CN114240162A - Personnel scheduling method, device, equipment and storage medium - Google Patents
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Abstract
The invention relates to big data technology, and discloses a personnel scheduling method, which comprises the following steps: calculating comprehensive scores of various operators for different types of operations according to a preset scoring rule and a historical operation data set, and determining the capability levels of the operators according to the scores; receiving a task to be dispatched, acquiring characteristic information of the task to be dispatched, and selecting a dispatching person from each operator according to the characteristic information and the capability level of the operator; and recommending the optimal route for the dispatching personnel based on a route recommendation algorithm. In addition, the invention also relates to a block chain technology, and the historical operation data set can be stored in the nodes of the block chain. The invention also provides a personnel scheduling device, electronic equipment and a storage medium. The invention can improve the efficiency of personnel scheduling.
Description
Technical Field
The present invention relates to the field of big data technologies, and in particular, to a method and an apparatus for scheduling people, an electronic device, and a computer-readable storage medium.
Background
With the development of science and technology, more and more services are dispatched by using intelligent platforms, but currently, the dispatching mode of operators by each platform is usually a claimed mode, namely, the platform is only responsible for collecting tasks, but cannot distribute the tasks, and the operators are required to select to receive the tasks by themselves. Because the capacities of different operators are different and the processing capacities of different types of jobs are also different, the way may often result in mismatching between the operators and actual processing services, which results in re-matching, or takes too long time, has low efficiency, and is not satisfactory for customers, so a more efficient personnel scheduling scheme is needed.
Disclosure of Invention
The invention provides a personnel scheduling method, a personnel scheduling device, electronic equipment and a computer readable storage medium, and mainly aims to improve the personnel scheduling efficiency.
In order to achieve the above object, the present invention provides a personnel scheduling method, including:
acquiring index data determined according to a historical operation data set, respectively calculating comprehensive scores of various operators for different types of operations based on the index data and a preset scoring rule, and determining the capability levels of the operators according to the scores;
receiving a task to be dispatched, acquiring characteristic information of the task to be dispatched, and selecting a dispatching person from each operator according to a place, a service type and the capability level of the operator in the characteristic information;
and recommending an optimal route for the dispatching personnel based on a route recommendation algorithm and the location of the task to be dispatched.
Optionally, the acquiring index data determined according to a historical job data set, and respectively calculating a comprehensive score of each worker for different types of jobs based on the index data and a preset scoring rule includes:
acquiring the job information with the finished state from a database to obtain a historical job data set;
dividing the historical job data set according to job types to obtain a plurality of sub-job data sets;
dividing each sub-job data set according to job processing personnel to obtain a personal job data set;
selecting field data under a preset dimension in the personal operation data set as index data;
respectively calculating the basic score of each index data according to a preset scoring rule;
and determining the weight of each index data based on an analytic hierarchy process, and combining the basic scores according to the weight to obtain a comprehensive score.
Optionally, the determining the weight of each index data based on the analytic hierarchy process includes:
establishing a hierarchical structure model of the index data according to an actual service target;
constructing a judgment matrix according to the hierarchical structure model;
and calculating the weight vector of the judgment matrix and carrying out consistency check on the judgment matrix to obtain the weight of each index data.
Optionally, the determining the capability level of the operator according to the score includes:
judging the capability level of the corresponding operator to be excellent when the score is greater than a preset threshold value;
and judging the corresponding ability level of the operator to be normal when the score is less than or equal to a preset threshold value.
Optionally, the receiving a task to be dispatched, obtaining feature information of the task to be dispatched, and selecting a person to be dispatched from the operators according to a location, a service type, and a capability level of the operator in the feature information includes:
receiving a task to be dispatched, and acquiring characteristic information of the task to be dispatched, wherein the characteristic information comprises a place and a service type;
selecting operators with the current positions and the places in the same area from all the operators to obtain a first candidate personnel set;
selecting the operating personnel with excellent capability level identification corresponding to the service type in the first candidate personnel set to obtain a second candidate personnel set;
if the second candidate personnel set is empty, selecting an operator with the capability level identification corresponding to the service type as a common operator in the first candidate personnel set as the second candidate personnel set;
and selecting one operator from the second candidate personnel set according to the distance between the operator and the place and the score of the operator to obtain a dispatched operator.
