Logistics and asset circulation scheme determination method, medium, equipment and program product

Abstract

The invention discloses a logistics and asset circulation scheme determination method, a medium, equipment and a program product. The method comprises the following steps: acquiring a target order information set; obtaining a logistics screening strategy, wherein the logistics screening strategy comprises at least one logistics constraint condition and an order constraint condition corresponding to the logistics constraint condition; the order constraint condition is represented through a tree structure, the tree structure comprises rule nodes and logic nodes, the rule nodes are used for representing rules satisfied by order information related to the logistics constraint condition, and the logic nodes are used for representing a logic relationship between the rules; based on rule nodes and logic nodes in each tree structure, determining a target tree structure hit by the target order information set, and determining an order constraint condition represented by the target tree structure as a target order constraint condition; and obtaining a target logistics constraint condition corresponding to the target order constraint condition, and determining a target logistics scheme based on the target logistics constraint condition.

Description

Technical Field

[0001] The present application relates to the field of computer software technology, and in particular to a method, medium, device and program product for determining a logistics and asset transfer plan. Background Art

[0002] Logistics demands are becoming increasingly diverse, and orders with different attributes have different requirements for logistics solutions. Therefore, it's necessary to configure personalized logistics solutions based on the order's attributes. Currently, the industry's commonly used logistics solution configuration is implemented using a table, where each row describes a set of constraints for an order and the corresponding logistics solution for orders that meet these constraints. However, this approach is only suitable for cases with relatively simple constraints. When order constraints are complex (e.g., those involving nested and combined logical relationships), it becomes difficult to effectively configure order constraints using a table. Summary of the Invention

[0003] In a first aspect, an embodiment of the present application provides a method for determining a logistics plan, the method comprising: obtaining a target order information set input by a user; obtaining a logistics screening strategy, the logistics screening strategy comprising at least one logistics constraint and an order constraint corresponding to the logistics constraint; the order constraint is represented by a tree structure, the tree structure comprising rule nodes and logic nodes, the rule nodes being used to represent rules satisfied by order information related to the logistics constraint, and the logic nodes being used to represent logical relationships between rules; based on the rule nodes and logic nodes in each tree structure, determining a target tree structure hit by the target order information set, and determining the order constraint represented by the target tree structure as a target order constraint; obtaining a target logistics constraint corresponding to the target order constraint, and determining a target logistics plan based on the target logistics constraint.

[0004] In an embodiment of the present application, a tree structure is used to represent order constraints, wherein the tree structure includes rule nodes and logic nodes. The rule nodes are used to represent the rules satisfied by the order information related to the logistics constraints, and the logic nodes are used to represent the logical relationship between the rules. By adopting rule nodes and logic nodes and utilizing the hierarchical relationship unique to the tree structure, various complex logical relationships satisfied by the rules of the order information can be represented. Moreover, by editing each node in the tree structure, the logical relationship represented by the logic node and / or the rule represented by the rule node can be edited, so as to configure dynamic order constraints for the logistics constraints according to actual conditions, so as to finely configure logistics plans for orders under various complex constraints.

[0005] In a second aspect, an embodiment of the present application provides a method for determining an asset transfer plan, the method comprising: obtaining a target asset information set input by a user; obtaining an asset transfer strategy, the asset transfer strategy comprising at least one transfer plan constraint and an asset information constraint corresponding to the transfer plan constraint; the transfer plan constraint is used to describe the screening conditions of the asset transfer plan; the asset information constraint is represented by a tree structure, the tree structure comprising rule nodes and logic nodes, the rule nodes being used to represent the rules satisfied by the asset information related to the transfer plan constraint, and the logic nodes being used to represent the logical relationship between the rules; based on the rule nodes and logic nodes in each tree structure, determining the target tree structure hit by the target asset information set, and determining the asset information constraint represented by the target tree structure as the target asset information constraint; obtaining the target transfer plan constraint corresponding to the target asset information constraint, and determining the target asset transfer plan based on the target transfer plan constraint.

[0006] In an embodiment of the present application, a tree structure is used to represent asset information constraints, wherein the tree structure includes rule nodes and logic nodes. The rule nodes are used to represent the rules satisfied by the asset information related to the circulation scheme constraints, and the logic nodes are used to represent the logical relationship between the rules. By adopting rule nodes and logic nodes and utilizing the hierarchical relationship unique to the tree structure, various complex logical relationships satisfied by the asset information rules can be represented. Moreover, by editing each node in the tree structure, the logical relationship represented by the logic node and / or the rule represented by the rule node can be edited, so as to configure dynamic asset information constraints for the circulation scheme constraints according to actual conditions, so as to finely configure asset circulation schemes for assets under various complex constraints.

[0007] In a third aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any embodiment of the present application.

[0008] In a fourth aspect, an embodiment of the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in any embodiment of the present application when executing the computer program.

[0009] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which implements the method described in any embodiment of the present application when executed by a processor.

