CN114418477A - Order commodity distribution scheduling method and system based on data analysis and electronic equipment - Google Patents
Order commodity distribution scheduling method and system based on data analysis and electronic equipment Download PDFInfo
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- CN114418477A CN114418477A CN202111543258.2A CN202111543258A CN114418477A CN 114418477 A CN114418477 A CN 114418477A CN 202111543258 A CN202111543258 A CN 202111543258A CN 114418477 A CN114418477 A CN 114418477A
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Abstract
The invention provides an order commodity distribution scheduling method and system based on data analysis and electronic equipment. The method comprises the steps of obtaining order information; selecting an order commodity distribution scheduling strategy through data analysis according to the order information and the service emphasis dimension; calculating distribution supplier score data under the order commodity distribution scheduling strategy; and comparing the distribution provider score data to select a first distribution provider. The invention realizes data analysis of the basic data of a plurality of suppliers, carries out intelligent scheduling according to the analysis result, accurately selects the optimal supplier, reduces the inventory cost, improves the delivery efficiency and ensures the commodity quality.
Description
Technical Field
The invention relates to the field of commodity distribution, in particular to a data analysis-based order commodity distribution scheduling method, a data analysis-based order commodity distribution scheduling system and electronic equipment.
Background
In the home decoration retail industry, because home decoration auxiliary material commodities have the characteristics of various varieties, disordered brands, scattered specifications and the like, and for home decoration retail enterprises of ToB and ToC, early screening, authentication, and fulfillment and distribution appointed To the later period are very important; for the client, the stability, timeliness and quality of commodity supply are important factors for establishing public praise of enterprises. When goods sold by home retail enterprises are specified to be supplied one-to-one, the risk that the suppliers cannot supply goods exists, manual intervention is needed to find temporary suppliers capable of providing goods, and the labor cost is high and the time efficiency is low. Therefore, a supply relationship of one-to-many suppliers exists in the current home decoration and retail business requirements, and aiming at the situation, the method provides the order commodity distribution scheduling method, the system and the electronic equipment based on data analysis. .
Disclosure of Invention
In view of the above-mentioned shortcomings in the prior art, an object of the present invention is to provide a method, a system and an electronic device for scheduling delivery of ordered goods based on data analysis, which are used to solve the above problems in the prior art.
In order to achieve the above and other related objects, the present invention provides a method for scheduling delivery of ordered commodities based on data analysis, the method comprising: acquiring order information; selecting an order commodity distribution scheduling strategy through data analysis according to the order information and the service emphasis dimension; calculating distribution supplier score data under the order commodity distribution scheduling strategy; and comparing the distribution provider score data to select a first distribution provider.
In an embodiment of the present invention, the method further includes: commodity information, commodity quantity, receiving address and distribution requirement.
In an embodiment of the present invention, the method extracts key information in the distribution request in the order information, wherein the key information includes distribution time; and performing data analysis according to the key information data and the service-oriented dimension.
In an embodiment of the present invention, the method further includes: the basic strategy dimension of the order commodity distribution scheduling strategy comprises distribution timeliness, commodity gross interest rate, commodity delivery time, commodity inventory turnover time and main and standby distribution suppliers; configuring and dividing K continuous adjacent interval ranges and the score percentage of each interval range by setting a threshold value for the basic strategy dimension, wherein K is a positive integer; setting the same initial total score for the basic strategy dimension; and adjusting the score weight according to the strategy dimension to configure various order commodity distribution scheduling strategies.
In an embodiment of the present invention, the method further includes configuring data information of a delivery provider in advance, where the data information of the delivery provider includes data of a provider basis and data of a commodity supply relationship, where the provider basis includes basic address information of the provider, a delivery range of the provider, and a delivery manner of the provider, and the data of the commodity supply relationship includes data of a provider corresponding to a commodity, a stocking time of the commodity provided by the provider, a freight cost of the commodity provided by the provider, a purchase price and a profit rate of the commodity provided by the provider. And configuring data information of a main delivery supplier and data information of alternative delivery suppliers of the commodities, wherein the number of the alternative delivery suppliers is N. And configuring the data information of the distribution supplier in a manual and/or excel batch import mode.
In an embodiment of the present invention, the method further includes: and calculating the total score of all basic strategy latitudes of the order commodity corresponding to the distribution scheduling strategy selected by the distribution supplier.
