Information generation method and device, equipment, medium and program product

Abstract

The embodiment of the invention discloses an information generation method and device, equipment, a medium and a program product. A specific embodiment of the method comprises the steps of determining an obtained value attribute net value influence factor set for a logistics party and an article demand influence factor set for an article value circulation party; according to the value attribute net value influence factor set and the article demand influence factor set, generating and obtaining a value attribute net value generation model and an article demand determination model; according to the obtained value attribute net value generation model and the article demand determination model, generating an obtained value attribute net value constraint model; according to the obtained value attribute net value constraint model, generating an influence factor optimization expression information set; and generating value attribute net value optimal information according to the obtained value attribute net value generation model and the influence factor optimization expression information set. The implementation mode is related to the intelligent supply chain, and the optimal information of the net value of the obtained value attribute can be accurately determined.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technology, and in particular to information generation methods, devices, equipment, media, and program products. Background Art

[0002] At present, third-party logistics parties can not only provide logistics services for the value transfer parties of goods, but also provide value-related operation services for goods. Logistics services and value-related operation services for goods can bring net value of value attributes to third-party logistics parties. For the generation of the total net value of value attributes, the commonly used method is: first, the first net value of value attributes for logistics services is determined by the logistics service provision department. Then, the second net value of value attributes for value operation services is determined by the value-related operation execution department. Finally, the sum of the first net value of value attributes and the second net value of value attributes is determined as the total net value of value attributes.

[0003] However, the inventors have found that when the above method is used to generate the total net value of the value attribute, the following technical problems often occur:

[0004] The logistics service provider and the item value-related operation execution department usually only consider the optimal net value of the acquired value attribute corresponding to their own department. From the overall perspective, it may lead to the situation that the total net value of the acquired value attribute obtained by the third-party logistics party is not the optimal net value of the acquired value attribute.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the inventive concept and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art. Summary of the invention

[0006] The content of this disclosure is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this disclosure is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0007] Some embodiments of the present disclosure propose information generation methods, devices, equipment, media and program products to solve the technical problems mentioned in the above background technology section.

[0008] In a first aspect, some embodiments of the present disclosure provide an information generation method, including: determining a set of influencing factors for a net value of acquired value attributes for a logistics party and a set of influencing factors for item demand for an item value circulation party, wherein the set of influencing factors for the net value of acquired value attributes includes: a logistics service level parameter, a circulation item value parameter, a circulation item demand parameter, and the set of influencing factors for item demand includes: the logistics service level parameter and the item value interest rate parameter; generating a net value of acquired value attribute generation model and an item demand determination model based on the set of influencing factors for the net value of acquired value attributes and the set of influencing factors for item demand; generating a net value of acquired value attribute generation model and an item demand determination model based on the set of influencing factors for the net value of acquired value attributes and the set of influencing factors for the item demand; and The net value generation model of value attributes and the above-mentioned item demand determination model are used to generate a constraint model for obtaining the net value of value attributes; based on the above-mentioned constraint model for obtaining the net value of value attributes, an optimized expression information group of influencing factors is generated, wherein the optimized expression information group of influencing factors includes: optimized expression information for the above-mentioned logistics service level parameters, optimized expression information for the above-mentioned circulation item value parameters, optimized expression information for the above-mentioned circulation item demand parameters, and optimized expression information for the above-mentioned item value interest rate parameters; based on the above-mentioned net value generation model for obtaining the net value of value attributes and the above-mentioned optimized expression information group of influencing factors, the optimal information for obtaining the net value of value attributes is generated.

[0009] Optionally, the above-mentioned determination of the set of influencing factors for obtaining the net value of value attributes for the logistics party and the set of influencing factors for item demand for the item value transfer party includes: determining the set of influencing factors for obtaining the net value of value attributes and the set of influencing factors for item demand based on service provision architecture information, wherein the above-mentioned service provision architecture information represents the architecture information of the above-mentioned logistics party providing logistics services and value information services to the above-mentioned item value transfer party.

[0010] Optionally, the above-mentioned generation of the net value of acquired value attributes and the above-mentioned influencing factor optimization expression information group set is used to generate the optimal information on the net value of acquired value attributes, including: determining the influencing factor optimization information group corresponding to each influencing factor optimization expression information group in the above-mentioned influencing factor optimization expression information group set to obtain the influencing factor optimization information group set; inputting each influencing factor optimization information group in the above-mentioned influencing factor optimization information group set into the above-mentioned net value of acquired value attributes generation model to generate the net value of acquired value attributes and obtain the net value set of acquired value attributes; determining the net value of acquired value attributes that meets the preset value condition in the above-mentioned net value set of acquired value attributes as the optimal information on the net value of acquired value attributes.

[0011] Optionally, the method further includes: determining an influencing factor optimization information group corresponding to the above-mentioned optimal information on obtaining the net value of the value attribute as a target influencing factor optimization information group; and sending the above-mentioned target influencing factor optimization information group to a client corresponding to the above-mentioned item value transfer party.

[0012] Optionally, the above-mentioned generation of an optimized expression information set of influencing factors based on the above-mentioned net value constraint model for obtaining value attributes includes: generating a Hessian matrix for the above-mentioned net value constraint model for obtaining value attributes; determining whether the above-mentioned net value constraint model for obtaining value attributes is a convex programming solution model based on the Hessian matrix; and in response to determining that it is not, generating an optimized expression information set of influencing factors.

[0013] Optionally, the method further includes: updating the service provision architecture information according to the optimal information of the net value of the value attribute, to obtain updated service provision architecture information; and sending the updated service provision architecture information to the client corresponding to the logistics party.

