CN112101791A - Call center multi-target scheduling method, system, equipment and medium - Google Patents
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Abstract
The invention discloses a multi-target scheduling method, a system, equipment and a medium for a call center, wherein the multi-target scheduling method for the call center comprises the following steps: constructing an objective function; obtaining an iterative solution according to a target function based on a greedy algorithm; and obtaining an optimal solution according to the iterative solution based on the beam search scheme. The optimization algorithm based on the greedy hybrid beam search can output a scheduling scheme which accords with hard constraints and balances multiple targets in a short time, so that the scheduling efficiency and quality are improved.
Description
Technical Field
The invention belongs to the technical field of scheduling of call centers, and particularly relates to a multi-target scheduling method, system, equipment and medium for a call center.
Background
An OTA (Online Travel Agency) platform has a huge calling amount and call center service personnel, and the scheduling of the call center service personnel also becomes a key problem. The traditional scheduling of call center customer service personnel is mainly judged and arranged through manual experience and rules, a large amount of labor is needed for each scheduling, and the calculation time is long. When the scheduling staff is adjusted temporarily or the call volume is increased/decreased instantly, the scheduling of the on-line customer service staff is disordered due to the fact that adjustment cannot be carried out timely, and a scheduling scheme which gives consideration to fairness and utilization rate and is better can not be found in limited time.
Disclosure of Invention
The invention aims to overcome the defect of disordered scheduling of a call center in the prior art and provides a multi-target scheduling method, a multi-target scheduling system, multi-target scheduling equipment and a multi-target scheduling medium for the call center.
The invention solves the technical problems through the following technical scheme:
the invention provides a multi-target scheduling method for a call center, which comprises the following steps:
constructing an objective function;
obtaining an iterative solution according to a target function based on a greedy algorithm;
an optimal solution is obtained from an iterative solution based on a beam search scheme.
Preferably, the step of constructing the objective function comprises:
and generating a subproblem corresponding to each target according to the plurality of targets, and obtaining an objective function according to the subproblems.
Preferably, the plurality of objectives includes a utilization objective, a fairness objective, an effectiveness objective;
the first sub-problem corresponding to the utilization rate target is the sum of the degree of under-fitting of each time interval;
the second sub-problem corresponding to the fairness objective is the variation coefficient of the working time of all the employees;
the third sub-problem corresponding to the effectiveness target is data of the number of arranged people/the number of required people;
the step of obtaining the objective function according to the subproblems comprises:
and weighting the sum of the degree of under-fitting of each time period, the variation coefficient of the working time of all the employees and the data of the number of arranged persons/the number of required persons to obtain an objective function.
Preferably, the step of obtaining the iterative solution according to the objective function based on the greedy algorithm includes:
generating an initial scheduling list;
acquiring a shift set which accords with preset constraints from an initial shift list;
each shift in the set of shifts is evaluated based on an objective function to obtain an iterative solution to replace the original shift with the iterative solution.
Preferably, the step of obtaining an iterative solution comprises:
running a greedy algorithm for n times in each iteration to obtain n iterative solutions;
the step of obtaining the optimal solution according to the iterative solution based on the beam search scheme comprises the following steps:
the best solution of the n iterative solutions is selected as the initial solution of the next round by using the objective function.
The invention also provides a multi-target scheduling system of the call center, which comprises a construction unit, an iteration acquisition unit and an optimal acquisition unit;
the construction unit is used for constructing an objective function;
the iteration obtaining unit is used for obtaining an iteration solution according to the objective function based on a greedy algorithm;
the optimal acquisition unit is used for obtaining an optimal solution according to the iterative solution based on the beam search scheme.
Preferably, the building unit is further configured to generate a sub-problem corresponding to each target according to the multiple targets, and obtain the target function according to the sub-problem.
Preferably, the plurality of objectives includes a utilization objective, a fairness objective, an effectiveness objective;
the first sub-problem corresponding to the utilization rate target is the sum of the degree of under-fitting of each time interval;
the second sub-problem corresponding to the fairness objective is the variation coefficient of the working time of all the employees;
the third sub-problem corresponding to the effectiveness target is data of the number of arranged people/the number of required people;
the construction unit is also used for weighting the data of the sum of the degree of under-fitting of each time period, the variation coefficient of the working time of all the employees and the arrangement number/demand number to obtain an objective function.
