Service distribution recommendation method and system

Abstract

The invention provides a service distribution recommendation method and system. The method comprises the following steps: S1, constructing an initial strategy table based on selected strategy factors and logical relationships; s2, based on the initial strategy table, flexible configuration is carried out according to actual service requirements, a shunting strategy is obtained, and a shunting strategy basic table is constructed; and S3, optimizing the shunting strategy basic table, and performing matching according to service requirements. According to the method, strategies can be integrated, the strategies can be continuously updated, accurate reservoir area setting is provided for services, and the user experience and the service execution efficiency are effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of logistics technology, and in particular to a business diversion recommendation method and system. Background Art

[0002] With the rapid development of the logistics industry, especially under the premise of complex and diverse industrial product logistics categories and refined management by manufacturers and cargo owners, the need for fast entry, exit and delivery of goods in warehouses has brought tremendous pressure to the business diversion setting. In the existing technology, the selection of warehouse areas is determined based on the subjective judgment of business personnel. Inaccurate warehouse diversion settings lead to the inability to receive goods in warehouses and put them on shelves, which causes a lot of waste of forklifts and human resources in warehouses, and many other problems.

[0003] Patent document CN108334444A (application number: 201711483096.1) discloses a multi-dimensional dynamic combination diversion service method, including the steps of: receiving user identity information corresponding to a user; traversing a preset diversion rule library according to priority until obtaining a target diversion rule located in the diversion rule library corresponding to the user identity information; determining a diversion result identifier of the user according to the user identity information and the target diversion rule. Summary of the invention

[0004] In view of the defects in the prior art, an object of the present invention is to provide a service diversion recommendation method and system.

[0005] A service diversion recommendation method provided by the present invention includes:

[0006] Step S1: construct an initial strategy table based on the selected strategy factors and logical relationships;

[0007] Step S2: Based on the initial strategy table, configure according to actual business needs, obtain the diversion strategy, and build the diversion strategy basic table;

[0008] Step S3: Optimize the diversion strategy basic table and match it according to business needs.

[0009] Preferably, the step S1 comprises:

[0010] Step S1.1: Select strategic factors, including: information flow source, base, arrival point code, and commodity category;

[0011] Step S1.2: define the logical relationship between each strategy factor;

[0012] Step S1.3: Construct an initial strategy table based on the selected strategy factors and the defined logical relationships between the strategy factors.

[0013] Preferably, step S3 includes: constructing a scoring model, and using the scoring model to score the diversion strategies in the diversion strategy basic table, and then dynamically sorting and adjusting the diversion strategies in the diversion strategy basic table according to the scores; configuring the matching priority based on the sorting;

[0014] The scoring model scores the diversion strategy based on a preset strategy mode.

[0015] Preferably, the scoring model includes: scoring according to the application frequency of the diversion strategy;

[0016] The scoring according to the application frequency of the diversion strategy includes:

[0017] Obtain historical business data, count the application frequency of diversion strategies in the diversion strategy basic table in the historical business data, and score the corresponding diversion strategies according to the application frequency of the diversion strategies.

[0018] Preferably, the application frequency of each diversion strategy in the diversion strategy basic table is counted in real time, and the score of the diversion strategy is adaptively adjusted according to the application frequency of the diversion strategy, thereby adjusting the matching priority of the diversion strategy;

[0019] When the application frequency of the diversion strategy exceeds the maximum diversion point scenario, the score of the current diversion strategy is reduced, and the priority of the current diversion strategy is reduced.

[0020] A service diversion recommendation system provided according to the present invention includes:

[0021] Module M1: Constructing the initial strategy table based on the selected strategy factors and logical relationships;

[0022] Module M2: Based on the initial strategy table, configure according to actual business needs, obtain the diversion strategy, and build the diversion strategy basic table;

[0023] Module M3: Optimize the basic table of diversion strategy and match it according to business needs.

[0024] Preferably, the module M1 comprises:

[0025] Module M1.1: Selection strategy factors, including: information flow source, base, arrival point code, and commodity category;

[0026] Module M1.2: Define the logical relationship between various strategic factors;

[0027] Module M1.3: Construct an initial strategy table based on the selected strategy factors and the defined logical relationships between the strategy factors.

[0028] Preferably, the module M3 includes: constructing a scoring model, and using the scoring model to score the diversion strategies in the diversion strategy basic table, and then dynamically sorting and adjusting the diversion strategies in the diversion strategy basic table according to the scores; configuring matching priorities based on the sorting;

[0029] The scoring model scores the diversion strategy based on a preset strategy mode.