[0014] In a second aspect, some embodiments of the present disclosure provide an information generating device, including: a determining unit, configured to determine a set of influencing factors for acquiring a net value attribute for a logistics party and a set of influencing factors for item demand for an item value circulation party, wherein the set of influencing factors for acquiring a net value attribute includes: logistics service level parameters, circulation item value parameters, circulation item demand parameters, and the set of influencing factors for item demand includes: the logistics service level parameters and item value interest rate parameters; a first generating unit, configured to generate a net value acquisition attribute generation model and an item demand determination model based on the set of influencing factors for acquiring a net value attribute and the set of influencing factors for item demand; a second generating unit, configured to generate a net value acquisition attribute generation model and an item demand determination model based on the set of influencing factors for acquiring a net value attribute and the set of influencing factors for item demand; According to the above-mentioned net value generation model for acquiring value attributes and the above-mentioned item demand determination model, a net value constraint model for acquiring value attributes is generated; the third generation unit is configured to generate an influencing factor optimization expression information group set according to the above-mentioned net value constraint model for acquiring value attributes, wherein the influencing factor optimization expression information group includes: optimization expression information for the above-mentioned logistics service level parameters, optimization expression information for the above-mentioned circulation item value parameters, optimization expression information for the above-mentioned circulation item demand parameters, and optimization expression information for the above-mentioned item value interest rate parameters; the fourth generation unit is configured to generate optimal information on the net value of acquired value attributes according to the above-mentioned net value generation model for acquiring value attributes and the above-mentioned influencing factor optimization expression information group set.

[0015] Optionally, the determination unit can be configured to: determine the above-mentioned set of influencing factors for obtaining the net value of value attributes and the above-mentioned set of influencing factors for item demand based on service provision architecture information, wherein the above-mentioned service provision architecture information represents the architecture information of the above-mentioned logistics direction providing logistics services and value information services to the above-mentioned item value transfer party.

[0016] Optionally, the fourth generation unit can be configured to: determine the influencing factor optimization information group corresponding to each influencing factor optimization expression information group in the above-mentioned influencing factor optimization expression information group set, and obtain the influencing factor optimization information group set; input each influencing factor optimization information group in the above-mentioned influencing factor optimization information group set into the above-mentioned acquisition value attribute net value generation model to generate the acquisition value attribute net value, and obtain the acquisition value attribute net value set; determine the acquisition value attribute net value that meets the preset value condition in the above-mentioned acquisition value attribute net value set as the acquisition value attribute net value optimal information.

[0017] Optionally, the above-mentioned device is configured to: determine the influencing factor optimization information group corresponding to the above-mentioned optimal information on obtaining the net value of the value attribute as the target influencing factor optimization information group; and send the above-mentioned target influencing factor optimization information group to the client corresponding to the above-mentioned item value transfer party.

[0018] Optionally, the third generation unit can be configured to: generate a Hessian matrix for the above-mentioned net value constraint model for obtaining value attributes; determine whether the above-mentioned net value constraint model for obtaining value attributes is a convex programming solution model based on the Hessian matrix; in response to determining that it is not, generate an influencing factor optimization information group set.

[0019] Optionally, the above-mentioned device is configured to: update the above-mentioned service provision architecture information according to the above-mentioned optimal information of the net value of the value attribute to obtain updated service provision architecture information; and send the above-mentioned updated service provision architecture information to the client corresponding to the above-mentioned logistics party.

[0020] In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation manner in the first aspect.

[0021] In a fourth aspect, some embodiments of the present disclosure provide a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner in the first aspect is implemented.

[0022] In a fifth aspect, some embodiments of the present disclosure provide a computer program product, including a computer program, which implements the method described in any implementation manner in the above-mentioned first aspect when executed by a processor.

[0023] The above-mentioned embodiments of the present disclosure have the following beneficial effects: the information generation method of some embodiments of the present disclosure can accurately determine the optimal information of the net value of the acquired value attribute. Specifically, the reason why the relevant optimal information of the net value of the acquired value attribute is not accurate is that the logistics service provider department and the department for executing the operation related to the value of the item usually only consider the optimal net value of the acquired value attribute corresponding to their own department. From the overall point of view, it may lead to the total net value of the acquired value attribute obtained by the third-party logistics party not being the optimal net value of the acquired value attribute. Based on this, the information generation method of some embodiments of the present disclosure first determines the net value of the acquired value attribute influencing factor set for the logistics party and the item demand influencing factor set for the item value circulation party, so as to be used for the subsequent generation of the net value of the acquired value attribute generation model and the item demand determination model. The above-mentioned net value of the acquired value attribute influencing factor set includes: logistics service level parameters, circulation item value parameters, circulation item demand parameters, and the above-mentioned item demand influencing factor set includes: the above-mentioned logistics service level parameters and the item value interest rate parameters. Then, according to the above-mentioned net value of the acquired value attribute influencing factor set and the above-mentioned item demand influencing factor set, the net value of the acquired value attribute generation model and the item demand determination model can be effectively generated. Here, the obtained net value generation model of the value attribute and the item demand determination model are used to generate the subsequent net value constraint model of the value attribute. Then, according to the above-mentioned net value generation model of the value attribute and the above-mentioned item demand determination model, the net value constraint model of the value attribute can be accurately generated. Here, the obtained net value constraint model of the value attribute is used to generate optimized expression information for logistics service level parameters, circulation item value parameters, circulation item demand parameters and item value interest rate parameters. Furthermore, according to the above-mentioned net value constraint model of the value attribute, an optimized expression information group of influencing factors can be accurately generated. Among them, the optimized expression information group of influencing factors includes: optimized expression information for the above-mentioned logistics service level parameters, optimized expression information for the above-mentioned circulation item value parameters, optimized expression information for the above-mentioned circulation item demand parameters, and optimized expression information for the above-mentioned item value interest rate parameters. Finally, according to the above-mentioned net value generation model of the value attribute and the above-mentioned influencing factor optimized expression information group, the optimal information of the net value of the value attribute can be accurately generated. In summary, the present disclosure generates a net value constraint model for acquiring value attributes, and generates multiple groups of multiple optimized expression information for logistics service level parameters, circulation item value parameters, circulation item demand parameters, and item value interest rate parameters based on the net value constraint model for acquiring value attributes (i.e., a set of influencing factor optimized expression information groups), so as to generate the total net value of the acquisition value attributes of the circulation party as a whole. In this way, the situation in which the total net value of the acquisition value attributes obtained by the logistics party is not the optimal net value of the acquisition value attributes (i.e., a non-global optimal solution) is avoided, so that the optimal total net value information of the acquisition value attributes (i.e., the optimal net value information of the acquisition value attributes) can be accurately determined. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0025] Figure 1-Figure 2 is a schematic diagram of an application scenario of the information generation method according to some embodiments of the present disclosure;

