2<c3，c1、c2、c3Are integers. By ciIndicating the number of customers to be served by a customer service, when a customer service event is triggered, assuming that the number of customers to be served by the customer service is c2<ci<c3Then it can be known from the rules that the customer service is in a saturated state. Therefore, the calculation formula of the pressure ranking value of customer service in the saturated state is as follows:
score1＝N2+[(ci-c2)/(c3-c2)]×(N3-N2)。
the pressure sequencing value calculation mode in other states is the same, and only the corresponding state interval value is adopted in the partitioned interval, and the description is omitted here.
3) And inserting the customer service into a customer service queue according to the pressure sorting value.
The state partition design of the customer service queue can make all the customer services in the corresponding state partition, but in fact, the customer services are still in the same sequencing queue, and only the customer services in the queue are clustered according to the respective pressure states.
(2) First position sub-area ordering
If within a certain status zone, it is often desirable for customers to be served continuously in order to achieve a better scheduling effect. Then, in the embodiment of the present invention, the same state partition is split twice, and is divided into a head sub-area (i.e., a first sub-area) and a normal sub-area (i.e., a second sub-area). When all the customer services in the state subarea are not distributed, all the customer services are in the common subarea, and only when a certain customer service is distributed to the customers and continuous distribution of the customers is desired, the customer service preferentially enters the first subarea. In the embodiment of the present invention, between two partitions (a first partition and a second partition) split in the same state partition, the customer service located in the first partition has a high priority assignment right relative to the customer service in the second partition, so in the embodiment of the present invention, the first sub-partition may be referred to as a head sub-partition, and the second sub-partition may be referred to as a normal sub-partition, to indicate that the customer service located in the head partition has a high priority assignment right relative to the customer service in the normal partition.
For example, for a customer service desiring x (0< x < c1) customers consecutively assigned in the free partition, the service is placed in the head allocation sub-area until the service leaves the free partition or the x customers desiring consecutive assignments are not reached in the service, as shown in fig. 4.
However, in a real scene, it takes a certain amount of time to take out one service from the service queue and allocate it. In order to improve the efficiency of concurrent processing, a plurality of customer services often enter the head subarea simultaneously at the same time. Therefore, the continuous allocation in the embodiment of the present invention is only relative continuous allocation, and the customer allocation of the customer service B is not absolutely performed as after the customer service a is continuously allocated to X customers, but multiple customer services can be allowed to enter the head sub-area at the same time to improve the concurrency performance.
In the embodiment of the present invention, the ordering rule in the head sub-area is based on a time sequence FIFO (First input First Output) for ordering. In order to ensure that customer service in the head sub-area is forever ranked in front of the ordinary sub-area, the ordering is based on the time factor only. In the embodiment of the invention, the sequencing of customer service in the head subarea is determined by taking the ratio of the current timestamp to the maximum value of the Long type as a time offset factor, and the specific calculation formula is as follows:
offset＝current_time/Long.MAX_VALUE
wherein, offset is the time offset factor, current _ time is the current timestamp, and Long. As can be seen from the above equation, the offset is only a fraction between 0,1), but its sensitivity is very high. Then, taking the ordering calculation formula of the head sub-area in the saturated state in the above pressure logical partition ordering example as follows:
score2＝N2+[offset/(c3-c2)]×(N3-N2)
usually score2This value, which is very close to N2, can be guaranteed to be in front of the normal subzone and therefore has a high priority. Of course, this is merely an example ordering rule and other ordering rules may be employed as appropriate.
(3) Co-regional concurrent ordering
According to the pressure value mapping result in the pressure logical partition ordering, the pressure values between at least two customer services, for example, the customer service a and the customer service B, may be the same at the same time, and therefore, the problem of pressure ordering value conflict between the customer services with the same pressure value needs to be solved.
It can be seen that the problem of conflict of the pressure ranking values mainly occurs in the common subarea, as shown in fig. 5, if the conflict between the customer service a and the customer service B is processed by a random method, the same customer service may be continuously distributed to a large number of customers in an extreme case, and other customer services have no embarrassment that the customers can be distributed.
In the embodiment of the invention, a time sensitivity solution is introduced, a tiny time offset factor is added to the sequencing value in the common subarea, and the time offset factor is acquired in a mode of adopting the time offset factor offset in the sequencing of the head allocation subarea. Therefore, the above formula for calculating the pressure ranking value of customer service in the saturated state evolves as:
score3＝N2+[(ci-c2+offset)/(c3-c2)]×(N3-N2)
the value of the offset is very small, but the sensitivity to concurrency under the same condition is high enough to solve the problem of conflict of the ordering values. Therefore, the problem of concurrent scheduling in the same region can be solved skillfully.
Embodiments of the present invention also provide a non-transitory computer-readable storage medium storing instructions, which when executed by a processor, cause the processor to perform the steps of the customer service real-time scheduling method as described in the foregoing description.
