Order management method, device and system

Abstract

The present application discloses an order management method, device and system, the method comprising: obtaining a target commodity order of a target object and a target delivery address of the target commodity order, the target commodity order comprising n commodities; obtaining a source address of each commodity to obtain n source address sets; determining a courier route corresponding to each of the n commodities according to the n source address sets and the target delivery address to obtain n courier route sets; determining logistics information corresponding to each courier route set in the n courier route sets to obtain n logistics information sets; determining a target source address of each of the n commodities according to the n logistics information sets and target preference information to obtain n target source addresses; obtaining logistics information corresponding to each target source information in the n target source addresses from the n logistics information sets to obtain n logistics information; generating a logistics order according to the n target source addresses and the n logistics information to obtain m logistics orders.

Description

Technical Field

[0001] The present application relates to the field of e-commerce or cross-border e-commerce technology, and specifically to an order management method, device and system. Background Art

[0002] With the rapid development of information technology, e-commerce has gradually become a hot topic. Users shop through various shopping platforms, which greatly facilitates their lives. Large shopping platforms can often bring all the goods in their supply chains together on one platform for display and sales. Users can also quickly choose the goods they want through a shopping platform. However, since the goods come from different sources, it is more troublesome to adjust the goods, which reduces the user experience. Therefore, how to improve the intelligence of order management to improve the user experience needs to be solved urgently. Summary of the invention

[0003] The embodiments of the present application provide an order management method, device, and system, which can improve the intelligence of order management to enhance user experience.

[0004] In a first aspect, an embodiment of the present application provides an order management method, the method comprising:

[0005] Obtain a target commodity order of a target object and a target delivery address of the target commodity order, wherein the target commodity order includes n commodities, each of which corresponds to at least one commodity, and n is an integer greater than 1;

[0006] Obtaining the supply source address of each of the n types of goods to obtain n supply source address sets, each type of goods corresponds to a supply source address set, and each supply source address set corresponds to at least one supply source address;

[0007] Determine the express delivery path corresponding to each of the n types of goods according to the n source address sets and the target delivery address, and obtain n express delivery path sets, where each type of goods corresponds to one express delivery path set;

[0008] Determine the logistics information corresponding to each of the n express path sets to obtain n logistics information sets, wherein the logistics information sets include estimated arrival time and cost information;

[0009] Acquire target preference information of the target object, wherein the target preference information includes at least one of the following: express time preference information, express fee preference information, and express security preference information;

[0010] Determine the target source address of each of the n commodities according to the n logistics information sets and the target preference information to obtain n target source addresses;

[0011] Obtaining logistics information corresponding to each target source of goods information in the n target source of goods addresses from the n logistics information sets to obtain n logistics information;

[0012] Generate logistics orders according to the n target source addresses and the n logistics information, obtain m logistics orders, and initiate the m logistics orders, where m is a positive integer less than or equal to n.

[0013] In a second aspect, an embodiment of the present application provides an order management device, the device comprising:

[0014] an acquisition unit, configured to acquire a target commodity order of a target object and a target delivery address of the target commodity order, wherein the target commodity order includes n commodities, each of which corresponds to at least one commodity, and n is an integer greater than 1; acquire a source address of each of the n commodities to obtain n source address sets, each of which corresponds to a source address set, and each source address set corresponds to at least one source address;

[0015] a determination unit, configured to determine a courier route corresponding to each of the n types of goods according to the n source address sets and the target delivery address, to obtain n courier route sets, one courier route set corresponding to each type of goods; determine logistics information corresponding to each courier route set in the n courier route sets, to obtain n logistics information sets, the logistics information sets including estimated arrival time and cost information;

[0016] The acquisition unit is further used to acquire target preference information of the target object, wherein the target preference information includes at least one of the following: express time preference information, express fee preference information, and express security preference information;

[0017] The determination unit is further configured to determine a target source address of each of the n types of commodities according to the n logistics information sets and the target preference information, to obtain n target source addresses;

[0018] The acquisition unit is further used to acquire the logistics information corresponding to each target source information in the n target source addresses from the n logistics information sets to obtain n logistics information;

[0019] A generating unit is used to generate logistics orders according to the n target source addresses and the n logistics information, obtain m logistics orders, and initiate the m logistics orders, where m is a positive integer less than or equal to n.