[0026] Figure 3 are flow charts of some embodiments of the information generation method according to the present disclosure;

[0027] Figure 4 are flow charts of other embodiments of the information generating method according to the present disclosure;

[0028] Figure 5 is a schematic diagram of the structure of some embodiments of the information generating device according to the present disclosure;

[0029] Figure 6 It is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0030] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0031] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0032] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0033] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0034] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0035] With regard to the collection, storage, and use of item data (e.g., logistics data) involved in this disclosure, before executing the corresponding operations, the relevant organizations or individuals shall fulfill obligations including conducting item data security impact assessments, fulfilling the obligation to inform the item data subject, and obtaining the authorization and consent of the item data subject in advance.

[0036] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0037] Figure 1-Figure 2 It is a schematic diagram of an application scenario of the information generation method according to some embodiments of the present disclosure.

[0038] exist Figure 1-Figure 2In the application scenario, first, the electronic device 101 can determine the net value influencing factor set 103 of the acquisition value attribute for the logistics party 102 and the item demand influencing factor set 105 for the item value circulation party 113. Among them, the above-mentioned net value influencing factor set 103 of the acquisition value attribute includes: logistics service level parameter 1034, circulation item value parameter 1035, circulation item demand parameter 1036. The above-mentioned item demand influencing factor set 105 includes: the above-mentioned logistics service level parameter 1054 and the item value interest rate parameter 1055. Optionally, in this application scenario, the net value influencing factor set 103 of the acquisition value attribute can also include: ordering fee 1031, financing interest rate 1032 and unit item logistics cost 1033. The item demand influencing factor set 105 can also include: other competitor prices 1051, financing interest rate 1052 and unit item logistics cost 1053. Then, the electronic device 101 can generate a net value acquisition model 104 and an item demand determination model 105 based on the above-mentioned net value acquisition influencing factor set 103 and the above-mentioned item demand influencing factor set 105. Next, a net value acquisition constraint model 108 is generated based on the above-mentioned net value acquisition generation model 104 and the above-mentioned item demand determination model 106. Furthermore, based on the above-mentioned net value acquisition constraint model 108, an influencing factor optimization expression information group set is generated. Among them, the influencing factor optimization expression information group includes: optimization expression information for the above-mentioned logistics service level parameters, optimization expression information for the above-mentioned circulation item value parameters, optimization expression information for the above-mentioned circulation item demand parameters, and optimization expression information for the above-mentioned item value interest rate parameters. In this application scenario, the influencing factor optimization expression information group set includes: influencing factor optimization expression information group 109 and influencing factor optimization expression information group 110. In this application scenario, the influencing factor optimization expression information group 109 may include: optimization expression information 1091 for the above-mentioned logistics service level parameters, optimization expression information 1092 for the above-mentioned circulation item value parameters, optimization expression information 1093 for the above-mentioned circulation item demand parameters, and optimization expression information 1094 for the above-mentioned item value interest rate parameters. The influencing factor optimization expression information group 110 may include: optimization expression information 1101 for the above-mentioned logistics service level parameters, optimization expression information 1102 for the above-mentioned circulation item value parameters, optimization expression information 1103 for the above-mentioned circulation item demand parameters, and optimization expression information 1104 for the above-mentioned item value interest rate parameters. Finally, according to the above-mentioned acquisition value attribute net value generation model 106 and the above-mentioned influencing factor optimization expression information group set, the acquisition value attribute net value optimal information 112 is generated. In this application scenario, the acquisition value attribute net value optimal information 112 may be "109812".

[0039] It should be noted that the electronic device 101 can be hardware or software. When the electronic device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or it can be implemented as a single server or a single terminal device. When the electronic device is embodied as software, it can be installed in the hardware devices listed above. It can be implemented as multiple software or software modules for providing distributed services, for example, or it can be implemented as a single software or software module. No specific limitation is made here.

[0040] It should be understood that Figure 1-Figure 2 The number of electronic devices in the embodiment is only for illustration. Any number of electronic devices may be provided according to implementation requirements.

[0041] Continue to refer Figure 3 , shows a process 300 of some embodiments of the information generation method according to the present disclosure. The information generation method comprises the following steps:

[0042] Step 301, determining a set of factors influencing the net value of the acquired value attribute for the logistics party and a set of factors influencing the item demand for the item value circulation party.

[0043] In some embodiments, the execution subject of the above information generation method (for example Figure 1The electronic device 101 shown can determine a set of influencing factors for acquiring a net value attribute for a logistics party and a set of influencing factors for item demand for an item value transfer party. The above-mentioned set of influencing factors for acquiring a net value attribute includes: a logistics service level parameter, a circulation item value parameter, and a circulation item demand parameter. The above-mentioned item demand influencing factor set includes: the above-mentioned logistics service level parameter and an item value interest rate parameter. The above-mentioned logistics party may be a provider of third-party logistics (3PL). The set of influencing factors for acquiring a net value attribute may be a set of influencing factors for generating a net value attribute for acquiring a value attribute. In practice, the above-mentioned net value of the value attribute may be income information (i.e., profit information) for the circulation items. The above-mentioned logistics service level parameter may be a parameter that characterizes the logistics service level. The logistics service level may be service level information of the logistics service. For example, the above-mentioned logistics service level parameter may be the on-time delivery rate of the logistics party. The above-mentioned on-time delivery rate of the logistics party may be obtained by dividing the number of on-time deliveries by the total number of deliveries. The circulation item value parameter may be a parameter that characterizes the value of the circulation item. The above-mentioned circulation item may be an item that is circulated by the item value transfer party. In practice, the above-mentioned circulating items may be distribution items. For example, the circulating items may be "oranges". The value of the above-mentioned circulating items may be the price of the circulating items. The item value transferor may be a distributor for item distribution that receives logistics services provided by the logistics party. The circulating item demand parameter may be a parameter that characterizes the demand for the circulating items by the item value transferor. The item value interest rate parameter may be a parameter that characterizes the financing interest rate proposed by the logistics party to the item value transferor.