Optionally, the recommending an optimal route for the dispatch personnel based on the route recommendation algorithm and the location of the task to be dispatched includes:
acquiring a road network diagram of an area where the task to be dispatched is located;
generating a road network topological graph according to the road network graph, wherein the road network topological graph comprises a plurality of nodes, and each node represents one road section;
judging whether every two nodes in the road network topological graph pass or not according to a preset passing rule, and updating the road network topological graph according to the judgment result of whether every two nodes pass or not;
selecting a shortest path from the updated road network topological graph according to the location of the task to be dispatched and the current position of the dispatched personnel to obtain an optimal route;
recommending the optimal route to the dispatch personnel.
Optionally, after the optimal route is recommended for the dispatch personnel based on the route recommendation algorithm and the location of the task to be dispatched, the method further includes:
when the task to be dispatched is converted into a complete state, acquiring the operation information of the task to be dispatched;
storing the job information into the historical data service set;
and after a preset time period is reached, recalculating the comprehensive scores of the operators for different types of jobs according to a preset scoring rule and the updated historical job data set.
In order to solve the above problem, the present invention further provides a personnel scheduling apparatus, including:
the scoring module is used for acquiring index data determined by each operator according to a preset scoring rule and a historical operation data set, respectively scoring different types of operations comprehensively based on the index data and the preset scoring rule, and determining the capability level of the operator according to the score;
the staff selection module is used for receiving a task to be dispatched, acquiring characteristic information of the task to be dispatched, and selecting a staff to be dispatched from all the operating staff according to the place, the service type and the capability level of the operating staff in the characteristic information;
and the route recommending module is used for recommending an optimal route for the dispatching personnel based on a route recommending algorithm and the location of the task to be dispatched. In order to solve the above problem, the present invention also provides an electronic device, including:
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 a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform the person scheduling method described above.
In order to solve the above problem, the present invention further provides a computer-readable storage medium, in which at least one computer program is stored, and the at least one computer program is executed by a processor in an electronic device to implement the people scheduling method described above.
According to the embodiment of the invention, the comprehensive scores of various operators for different types of operations are calculated through the preset scoring rules and the historical operation data sets, and the capability levels of the operators are determined according to the scores, so that the processing capabilities of the operators for various types of operations can be effectively evaluated, and the proper operators can be subsequently allocated to tasks; receiving a task to be dispatched, acquiring characteristic information of the task to be dispatched, selecting a dispatching person according to the characteristic information and the capability level of an operator, selecting a proper operator according to the capability level (processing capability) and an actual distance, and taking quality and efficiency into consideration; the optimal route is recommended for the dispatching personnel based on the route recommendation algorithm, so that the processing time of the operating personnel can be effectively saved, and the efficiency is improved. Therefore, the personnel scheduling method, the personnel scheduling device, the electronic equipment and the computer readable storage medium can improve the personnel scheduling efficiency.
Drawings
Fig. 1 is a schematic flow chart of a personnel scheduling method according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of calculating a composite score according to an embodiment of the present invention;
fig. 3 is a functional block diagram of a personnel scheduling apparatus according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device for implementing the staff scheduling method according to an embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment of the application provides a personnel scheduling method. The executing body of the personnel scheduling method includes, but is not limited to, at least one of electronic devices such as a server and a terminal, which can be configured to execute the method provided by the embodiment of the present application. In other words, the personnel scheduling method may be performed by software or hardware installed in the terminal device or the server device, and the software may be a block chain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like.
Fig. 1 is a schematic flow chart of a personnel scheduling method according to an embodiment of the present invention.