Preferably, the iteration obtaining unit is further configured to generate an initial shift list; acquiring a shift set which accords with preset constraints from an initial shift list; each shift in the set of shifts is evaluated based on an objective function to obtain an iterative solution to replace the original shift with the iterative solution.
Preferably, the iteration obtaining unit is further configured to run a greedy algorithm for n times for each iteration to obtain n iteration solutions;
the optimal obtaining unit is further configured to select a best solution of the n iterative solutions as an initial solution of a next round by using the objective function.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein when the processor executes the computer program, the multi-target scheduling method of the call center is realized.
The invention also provides a computer readable storage medium on which a computer program is stored, the computer program, when executed by a processor, implements the call center multi-objective scheduling method of the invention.
The positive progress effects of the invention are as follows: the optimization algorithm based on the greedy hybrid beam search can output a scheduling scheme which accords with hard constraints and balances multiple targets in a short time, so that the scheduling efficiency and quality are improved.
Drawings
Fig. 1 is a flowchart of a call center multi-target scheduling method according to embodiment 1 of the present invention.
Fig. 2 is a schematic diagram of a search iteration solution of the call center multi-target scheduling method according to embodiment 1 of the present invention.
Fig. 3 is a schematic diagram of selecting an optimal solution for the multi-objective scheduling method of the call center in embodiment 1 of the present invention.
Fig. 4 is a schematic diagram of a call center multi-target scheduling system according to embodiment 2 of the present invention.
Fig. 5 is a schematic structural diagram of an electronic device according to embodiment 3 of the present invention.
Detailed Description
The invention is further illustrated by the following examples, which are not intended to limit the scope of the invention.
Example 1
The embodiment provides a multi-target scheduling method for a call center. Referring to fig. 1, the multi-target scheduling method of the call center comprises the following steps:
and step S101, constructing an objective function.
And S102, obtaining an iterative solution according to the objective function based on a greedy algorithm.
And S103, obtaining an optimal solution according to the iterative solution based on the beam search scheme.
During specific implementation, firstly, the scheduling problem is disassembled into subproblems of single-day single group, the subproblems are solved by using a greedy algorithm, and then the optimal problems are selected from the subproblems by using a beam search method, so that the overall problem is solved.
As an alternative embodiment, first, in step S101, multiple targets are converted into a mathematical problem. The problem has three goals to be achieved, respectively:
the first target is: the utilization rate target is that the number of people arranged in each time interval is as close as possible to the number of people required;
and a second target: the fairness goal is that the working time of each unit group for distributing work is as close as possible;
and a third target: validity goal, the gap for a single session cannot be too large.
The conversion of the data into the mathematical problem corresponds to the sum of the under-fitting degree of each time period, the variation coefficient of the working time of all the employees and the data of the number of arranged persons/required persons, and the objective function is obtained after the three parts are weighted.
Then, in step S102, a solution is iteratively searched for based on a greedy algorithm. As an illustration, an iterative solution based on a greedy algorithm search model is shown in fig. 2.
And converting the configuration item information in the configuration table into corresponding internal constraints, wherein the configuration comprises the start time, the end time, the overtime time, the eating time, the rest time and the like of different shifts.
An initial shift list is generated based on the rules, an initial shift list is generated based on the logic provided by the service and the number of shifts that can be scheduled currently, wherein the logic can be set by the user based on the provided configuration list.
Randomly selecting a date Y and an employee group X as the optimization object of the time.
And the computer worker group X conforms to all shift sets shift _ set of hard constraints in the date Y, wherein the hard constraints comprise an on-duty interval constraint, a class constraint of the shift, an overtime time constraint and the like.
And (4) calculating the score of the target function for all shifts in the shift _ set, and taking the shift with the highest score as the iterative solution of the round to replace the original shift.
Then, in step S103, the beam search scheme is used for algorithm optimal solution selection. The selection of the optimal solution of the algorithm using the beam search scheme is shown in fig. 3.
And aiming at the initial solution, running a greedy algorithm for n times in each iteration to obtain solution _ list of n iterations.
The best solution in solution _ list is selected as the initial solution _ new of the next round using the phased objective function.
The staged objective function is mainly divided into two stages before the target triple is satisfied and after the target triple is satisfied. Because three targets are respectively controlled by three parts of the target function at present, the three targets are most difficult to meet due to the problem of difficulty of searching, the three targets are divided into staged functions, and different weights are set for the three targets in two stages, so that the searching speed is controlled.