[0010] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The drawings herein are incorporated into the specification and constitute a part of this application. These drawings illustrate embodiments consistent with this application and, together with the specification, are used to illustrate the technical solutions of this application.

[0012] Figure 1A It is a schematic diagram of the logistics solution configuration method in the related art.

[0013] Figure 1B It is a schematic diagram of a logistics solution configuration table in the related art.

[0014] Figure 2 It is a flow chart of a method for determining a logistics plan in an embodiment of the present application.

[0015] Figure 3 It is a schematic diagram of the tree structure of an embodiment of the present application.

[0016] Figure 4 It is a schematic diagram of the process of determining the target logistics plan in an embodiment of the present application.

[0017] Figure 5 It is a schematic diagram of a visualization interface of an embodiment of the present application.

[0018] Figure 6 It is a schematic diagram of the system architecture of an embodiment of the present application.

[0019] Figure 7 It is a schematic diagram of the tree structure and status of multiple versions of an embodiment of the present application.

[0020] Figure 8 It is a schematic diagram of the conversion relationship between the states of multiple versions of an embodiment of the present application.

[0021] Figure 9 It is a schematic diagram of the approval process of an embodiment of the present application.

[0022] Figure 10 It is a schematic diagram of the online process of the rule set of an embodiment of the present application.

[0023] Figure 11 It is a flowchart of a method for determining an asset transfer plan in an embodiment of the present application.

[0024] Figure 12 It is a schematic diagram of the meta-rule model of an embodiment of the present application.

[0025] Figure 13 It is a schematic diagram of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0027] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of.

[0028] It should be understood that although the terms first, second, third, etc. may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0029] In order to enable people in this technical field to better understand the technical solutions in the embodiments of the present application, and to make the above-mentioned purposes, features and advantages of the embodiments of the present application more obvious and easy to understand, the technical solutions in the embodiments of the present application are further described in detail below with reference to the accompanying drawings.

[0030] Currently, the logistics solution configuration commonly used in the industry is implemented based on tables. Each row in the table is used to describe a set of constraints and the logistics solution corresponding to the orders that meet this set of constraints. Figure 1A The following diagram shows a specific embodiment of the logistics solution configuration method. In this solution, the logistics solution is determined based on two conditions: the product category in the order and the delivery destination of the order. Multiple rows can be written in the table, each row is used to describe a set of constraints satisfied by the product category and the delivery destination, and the logistics solution corresponding to the order that satisfies this set of constraints. Figure 1B As shown in the example, orders for mobile phones shipped to all destinations are shipped by air, while orders for baby wipes, shower gel, or toothbrushes shipped to all destinations are shipped by sea. If you need to set additional constraints beyond the product category and shipping destination, you can add at least one column to each row.

[0031] The logic of determining the logistics plan in the above configuration method is relatively simple. It only requires keyword matching of the order information entered by the user with the constraints in each row. If the order information entered by the user can simultaneously hit the constraints represented by each column in a row, the logistics plan in that row will be adopted. However, the above method is only suitable for handling situations where the constraints are relatively simple. When the constraints are relatively complex, it is difficult to effectively configure the constraints of the order through a table. For example, when a set of constraints includes multiple nested logical relationships (such as logical "and", logical "or" and logical "not") (for example, "the product category includes baby wipes, and the logistics attributes of the product include alcohol or the delivery destination of the product does not include region Y or the merchant ID includes '123' or '124'"), it is difficult to effectively configure the constraints of the order through a table.

[0032] Based on this, this application proposes a method for determining a logistics plan, see Figure 2 , the method comprising:

[0033] Step S12: Obtain the target order information set input by the user;

[0034] Step S14: Obtaining a logistics screening strategy, wherein the logistics screening strategy includes at least one logistics constraint and an order constraint corresponding to the logistics constraint. The order constraint is represented by a tree structure, which includes rule nodes and logic nodes. The rule nodes are used to represent rules satisfied by order information related to the logistics constraint, and the logic nodes are used to represent logical relationships between rules.

[0035] Step S16: determining a target tree structure hit by the target order information set based on the rule nodes and logic nodes in each tree structure, and determining the order constraint condition represented by the target tree structure as the target order constraint condition;

[0036] Step S18: Obtain target logistics constraints corresponding to the target order constraints, and determine a target logistics plan based on the target logistics constraints.

[0037] The embodiment of the present application uses a tree structure to represent order constraints. The tree structure includes rule nodes and logic nodes. Rule nodes are used to represent the rules satisfied by the order information related to the logistics constraints, and logic nodes are used to represent the logical relationships between the rules. By using rule nodes and logic nodes and utilizing the hierarchical relationships unique to the tree structure, it is possible to represent various complex logical relationships satisfied by the rules of the order information, thereby enabling the refined configuration of logistics solutions for orders under various complex constraints. The following examples illustrate the implementation details of the embodiment of the present application.

[0038] In an actual application scenario, the method of the embodiment of the present application can be applied to the server of an e-commerce platform. The server can interact with the client of the e-commerce platform.