In this embodiment, the method for scheduling people includes:
and S1, acquiring index data determined according to the historical operation data set, respectively calculating comprehensive scores of the operators for different types of operations based on the index data and preset scoring rules, and determining the ability levels of the operators according to the scores.
The historical job data set in the embodiment of the present invention refers to information related to a completed job, including, but not limited to, a job processing duration, a client rating star rating, a rating tag, a rating content, a job handler, a job type, and the like.
The worker refers to a part or all of the staff members qualified to process the job task.
The scoring rule is a standard rule for how to score a preset index on the basis, for example, the preset index is the job processing time, and the scoring rule is that the job processing time is 80 minutes if the job processing time is greater than or equal to the average processing time, and 60 minutes if the job processing time is less than the average processing time.
In detail, referring to fig. 2, the acquiring index data determined according to a historical job data set, and calculating a comprehensive score of each worker for different types of jobs based on the index data and a preset scoring rule respectively includes:
s11, acquiring the completed job information from the database to obtain a historical job data set;
s12, dividing the historical job data set according to job types to obtain a plurality of sub job data sets;
s13, dividing each sub-job data set according to job handlers to obtain a personal job data set;
s14, selecting field data under a preset dimension in the personal operation data set as index data;
s15, respectively calculating the basic scores of the index data according to a preset scoring rule;
and S16, determining the weight of each index data based on an analytic hierarchy process, and combining the basic scores according to the weight to obtain a comprehensive score.
Further, the determining the weight of each index data based on the analytic hierarchy process includes:
establishing a hierarchical structure model of the index data according to an actual service target;
constructing a judgment matrix according to the hierarchical structure model;
and calculating the weight vector of the judgment matrix and carrying out consistency check on the judgment matrix to obtain the weight of each index data.
In detail, the determining the capability level of the worker according to the score includes:
judging the capability level of the corresponding operator to be excellent when the score is greater than a preset threshold value;
judging the corresponding ability level of the operator to be normal when the score is less than or equal to a preset threshold value;
and grouping the operators according to the capability level.
Optionally, to further ensure the security and privacy of the historical job data set, the historical data set may also be stored in a node of a block chain.
The embodiment of the invention adopts a customized grading rule to calculate the basic scores of all indexes in the historical operation data set, and then carries out corresponding combination calculation by different weights to obtain the grades of the operators in different operations. The score at this time is the score information of the operator for different operation types, and after the score of the operator is obtained, the score can be grouped according to the score, for example, a dripping high-quality driver and a common driver are only aimed at a certain operation type, and the same operator may be a "common driver" in the operation type, but is a "high-quality driver" in other operation types.
And S2, receiving a task to be dispatched, acquiring the characteristic information of the task to be dispatched, and selecting a dispatching person from the operators according to the location, the service type and the capability level of the operators in the characteristic information.
In detail, the receiving a task to be dispatched, obtaining feature information of the task to be dispatched, and selecting a dispatching person from the operators according to a place, a service type and a capability level of the operator in the feature information includes:
receiving a task to be dispatched, and acquiring characteristic information of the task to be dispatched, wherein the characteristic information comprises a place and a service type;
selecting operators with the current positions and the places in the same area from all the operators to obtain a first candidate personnel set;
selecting the operating personnel with excellent capability level identification corresponding to the service type in the first candidate personnel set to obtain a second candidate personnel set;
if the second candidate personnel set is empty, selecting an operator with the capability level identification corresponding to the service type as a common operator in the first candidate personnel set as the second candidate personnel set;
and selecting one operator from the second candidate personnel set according to the distance between the operator and the place and the score of the operator to obtain a dispatched operator.
The method and the device for dispatching the task determine the area range according to the work place of the task to be dispatched, acquire the workers which can be dispatched currently in the area range, further narrow the selection range according to the capability rating grade of the task to be dispatched, and comprehensively select the workers which are close to the task to be dispatched and have high rating to obtain the dispatched workers.
And S3, recommending an optimal route for the dispatching personnel based on a route recommendation algorithm and the location of the task to be dispatched.