And repeating the ab steps for the new initial solution _ new until the search time constraint is met to obtain the final optimized solution.
The multi-target scheduling method for the call center has the technical effects that: firstly, a multi-target scheduling scheme is formed according to the scheduling condition of the hotel in a targeted manner, so that the multi-target requirement in the actual service scene is better met. Secondly, a beam search scheme is creatively introduced, so that the overall search result is better close to the global optimum. Thirdly, the space for configuration adjustment is increased in consideration of the flexibility of use.
The call center multi-target scheduling method of the embodiment forms a greedy mixed beam search optimization algorithm based on the current scheduling condition of the hotel, and can output a scheduling scheme which accords with hard constraints and balances multiple targets within 5 minutes, so that the scheduling efficiency and quality are improved. And moreover, various parameter configurations are provided, the adjustment of the start, the end, the eating and the rest time of different shifts can be conveniently carried out, and the convenience and the usability of the algorithm are improved.
The call center multi-target scheduling method of the embodiment improves scheduling efficiency: the system and the method can be used for quickly scheduling the customer service staff and reducing the labor time consumed by scheduling.
The call center multi-target scheduling method of the embodiment improves the scheduling quality: and a better scheduling personnel combination is obtained through an algorithm, so that the utilization rate of the scheduled work is improved.
The multi-target scheduling method for the call center meets the multi-target requirement: efficiency and quality are met, meanwhile, the problems of man-hour fairness and gaps in individual time intervals can be considered, and the multi-target requirement of scheduling is met.
The multi-target scheduling method for the call center meets the flexible configuration requirement: when the number of classes of customer service needs to be limited, the algorithm can directly complete the limitation requirement by modifying the configuration items, so that a new class list can be generated through quick iteration.
Example 2
The embodiment provides a multi-target scheduling system of a call center. Referring to fig. 4, the multi-objective scheduling system of the call center includes a construction unit 201, an iteration obtaining unit 202, and an optimal obtaining unit 203.
The constructing unit 201 is configured to construct an objective function; the iteration obtaining unit 202 is configured to obtain an iteration solution according to the objective function based on a greedy algorithm; the optimal obtaining unit 203 is configured to obtain an optimal solution according to the iterative solution based on the beam search scheme.
During specific implementation, firstly, the scheduling problem is disassembled into subproblems of single-day single group, the subproblems are solved by using a greedy algorithm, and then the optimal problems are selected from the subproblems by using a beam search method, so that the overall problem is solved.
As an alternative embodiment, first, the construction unit 201 converts multiple targets into a mathematical problem. The problem has three goals to be achieved, respectively:
the first target is: the utilization rate target is that the number of people arranged in each time interval is as close as possible to the number of people required;
and a second target: the fairness goal is that the working time of each unit group for distributing work is as close as possible;
and a third target: validity goal, the gap for a single session cannot be too large.
The conversion of the data into the mathematical problem corresponds to the sum of the under-fitting degree of each time period, the variation coefficient of the working time of all the employees and the data of the number of arranged persons/required persons, and the objective function is obtained after the three parts are weighted.
Then, the iteration obtaining unit 202 searches for the optimal solution of the model based on the greedy algorithm. As an illustration, the optimal solution of the model is searched based on the greedy algorithm, see fig. 2.
And converting the configuration item information in the configuration table into corresponding internal constraints, wherein the configuration comprises the start time, the end time, the overtime time, the eating time, the rest time and the like of different shifts.
An initial shift list is generated based on the rules, an initial shift list is generated based on the logic provided by the service and the number of shifts that can be scheduled currently, wherein the logic can be set by the user based on the provided configuration list.
Randomly selecting a date Y and an employee group X as the optimization object of the time.
And the computer worker group X conforms to all shift sets shift _ set of hard constraints in the date Y, wherein the hard constraints comprise an on-duty interval constraint, a class constraint of the shift, an overtime time constraint and the like.
And (4) calculating the score of the target function for all shifts in the shift _ set, and taking the shift with the highest score as the iterative solution of the round to replace the original shift.
Then, the optimal acquisition unit 203 performs the optimal solution selection of the algorithm using the beam search scheme. The selection of the optimal solution of the algorithm using the beam search scheme is shown in fig. 3.