In an embodiment of the present invention, the method creates the commodity purchase order to the first delivery provider according to the order information; and if the first delivery provider feeds back that the commodity is not available, selecting a second delivery provider according to the delivery provider score data, and creating the commodity purchase order for the second delivery provider.
To achieve the above and other related objects, the present invention provides a data analysis-based order commodity distribution scheduling system, comprising: the order acquisition module is used for acquiring order information; the strategy selection module is used for selecting an order commodity distribution scheduling strategy through data analysis according to the order information and the business-oriented dimension; the data processing module is used for calculating distribution supplier score data according to the order commodity distribution scheduling strategy and comparing the distribution supplier score data; and the supplier selecting module is used for selecting the distribution supplier.
To achieve the above and other related objects, the present invention provides a computer-readable storage medium, wherein a computer program is stored, and when the computer program is loaded and executed by a processor, the method for scheduling delivery of ordered commodities based on data analysis is implemented.
To achieve the above and other related objects, the present invention provides an electronic device, comprising: a processor, a memory, and a communication interface; wherein the memory is for storing a computer program; the processor is used for loading and executing the computer program to enable the electronic equipment to execute the order commodity distribution scheduling method based on data analysis; the communication interface is used for realizing communication between the access device and other equipment.
As described above, the order commodity distribution scheduling method, system and electronic device based on data analysis provided by the present invention are directed to the problems that a supplier cannot supply goods in a commodity one-to-one distribution scene, and needs manual intervention to find a temporary supplier capable of providing goods, which is high in labor cost and low in time efficiency. According to the invention, on the basis of modifying the one-to-one delivery scene into the one-to-many supplier supply relationship, the data analysis is carried out on the basic data of each supplier, the intelligent scheduling is carried out according to the analysis result, the manual screening behavior is separated, the optimal supplier is accurately selected, the inventory cost is reduced, the delivery efficiency is improved, and the commodity quality is ensured.
Drawings
Fig. 1 is a schematic diagram illustrating a process of creating a scheduling policy model of an order commodity distribution scheduling method based on data analysis according to an embodiment of the present invention.
Fig. 2 is a flowchart illustrating an order commodity distribution scheduling method based on data analysis according to an embodiment of the present invention.
Fig. 3 is a block diagram of an order commodity distribution scheduling system based on data analysis according to an embodiment of the present invention.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.
The invention provides an order commodity distribution scheduling method and system based on data analysis and electronic equipment, and aims to solve the problems that in the prior art, a supplier cannot supply commodities in a home decoration auxiliary material commodity one-to-one distribution scene of a home decoration retail industry, needs to manually intervene to find a temporary supplier capable of providing the commodities, and is high in labor cost and low in time efficiency.
As shown in fig. 1, the present embodiment provides a schematic flow chart of creating a scheduling policy model of an order commodity distribution scheduling method based on data analysis, where the method includes the following steps:
s12: the delivery provider data information is entered.
Specifically, data information of a distribution provider is configured on a data layer through manual input or an excel batch import mode, and the data information of the distribution provider comprises provider basic data and commodity supply relation data. The supplier basic data comprises basic address information of a supplier, a distribution range of the supplier and a distribution mode of the supplier; the commodity supply relation data comprises corresponding supplier matching data of commodity purchase, the stocking time of corresponding commodities provided by the suppliers, the freight cost of corresponding commodities provided by the suppliers, the purchase price and the profit rate of corresponding commodities provided by the suppliers. It should be noted that, N suppliers for commodity purchase may be provided, and one of the commodity purchase suppliers is configured as a main delivery supplier and the other commodity purchase suppliers are configured as alternative delivery suppliers according to preset rules.
S12: and configuring an order commodity distribution scheduling strategy model according to the distribution supplier data information.
Specifically, first, a calculation method of order commodity distribution scheduling policy basic policy dimensions is determined according to distribution provider data information of S12, and includes a distribution timeliness calculation method, a commodity gross profit rate calculation method, a commodity delivery time calculation method, an order automatic conversion method, a commodity inventory turnover calculation method, a master and slave provider scheduling method, and a scheduling bottom policy. For example, the delivery time limit, the commodity gross interest rate and the commodity delivery time are divided into H, I, J continuous adjacent interval ranges by setting threshold values, and different score percentages are set for the interval ranges with different dimensionalities of the basic strategies of the commodity delivery scheduling strategies for each order, wherein K, I, J is a positive integer. As another example, whether a distribution provider is setting two different score percentages high and low for a primary distribution provider or not.