[0039] The logistics plan in the embodiments of this application may include, but is not limited to, the mode of transportation (e.g., air transport, sea transport), the logistics company responsible for delivery, protection measures for logistics objects (e.g., refrigerated transportation), and / or logistics timeliness (e.g., same-day delivery, next-day delivery), etc. The specific content included in the logistics plan can be set according to actual needs and is not limited by this application.

[0040] In step S12, the user can input the target order information set through the client, and the server can obtain the target order information set input by the user through the client. The target order information set frame may include at least one order information. The order information includes but is not limited to at least one of the following: category information of the goods in the order (such as clothing, skin care products, electronic products, office supplies, etc.), product attribute information (such as magnetic, dotted, alcohol-containing, etc.), size information, price information, delivery destination, and shipping merchant information. Different order information may be suitable for different logistics solutions. By obtaining the target order information set, a logistics solution can be refined and customized for the user based on the order information in the target order information set.

[0041] In step S14, a logistics screening strategy may be obtained. The logistics screening strategy may be pre-configured and stored on the server. The logistics screening strategy may include logistics constraints and their corresponding order constraints.

[0042] Logistics constraints are used to represent the conditions that a logistics plan must meet. In some embodiments, the logistics constraints include an association between the logistics plan and the order constraints. The association may include a binding relationship and an exclusion relationship.

[0043] A binding relationship represents the binding of logistics solutions included in the logistics constraints to the logistics solutions corresponding to order information that satisfies the order constraints. For example, suppose the logistics solution included in the logistics constraints includes a delivery method, and that delivery method is air freight. The order information includes a product category, and the order constraints include the product category of mobile phones. This binding relationship means that the logistics solution corresponding to mobile phones is bound to the delivery method of air freight. This means that the target logistics solution obtained should be the one that uses air freight as the delivery method.

[0044] The exclusion relationship indicates that, from the logistics solutions corresponding to order information that satisfies the order constraints, the logistics solutions included in the logistics constraints are excluded. For example, suppose the logistics solutions included in the logistics constraints include a delivery method, and that delivery method is air freight. The order information includes a product category, and the order constraints include the product category of mobile phones. This exclusion relationship can mean that, from the logistics solutions corresponding to mobile phones, air freight is excluded as a delivery method. In other words, the target logistics solution ultimately obtained should be a delivery solution that does not use air freight.

[0045] Order constraints are used to represent the conditions that order information must satisfy. Order constraints can be represented using a tree structure. The tree structure includes rule nodes, which are used to represent the rules that order information must satisfy related to logistics constraints. Different types of order information may require different conditions. Assuming that order information includes the product category to which the goods in the order belong, the order's delivery destination, the shipping merchant's ID, and the order's logistics attributes, you can set conditions corresponding to the product category, the delivery destination, the shipping merchant's ID, and the logistics attributes of the order, respectively.

[0046] In some embodiments, a rule node includes an lvalue item, an rvalue item, and an operation item, wherein the lvalue item is used to represent the type of order information, the rvalue item is used to represent the content of the order information, and the operation item is used to represent the inclusion relationship between the lvalue item and the rvalue item. The rule represented by the rule node can be a dynamic rule obtained by processing the lvalue item and the rvalue item through the inclusion relationship represented by the operation item. By configuring the lvalue item, the rvalue item, and / or the operation item, different rules can be configured, and then different order constraints can be represented by the configured rules, thereby adapting to different application scenarios.

[0047] The above-mentioned inclusion relationships include "include" and "do not include". "Include" means that the specific type of order information represented by the left-hand item includes the content of the order information represented by the right-hand item, and "do not include" means that the specific type of order information represented by the left-hand item does not include the content of the order information represented by the right-hand item. For example, assuming that the left-hand item is the delivery destination of the order and the right-hand item is "the United States", when the inclusion relationship represented by the above-mentioned operation item is "include", the rule represented by the rule node is "the delivery destination of the order includes the United States"; when the inclusion relationship represented by the above-mentioned operation item is "do not include", the rule represented by the rule node is "the delivery destination of the order does not include the United States".

[0048] In some embodiments, the right-hand side item may include one or more values. When the right-hand side item of a rule node includes multiple values, the logical relationship between the multiple values is a logical OR. For example, if the left-hand side item is the delivery destination, the operation item indicates the inclusion relationship of "includes," and the right-hand side item includes "United States" and "Australia," then the rule represented by the rule node is: "The delivery destination includes either the United States or Australia."

[0049] The tree structure also includes logic nodes, which represent logical relationships between rules. In some embodiments, the logic nodes include rule operators for representing logical relationships. Order constraints are dynamic constraints derived by operating the rule operators included in the logic nodes on the rules represented by the rule nodes. By configuring the logic nodes and / or rule nodes, a variety of order constraints can be represented according to actual needs.