And aiming at the initial solution, running a greedy algorithm for n times in each iteration to obtain solution _ list of n iterations.
The best solution in solution _ list is selected as the initial solution _ new of the next round using the phased objective function.
The staged objective function is mainly divided into two stages before the target triple is satisfied and after the target triple is satisfied. Because three targets are respectively controlled by three parts of the target function at present, the three targets are most difficult to meet due to the problem of difficulty of searching, the three targets are divided into staged functions, and different weights are set for the three targets in two stages, so that the searching speed is controlled.
And repeating the ab steps for the new initial solution _ new until the search time constraint is met to obtain the final optimized solution.
The multi-target scheduling system of the call center has the technical effects that: firstly, a multi-target scheduling scheme is formed according to the scheduling condition of the hotel in a targeted manner, so that the multi-target requirement in the actual service scene is better met. Secondly, a beam search scheme is creatively introduced, so that the overall search result is better close to the global optimum. Thirdly, the space for configuration adjustment is increased in consideration of the flexibility of use.
The call center multi-target scheduling system of the embodiment forms a greedy mixed beam search optimization algorithm based on the current scheduling condition of the hotel, and can output a scheduling scheme which accords with hard constraints and balances multiple targets within 5 minutes, so that the scheduling efficiency and quality are improved. And moreover, various parameter configurations are provided, the adjustment of the start, the end, the eating and the rest time of different shifts can be conveniently carried out, and the convenience and the usability of the algorithm are improved.
The call center multi-target scheduling system of the embodiment improves scheduling efficiency: the system and the method can be used for quickly scheduling the customer service staff and reducing the labor time consumed by scheduling.
The call center multi-target scheduling system of the embodiment improves scheduling quality: and a better scheduling personnel combination is obtained through an algorithm, so that the utilization rate of the scheduled work is improved.
The multi-target scheduling system of the call center meets the multi-target requirement: efficiency and quality are met, meanwhile, the problems of man-hour fairness and gaps in individual time intervals can be considered, and the multi-target requirement of scheduling is met.
The call center multi-target scheduling system of the embodiment meets the flexible configuration requirement: when the number of classes of customer service needs to be limited, the algorithm can directly complete the limitation requirement by modifying the configuration items, so that a new class list can be generated through quick iteration.
Example 3
Fig. 5 is a schematic structural diagram of an electronic device provided in this embodiment. The electronic device comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein when the processor executes the program, the multi-target scheduling method of the call center in embodiment 1 is realized. The electronic device 30 shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiment of the present invention.
As shown in fig. 5, the electronic device 30 may be embodied in the form of a general purpose computing device, which may be, for example, a server device. The components of the electronic device 30 may include, but are not limited to: the at least one processor 31, the at least one memory 32, and a bus 33 connecting the various system components (including the memory 32 and the processor 31).
The bus 33 includes a data bus, an address bus, and a control bus.
The memory 32 may include volatile memory, such as Random Access Memory (RAM)321 and/or cache memory 322, and may further include Read Only Memory (ROM) 323.
The processor 31 executes various functional applications and data processing, such as the call center multi-target scheduling method of embodiment 1 of the present invention, by running the computer program stored in the memory 32.
The electronic device 30 may also communicate with one or more external devices 34 (e.g., keyboard, pointing device, etc.). Such communication may be through input/output (I/O) interfaces 35. Also, model-generating device 30 may also communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet) via network adapter 36. As shown, network adapter 36 communicates with the other modules of model-generating device 30 via bus 33. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the model-generating device 30, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, etc.
It should be noted that although in the above detailed description several units/modules or sub-units/modules of the electronic device are mentioned, such a division is merely exemplary and not mandatory. Indeed, the features and functionality of two or more of the units/modules described above may be embodied in one unit/module according to embodiments of the invention. Conversely, the features and functions of one unit/module described above may be further divided into embodiments by a plurality of units/modules.
Example 4
The present embodiment provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the call center multi-objective scheduling method of embodiment 1.
More specific examples, among others, that the readable storage medium may employ may include, but are not limited to: a portable disk, a hard disk, random access memory, read only memory, erasable programmable read only memory, optical storage device, magnetic storage device, or any suitable combination of the foregoing.
In a possible implementation, the invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps of implementing the call centre multi-objective scheduling method of embodiment 1, when said program product is run on said terminal device.