[0044] In some optional implementations of some embodiments, the execution subject may determine the above-mentioned acquisition value attribute net value influencing factor set and the above-mentioned item demand influencing factor set based on the service provision architecture information. The above-mentioned service provision architecture information represents the architecture information of the above-mentioned logistics party providing logistics services and value information services to the above-mentioned item value transfer party. The above-mentioned architecture information represents the process information of the logistics party providing logistics services and value information services to the item value transfer party.

[0045] In practice, the above process information may include the following sub-information:

[0046] The first sub-information: represents the information that the logistics party determines to provide services to the item value transfer party after it has a preliminary understanding of the credit information and business conditions (for example, capital scale, basic market potential) of the item value transfer party.

[0047] Second sub-information: information representing the logistics service level and financing interest rate determined by the logistics party.

[0048] The third sub-information: information that represents the price of the transferred goods in the regional market determined by the transferor of the value of the goods, and the purchase quantity of the transferred goods from the supplier based on this price.

[0049] The fourth sub-information: information representing the logistics party’s delivery of product logistics services and financing services, and the retailer’s payment for comprehensive services.

[0050] Step 302: Generate a value attribute net value generation model and an item demand determination model based on the above-mentioned value attribute net value influencing factor set and the above-mentioned item demand influencing factor set.

[0051] In some embodiments, the execution subject may generate a net value generation model for acquired value attributes and a model for determining item demand based on the net value influencing factor set for acquired value attributes and the item demand influencing factor set for acquired value attributes. The net value generation model for acquired value attributes may be a model for generating net value for acquired value attributes. The item demand determination model may be a model for determining the demand for the transferred items by the item value transfer party.

[0052] As an example, the execution subject may construct a recurrent neural network for obtaining the net value of the value attribute based on the above-mentioned set of influencing factors of the net value of the value attribute and the above-mentioned set of influencing factors of the item demand, as a model for obtaining the net value of the value attribute. The execution subject may construct a recurrent neural network for determining the item demand for the circulating items based on the above-mentioned set of influencing factors of the net value of the value attribute, as a model for determining the item demand.

[0053] In practice, the set of factors influencing the demand for goods includes: the market scale parameters of the goods of the goods value transfer party, the price parameters of the first goods of the goods value transfer party, the price parameters of the second goods of the goods of the other competitors, the first demand sensitivity coefficient parameters for the price of the first goods of the goods, the second demand sensitivity coefficient parameters for the price of the second goods of the goods, the first logistics service level parameters corresponding to the logistics party, the second logistics service level parameters corresponding to the other logistics parties, the third demand sensitivity coefficient parameters for the first logistics service level, and the fourth demand sensitivity coefficient parameters for the second logistics service level. Among them, the corresponding value of the first logistics service level parameter is higher than the corresponding value of the second logistics service level parameter. The corresponding value of the third demand sensitivity coefficient parameter is higher than the corresponding value of the fourth demand sensitivity coefficient parameter. The corresponding value of the second circulation price parameter has a positive impact on the information of the market scale of circulation goods. The corresponding value of the second logistics service level parameter has a negative impact on the information of the market scale of circulation goods.

[0054] The logistics service level parameters include: a first logistics service level parameter and a second logistics service level parameter. The circulation item value parameters include: a first circulation item price parameter and a second circulation item price parameter.

[0055] Optionally, the item demand determination model is generated by the following steps:

[0056] The first step is to multiply the first demand sensitivity coefficient parameter and the first circulation item price parameter to obtain a first multiplication result formula, and to multiply the second demand sensitivity coefficient parameter and the second circulation item price parameter to obtain a second multiplication result formula.

[0057] The second step is to multiply the first logistics service level parameter and the third demand sensitivity coefficient parameter to obtain a third multiplication result formula, and to multiply the second logistics service level parameter and the fourth demand sensitivity coefficient parameter to obtain a fourth multiplication result formula.

[0058] The third step is to subtract the first multiplication result formula from the second multiplication result formula to obtain the first subtraction result formula, and to subtract the fourth multiplication result formula from the third multiplication result formula to obtain the second subtraction result formula.

[0059] The fourth step is to use the addition formula of the market size parameters of the circulating goods, the first subtraction result formula and the second subtraction result formula as the model for determining the demand for goods.

[0060] In practice, the set of factors influencing the net value of value attributes includes: total payment cost parameter per unit item, item demand parameter representing the demand for circulating items, unit logistics cost parameter, equity capital parameter corresponding to the item value transfer party, influencing parameter representing the influence coefficient of the first logistics service level on logistics cost, financing interest rate parameter, and risk-free interest rate parameter.

[0061] Optionally, the net value generation model for obtaining the value attribute can be generated by the following steps:

[0062] The first step is to multiply the total payment cost parameter per unit item and the item demand parameter to obtain the fifth multiplication result formula.

[0063] The second step is to multiply the unit logistics cost parameter and the item demand parameter to obtain the sixth multiplication result formula.

[0064] The third step is to subtract the own capital amount parameter from the first addition result formula of the fifth multiplication result formula and the sixth multiplication result formula to obtain the third subtraction result formula.

[0065] The fourth step is to subtract the risk-free interest rate parameter from the above financing interest rate parameter to obtain the fourth subtraction result formula.