In detail, the recommending an optimal route for the dispatching personnel based on the route recommending algorithm and the location of the task to be dispatched comprises the following steps:
acquiring a road network diagram of an area where the task to be dispatched is located;
generating a road network topological graph according to the road network graph, wherein the road network topological graph comprises a plurality of nodes, and each node represents one road section;
judging whether every two nodes in the road network topological graph pass or not according to a preset passing rule, and updating the road network topological graph according to the judgment result of whether every two nodes pass or not;
selecting a shortest path from the updated road network topological graph according to the location of the task to be dispatched and the current position of the dispatched personnel to obtain an optimal route;
recommending the optimal route to the dispatch personnel.
The shortest path selected from the updated road network topological graph according to the location of the task to be dispatched and the current position of the dispatched personnel can use a shortest path algorithm, such as Dijkstra algorithm, SPFA algorithm, Bellman-Ford algorithm and Floyd-Warshall algorithm.
Preferably, after recommending an optimal route for the dispatching personnel based on a route recommendation algorithm and the location of the task to be dispatched, in an embodiment of the present invention, when the task to be dispatched is completed, the task information of the task to be dispatched is obtained to update the historical service data set, and the score of each operator is updated regularly, which specifically includes:
when the task to be dispatched is converted into a complete state, acquiring the operation information of the task to be dispatched;
storing the job information into the historical data service set;
and after a preset time period is reached, recalculating the comprehensive scores of the operators for different types of jobs according to a preset scoring rule and the updated historical job data set.
The job information includes, but is not limited to, job processing duration, client rating star level, rating label, rating content, job handler, and job type.
After a new job is performed by the operator, new job history data is generated, and the history job data set needs to be updated and a new score is calculated. Therefore, it is necessary to collect index data such as work effect, compare the index data with a preset scoring rule at regular time, update the work ability level of the worker at regular time, and gradually increase the historical data to calculate the work type most suitable for the worker.
Optionally, when the dispatched personnel is performing work and delay is caused by some irresistible factors, the tasks may be forwarded to other suitable personnel, specifically, the tasks include:
when a preset blocking event occurs to the task to be dispatched, adjusting the priority of the task to be dispatched;
and reselecting and selecting the operator for the task to be dispatched according to the priority and recommending the nearest route for the operator.
When the job may not be completed in time due to irresistible factors of the job personnel, for example, the customer problem cannot be completed in time or the customer is due to the fact that a new task is already allocated, the customer can apply for refusing to connect the next new task. At the moment, the tasks return to the task pool, the distribution priority is improved, and the tasks are distributed to other operators in an intelligent allocation mode, so that seamless connection of the operations is realized.
According to the embodiment of the invention, the comprehensive scores of various operators for different types of operations are calculated through the preset scoring rules and the historical operation data sets, and the capability levels of the operators are determined according to the scores, so that the processing capabilities of the operators for various types of operations can be effectively evaluated, and the proper operators can be subsequently allocated to tasks; receiving a task to be dispatched, acquiring characteristic information of the task to be dispatched, selecting a dispatching person according to the characteristic information and the capability level of an operator, selecting a proper operator according to the capability level (processing capability) and an actual distance, and taking quality and efficiency into consideration; the optimal route is recommended for the dispatching personnel based on the route recommendation algorithm, so that the processing time of the operating personnel can be effectively saved, and the efficiency is improved. Therefore, the personnel scheduling method provided by the invention can improve the personnel scheduling efficiency.
Fig. 3 is a functional block diagram of a personnel scheduling apparatus according to an embodiment of the present invention.
The people scheduling apparatus 100 according to the present invention may be installed in an electronic device. According to the realized functions, the personnel scheduling device 100 can comprise a scoring module 101, a personnel selection module 102 and a route recommendation module 103. The module of the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and that can perform a fixed function, and that are stored in a memory of the electronic device.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the scoring module 101 is configured to acquire index data determined according to a preset scoring rule and a historical operation data set, calculate comprehensive scores of various operators for different types of operations based on the index data and the preset scoring rule, and determine capability levels of the operators according to the scores.