[0020] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor, a memory, a human body communication chip, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the embodiment of the present application.

[0021] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps described in the first aspect of the embodiment of the present application.

[0022] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in the first aspect of the embodiment of the present application. The computer program product may be a software installation package.

[0023] In a sixth aspect, an embodiment of the present application provides an order management system, and the order management system is the device described in the second aspect.

[0024] The implementation of the embodiments of the present application has the following beneficial effects:

[0025] It can be seen that the order management method, device and system described in the embodiments of the present application obtain the target product order of the target object and the target delivery address of the target product order, the target product order includes n kinds of products, each product corresponds to at least one product, n is an integer greater than 1, obtain the source address of each of the n kinds of products, and obtain n source address sets, each product corresponds to a source address set, and each source address set corresponds to at least one source address, determine the express delivery path corresponding to each of the n kinds of products according to the n source address sets and the target delivery address, and obtain n express delivery path sets, each product corresponds to an express delivery path set, determine the logistics information corresponding to each express delivery path set in the n express delivery path sets, and obtain n logistics information sets, the logistics information sets include estimated arrival time and cost information, and obtain the target preference of the target object. Information, the target preference information includes at least one of the following: express time preference information, express fee preference information, express security preference information, determine the target source address of each of the n commodities according to the n logistics information sets and the target preference information, and obtain n target source addresses, obtain the logistics information corresponding to each target source information in the n target source addresses from the n logistics information sets, and obtain n logistics information, generate logistics orders according to the n target source addresses and the n logistics information, and obtain m logistics orders, initiate m logistics orders, m is a positive integer less than or equal to n, and the required commodities can be selected at one time through one platform, and the source of commodities can be decentralized. In addition, orders can be dynamically optimized based on user preferences and actual supply conditions to improve the intelligence of order management, thereby improving the intelligence of order management and improving user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0027] Figure 1 It is a flowchart of an order management method provided in an embodiment of the present application;

[0028] Figure 2 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application;

[0029] Figure 3 It is a block diagram of the functional units of an order management device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0031] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0032] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0033] In the embodiment of the present application, the electronic device may include a cross-border e-commerce platform or other shopping platform. The cross-border e-commerce platform may include a server, and the server may include a cloud server.

[0034] The embodiments of the present application are described in detail below.

[0035] See also Figure 1 , Figure 1 : is a flowchart of an order management method provided in an embodiment of the present application, and the order management method may include the following steps:

[0036] 101. Obtain a target product order of a target object and a target delivery address of the target product order, wherein the target product order includes n types of products, each type of product corresponds to at least one product, and n is an integer greater than 1.

[0037] In the embodiment of the present application, the target object may be a consumer or a user. The embodiment of the present application may be applied to a cross-border e-commerce platform or a domestic shopping platform.

[0038] In the specific implementation, the target product order of the target object and the target delivery address of the target product order can be obtained. The target product order includes n kinds of products, each of which corresponds to at least one product, and n is an integer greater than 1. For example, we as users will buy a large number of products on a platform, but the products can be located in different warehouses, and each warehouse corresponds to a source address.

[0039] 102. Obtain the supply source address of each of the n types of goods to obtain n supply source address sets, each type of goods corresponds to a supply source address set, and each supply source address set corresponds to at least one supply source address.

[0040] In the embodiment of the present application, each commodity can correspond to at least one source address. On the same shopping platform, the sales price of commodities with different source addresses can be the same, but the logistics time and logistics cost of commodities with different source addresses may be different.

[0041] In the specific implementation, the source address of each of the n commodities can be obtained to obtain n source address sets. Each commodity corresponds to a source address set, and each source address set corresponds to at least one source address. The remaining inventory quantity of each source address is also different. When the number of commodities required by the user exceeds the remaining inventory quantity of a certain source address (warehouse), a certain number of commodities can be dispatched from other source addresses (warehouses) to meet the user's needs.

[0042] 103. Determine the express delivery path corresponding to each of the n kinds of goods according to the n source address sets and the target delivery address, and obtain n express delivery path sets, one express delivery path set corresponding to each kind of goods.