[0066] The fifth step is to determine the multiplication formula of the third subtraction result formula and the fourth subtraction result formula as the seventh multiplication result formula.

[0067] The sixth step is to determine the unit logistics cost parameter and multiply it by the item demand parameter to obtain the eighth multiplication result formula.

[0068] In the seventh step, the influencing parameter, the first logistics service level parameter and the item demand parameter are multiplied to obtain the ninth multiplication result formula.

[0069] Step 8. Add the seventh multiplication result formula to the eighth multiplication result formula to obtain the second addition result formula.

[0070] The ninth step is to subtract the ninth multiplication result formula from the second subtraction result formula to obtain the fifth subtraction result formula, which is used as a model for generating the net value of value attributes.

[0071] Step 303: Generate a net value constraint model for acquired value attributes based on the above-mentioned net value generation model for acquired value attributes and the above-mentioned item demand determination model.

[0072] In some embodiments, the execution subject may generate a net value constraint model for acquiring value attributes based on the net value generation model for acquiring value attributes and the item demand determination model. The net value constraint model for acquiring value attributes may be a constraint model for acquiring value attributes net value.

[0073] As an example, first, in the case where the above-mentioned net value generation model for acquiring value attributes and the above-mentioned item demand determination model are respectively recurrent neural network models, the above-mentioned execution subject can use the item demand determination model as a sub-model to connect to the net value generation model for acquiring value attributes to obtain the connected model. Then, the splicing model of the above-mentioned connected model and the maximum profit determination model is determined as the net value constraint model for acquiring value attributes. Among them, the maximum profit determination model can be a regression model. For example, the maximum profit determination model can be a convolutional neural network.

[0074] In practice, first, the above-mentioned item demand determination model (i.e., item demand determination formula) is determined as the item demand parameter. Then, the item demand determination model is substituted into the net value generation model for obtaining the value attribute to generate the substituted model. Next, a maximum profit constraint model for the substituted model is generated as the net value constraint model for obtaining the value attribute. The maximum profit constraint model can be a convolutional neural network model.

[0075] Step 304: Generate an influencing factor optimization expression information set based on the above-mentioned net value constraint model for obtaining value attributes.

[0076] In some embodiments, the execution subject may generate an optimized expression information group set of influencing factors according to the above-mentioned acquisition value attribute net value constraint model. The optimized expression information group of influencing factors includes: optimized expression information for the above-mentioned logistics service level parameters, optimized expression information for the above-mentioned circulation item value parameters, optimized expression information for the above-mentioned circulation item demand parameters, and optimized expression information for the above-mentioned item value interest rate parameters. The optimized expression information may be information representing the optimized parameter expression method. The optimized expression information for the above-mentioned logistics service level parameters may represent the optimized parameter expression method of the logistics service level parameters. The optimized expression information for the above-mentioned circulation item value parameters may represent the optimized parameter expression method of the circulation item value parameters. The optimized expression information for the above-mentioned circulation item demand parameters may represent the optimized parameter expression method of the circulation item demand parameters. The optimized expression information for the above-mentioned item value interest rate parameters represents the optimized parameter expression method of the item value interest rate parameters.

[0077] In some optional implementations of some embodiments, the generation of the influencing factor optimization expression information set according to the above-mentioned acquisition of the value attribute net value constraint model may include the following steps:

[0078] The first step is to generate the Hessian matrix for the above-mentioned net value constraint model for obtaining value attributes.

[0079] As an example, the above-mentioned execution entity can respectively obtain a block matrix composed of the second-order partial derivatives of the first circulation item price parameter and the first logistics service level parameter as the above-mentioned Hessian matrix.

[0080] The second step is to determine whether the above-mentioned net value constraint model for obtaining value attributes is a convex programming solution model based on the Hessian matrix.

[0081] As an example, in response to determining that the Hessian matrix is ​​a non-positive definite matrix, the net value constraint model for obtaining the value attribute is determined to be a non-convex programming solution model. In response to determining that the Hessian matrix is ​​a positive definite matrix, the net value constraint model for obtaining the value attribute is determined to be a convex programming solution model.

[0082] The third step is to generate an influencing factor optimization information set in response to determining that the answer is no.

[0083] As an example, in response to determining that it is not, the execution subject may generate an influencing factor optimization information set by setting Lagrange multipliers using Kuhn-Tucker conditions (KT conditions).

[0084] Step 205, generating optimal information on the net value of the value attribute based on the above-mentioned model for generating the net value of the value attribute and the above-mentioned influencing factor optimization expression information set.

[0085] In some embodiments, the execution subject may generate optimal information on the net value of the value attribute based on the net value generation model of the value attribute and the influencing factor optimization expression information set. In practice, the optimal information on the net value of the value attribute may be the maximum profit information for the circulating items.

[0086] As an example, first, for each group of influencing factor optimization expression information groups in the influencing factor optimization expression information group set, in the first step, the above-mentioned execution entity can substitute the above-mentioned influencing factor optimization expression information group into the acquisition value attribute net value generation model to obtain the acquisition value attribute net value generation model after substitution. The second step is to determine the influencing factor set corresponding to the substituted acquisition value attribute net value generation model. The third step is to determine the data set corresponding to the above-mentioned influencing factor set. The fourth step is to substitute the data set into the acquisition value attribute net value generation model after substitution to obtain the acquisition value attribute net value information. Finally, the maximum value in the obtained acquisition value attribute net value information set is determined as the optimal acquisition value attribute net value information.

[0087] In some optional implementations of some embodiments, after step 205, the steps further include:

[0088] In the first step, based on the optimal information of the net value of the value attribute obtained above, the service provision architecture information is updated to obtain the updated service provision architecture information.

[0089] As an example, the execution subject may determine to obtain the optimal value attribute net value information and add it to the service provision architecture information to generate updated service provision architecture information.

[0090] The second step is to send the updated service provision architecture information to the client corresponding to the logistics party.