The historical job data set in the embodiment of the present invention refers to information related to a completed job, including, but not limited to, a job processing duration, a client rating star rating, a rating tag, a rating content, a job handler, a job type, and the like.
The worker refers to a part or all of the staff members qualified to process the job task.
The scoring rule is a standard rule for basically scoring a preset index.
In detail, when index data determined according to a preset scoring rule and a historical job data set is acquired, and comprehensive scores of different types of jobs are respectively calculated for each worker based on the index data and the preset scoring rule, the scoring module 101 is specifically configured to:
acquiring the job information with the finished state from a database to obtain a historical job data set;
dividing the historical job data set according to job types to obtain a plurality of sub-job data sets;
dividing each sub-job data set according to job processing personnel to obtain a personal job data set;
selecting field data under a preset dimension in the personal operation data set as index data;
respectively calculating the basic score of each index data according to a preset scoring rule;
and determining the weight of each index data based on an analytic hierarchy process, and combining the basic scores according to the weight to obtain a comprehensive score.
Further, the determining the weight of each index data based on the analytic hierarchy process includes:
establishing a hierarchical structure model of the index data according to an actual service target;
constructing a judgment matrix according to the hierarchical structure model;
and calculating the weight vector of the judgment matrix and carrying out consistency check on the judgment matrix to obtain the weight of each index data.
In detail, when determining the capability level of the operator according to the score, the scoring module 101 is specifically configured to:
judging the capability level of the corresponding operator to be excellent when the score is greater than a preset threshold value;
judging the corresponding ability level of the operator to be normal when the score is less than or equal to a preset threshold value;
and grouping the operators according to the capability level.
The staff selecting module 102 is configured to receive a task to be dispatched, obtain feature information of the task to be dispatched, and select a staff to be dispatched from the staff according to a location, a service type, and a capability level of the staff in the feature information.
In detail, the people selection module 102 is specifically configured to:
receiving a task to be dispatched, and acquiring characteristic information of the task to be dispatched, wherein the characteristic information comprises a place and a service type;
selecting operators with the current positions and the places in the same area from all the operators to obtain a first candidate personnel set;
selecting the operating personnel with excellent capability level identification corresponding to the service type in the first candidate personnel set to obtain a second candidate personnel set;
if the second candidate personnel set is empty, selecting an operator with the capability level identification corresponding to the service type as a common operator in the first candidate personnel set as the second candidate personnel set;
and selecting one operator from the second candidate personnel set according to the distance between the operator and the place and the score of the operator to obtain a dispatched operator.
The route recommending module 103 is configured to recommend an optimal route for the dispatching personnel based on a route recommending algorithm and the location of the task to be dispatched.
In detail, the route recommendation module 103 is specifically configured to:
acquiring a road network diagram of an area where the task to be dispatched is located;
generating a road network topological graph according to the road network graph, wherein the road network topological graph comprises a plurality of nodes, and each node represents one road section;
judging whether every two nodes in the road network topological graph pass or not according to a preset passing rule, and updating the road network topological graph according to the judgment result of whether every two nodes pass or not;
selecting a shortest path from the updated road network topological graph according to the location of the task to be dispatched and the current position of the dispatched personnel to obtain an optimal route;
recommending the optimal route to the dispatch personnel.
According to the embodiment of the invention, the comprehensive scores of various operators for different types of operations are calculated through the preset scoring rules and the historical operation data sets, and the capability levels of the operators are determined according to the scores, so that the processing capabilities of the operators for various types of operations can be effectively evaluated, and the proper operators can be subsequently allocated to tasks; receiving a task to be dispatched, acquiring characteristic information of the task to be dispatched, selecting a dispatching person according to the characteristic information and the capability level of an operator, selecting a proper operator according to the capability level (processing capability) and an actual distance, and taking quality and efficiency into consideration; the optimal route is recommended for the dispatching personnel based on the route recommendation algorithm, so that the processing time of the operating personnel can be effectively saved, and the efficiency is improved. Therefore, the personnel scheduling device provided by the invention can improve the efficiency of personnel scheduling.