[0050] Logical relationships include logical AND and logical OR. By using logical nodes, multiple rules can be combined in complex logic. For example, suppose one rule node represents the rule "the order's delivery destination does not include the United States," and another rule node represents the rule "the product category includes mobile phones." And if the logical relationship represented by the logical node is logical AND, then the rule represented by this logical node and the two rule nodes is "the order's delivery destination does not include the United States, and the product category includes mobile phones."

[0051] In some embodiments, the tree structure includes at least three layers. The first layer is the root node, which is a logical node. The second layer is the child nodes of the root node, which may include logical nodes or rule nodes. The third layer nodes are the child nodes of the second layer nodes, which may include logical nodes or rule nodes. The leaf nodes of the tree structure are rule nodes. Figure 3 As shown, the logical relationship represented by the root node L0 is logical AND. The root node L0 includes four child nodes, which are respectively recorded as node L11, node L12, node L13 and node L14. Among them, node L11, node L12 and node L13 are rule nodes, and node L14 is a logical node. Node L14 includes two nodes, node L21 and node L22, and both node L21 and node L22 are rule nodes. The rules represented by each rule node are shown in the text in the oval figure in the figure. Then, Figure 3 The order constraints represented by the tree structure in are:

[0052] The category includes skin care products or hair care products;

[0053] And the logistics properties do not include strong magnetism or alcohol;

[0054] and the destination includes the United States or Australia;

[0055] And it meets the following requirements: the merchant ID contains (123 or 124), or the logistics attribute contains lighter.

[0056] It can be seen that by adopting a tree structure and defining rule nodes and logic nodes in the tree structure, various rules and their complex logical combination relationships can be expressed, thereby enabling the refined determination of logistics plans based on order information in multiple dimensions.

[0057] One or more tree structures may be generated in advance, and logistics constraints corresponding to each tree structure may be generated. Then, an association relationship between the tree structure and the corresponding logistics constraints may be established to obtain a logistics screening strategy.

[0058] After obtaining the logistics screening strategy, in step S16, the target order information set input by the user may be matched with each tree structure in the logistics screening strategy to determine the target tree structure hit by the target order information set.

[0059] Specifically, if the logical relationship represented by the root node of the tree structure is logical and, when the target order information set matches the rules represented by each subtree with the child node of the root node as the root node, the tree structure is determined to be the target tree structure hit by the target order information set; when the target order information set does not match the rule represented by any subtree with the child node of the root node as the root node, it is determined that the target order information set does not hit the tree structure.

[0060] If the logical relationship represented by the root node of the tree structure is a logical OR, when the target order information set matches the rule represented by any subtree with the child node of the root node as the root node, the tree structure is determined to be the target tree structure hit by the target order information set; when the target order information set does not match the rules represented by each subtree with the child node of the root node as the root node, it is determined that the target order information set does not hit the tree structure.

[0061] The rules represented by the subtree are determined based on the logical relationships represented by the respective logic nodes on the subtree and the rules represented by the respective rule nodes on the subtree.

[0062] Below is Figure 3 Taking the tree structure shown in FIG. 1 as an example, the process of determining the target tree structure is described.

[0063] like Figure 3As shown, the logical relationship represented by the root node of the tree structure is logical AND. The child nodes of the root node include node L11, node L12, node L13 and node L14. Therefore, the subtrees with the child nodes of the root node as the root node include the subtree with node L11 as the root node (that is, node L11 itself, hereinafter referred to as subtree 1), the subtree with node L12 as the root node (that is, node L12 itself, hereinafter referred to as subtree 2), the subtree with node L13 as the root node (that is, node L13 itself, hereinafter referred to as subtree 3) and the subtree with node L14 as the root node (including node L14 and its two child nodes L21 and L22, hereinafter referred to as subtree 4). If the target order information set matches the rules represented by subtree 1, the rules represented by subtree 2, the rules represented by subtree 3 and the rules represented by subtree 4, it means that the target order information set hits Figure 3 The tree structure shown, therefore, Figure 3 The tree structure shown is the target tree structure.

[0064] Among them, subtree 1, subtree 2 and subtree 3 each contain a rule node. Therefore, when matching the target order information set with these subtrees, it is only necessary to determine whether the order information in the target order information set satisfies the rule described by the rule node. Taking subtree 1 as an example, if the destination in the target order information set includes the United States or Australia, the target order information set matches the rule represented by subtree 1; if the destination in the target order information set does not include the United States or Australia, the target order information set does not match the rule represented by subtree 1. The matching method of the target order information set with subtree 2 and subtree 3 is also similar and will not be repeated here.

[0065] Because subtree 4 contains multiple nodes, each node in subtree 4 must be considered when matching the target order information set with subtree 4. Because the logical relationships represented by the logical nodes in subtree 4 are logical OR, the target order information set only needs to meet the rules represented by any child node of that logical node to be considered a match with subtree 4.

[0066] If Figure 3 If the logical relationship represented by the root node of the tree structure shown is changed to a logical OR, then as long as the target order information set successfully matches one of the rules represented by subtree 1, the rules represented by subtree 2, the rules represented by subtree 3, and the rules represented by subtree 4, the tree structure becomes the target tree structure. The specific matching method can be referred to in the previous embodiment and will not be repeated here.