[0091] The above-mentioned embodiments of the present disclosure have the following beneficial effects: the information generation method of some embodiments of the present disclosure can accurately determine the optimal information of the net value of the acquired value attribute. Specifically, the reason why the relevant optimal information of the net value of the acquired value attribute is not accurate is that the logistics service provider department and the department for executing the operation related to the value of the item usually only consider the optimal net value of the acquired value attribute corresponding to their own department. From the overall point of view, it may lead to the total net value of the acquired value attribute obtained by the third-party logistics party not being the optimal net value of the acquired value attribute. Based on this, the information generation method of some embodiments of the present disclosure first determines the net value of the acquired value attribute influencing factor set for the logistics party and the item demand influencing factor set for the item value circulation party, so as to be used for the subsequent generation of the net value of the acquired value attribute generation model and the item demand determination model. The above-mentioned net value of the acquired value attribute influencing factor set includes: logistics service level parameters, circulation item value parameters, circulation item demand parameters, and the above-mentioned item demand influencing factor set includes: the above-mentioned logistics service level parameters and the item value interest rate parameters. Then, according to the above-mentioned net value of the acquired value attribute influencing factor set and the above-mentioned item demand influencing factor set, the net value of the acquired value attribute generation model and the item demand determination model can be effectively generated. Here, the obtained net value generation model of the value attribute and the item demand determination model are used to generate the subsequent net value constraint model of the value attribute. Then, according to the above-mentioned net value generation model of the value attribute and the above-mentioned item demand determination model, the net value constraint model of the value attribute can be accurately generated. Here, the obtained net value constraint model of the value attribute is used to generate optimized expression information for logistics service level parameters, circulation item value parameters, circulation item demand parameters and item value interest rate parameters. Furthermore, according to the above-mentioned net value constraint model of the value attribute, an optimized expression information group of influencing factors can be accurately generated. Among them, the optimized expression information group of influencing factors includes: optimized expression information for the above-mentioned logistics service level parameters, optimized expression information for the above-mentioned circulation item value parameters, optimized expression information for the above-mentioned circulation item demand parameters, and optimized expression information for the above-mentioned item value interest rate parameters. Finally, according to the above-mentioned net value generation model of the value attribute and the above-mentioned influencing factor optimized expression information group, the optimal information of the net value of the value attribute can be accurately generated. In summary, the present disclosure generates a net value constraint model for acquiring value attributes, and generates multiple groups of multiple optimized expression information for logistics service level parameters, circulation item value parameters, circulation item demand parameters, and item value interest rate parameters based on the net value constraint model for acquiring value attributes (i.e., a set of influencing factor optimized expression information groups), so as to generate the total net value of the acquisition value attributes of the circulation party as a whole. In this way, the situation in which the total net value of the acquisition value attributes obtained by the logistics party is not the optimal net value of the acquisition value attributes (i.e., a non-global optimal solution) is avoided, so that the optimal total net value information of the acquisition value attributes (i.e., the optimal net value information of the acquisition value attributes) can be accurately determined.

[0092] Further references Figure 4 , shows a process 400 of another embodiment of the information generation method according to the present disclosure. The information generation method comprises the following steps:

[0093] Step 401, determining a set of factors influencing the net value of the acquired value attribute for the logistics party and a set of factors influencing the item demand for the item value circulation party.

[0094] Step 402: Generate a value attribute net value generation model and an item demand determination model based on the above-mentioned value attribute net value influencing factor set and the above-mentioned item demand influencing factor set.

[0095] Step 403: Generate a net value constraint model for acquired value attributes based on the above-mentioned net value generation model for acquired value attributes and the above-mentioned item demand determination model.

[0096] Step 404: Generate an influencing factor optimization expression information set based on the above-mentioned net value constraint model for obtaining value attributes.

[0097] In some embodiments, the specific implementation of steps 401-404 and the technical effects thereof can be referred to in Figure 3 Steps 301-304 in the corresponding embodiment are not described in detail here.

[0098] Step 405: determine the influencing factor optimization information group corresponding to each influencing factor optimization expression information group in the influencing factor optimization expression information group set to obtain the influencing factor optimization information group set.

[0099] In some embodiments, an execution entity (e.g. Figure 1 The electronic device 101 shown can determine the influencing factor optimization information group corresponding to each influencing factor optimization expression information group in the influencing factor optimization expression information group set to obtain the influencing factor optimization information group set.

[0100] As an example, first, for each influencing factor optimized expression information group in the influencing factor optimized expression information group set, a data group required for obtaining the influencing factor optimized expression information group is obtained. Then, each data group in the obtained data group set is sequentially substituted into the corresponding influencing factor optimized expression information group to generate an influencing factor optimized information group, thereby obtaining an influencing factor optimized information group set.

[0101] Step 406, input each influencing factor optimization information group in the above-mentioned influencing factor optimization information group set into the above-mentioned acquisition value attribute net value generation model to generate the acquisition value attribute net value and obtain the acquisition value attribute net value set.

[0102] In some embodiments, the execution entity may input each influencing factor optimization information group in the influencing factor optimization information group set into the acquisition value attribute net value generation model to generate an acquisition value attribute net value and obtain an acquisition value attribute net value set.

[0103] Step 407: determine the acquired value attribute net value that meets the preset value condition in the acquired value attribute net value set as the acquired value attribute net value optimal information.

[0104] In some embodiments, the execution subject may determine the net value of the acquired value attribute that satisfies the preset value condition in the above-mentioned net value set of acquired value attributes as the optimal net value information of the acquired value attributes. The preset value condition may be that the net value of the acquired value attribute is the net value of the acquired value attribute with the largest value in the above-mentioned net value set of acquired value attributes.

[0105] In some optional implementations of some embodiments, after step 407, the steps further include:

[0106] In the first step, the above-mentioned execution entity can determine the influencing factor optimization information group corresponding to the above-mentioned optimal information on the net value of the value attribute as the target influencing factor optimization information group.