[0043] In an embodiment of the present application, the express delivery route corresponding to each of n kinds of goods can be determined based on each source address in each source address set and the target delivery address, so as to obtain n express delivery route sets, each kind of goods corresponds to an express delivery route set, and each express delivery route set corresponds to at least one express delivery route. Different express delivery routes have different express delivery times and express delivery fees.

[0044] 104. Determine the logistics information corresponding to each of the n express route sets to obtain n logistics information sets, wherein the logistics information sets include estimated arrival time and cost information.

[0045] In the embodiment of the present application, the logistics information may include at least one of the following: logistics time, logistics route, logistics method, logistics cost, logistics safety level, etc., which are not limited here.

[0046] In a specific implementation, the logistics information corresponding to each of the n express route sets can be determined to obtain n logistics information sets, where the logistics information sets include estimated arrival time and cost information, and each express route corresponds to one piece of logistics information.

[0047] 105. Obtain target preference information of the target object, where the target preference information includes at least one of the following: express time preference information, express fee preference information, and express security preference information.

[0048] In the embodiment of the present application, the target preference information may include at least one of the following: express time preference information, express fee preference information, and express security preference information, which are not limited here.

[0049] In the specific implementation, the target preference information of the target object can be obtained through the big data principle.

[0050] Optionally, the above step 105, obtaining the target preference information of the target object, may include the following steps:

[0051] Obtain historical order records of the target object to obtain multiple historical order records; obtain logistics information corresponding to each historical order record in the multiple historical order records to obtain multiple logistics information; the logistics information includes at least one of the following: logistics time, logistics cost, and logistics service evaluation parameters; determine the reference preference information based on the multiple logistics information; obtain attribute information of the n kinds of commodities to obtain n attribute information; optimize the reference preference information based on the n attribute information to obtain the target preference information.

[0052] The logistics information may include at least one of the following: logistics time, logistics cost, logistics service evaluation parameters, which are not limited here. The attribute information of the commodity may include at least one of the following: commodity name, commodity type, commodity classification number, commodity price range, commodity brand, etc., which are not limited here.

[0053] In an embodiment of the present application, a machine learning function may be provided. Specifically, historical order records of a target object may be obtained to obtain multiple historical order records, and then logistics information corresponding to each historical order record in the multiple historical order records may be obtained to obtain multiple logistics information. Reference preference information may be determined based on the multiple logistics information. Since logistics information may reflect user preferences, historical logistics information may be used to accurately analyze user behavior, and then attribute information of n kinds of goods may be obtained to obtain n attribute information. The reference preference information may be optimized based on the n attribute information to obtain target preference information. That is, user preferences may be dynamically adjusted based on the attribute information of the goods being shopped this time, so that the order is more in line with user preferences and the actual situation of the goods, which helps to improve the intelligence of order management and enhance user experience.

[0054] Furthermore, the above step of determining the reference preference information according to the multiple logistics information may include the following steps:

[0055] Determine the evaluation value corresponding to each of the multiple logistics information to obtain multiple evaluation values; determine the target mean and target mean square deviation of the multiple evaluation values; dynamically adjust the target mean according to the target mean square deviation to obtain the target evaluation value; determine the reference preference information corresponding to the target evaluation value.

[0056] In the embodiment of the present application, the evaluation value corresponding to each logistics information in the multiple logistics information can be determined to obtain multiple evaluation values. Specifically, the evaluation index of each logistics information can be determined. The evaluation index can include at least one of the following: logistics time, logistics service score, logistics safety, logistics cost, etc., which are not limited here. Each evaluation index can correspond to an evaluation value. Finally, these evaluation values ​​are weighted to obtain the evaluation value corresponding to each logistics information. Then, the target mean and target mean square deviation of multiple evaluation values ​​can be determined. The mean reflects the user's normalized preference, and the variance reflects the user's preference fluctuation. Then, the target mean is dynamically adjusted according to the target mean square deviation to obtain the target evaluation value. For example, the corresponding relationship between the mean square deviation and the fluctuation parameter can be pre-set to determine the target fluctuation parameter corresponding to the target mean square deviation. Under normal circumstances, the fluctuation parameter can range from -0.2 to 0.2. Then, the target evaluation value = (1 + target fluctuation parameter) * evaluation value. Finally, the reference preference information corresponding to the target evaluation value can be determined. Different evaluation values ​​correspond to different preferences. Based on different evaluation values, the user's preference can be accurately described.