[0030] Preferably, the scoring model includes: scoring according to the application frequency of the diversion strategy;

[0031] The scoring according to the application frequency of the diversion strategy includes:

[0032] Obtain historical business data, count the application frequency of diversion strategies in the diversion strategy basic table in the historical business data, and score the corresponding diversion strategies according to the application frequency of the diversion strategies.

[0033] Preferably, the application frequency of each diversion strategy in the diversion strategy basic table is counted in real time, and the score of the diversion strategy is adaptively adjusted according to the application frequency of the diversion strategy, thereby adjusting the matching priority of the diversion strategy;

[0034] When the application frequency of the diversion strategy exceeds the maximum diversion point scenario, the score of the current diversion strategy is reduced, and the priority of the current diversion strategy is reduced.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] 1. The present invention solves the problem of wrong storage area diversion setting and slow storage area diversion setting efficiency in the complex information age by adopting a strategy table;

[0037] 2. The present invention can integrate strategies and continuously update strategies to provide accurate warehouse area settings for businesses, effectively improving user experience and business execution efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0039] Figure 1 A flowchart of the recommended method for business diversion. DETAILED DESCRIPTION

[0040] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0041] Example 1

[0042] According to a service diversion recommendation method provided by the present invention, Figure 1 As shown, including:

[0043] Step S1: construct an initial strategy table based on the selected strategy factors and logical relationships;

[0044] Step S2: Based on the initial strategy table, flexibly configure according to actual business needs, obtain the diversion strategy, and build the diversion strategy basic table;

[0045] Step S3: Optimize the diversion strategy basic table and match it according to business needs.

[0046] Specifically, the step S1 includes:

[0047] Step S1.1: Select strategic factors, including: information flow source, base, arrival point code, and commodity category;

[0048] Step S1.2: define the logical relationship between each strategy factor;

[0049] Step S1.3: Construct an initial strategy table based on the selected strategy factors and the defined logical relationships between the strategy factors.

[0050] Specifically, the module M3 includes: constructing a scoring model, and using the scoring model to score the diversion strategies in the diversion strategy basic table, and then dynamically sorting and adjusting the diversion strategies in the diversion strategy basic table according to the scores; configuring the matching priority based on the sorting;

[0051] The scoring model scores the diversion strategy based on a preset strategy mode.

[0052] In this embodiment, step S3 includes:

[0053] Step S3.1: Obtain historical business data, count the application frequencies of the diversion strategies in the diversion strategy basic table in the historical business data, and dynamically sort and adjust the diversion strategies in the diversion strategy basic table according to the application frequencies;

[0054] Step S3.2: Match the diversion strategies to corresponding scores according to the ranking. The diversion strategies with higher scores have higher matching priority.

[0055] In this embodiment, the application frequency of each diversion strategy in the diversion strategy basic table is counted in real time, and the score of the diversion strategy is adaptively adjusted according to the application frequency of the diversion strategy, thereby adjusting the matching priority of the diversion strategy;

[0056] The adaptively adjusting the score of the diversion strategy according to the application frequency of the diversion strategy includes: dynamically reducing the score of the existing diversion strategy according to the application frequency of the diversion strategy, so that the current diversion strategy basic table better adapts to the actual business.

[0057] Specifically, dynamically reducing the score of the existing diversion strategy according to the application frequency of the diversion strategy so that the current diversion strategy basic table better adapts to the actual business includes:

[0058] When the application frequency of the diversion strategy exceeds the maximum diversion point scenario, the score of the current diversion strategy is reduced, and the priority of the current diversion strategy is reduced.

[0059] The present invention also provides a business diversion recommendation system, which can be implemented by executing the process steps of the business diversion recommendation method, that is, those skilled in the art can understand the business diversion recommendation method as a preferred implementation of the business diversion recommendation system.

[0060] Example 2

[0061] Embodiment 2 is a preferred embodiment of Embodiment 1

[0062] A business adaptive recommendation and diversion method provided by the present invention includes:

[0063] Step 1: Develop a business model based on existing business scenarios and basic business data, and visualize it as a recommended strategy table;

[0064] Step 2: Create an adaptive recommendation diversion method based on the business diversion recommendation strategy table;

[0065] Step 3: Business diversion application, enable the adaptive recommendation diversion method;

[0066] Step 4: Business diversion data verification and data accuracy calibration;

[0067] Step 5: Evaluate the calibration data results, tune and set the adaptive recommendation algorithm, and return to step 1;

[0068] Specifically, step 1 includes: collecting data from logistics warehousing operations, warehousing receiving standards, etc. to form a strategy table. The dimensions of the strategy table include: system source (source of information flow, including Oubei Mall, Ouye Procurement, Baowu Group PSCs system, etc.), base, arrival point code, receiving department, declaration department, major category of commodity category, page category, medium category, whether consignment, hazardous chemical category, specification, brief description of materials, internal and external storage, tight storage, value, consignor weight, length, width, height, unit of measurement, commodity name, commodity code, packaging type, supplier code set; the logical relationships of the strategy table include and, or, multi-dimensional combination, equal, not equal to characters including: greater than, less than, greater than or equal to, less than or equal to calculation logic.