Further, the same initial total score is set for the basic strategy dimensions, and the score weights of different basic strategy dimensions are adjusted to configure a plurality of different order commodity distribution scheduling strategy models. For example, the delivery timeliness scheduling policy model is obtained by increasing the initial total score of the delivery timeliness policy dimension by L times.
As shown in fig. 2, the present embodiment provides a flow chart of an order commodity distribution scheduling method based on data analysis based on the created model in fig. 1, where the method includes the following steps:
s21: and obtaining order information.
Specifically, the commodity information, the commodity quantity, the receiving address, the distribution requirement, the order completion time, the expected receiving date, the installation and processing requirement and the remark information of the order placed by the user are acquired by receiving the information pushed by the order system. Wherein, the delivery address includes: detailed longitude and latitude of the address, and floor information.
S22: and selecting an order commodity distribution scheduling strategy through data analysis according to the order information and the service-oriented dimension.
Specifically, extracting key information in the distribution requirement in the order information, wherein the key information comprises distribution time;
and performing data analysis by using key information data and the service-oriented dimension. Firstly, special requirements of a user are obtained by analyzing keywords of user order information so as to select an order commodity distribution scheduling strategy meeting the requirements of the user. Otherwise, selecting an order commodity distribution scheduling strategy according to the current service side dimension.
S23: and calculating distribution supplier score data under the order commodity distribution scheduling strategy.
Specifically, N distribution supplier data information corresponding to the order commodities is obtained through a data layer, the range of the data information state value of each supplier in the interval range of the selected order commodity distribution scheduling strategy under different basic strategy dimensions of the basic strategy dimensions is judged, and the score of each supplier in the basic strategy dimension is calculated according to the score percentage of the range of the interval range and the total score of the basic strategy dimension.
Further, the total score of all basic strategy latitudes of each supplier in the selected order commodity distribution scheduling strategy is calculated.
S24: and comparing the distribution provider score data to select a first distribution provider.
Specifically, the supplier with the highest comparison acquisition score data is taken as the first delivery supplier.
And further, the commodity purchase order is created to a first delivery provider according to order information, if the commodity is not available, a second delivery provider with the second highest score is selected according to the score data of the delivery provider, and the commodity purchase order is created to the second delivery provider. Until the best distribution supplier is selected.
All or part of the steps for implementing the above method embodiments may be performed by hardware associated with a computer program. Based upon such an understanding, the present invention also provides a computer program product comprising one or more computer instructions. The computer instructions may be stored in a computer readable storage medium. The computer-readable storage medium can be any available medium that a computer can store or a data storage device, such as a server, a data center, etc., that is integrated with one or more available media.
Referring to fig. 3, the present embodiment provides an order commodity distribution scheduling system 20 based on data analysis, which is installed in an electronic device as a software to execute the order commodity distribution scheduling method based on data analysis in the foregoing method embodiments when running. Since the technical principle of the embodiment of the system is similar to that of the embodiment of the method, repeated description of the same technical details is omitted.
The data analysis-based order commodity distribution scheduling 30 of the present embodiment specifically includes: the order acquisition module 31, the strategy selection module 32, the data processing module 33 and the supplier selection module 34. The order obtaining module 31 is configured to obtain order information; the strategy selection module 32 is used for selecting an order commodity distribution scheduling strategy through data analysis according to the order information and the service-oriented dimension; the data processing module 33 is configured to calculate delivery provider score data according to the order commodity delivery scheduling policy and compare the delivery provider score data; the supplier selection module 34 is used to select a delivery supplier.
Those skilled in the art should understand that the division of the modules in the embodiment of fig. 3 is only a logical division, and the actual implementation can be fully or partially integrated into one or more physical entities. And the modules can be realized in a form that all software is called by the processing element, or in a form that all the modules are realized in a form that all the modules are called by the processing element, or in a form that part of the modules are called by the hardware. For example, the data processing module 33 may be a separate processing element, or may be integrated in a chip, or may be stored in a memory in the form of program code, and the function of the data processing module 33 is called and executed by a certain processing element. Other modules are implemented similarly. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.
Referring to fig. 4, the embodiment provides an electronic device, which may be a portable computer, a smart phone, a tablet computer, or the like. In detail, the electronic device comprises at least, connected by a bus 41: a memory 42, a processor 43, and a communication interface 44, wherein the communication interface 44 is used for implementing communication between the data access device and other devices, the memory 42 is used for storing computer programs, and the processor 43 is used for executing the computer programs stored in the memory 42 to execute all or part of the steps in the foregoing method embodiments.