[0057] Optionally, the above step of optimizing the reference preference information according to the n attribute information to obtain the target preference information may include the following steps:

[0058] Classify the n attribute information to obtain k attribute information sets, where k is a positive integer less than or equal to n; obtain the number of occurrences of the attribute information corresponding to each attribute information set in the k attribute information sets from the multiple historical order records to obtain k occurrences; each historical order corresponds to one attribute information; determine k weight values ​​according to the k occurrences; obtain the evaluation value corresponding to each of the k occurrences from the multiple evaluation values ​​to obtain k reference evaluation value sets; determine the mean of each reference evaluation value set in the k reference evaluation value sets to obtain k means; perform weighted operation based on the k means and the k weight values ​​to obtain a first evaluation value; determine a target deviation between the first evaluation value and the target evaluation value; determine a target fine-tuning coefficient corresponding to the target deviation; optimize the reference preference information according to the target fine-tuning coefficient to obtain the target preference information.

[0059] In the embodiment of the present application, n attribute information can be classified to obtain k attribute information sets, where k is a positive integer less than or equal to n. Then, the number of occurrences of the attribute information corresponding to each attribute information set in the k attribute information sets is obtained from multiple historical order records to obtain k occurrences. Each historical order corresponds to one attribute information. Then, k weight values ​​can be determined according to the k occurrences, that is, the proportion of each occurrence is determined to obtain k weight values.

[0060] Next, the evaluation value corresponding to each of the k occurrences can be obtained from multiple evaluation values ​​to obtain k reference evaluation value sets, and the mean of each reference evaluation value set in the k reference evaluation value sets can be determined to obtain k means. Then, a weighted operation is performed based on the k means and k weight values ​​to obtain a first evaluation value, and a target deviation between the first evaluation value and the target evaluation value can also be determined, target deviation = (first evaluation value - target evaluation value) / target evaluation value, and then a mapping relationship between a preset deviation and a fine-tuning coefficient is pre-set, and a target fine-tuning coefficient corresponding to the target deviation is determined based on the mapping relationship. Finally, the reference preference information can be optimized according to the target fine-tuning coefficient to obtain target preference information, target preference information = (1 + target fine-tuning coefficient) * reference preference information. In this way, the corresponding attribute information of the currently purchased goods can be combined, and the attribute information can be mapped to the user's shopping habits based on big data, that is, the current user preferences can be dynamically fine-tuned in combination with the corresponding order rules, so that the shopping user is more adapted to the current user, which helps to improve the user experience.

[0061] 106. Determine the target source address of each of the n commodities according to the n logistics information sets and the target preference information, and obtain n target source addresses.

[0062] In the embodiment of the present application, since different preference information corresponds to different logistics information, a reasonable target source address can be selected for each commodity to obtain n target source addresses.

[0063] 107. Obtain the logistics information corresponding to each target source information in the n target source addresses from the n logistics information sets to obtain n logistics information.

[0064] In an embodiment of the present application, logistics information corresponding to each target source information in n target source addresses can be obtained from n logistics information sets to obtain n logistics information. Since the logistics information has been planned, the corresponding logistics information can be directly improved after the target source address is determined.

[0065] 108. Generate logistics orders according to the n target source addresses and the n logistics information, obtain m logistics orders, and initiate the m logistics orders, where m is a positive integer less than or equal to n.

[0066] In the embodiment of the present application, a logistics order can be generated according to n target source addresses and n logistics information, and m logistics orders are obtained, and m logistics orders are initiated, where m is a positive integer less than or equal to n. Of course, if the target source addresses are the same, the corresponding logistics orders can be merged.