Fig. 4 is a schematic structural diagram of an electronic device for implementing a personnel scheduling method according to an embodiment of the present invention.
The electronic device 1 may comprise a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may further comprise a computer program, such as a person scheduler, stored in the memory 11 and operable on the processor 10.
In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same function or different functions, and includes one or more Central Processing Units (CPUs), a microprocessor, a digital Processing chip, a graphics processor, a combination of various control chips, and the like. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the whole electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device by running or executing programs or modules (e.g., executive scheduler, etc.) stored in the memory 11 and calling data stored in the memory 11.
The memory 11 includes at least one type of readable storage medium including flash memory, removable hard disks, multimedia cards, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disks, optical disks, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device, for example a removable hard disk of the electronic device. The memory 11 may also be an external storage device of the electronic device in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used not only to store application software installed in the electronic device and various types of data, such as codes of a person scheduler, etc., but also to temporarily store data that has been output or is to be output.
The communication bus 12 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is arranged to enable connection communication between the memory 11 and at least one processor 10 or the like.
The communication interface 13 is used for communication between the electronic device and other devices, and includes a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), which are typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit such as a Keyboard (Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable, among other things, for displaying information processed in the electronic device and for displaying a visualized user interface.
Fig. 4 only shows an electronic device with components, and it will be understood by those skilled in the art that the structure shown in fig. 4 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than those shown, or some components may be combined, or a different arrangement of components.
For example, although not shown, the electronic device may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management and the like are realized through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.
The person scheduler stored in the memory 11 of the electronic device 1 is a combination of instructions that, when executed in the processor 10, enable:
acquiring index data determined according to a preset scoring rule and a historical operation data set, respectively calculating comprehensive scores of various operators for different types of operations based on the index data and the preset scoring rule, and determining the ability level of the operators according to the scores;
receiving a task to be dispatched, acquiring characteristic information of the task to be dispatched, and selecting a dispatching person from each operator according to a place, a service type and the capability level of the operator in the characteristic information;
and recommending an optimal route for the dispatching personnel based on a route recommendation algorithm and the location of the task to be dispatched.
Specifically, the specific implementation method of the instruction by the processor 10 may refer to the description of the relevant steps in the embodiment corresponding to the drawings, which is not described herein again.
Further, the integrated modules/units of the electronic device 1, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. The computer readable storage medium may be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).
The present invention also provides a computer-readable storage medium, storing a computer program which, when executed by a processor of an electronic device, may implement:
acquiring index data determined according to a historical operation data set, respectively calculating comprehensive scores of various operators for different types of operations based on the index data and a preset scoring rule, and determining the capability levels of the operators according to the scores;
receiving a task to be dispatched, acquiring characteristic information of the task to be dispatched, and selecting a dispatching person from each operator according to a place, a service type and the capability level of the operator in the characteristic information;
and recommending an optimal route for the dispatching personnel based on a route recommendation algorithm and the location of the task to be dispatched.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules 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.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A method for scheduling people, the method comprising:
acquiring index data determined according to a preset scoring rule and a historical operation data set, respectively calculating comprehensive scores of various operators for different types of operations based on the index data and the preset scoring rule, and determining the ability level of the operators according to the scores;
receiving a task to be dispatched, acquiring characteristic information of the task to be dispatched, and selecting a dispatching person from each operator according to a place, a service type and the capability level of the operator in the characteristic information;
and recommending an optimal route for the dispatching personnel based on a route recommendation algorithm and the location of the task to be dispatched.