[0067] After the target tree structure is determined, the order constraints represented by the target tree structure may be determined as target order constraints.

[0068] In step S18, the initial logistics plan set can be screened based on the target logistics constraints to obtain the target logistics plan. Figure 4 The initial logistics plan can include plans A, B, C, D, E and F. After the user places an order, the order information can be extracted from the target order information set, including product category, delivery destination, merchant ID and logistics attributes. Then, the extracted order information is matched with the rule tree (i.e., tree structure) in the logistics screening strategy. Figure 4 As can be seen, the order information successfully matches Rule Trees 1 and 3, but fails to match Rule Trees 2 and 4. The logistics constraints corresponding to Rule Tree 1 include binding Plans G, H, and I to the logistics plans corresponding to order information that meets the corresponding order constraints. The logistics constraints corresponding to Rule Tree 3 include excluding Plans C and D from the logistics plans corresponding to order information that meets the corresponding order constraints. Therefore, Plans G, H, and I can be added to the initial logistics plan, while Plans C and D can be deleted. The resulting target logistics plan includes Plans A, B, E, F, G, H, and I.

[0069] In some embodiments, an initial set of logistics solutions can be screened based on target logistics constraints to obtain at least one candidate logistics solution, and a target logistics solution selected by the user from the at least one candidate logistics solution can be obtained. Continuing with the previous example, solutions A, B, E, F, G, H, and I can be presented to the user via the client as candidate logistics solutions. The user can then select one of these candidate logistics solutions as the target logistics solution via the client.

[0070] In some embodiments, a logistics screening policy can be pre-edited by the user. Specifically, the server can provide a visual interface to which the user can send a request to create a logistics screening policy. In response to receiving the request to create a logistics screening policy, the server displays a first edit item for editing logistics constraints and a second edit item for editing order constraints on the visual interface. The user can also perform editing operations on the visual interface. The server can generate logistics constraints based on the user's first edit operation on the first edit item, generate order constraints based on the user's second edit operation on the second edit item, and create a logistics screening policy based on the generated logistics constraints and order constraints. The second edit item includes a first sub-item for editing a rule node and a second sub-item for editing a logic node. The second edit operation includes an edit operation on the first sub-item and an edit operation on the second sub-item. Edit operations include a create operation (for creating a new first sub-item or second sub-item), a delete operation (for deleting an already created first sub-item or second sub-item), and / or a modify operation (for modifying an already created first sub-item or second sub-item).

[0071] Figure 5 A schematic diagram of the visualization interface is shown. Figure 5 As shown in the figure, users can edit logistics constraints through the first editing item. The first editing item includes sub-items for inputting logistics plans and sub-items for selecting association relationships. Users can input logistics plan information in the sub-items for inputting logistics plans, as shown in "Scheme A", "Scheme B" and "Scheme C" in the figure. Users can also select the association relationship as a binding relationship or an exclusion relationship through the sub-item for selecting the association relationship. Figure 5 The relationship shown is a binding relationship. Users can also edit order constraints through the second editing option. Figure 5 The order constraints shown already include the category ID, logistics attributes, delivery destination, merchant ID, and logistics attributes. In addition to the conditions shown in the figure, users can create new first sub-items by creating a first sub-item to add a new rule node to the rule tree, and create new second sub-items by creating a second sub-item to add a new logical node to the rule tree. Furthermore, users can delete edited first or second sub-items by deleting a first or second sub-item, respectively.

[0072] Furthermore, the first sub-item may include a sub-item for editing the left-hand item, a sub-item for editing the right-hand item, and a sub-item for editing the operation item. After the user creates the first sub-item, the three sub-items may be displayed in the created first sub-item, allowing the user to edit the order information type, the order information content, and the inclusion relationship between the left-hand item and the right-hand item, respectively.

[0073] The above embodiments provide a visual or programmatic way to define rules. Users can add, delete, and modify nodes and branches in the rule tree through interface operations, thereby building complex rule logic. When the rule tree is matched, the input data is processed according to the structure and definition of the rule tree. Starting from the root node, the input order information is judged according to the conditions of the node, and the operations of subsequent nodes are performed along the corresponding branches until the leaf node is reached to obtain the final result. The above process supports dynamic updating of rules while the system is running. When the service rules change, the structure and content of the rule tree can be easily modified without stopping the entire system, which enables the system to quickly adapt to changing service needs.

[0074] The following is an example of the system architecture and overall process of the embodiment of the present application with reference to the accompanying drawings. The embodiment of the present application mainly includes three modules: rule set management module, rule tree configuration module and logistics solution matching module. Figure 6 shown.