[0107] In the second step, the above-mentioned execution entity can send the above-mentioned target influencing factor optimization information group to the client corresponding to the above-mentioned item value transfer party.

[0108] from Figure 4 It can be seen that Figure 3 Compared with the description of some corresponding embodiments, Figure 4 In the corresponding information generation method process 400 in some embodiments, the net value of the acquired value attribute corresponding to each influencing factor optimization expression information group in the influencing factor optimization expression information group set is screened, so as to accurately and effectively determine the optimal information of the net value of the acquired value attribute.

[0109] Further references Figure 5 As an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of an information generating device, and these device embodiments are Figure 3 Corresponding to the method embodiments shown, the information generating device can be specifically applied to various electronic devices.

[0110] like Figure 5As shown, an information generating device 500 includes: a determining unit 501, a first generating unit 502, a second generating unit 503, a third generating unit 504 and a fourth generating unit 505. The determining unit 501 is configured to determine a set of influencing factors for acquiring a net value attribute for a logistics party and a set of influencing factors for item demand for an item value circulation party, wherein the set of influencing factors for acquiring a net value attribute includes: a logistics service level parameter, a circulation item value parameter, a circulation item demand parameter, and the set of influencing factors for item demand includes: the logistics service level parameter and the item value interest rate parameter; the first generating unit 502 is configured to generate a net value acquisition value attribute generation model and an item demand determination model according to the set of influencing factors for acquiring a net value attribute and the set of influencing factors for item demand; the second generating unit 503 is configured to generate a net value acquisition value attribute generation model and an item demand determination model according to the set of influencing factors for acquiring a net value attribute The third generation unit 504 is configured to generate an influencing factor optimization expression information group set according to the above-mentioned acquisition of value attribute net value constraint model, wherein the influencing factor optimization expression information group includes: optimization expression information for the above-mentioned logistics service level parameters, optimization expression information for the above-mentioned circulation item value parameters, optimization expression information for the above-mentioned circulation item demand parameters, and optimization expression information for the above-mentioned item value interest rate parameters; the fourth generation unit 505 is configured to generate the optimal information on the acquisition of value attribute net value according to the above-mentioned acquisition of value attribute net value generation model and the above-mentioned influencing factor optimization expression information group set.

[0111] In some optional implementations of some embodiments, the determination unit 501 may be further configured to: determine the set of factors influencing the acquisition of the net value of the value attributes and the set of factors influencing the demand for the item based on service provision architecture information, wherein the service provision architecture information represents architecture information of the logistics direction providing logistics services and value information services to the value transfer party of the item.

[0112] In some optional implementations of some embodiments, the fourth generation unit 505 may be further configured to: determine the influencing factor optimization information group corresponding to each influencing factor optimization expression information group in the influencing factor optimization expression information group set to obtain an influencing factor optimization information group set; input each influencing factor optimization information group in the influencing factor optimization information group set into the acquisition value attribute net value generation model to generate an acquisition value attribute net value to obtain an acquisition value attribute net value set; determine the acquisition value attribute net value that meets the preset value condition in the acquisition value attribute net value set as the acquisition value attribute net value optimal information.

[0113] In some optional implementations of some embodiments, the information generating device 500 further includes: an information determining unit and a first sending unit (not shown in the figure). The information determining unit may be configured to: determine the influencing factor optimization information group corresponding to the above-mentioned optimal information on obtaining the net value of the value attribute as the target influencing factor optimization information group. The first sending unit may be configured to: send the target influencing factor optimization information group to the client corresponding to the above-mentioned item value transfer party.

[0114] In some optional implementations of some embodiments, the third generation unit 504 may be further configured to: generate a Hessian matrix for the value attribute net value constraint model; determine whether the value attribute net value constraint model is a convex programming solution model based on the Hessian matrix; and in response to determining that it is not, generate an influencing factor optimization information group set.

[0115] In some optional implementations of some embodiments, the information generating device 500 further includes: an updating unit and a second sending unit (not shown in the figure). The updating unit may be configured to: update the service provision architecture information according to the optimal value attribute net value information, and obtain updated service provision architecture information. The second sending unit may be configured to: send the updated service provision architecture information to the client corresponding to the logistics party.

[0116] It is understandable that the units recorded in the information generating device 500 are similar to those in the reference Figure 3 Therefore, the operations, features and beneficial effects described above for the method are also applicable to the information generating device 500 and the units included therein, and will not be described in detail here.

[0117] Reference below Figure 6 , which shows an electronic device (eg, Figure 1 Schematic diagram of the structure of the electronic device 101)600. Figure 6 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0118] like Figure 6As shown, the electronic device 600 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory 602 or a program loaded from a storage device 608 into a random access memory 603. Various programs and data required for the operation of the electronic device 600 are also stored in the random access memory 603. The processing device 601, the program stored in the read-only memory 602, and the random access memory 603 are connected to each other via a bus 604. An input / output interface 605 is also connected to the bus 604.

[0119] Typically, the following devices may be connected to the input / output interface 605: an input device 606 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 607 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 608 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 609. The communication device 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 6 The electronic device 600 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 6 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0120] In particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from a network through a communication device 609, or installed from a storage device 608, or installed from a storage device 602. When the computer program is executed by the processing device 601, the above-mentioned functions defined in the method of some embodiments of the present disclosure are executed.