Where program code for carrying out the invention is written in any combination of one or more programming languages, the program code may be executed entirely on the user device, partly on the user device, as a stand-alone software package, partly on the user device and partly on a remote device or entirely on the remote device.
While specific embodiments of the invention have been described above, it will be appreciated by those skilled in the art that this is by way of example only, and that the scope of the invention is defined by the appended claims. Various changes and modifications to these embodiments may be made by those skilled in the art without departing from the spirit and scope of the invention, and these changes and modifications are within the scope of the invention.
Claims (12)
1. A multi-target scheduling method for a call center is characterized by comprising the following steps:
constructing an objective function;
obtaining an iterative solution according to the objective function based on a greedy algorithm;
and obtaining an optimal solution according to the iterative solution based on the beam search scheme.
2. The multi-objective scheduling method for a call center as claimed in claim 1, wherein the step of constructing the objective function comprises:
and generating a subproblem corresponding to each target according to the plurality of targets, and obtaining the target function according to the subproblems.
3. The method of claim 2 wherein the plurality of objectives includes a utilization objective, a fairness objective, an effectiveness objective;
the first sub-problem corresponding to the utilization rate target is the sum of the degree of under-fitting of each time interval;
the second sub-problem corresponding to the fairness objective is the variation coefficient of the working time of all the employees;
the third sub-problem corresponding to the effectiveness target is data of arrangement number of people/demand number of people;
the step of obtaining the objective function according to the subproblems comprises:
and weighting the sum of the degree of under-fitting of each time period, the variation coefficient of the working time of all the employees and the data of the number of arranged persons/the number of required persons to obtain the objective function.
4. The multi-objective scheduling method for the call center as claimed in claim 3, wherein the step of obtaining an iterative solution according to the objective function based on a greedy algorithm comprises:
generating an initial scheduling list;
acquiring a shift set which accords with preset constraints from the initial shift list;
evaluating each shift in the set of shifts based on the objective function to obtain an iterative solution, and replacing an original shift with the iterative solution.
5. The multi-objective scheduling method for a call center of claim 4 wherein the step of obtaining an iterative solution comprises:
running a greedy algorithm for n times in each iteration to obtain n iterative solutions;
the step of obtaining the optimal solution according to the iterative solution based on the beam search scheme comprises the following steps:
and selecting the best solution of the n iterative solutions as the initial solution of the next round by using the objective function.
6. A multi-target scheduling system of a call center is characterized by comprising a construction unit, an iteration acquisition unit and an optimal acquisition unit;
the construction unit is used for constructing an objective function;
the iteration obtaining unit is used for obtaining an iteration solution according to the objective function based on a greedy algorithm;
the optimal obtaining unit is used for obtaining an optimal solution according to the iterative solution based on the beam search scheme.
7. The call center multi-objective scheduling system of claim 6, wherein the building unit is further configured to generate a sub-problem corresponding to each of the objectives according to a plurality of objectives, and obtain the objective function according to the sub-problem.
8. The call center multi-objective scheduling system of claim 7 wherein the plurality of objectives comprises a utilization objective, a fairness objective, an effectiveness objective;
the first sub-problem corresponding to the utilization rate target is the sum of the degree of under-fitting of each time interval;
the second sub-problem corresponding to the fairness objective is the variation coefficient of the working time of all the employees;
the third sub-problem corresponding to the effectiveness target is data of arrangement number of people/demand number of people;
the construction unit is also used for weighting the data of the sum of the degree of under-fitting of each time interval, the variation coefficient of the working time of all the employees and the arrangement number/demand number to obtain the objective function.
9. The call center multi-objective scheduling system of claim 8 wherein the iterative acquisition unit is further configured to generate an initial scheduling table; acquiring a shift set which accords with preset constraints from the initial shift list; evaluating each shift in the set of shifts based on the objective function to obtain an iterative solution, and replacing an original shift with the iterative solution.
10. The call center multi-objective scheduling system of claim 9 wherein the iteration obtaining unit is further configured to run a greedy algorithm n times per iteration to obtain n of the iterative solutions;
the optimal obtaining unit is further configured to select a best solution of the n iterative solutions as an initial solution of a next round by using the objective function.
11. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the call center multi-objective scheduling method of any one of claims 1 to 5 when executing the computer program.
12. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the call center multi-objective scheduling method of any one of claims 1 to 5.
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