[0075] Through the rule set management module, users can manage the version of the rule tree, such as creating a new rule set version or deleting a rule tree version. They can also manage the status of each rule version. The status of the rule tree version includes enabled and disabled states, such as Figure 7 As shown in , if there are multiple rule tree versions, one of them can be set to enabled and the others can be set to disabled. Furthermore, the status of the rule tree version can also include other states, such as draft, testing, deleted, etc. Figure 8 After the user creates or copies a rule tree version, the rule tree version is in the draft state. The user can test the rule tree version in the draft state, so that the rule tree version switches to the testing state. If the test fails, it returns to the draft state after the test. If the test passes, the rule tree version can be enabled and switched to the enabled state. The rule tree version in the enabled state can be disabled, thus switching to the disabled state. In addition, the rule tree in the draft state can be deleted, thus switching to the deleted state. For further information, see Figure 9 Before enabling a rule set, you can review it online. Only approved rule sets are synchronized online. If approval is rejected or withdrawn, the rule set version returns to the testing state. Additionally, you can control user account permissions to prevent unauthorized users from editing the rule tree and its versions. User operations on the rule tree and its versions can also be recorded in the operation log for later review.

[0076] The Rule Tree configuration module can be used to configure the Rule Tree. For details on how to configure the Rule Tree, refer to Figure 5The corresponding embodiments are not described here. Multiple rule trees can be configured in a version of the rule set. Each rule tree can be configured with a proprietary name to describe the configured rules. This module supports online real-time configuration of the rule tree. Users do not need to upload the offline configuration form to the system, which makes the configuration efficiency higher. In some embodiments, the background can also verify the configuration of the rule tree according to preset verification rules. For example, it can verify whether the information entered by the user is legal (such as whether the value range is within the preset range) and whether necessary configuration information in the rule tree is missing. After configuring the rule tree, the rule tree can be tested for matching. Specifically, at least one item of information included in the rule tree can be entered and tested to see whether the rule tree can be filtered out by the entered information. If so, the test passes; otherwise, the test fails. After the test passes, the configuration of the rule tree can be saved. Through the logistics plan matching module, it is possible to match and filter logistics plans based on conditions such as product category, merchant ID, logistics attributes, destination, freight template, etc. In the embodiment of the present application, the configured rule tree can be tested by testing traffic. After the test is passed, the rule tree can be put into formal use and the target logistics plan can be determined for the formal traffic. Figure 10 After the rule set configuration is completed and approved and put online, the currently effective rule set version is updated to the database and online cache, and officially takes effect on online line selection traffic.

[0077] See also Figure 11 , an embodiment of the present application further provides a method for determining an asset transfer plan, the method comprising:

[0078] Step S22: Acquire the target asset information set input by the user;

[0079] Step S24: Obtain an asset transfer strategy, wherein the asset transfer strategy includes at least one transfer plan constraint and an asset information constraint corresponding to the transfer plan constraint. The transfer plan constraint is used to describe the screening conditions of the asset transfer plan. The asset information constraint is represented by a tree structure, which includes rule nodes and logic nodes. The rule nodes are used to represent rules satisfied by asset information related to the transfer plan constraint, and the logic nodes are used to represent logical relationships between rules.

[0080] Step S26: determining a target tree structure hit by the target asset information set based on the rule nodes and logic nodes in each tree structure, and determining the asset information constraint condition represented by the target tree structure as the target asset information constraint condition;

[0081] Step S28: Obtain target transfer plan constraints corresponding to the target asset information constraints, and determine the target asset transfer plan based on the target transfer plan constraints.

[0082] The assets in this embodiment can be the orders in the aforementioned embodiments, the target asset information set corresponds to the target order information set in the aforementioned embodiments, the asset circulation strategy corresponds to the logistics screening strategy in the aforementioned embodiments, the circulation plan constraints correspond to the logistics constraints in the aforementioned embodiments, the asset information constraints correspond to the order constraints in the aforementioned embodiments, and the asset circulation plan corresponds to the logistics plan in the aforementioned embodiments.

[0083] In addition, in addition to being applicable to the logistics scenarios in the aforementioned embodiments, the embodiments of the present application can also be applied to other scenarios that require asset transfer and delivery.

[0084] For example, in a financial investment scenario, investors need to select an investment portfolio that suits them from a wide range of financial products based on factors such as their own risk tolerance and investment objectives. In this scenario, the constraints of the circulation plan may include the investment risk level (such as low risk, medium risk, high risk), the investment period (short-term, medium-term, long-term), the expected rate of return, etc., and the asset information constraints may include the type of financial product (stocks, bonds, funds, etc.), the product's historical performance, the reputation of the issuing institution, etc. Investors can enter their own target asset information set, including their investment goals and risk preferences. The system will then select an investment portfolio plan that meets the investor's needs based on the preset asset circulation strategy, through the rule nodes in the tree structure (such as rules corresponding to product type and risk level) and the logic nodes (such as logical relationships such as "and" and "or").