[0069] The information recorded in the strategy table is a free combination of various dimensions. The free combination here is not an exhaustive combination in the form of Cartesian product, but a basic strategy table configuration based on specific business requirements. The reason why it is called free combination is that it reflects the flexibility and scalability of the basic strategy table. The basic strategy table is established according to actual business requirements. The goal is to be as close to the production scenario as possible, eliminate invalid interference items, and improve the efficiency of the strategy.

[0070] As the basic data for recommending the diversion method, the initial strategy table has strong business nature. Therefore, when the strategy table is visualized, practicality is emphasized, rather than extensiveness. Therefore, when formulating the strategy table, the present invention requires sufficient market research to avoid invalid strategy table factor combinations. For example, only the system source (the source of information flow, including Oubei Mall, Ouye Procurement, Baowu Shares PSCs System, etc.), base (Qingshan Base, Baoshan Base, Zhanjiang Base, etc.), arrival point code (Wuhan arrival point, Baoshan acceptance point, Nanjing warehouse, etc.), and commodity category (office supplies, chemical products, daily necessities, etc.) are considered. If the basic strategy table is formed in an exhaustive manner, then the formed and complex combination methods may be useless data. Therefore, the present invention needs communication and research in the early stage of forming the strategy to form an effective strategy combination. For example, chemical products whose information system source is Oubei Mall can only be sent to Baoshan Base, and the acceptance point must be Baoshan acceptance point. Then we can quickly extract effective combination basic strategies from multiple dimensions: the system source is equal to Oubei Mall, the base must be Baoshan base, and the product category is chemical products, and the arrival point must be Baoshan acceptance point.

[0071] Go to step 2. In step 1, several effective strategies were extracted. Diversion itself is to improve the execution efficiency of the business. Although the invalid interference items are effectively reduced on the basis of the strategy table, it is not possible to efficiently utilize the existing diversion strategy. Therefore, in this scenario, it is necessary to adjust some algorithms of the diversion strategy table in order to achieve a higher diversion operation goal.

[0072] Combined with the actual diversion business documents, in this scenario, combined with about 1 million business data in actual applications, the application frequency of the diversion strategy basic table is dynamically sorted and adjusted, and the diversion strategy table with a higher frequency of application will be adapted first. The initial method of the adaptive diversion method is to match and score according to the existing diversion business data and the existing basic strategy table in the actual business scenario. The scoring algorithm selected here is not the only one. In order to more simply explain the operation process of the method, in this embodiment, the frequency priority method is selected to score the diversion strategy. Score the basic strategy table according to the frequency of access in the time period, with a full score of 10 points, and the highest and lowest access frequencies of the existing historical diversion business data are used as the scoring interval. Give the basic strategy a corresponding matching score. The higher the score, the higher the priority matching level of the strategy. In real business, all diversion points have job requirements. According to the highest throughput of the diversion point, set the maximum value of each matching strategy diversion point to prevent diversion overload problems.

[0073] Step 3: Select the diversion strategy to be applied and initialize the diversion method. This scenario requires the participation of the implementation personnel. It is necessary to adjust the optimal initial value of the scoring algorithm for the business scenarios that are currently and will occur in combination with the on-site diversion scenario. This is the practical application of the methods in the previous steps. You can appropriately increase the basic strategy table or change the existing basic strategy table score to achieve the best practical application experience.

[0074] Go to step 4, business diversion activates the diversion algorithm. In this scenario, when a piece or batch of business data calls the adaptive diversion method. According to the factors of the current business data, the diversion strategy with high dynamic sorting score conditions will be preferentially adapted according to the initial dynamic score. The diversions that have passed the score will be released to the corresponding diversion points, and the data that does not meet the diversion standards will be calibrated.