[0121] It should be noted that the computer-readable medium in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In some embodiments of the present disclosure, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In some embodiments of the present disclosure, the computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0122] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0123] The above-mentioned computer-readable medium may be included in the above-mentioned electronic device; or it may exist independently without being assembled into the electronic device. The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed by the electronic device, the electronic device: determines a set of influencing factors for the net value of the acquired value attribute for the logistics party and a set of influencing factors for the item demand for the item value circulation party, wherein the above-mentioned set of influencing factors for the net value of the acquired value attribute includes: logistics service level parameters, circulation item value parameters, circulation item demand parameters, and the above-mentioned set of influencing factors for item demand includes: the above-mentioned logistics service level parameters and item value interest rate parameters; based on the above-mentioned set of influencing factors for the net value of the acquired value attribute and the above-mentioned set of influencing factors for item demand, generates a net value acquisition attribute generation model and an item demand generation model. Determine the model; generate a net value constraint model for acquiring value attributes based on the above-mentioned net value generation model for acquiring value attributes and the above-mentioned item demand determination model; generate an influencing factor optimization expression information group set based on the above-mentioned net value constraint model for acquiring value attributes, wherein the influencing factor optimization expression information group includes: optimization expression information for the above-mentioned logistics service level parameters, optimization expression information for the above-mentioned circulation item value parameters, optimization expression information for the above-mentioned circulation item demand parameters, and optimization expression information for the above-mentioned item value interest rate parameters; generate optimal information on the net value of acquired value attributes based on the above-mentioned net value generation model for acquiring value attributes and the above-mentioned optimization expression information group set for influencing factors.

[0124] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0125] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0126] The units described in some embodiments of the present disclosure may be implemented by software or by hardware. The described units may also be provided in a processor, for example, may be described as: a processor including a determination unit, a first generation unit, a second generation unit, a third generation unit, and a fourth generation unit. The names of these units do not constitute limitations on the units themselves in certain circumstances, for example, the fourth generation unit may also be described as "a unit for generating optimal information on obtaining the net value of value attributes according to the above-mentioned value attribute net value generation model and the above-mentioned influencing factor optimization expression information set".

[0127] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0128] Some embodiments of the present disclosure further provide a computer program product, including a computer program, which implements any of the above-mentioned information generation methods when executed by a processor.

[0129] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with the technical features with similar functions disclosed in the embodiments of the present disclosure (but not limited to) and the technical solutions formed.

Claims

1. A method for generating information, comprising: Determine a net value influencing factor set for the logistics party and an item demand influencing factor set for the item value circulation party, wherein the net value influencing factor set includes: logistics service level parameters, circulation item value parameters, circulation item demand parameters, and the item demand influencing factor set includes: the logistics service level parameters and item value interest rate parameters; Generate a net value generation model for acquired value attributes and a model for determining item demand based on the set of factors influencing the net value of acquired value attributes and the set of factors influencing item demand; Generate a net value constraint model for acquiring value attributes according to the net value generation model for acquiring value attributes and the item demand determination model; According to the obtained value attribute net value constraint model, an influencing factor optimization expression information group set is generated, wherein the influencing factor optimization expression information group includes: optimization expression information for the logistics service level parameter, optimization expression information for the circulation item value parameter, optimization expression information for the circulation item demand parameter, and optimization expression information for the item value interest rate parameter; According to the value attribute net value generation model and the influencing factor optimization expression information set, the optimal value attribute net value information is generated.

2. The method according to claim 1, wherein: The determination of the net value influencing factor set of the acquired value attribute for the logistics party and the item demand influencing factor set for the item value circulation party includes: The set of factors influencing the net value of the value attributes and the set of factors influencing the item demand are determined according to the service provision architecture information, wherein the service provision architecture information represents the architecture information of the logistics direction providing logistics services and value information services to the item value transfer party.

3. The method according to claim 1, wherein: The step of generating optimal information on the net value of the value attribute according to the net value generation model of the value attribute and the influencing factor optimization expression information set includes: Determine the influencing factor optimization information group corresponding to each influencing factor optimization expression information group in the influencing factor optimization expression information group set to obtain the influencing factor optimization information group set; Inputting each influencing factor optimization information group in the influencing factor optimization information group set into the acquisition value attribute net value generation model to generate an acquisition value attribute net value, thereby obtaining an acquisition value attribute net value set; The acquired value attribute net value that meets the preset value condition in the acquired value attribute net value set is determined as the acquired value attribute net value optimal information.

4. The method according to claim 3, wherein: The method further comprises: Determine the influencing factor optimization information group corresponding to the optimal information of obtaining the value attribute net value as the target influencing factor optimization information group; The target influencing factor optimization information group is sent to the client corresponding to the item value transfer party.

5. The method according to claim 1, wherein: The step of generating an influencing factor optimization expression information set according to the acquired value attribute net value constraint model includes: Generating a Hessian matrix for the net value constraint model of the acquired value attribute; According to the Hessian matrix, determining whether the net value constraint model for obtaining value attributes is a convex programming solution model; In response to determining that no, an influencing factor optimization information set is generated.

6. The method according to claim 2, wherein: The method further comprises: According to the obtained optimal value attribute net value information, the service provision architecture information is updated to obtain updated service provision architecture information; The updated service provision architecture information is sent to the client corresponding to the logistics party.

7. An information generating device, comprising: A determination unit is configured to determine a net value influencing factor set of the acquired value attribute for the logistics party and an item demand influencing factor set for the item value circulation party, wherein the net value influencing factor set of the acquired value attribute includes: a logistics service level parameter, a circulation item value parameter, and a circulation item demand parameter, and the item demand influencing factor set includes: the logistics service level parameter and the item value interest rate parameter; A first generating unit is configured to generate a net value generation model for acquired value attributes and a product demand determination model according to the net value influencing factor set for acquired value attributes and the product demand influencing factor set; A second generating unit is configured to generate an acquisition value attribute net value constraint model according to the acquisition value attribute net value generating model and the item demand determining model; The third generating unit is configured to generate an influencing factor optimization expression information group set according to the acquired value attribute net value constraint model, wherein the influencing factor optimization expression information group includes: optimization expression information for the logistics service level parameter, optimization expression information for the circulation item value parameter, optimization expression information for the circulation item demand parameter, and optimization expression information for the item value interest rate parameter; The fourth generating unit is configured to generate optimal information of acquiring the net value of the value attribute according to the acquiring the net value generation model of the value attribute and the influencing factor optimization expression information set.

8. An electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

9. A computer readable 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 6 is implemented.

10. A computer program product, comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 6.

Images