[0085] For example, in the field of intellectual property, when an enterprise or individual transfers or licenses intellectual property, it is necessary to match the appropriate intellectual property according to the needs and conditions of the transferee. The constraints of the transfer plan may include the type of intellectual property (patents, trademarks, copyrights, etc.), technical fields, and licensing methods (exclusive licenses, exclusive licenses, etc.). Asset information constraints may include the legal status of the intellectual property (valid, invalid, expired, etc.), technological maturity, market application prospects, etc. The transferee can input the demand information of the target intellectual property, and the system will screen out the intellectual property transfer plans that meet the transferee's requirements according to the asset transfer strategy through the rule nodes and logical nodes in the tree structure, such as a list of transferable patents.

[0086] Figure 12A schematic diagram of a meta-rule model for implementing a tree structure in an embodiment of the present application is shown. A tenant ID, scenario ID, and rule meta-configuration list can be defined in the meta-rule model. The tenant ID is used to uniquely identify a tenant, and the scenario ID is used to uniquely identify a scenario. A tenant can be a tenant managing logistics solutions, a tenant managing financial investment solutions, or a tenant managing intellectual property services, among others. Accordingly, a scenario can be a logistics distribution scenario, a financial investment scenario, or an intellectual property scenario, among others. The meta-rule configuration can define the tenant ID, scenario ID, meta-configuration ID, meta-configuration type (e.g., string), and the types of operations supported by the meta-configuration. Rule sets can also be defined, and their configuration permissions, status, version, and approval status can be managed. A rule set can define information such as the tenant ID, scenario ID, the user's ID and name who configured the rule set, the current status of the rule set, the configuration name, the configuration file path, the number of rules, the environment, the approval status, the approval flow ID, and a list of rule trees. A rule set can include one or more rule trees, which can be implemented based on a JSON structure and include nodes and associated information. A node includes a left value, a matching type (i.e., an operation item), a right value, and child nodes; associated information includes a key, a name, and a value.

[0087] Through the above-mentioned meta-rule model, users only need to define the parameters of the meta-rule model under various application scenarios to screen and fine-tune the target asset transfer plans under various scenarios. There is no need to configure the target asset transfer plan under each condition through code, which realizes low-code configuration processing and reduces development costs.

[0088] An embodiment of the present application further provides a computer device, which comprises at least a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in any of the aforementioned embodiments is implemented.

[0089] Figure 13 1 shows a more specific hardware structure diagram of a computer device provided in an embodiment of the present application. The device may include: a processor 102, a memory 104, an input / output interface 106, a communication interface 108, and a bus 110. The processor 102, the memory 104, the input / output interface 106, and the communication interface 108 are connected to each other within the device via the bus 110.

[0090] The processor 102 can be implemented using a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is configured to execute relevant programs to implement the technical solutions provided in the embodiments of the present application. The processor 102 can also include a graphics card, which can be an Nvidia Titan X graphics card or an 1080Ti graphics card.

[0091] The memory 104 can be implemented in the form of a read-only memory (ROM), a random access memory (RAM), a static storage device, a dynamic storage device, etc. The memory 104 can store an operating system and other application programs. When the technical solutions provided in the embodiments of the present application are implemented through software or firmware, the relevant program codes are stored in the memory 104 and are called and executed by the processor 102.

[0092] The input / output interface 106 is used to connect input / output modules to implement information input and output. The input / output modules can be configured as components within the device (not shown) or can be externally connected to the device to provide corresponding functions. Input devices may include a keyboard, mouse, touch screen, microphone, various sensors, etc., and output devices may include a display, speaker, vibrator, indicator light, etc.

[0093] The communication interface 108 is used to connect to a communication module (not shown) to enable communication between the device and other devices. The communication module can communicate via a wired method (such as USB, network cable, etc.) or a wireless method (such as mobile network, Wi-Fi, Bluetooth, etc.).

[0094] The bus 110 comprises a pathway for transmitting information between the various components of the device, such as the processor 102 , the memory 104 , the input / output interface 106 , and the communication interface 108 .

[0095] It should be noted that although the above device only shows the processor 102, the memory 104, the input / output interface 106, the communication interface 108, and the bus 110, in a specific implementation, the device may also include other components necessary for normal operation. In addition, it will be understood by those skilled in the art that the above device may only include the components necessary to implement the embodiments of the present application, and does not necessarily include all the components shown in the figure.

[0096] An embodiment of the present application provides a computer program product, including a computer program, which implements the method described in any embodiment of the present application when executed by a processor.

[0097] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any of the aforementioned embodiments.

[0098] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be used to store information using any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computer device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0099] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The device embodiment described above is merely illustrative, wherein the modules described as separate components may or may not be physically separated, and the functions of each module can be implemented in the same one or more software and / or hardware when implementing the embodiment of this application. It is also possible to select some or all of the modules according to actual needs to achieve the purpose of the embodiment. Those of ordinary skill in the art can understand and implement it without paying any creative work.

[0100] The above is only a specific implementation of the embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the embodiment of the present application. These improvements and modifications should also be regarded as the scope of protection of the embodiment of the present application.