The above-mentioned system bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The system bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus. The communication interface is used for realizing communication between the database access device and other equipment (such as a client, a read-write library and a read-only library). The Memory may include a Random Access Memory (RAM), and may further include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory.
The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the Integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
In summary, according to the order commodity distribution scheduling method, system and electronic device based on data analysis provided by the invention, for home decoration retail enterprises, management and control on provider information entry in the early stage are enhanced by adopting a strict-in and wide-out mode, the provider basic data is analyzed, and the sales commodities are intelligently distributed and scheduled according to the analysis result, so that the behavior that a home decoration auxiliary material sales order needs manual intervention to issue a purchase order in a fulfillment process is avoided. Therefore, the invention effectively overcomes various defects in the prior art and has high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (10)
1. A data analysis-based order commodity distribution scheduling method is characterized by comprising the following steps:
acquiring order information;
selecting an order commodity distribution scheduling strategy through data analysis according to the order information and the service emphasis dimension;
calculating distribution supplier score data under the order commodity distribution scheduling strategy;
and comparing the distribution provider score data to select a first distribution provider.
2. The method of claim 1, wherein the order information comprises: commodity information, commodity quantity, receiving address and distribution requirement.
3. The method of claim 1 or 2, further comprising:
extracting key information in the distribution requirement in the order information, wherein the key information comprises expected distribution time;
and performing data analysis according to the key information data and the service-oriented dimension.
4. The method of claim 1, further comprising:
the basic strategy dimension of the order commodity distribution scheduling strategy comprises distribution timeliness, commodity gross interest rate, commodity delivery time, commodity inventory turnover time and main and standby distribution suppliers;
configuring and dividing K continuous adjacent interval ranges and the score percentage of each interval range by setting a threshold value for the basic strategy dimension, wherein K is a positive integer;
setting the same initial total score for the basic strategy dimension;
and adjusting the score weight according to the strategy dimension to configure various order commodity distribution scheduling strategies.
5. The method of claim 1, further comprising:
pre-configuring data information of a delivery provider, wherein the data information of the delivery provider comprises basic data of the provider and commodity supply relation data, the basic data of the provider comprises basic address information of the provider, a delivery range of the provider and a delivery mode of the provider, and the commodity supply relation data comprises corresponding provider data of a provided commodity, stock time of the provided commodity of the provider, freight cost of the provided commodity of the provider, purchase price and profitability of the provided commodity of the provider;
configuring data information of a main delivery supplier and data information of alternative delivery suppliers of the commodities, wherein the number of the alternative delivery suppliers is N;
and configuring the data information of the distribution supplier in a manual and/or excel batch import mode.
6. The method of claim 4 or 5, further comprising:
and calculating the total score of all basic strategy latitudes of the order commodity corresponding to the distribution scheduling strategy selected by the distribution supplier.
7. The method of claim 1, further comprising:
creating the commodity purchase order to the first delivery provider according to the order information;
and if the first delivery provider feeds back that the commodity is not available, selecting a second delivery provider according to the delivery provider score data, and creating the commodity purchase order for the second delivery provider.
8. An order commodity distribution scheduling system based on data analysis, the system comprising:
the order acquisition module is used for acquiring order information;
the strategy selection module is used for selecting an order commodity distribution scheduling strategy through data analysis according to the order information and the business-oriented dimension;
the data processing module is used for calculating distribution supplier score data according to the order commodity distribution scheduling strategy and comparing the distribution supplier score data;
and the supplier selecting module is used for selecting the distribution supplier.
9. A computer-readable storage medium, in which a computer program is stored, which, when being loaded and executed by a processor, implements the method for scheduling delivery of ordered commodities based on data analysis according to any one of claims 1 to 7.
10. An electronic device, comprising: a processor, a memory, and a communication interface; wherein the content of the first and second substances,
the memory is used for storing a computer program;
the processor is used for loading and executing the computer program to enable the electronic equipment to execute the order commodity distribution scheduling method based on data analysis according to any one of claims 1 to 7;
the communication interface is used for realizing communication between the access device and other equipment.
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| CN118096029A (en) * | 2024-04-23 | 2024-05-28 | 宁波安得智联科技有限公司 | Order aging analysis method, device, equipment and computer storage medium |
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| CN118096029A (en) * | 2024-04-23 | 2024-05-28 | 宁波安得智联科技有限公司 | Order aging analysis method, device, equipment and computer storage medium |
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