2. The personnel scheduling method according to claim 1, wherein said obtaining index data determined according to a preset scoring rule and a historical job data set, and calculating a composite score for different types of jobs for each worker based on said index data and a preset scoring rule, respectively, comprises:
acquiring the job information with the finished state from a database to obtain a historical job data set;
dividing the historical job data set according to job types to obtain a plurality of sub-job data sets;
dividing each sub-job data set according to job processing personnel to obtain a personal job data set;
selecting field data under a preset dimension in the personal operation data set as index data;
respectively calculating the basic score of each index data according to a preset scoring rule;
and determining the weight of each index data based on an analytic hierarchy process, and combining the basic scores according to the weight to obtain a comprehensive score.
3. The personnel scheduling method of claim 2 wherein said determining a weight for each of said indicator data based on an analytic hierarchy process comprises:
establishing a hierarchical structure model of the index data according to an actual service target;
constructing a judgment matrix according to the hierarchical structure model;
and calculating the weight vector of the judgment matrix and carrying out consistency check on the judgment matrix to obtain the weight of each index data.
4. The personnel scheduling method of claim 1 wherein said determining a capability level of said worker based on said score comprises:
judging the capability level of the corresponding operator to be excellent when the score is greater than a preset threshold value;
and judging the corresponding ability level of the operator to be normal when the score is less than or equal to a preset threshold value.
5. The personnel scheduling method of claim 1, wherein said receiving a task to be dispatched and obtaining characteristic information of said task to be dispatched, and selecting a person to be dispatched from said respective operators according to a location, a service type and a capability level of said operator in said characteristic information comprises:
receiving a task to be dispatched, and acquiring characteristic information of the task to be dispatched, wherein the characteristic information comprises a place and a service type;
selecting operators with the current positions and the places in the same area from all the operators to obtain a first candidate personnel set;
selecting the operating personnel with excellent capability level identification corresponding to the service type in the first candidate personnel set to obtain a second candidate personnel set;
if the second candidate personnel set is empty, selecting an operator with the capability level identification corresponding to the service type as a common operator in the first candidate personnel set as the second candidate personnel set;
and selecting one operator from the second candidate personnel set according to the distance between the operator and the place and the score of the operator to obtain a dispatched operator.
6. The person scheduling method according to claim 1, wherein the recommending an optimal route for the dispatched person based on a route recommendation algorithm and the location of the task to be dispatched comprises:
acquiring a road network diagram of an area where the task to be dispatched is located;
generating a road network topological graph according to the road network graph, wherein the road network topological graph comprises a plurality of nodes, and each node represents one road section;
judging whether every two nodes in the road network topological graph pass or not according to a preset passing rule, and updating the road network topological graph according to the judgment result of whether every two nodes pass or not;
selecting a shortest path from the updated road network topological graph according to the location of the task to be dispatched and the current position of the dispatched personnel to obtain an optimal route;
recommending the optimal route to the dispatch personnel.
7. The person scheduling method according to any one of claims 1 to 6, wherein after the optimal route is recommended for the dispatched person based on a route recommendation algorithm and the location of the task to be dispatched, the method further comprises:
when the task to be dispatched is converted into a complete state, acquiring the operation information of the task to be dispatched;
storing the job information into the historical data service set;
and after a preset time period is reached, recalculating the comprehensive scores of the operators for different types of jobs according to a preset scoring rule and the updated historical job data set.
8. A people scheduling apparatus, the apparatus comprising:
the scoring module is used for acquiring index data determined according to a preset scoring rule and a historical operation data set, respectively calculating comprehensive scores of various operators for different types of operations based on the index data and the preset scoring rule, and determining the ability level of the operators according to the scores;
the staff selection module is used for receiving a task to be dispatched, acquiring characteristic information of the task to be dispatched, and selecting a staff to be dispatched from all the operating staff according to the place, the service type and the capability level of the operating staff in the characteristic information;
and the route recommending module is used for recommending an optimal route for the dispatching personnel based on a route recommending algorithm and the location of the task to be dispatched.
9. An electronic device, characterized in that the electronic device comprises:
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 a computer program executable by the at least one processor to enable the at least one processor to perform the person scheduling method of any one of claims 1 to 7.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the person scheduling method according to any one of claims 1 to 7.
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