Claims

1. A method for determining a logistics plan, the method comprising: Get the target order information set entered by the user; Obtaining a logistics screening strategy, where the logistics screening strategy includes at least one logistics constraint and an order constraint corresponding to the logistics constraint; The order constraints are represented by a tree structure, which includes rule nodes and logic nodes. The rule nodes are used to represent the rules satisfied by the order information related to the logistics constraints, and the logic nodes are used to represent the logical relationships between the rules. Determine, based on the rule nodes and logic nodes in each tree structure, a target tree structure hit by the target order information set, and determine the order constraint condition represented by the target tree structure as the target order constraint condition; Obtain target logistics constraints corresponding to the target order constraints, and determine a target logistics plan based on the target logistics constraints.

2. According to the method of claim 1, the logic node includes a rule operator for representing the logical relationship, and the order constraint condition is a dynamic constraint condition obtained by operating the rule represented by the rule node through the rule operator included in the logic node.

3. According to the method of claim 1, the rule node includes a left value item, a right value item and an operation item, the left value item is used to represent the type of order information, the right value item is used to represent the content of the order information, and the operation item is used to represent the inclusion relationship between the left value item and the right value item.

4. The method according to claim 3, wherein the rule represented by the rule node is a dynamic rule obtained by processing the left value item and the right value item through the inclusion relationship represented by the operation item.

5. The method according to claim 3, wherein the inclusion relationship is used to represent: The specific type of order information represented by the left value item contains the content of the order information represented by the right value item; or The specific type of order information represented by the left value item does not include the content of the order information represented by the right value item.

6. The method according to claim 1, wherein the logistics constraint conditions include an association relationship between the logistics plan and the order constraint conditions, and the association relationship includes: A binding relationship is used to indicate that, among the logistics plans corresponding to the order information that meets the order constraint conditions, the logistics plans included in the logistics constraint conditions are bound; or The exclusion relationship is used to indicate that, among the logistics plans corresponding to the order information that meets the order constraint conditions, the logistics plans included in the logistics constraint conditions are excluded.

7. The method according to claim 1, wherein determining the target tree structure hit by the target order information set based on the rule nodes and logic nodes in each tree structure comprises: If the logical relationship represented by the root node of the tree structure is a logical AND, and if the target order information set matches the rules represented by each subtree with the child node of the root node as the root node, the tree structure is determined to be the target tree structure hit by the target order information set; otherwise, the target order information set is determined to not hit the tree structure; If the logical relationship represented by the root node of the tree structure is a logical OR, and if the target order information set matches the rule represented by any subtree with a child node of the root node as the root node, the tree structure is determined to be the target tree structure hit by the target order information set; otherwise, the target order information set is determined to not hit the tree structure; The rules represented by the subtree are determined based on the logical relationships represented by the respective logic nodes on the subtree and the rules represented by the respective rule nodes on the subtree.

8. The method according to claim 1, wherein determining a target logistics solution based on the target logistics constraint condition comprises: The initial logistics plan set is screened based on the target logistics constraint conditions to obtain the target logistics plan.

9. The method according to claim 8, wherein the screening of the initial logistics plan set based on the target logistics constraint condition to obtain the target logistics plan comprises: Screening the initial logistics plan set based on the target logistics constraint condition to obtain at least one candidate logistics plan; A target logistics plan selected by a user from the at least one candidate logistics plan is obtained.

10. The method according to claim 1, further comprising: In response to receiving a request to create a logistics screening policy, a first editing item for editing logistics constraints and a second editing item for editing order constraints are displayed on a visual interface; the order constraints are represented by a tree structure, the tree structure including rule nodes and logic nodes, the rule nodes representing rules satisfied by order information related to the logistics constraints, and the logic nodes representing logical relationships between the rules; generating a logistics constraint condition based on a first editing operation of the user on the first editing item; generating an order constraint condition based on a second editing operation of the user on the second editing item; Create a logistics screening strategy based on the generated logistics constraints and generated order constraints; The second editing item includes a first sub-item for editing the rule node and a second sub-item for editing the logic node, and the second editing operation includes an editing operation on the first sub-item and an editing operation on the second sub-item.

11. A method for determining an asset transfer plan, the method comprising: Get the target asset information set input by the user; Obtaining an asset transfer strategy, the asset transfer strategy including at least one transfer plan constraint and an asset information constraint corresponding to the transfer plan constraint; the transfer plan constraint describing a screening condition for the asset transfer plan; the asset information constraint represented by a tree structure including rule nodes and logic nodes, the rule nodes representing rules satisfied by asset information related to the transfer plan constraint, and the logic nodes representing logical relationships between rules; Determine a target tree structure hit by the target asset information set based on rule nodes and logic nodes in each tree structure, and determine the asset information constraint condition represented by the target tree structure as the target asset information constraint condition; Obtain target transfer plan constraints corresponding to the target asset information constraints, and determine a target asset transfer plan based on the target transfer plan constraints.

12. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 11 is implemented.

13. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 11 when executing the computer program.

14. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 11 is implemented.

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