[0075] The business itself will also be affected by external factors, such as policies, holidays, etc. In some scenarios, the business volume at the diversion point will exceed the load. Based on the score, the corresponding matching strategy overcurrent protection is added to the partition traffic. When the system detects that the frequency exceeds the maximum value of the diversion point, the method will start the protection strategy, reduce the priority of the diversion strategy, and play an early warning feedback role.

[0076] Step 5: Update and adjust the adaptive diversion strategy. Based on the data from step 4, when the business volume accumulates to a critical value, the critical value can be set by yourself. It determines the frequency of model regression. For example, for every 5,000 new business data, the business scoring model will be regressed and evaluated. According to the frequency of business that has occurred, the existing partition strategy score will be dynamically increased or decreased to make the dynamic scoring strategy better adapt to the actual business. For scenarios with overload or too low diversion, adaptive diversion will calibrate the corresponding partition strategy table, and the strategy regression optimization is required.

[0077] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0078] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A service diversion recommendation method, characterized in that: include: Step S1: construct an initial strategy table based on the selected strategy factors and logical relationships; Step S2: Based on the initial strategy table, configure according to actual business needs, obtain the diversion strategy, and build the diversion strategy basic table; Step S3: Optimize the diversion strategy basic table and match it according to business needs.

2. The service diversion recommendation method according to claim 1, characterized in that: The step S1 comprises: Step S1.1: Select strategic factors, including: information flow source, base, arrival point code, and commodity category; Step S1.2: define the logical relationship between each strategy factor; Step S1.3: Construct an initial strategy table based on the selected strategy factors and the defined logical relationships between the strategy factors.

3. The service diversion recommendation method according to claim 1, characterized in that: The step S3 includes: constructing a scoring model, and using the scoring model to score the diversion strategies in the diversion strategy basic table, and then dynamically sorting and adjusting the diversion strategies in the diversion strategy basic table according to the scores; and configuring the matching priority based on the sorting; The scoring model scores the diversion strategy based on a preset strategy mode.

4. The service diversion recommendation method according to claim 3, characterized in that: The scoring model includes: scoring according to the application frequency of the diversion strategy; The scoring according to the application frequency of the diversion strategy includes: Obtain historical business data, count the application frequency of diversion strategies in the diversion strategy basic table in the historical business data, and score the corresponding diversion strategies according to the application frequency of the diversion strategies.

5. The service diversion recommendation method according to claim 3, characterized in that: Real-time statistics are collected on the application frequency of each diversion strategy in the diversion strategy basic table, and the score of the diversion strategy is adaptively adjusted according to the application frequency of the diversion strategy, thereby adjusting the matching priority of the diversion strategy; When the application frequency of the diversion strategy exceeds the maximum diversion point scenario, the score of the current diversion strategy is reduced, and the priority of the current diversion strategy is reduced.

6. A business diversion recommendation system, characterized in that: include: Module M1: Constructing the initial strategy table based on the selected strategy factors and logical relationships; Module M2: Based on the initial strategy table, configure according to actual business needs, obtain the diversion strategy, and build the diversion strategy basic table; Module M3: Optimize the basic table of diversion strategy and match it according to business needs.

7. The business diversion recommendation system according to claim 6, characterized in that: The module M1 comprises: Module M1.1: Selection strategy factors, including: information flow source, base, arrival point code, and commodity category; Module M1.2: Define the logical relationship between various strategic factors; Module M1.3: Construct an initial strategy table based on the selected strategy factors and the defined logical relationships between the strategy factors.

8. The business diversion recommendation system according to claim 6, characterized in that: The module M3 includes: constructing a scoring model, and using the scoring model to score the diversion strategies in the diversion strategy basic table, and then dynamically sorting and adjusting the diversion strategies in the diversion strategy basic table according to the scores; configuring matching priorities based on the sorting; The scoring model scores the diversion strategy based on a preset strategy mode.

9. The business diversion recommendation system according to claim 8, characterized in that: The scoring model includes: scoring according to the application frequency of the diversion strategy; The scoring according to the application frequency of the diversion strategy includes: Obtain historical business data, count the application frequency of diversion strategies in the diversion strategy basic table in the historical business data, and score the corresponding diversion strategies according to the application frequency of the diversion strategies.

10. The business diversion recommendation system according to claim 8, characterized in that: Real-time statistics are collected on the application frequency of each diversion strategy in the diversion strategy basic table, and the score of the diversion strategy is adaptively adjusted according to the application frequency of the diversion strategy, thereby adjusting the matching priority of the diversion strategy; When the application frequency of the diversion strategy exceeds the maximum diversion point scenario, the score of the current diversion strategy is reduced, and the priority of the current diversion strategy is reduced.

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