An embodiment of the present invention further provides an electronic device for executing a tracking scheduling method, as shown in fig. 6, the electronic device includes: at least one processor 1 and a memory 2. The memory 2 is communicatively connected to the at least one processor 1, for example the memory 2 and the at least one processor 1 are connected by a bus. The memory 2 stores instructions executable by the at least one processor 1 to cause the at least one processor 1 to perform the steps of the method for real-time customer service dispatch as described in the foregoing description.
The customer service real-time scheduling method, the nonvolatile computer readable storage medium and the electronic device in the embodiment of the invention adopt two-stage partition strategies such as pressure partition sequencing, first sub-region sequencing, second sub-region sequencing, same-region concurrent sequencing and the like based on the same online customer service queue, and have great advantages in improving customer service quality and service efficiency and consistency of states of dispatches. Meanwhile, the invention also provides an offset sorting value under the condition of concurrent in the same region, thereby improving the capability of processing concurrent scheduling. In addition, the invention has no redundant hypothesis and constraint condition, thereby having strong expandability, being capable of adapting to various scheduling scenes, and being capable of greatly improving the performance by applying the technical scheme of the invention to the distributed cache queue.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A customer service real-time scheduling method comprises the following steps:
partitioning the customer service queue according to the pressure state of the customer service;
determining a pressure sorting value of the customer service in the customer service queue according to the pressure value of the customer service, and inserting the customer service into the customer service queue according to the pressure sorting value;
dividing each subarea in the customer service queue into a first subarea and a second subarea, putting all the customer services which are not allocated to the customers under the subarea into the second subarea, and transferring the customer services which are allocated to the customers in the second subarea and hope to be continuously allocated to the customers from the second subarea to the first subarea.
2. The method of claim 1, wherein transferring customer service in the second sub-area that is assigned to customers and that wishes to continue to be assigned to customers from the second sub-area to the first sub-area comprises:
adjusting a pressure ranking value of the customer service with a time-shift factor to shift the customer compliance with the second sub-zone into the first sub-zone.
3. The customer service real-time scheduling method according to claim 1, wherein:
the pressure sequencing value of the customer service in the second subregion is:
score1＝Na+[(ci-ca)/(cb-ca)]×(Nb-Na)
wherein, score1A pressure ranking value, N, for customer service in the second subregionaA first boundary value, N, for the second subregion and the subregion to which the first subregion belongsbA second boundary value for the second subregion and the subregion to which the first subregion belongs, caTo correspond to NaPressure value of cbTo correspond to NbPressure value of ciA pressure value for any customer service in the second sub-zone, wherein Nb>Na，cb>ci>ca，cb、caAnd ciAre all integers.
4. The customer service real-time scheduling method according to claim 2, wherein:
the pressure sequencing values of customer service in the first sub-zone are:
score2＝Na+[offset/(cb-ca)]×(Nb-Na)
wherein, score2A pressure ranking value, N, for customer service in the first sub-zoneaA first boundary value, N, for the second subregion and the subregion to which the first subregion belongsbA second boundary value for the second subregion and the subregion to which the first subregion belongs, caTo correspond to NaPressure value of cbTo correspond to NbIs the time offset factor, which is the ratio of the timestamp when the customer service was distributed to the customer to the maximum value of the long integer, where N isb>Na，cb>ca，cbAnd caAre integers.
5. The customer service real-time scheduling method according to claim 1, wherein:
and for a plurality of customer services with the same pressure sequencing values in the second sub-area, finely adjusting the pressure sequencing values among the customer services by using a time offset factor, and sequencing the customer services according to the finely adjusted pressure sequencing values.
6. The real-time customer service scheduling method according to claim 5, wherein:
the pressure ranking values after the customer service fine adjustment with the same pressure ranking value in the second sub-area are as follows:
score3＝Na+[(ci-ca+offset)/(cb-ca)]×(Nb-Na)
wherein, score3Sorting the values of the pressure after the fine adjustment，NaA first boundary value, N, for the second subregion and the subregion to which the first subregion belongsbA second boundary value for the second subregion and the subregion to which the first subregion belongs, caTo correspond to NaPressure value of cbTo correspond to NbPressure value of ciThe offset is the time offset factor which is the ratio of the timestamp of any customer service inserted into the customer service queue to the maximum value of the long integer, wherein N is the pressure value of any customer service in the second subareab>Na，cb>ci>ca，cb、caAnd ciAre all integers.
7. The customer service real-time scheduling method according to claim 1, wherein:
the partitions include idle partitions, active partitions, saturated partitions, and burst partitions.
8. The customer service real-time scheduling method according to claim 1, wherein:
when any customer service event comes, the customer service pressure is evaluated to obtain the pressure value, the pressure ranking value is further determined, and the customer service is inserted into the customer service queue according to the pressure ranking value.
9. A non-transitory computer readable storage medium storing instructions, wherein the instructions, when executed by a processor, cause the processor to perform the steps in the customer service real-time scheduling method of any one of claims 1 to 8.
10. An electronic device, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the steps in the real-time customer service dispatch method of any of claims 1-8.
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