[0067] It can be seen that the order management method described in the embodiment of the present application obtains the target product order of the target object and the target delivery address of the target product order, the target product order includes n kinds of products, each product corresponds to at least one product, n is an integer greater than 1, obtains the source address of each of the n kinds of products, and obtains n source address sets, each product corresponds to a source address set, and each source address set corresponds to at least one source address, determines the express delivery path corresponding to each of the n kinds of products according to the n source address sets and the target delivery address, and obtains n express delivery path sets, each product corresponds to an express delivery path set, determines the logistics information corresponding to each express delivery path set in the n express delivery path sets, and obtains n logistics information sets, the logistics information sets include estimated arrival time and cost information, obtains the target preference information of the target object, and obtains the target product. The target preference information includes at least one of the following: express time preference information, express fee preference information, and express security preference information. The target source address of each of the n commodities is determined according to the n logistics information sets and the target preference information to obtain n target source addresses. The logistics information corresponding to each target source information in the n target source addresses is obtained from the n logistics information sets to obtain n logistics information. Logistics orders are generated according to the n target source addresses and the n logistics information to obtain m logistics orders. M logistics orders are initiated, where m is a positive integer less than or equal to n. The required commodities can be selected at one time through one platform, and the source of commodities can be decentralized. In addition, orders can be dynamically optimized based on user preferences and actual supply conditions to improve the intelligence of order management, thereby improving the intelligence of order management and improving user experience.

[0068] For the above embodiments, please refer to Figure 2 , Figure 2 : is a structural diagram of an electronic device provided in an embodiment of the present application. As shown in the figure, the electronic device includes a processor, a memory, a communication interface, and one or more programs. The one or more programs are stored in the memory and configured to be executed by the processor. In the embodiment of the present application, the program includes instructions for executing the following steps:

[0069] Obtain a target commodity order of a target object and a target delivery address of the target commodity order, wherein the target commodity order includes n commodities, each of which corresponds to at least one commodity, and n is an integer greater than 1;

[0070] Obtaining the supply source address of each of the n types of goods to obtain n supply source address sets, each type of goods corresponds to a supply source address set, and each supply source address set corresponds to at least one supply source address;

[0071] Determine the express delivery path corresponding to each of the n types of goods according to the n source address sets and the target delivery address, and obtain n express delivery path sets, where each type of goods corresponds to one express delivery path set;

[0072] Determine the logistics information corresponding to each of the n express path sets to obtain n logistics information sets, wherein the logistics information sets include estimated arrival time and cost information;

[0073] Acquire target preference information of the target object, wherein the target preference information includes at least one of the following: express time preference information, express fee preference information, and express security preference information;

[0074] Determine the target source address of each of the n commodities according to the n logistics information sets and the target preference information to obtain n target source addresses;

[0075] Obtaining logistics information corresponding to each target source of goods information in the n target source of goods addresses from the n logistics information sets to obtain n logistics information;

[0076] Generate logistics orders according to the n target source addresses and the n logistics information, obtain m logistics orders, and initiate the m logistics orders, where m is a positive integer less than or equal to n.

[0077] Optionally, in the aspect of acquiring the target preference information of the target object, the program includes instructions for executing the following steps:

[0078] Obtaining historical order records of the target object to obtain multiple historical order records;

[0079] Obtaining a piece of logistics information corresponding to each of the plurality of historical order records, to obtain a plurality of logistics information; the logistics information includes at least one of the following: logistics time, logistics cost, and logistics service evaluation parameter;

[0080] Determining the reference preference information according to the plurality of logistics information;

[0081] Obtaining attribute information of the n types of commodities to obtain n pieces of attribute information;

[0082] The reference preference information is optimized according to the n attribute information to obtain the target preference information.

[0083] Optionally, in determining the reference preference information according to the plurality of logistics information, the program includes instructions for performing the following steps:

[0084] Determine an evaluation value corresponding to each piece of logistics information in the plurality of logistics information to obtain a plurality of evaluation values;

[0085] Determining a target mean and a target mean square error of the plurality of evaluation values;

[0086] Dynamically adjust the target mean value according to the target mean square error to obtain a target evaluation value;

[0087] The reference preference information corresponding to the target evaluation value is determined.

[0088] Optionally, in the aspect of optimizing the reference preference information according to the n attribute information to obtain the target preference information, the program includes instructions for executing the following steps:

[0089] Classify the n attribute information to obtain k attribute information sets, where k is a positive integer less than or equal to n;

[0090] Obtaining the number of occurrences of attribute information corresponding to each attribute information set in the k attribute information sets from the multiple historical order records, and obtaining k occurrence numbers; each historical order corresponds to one attribute information;

[0091] Determine k weight values ​​according to the k occurrence times;

[0092] Obtaining an evaluation value corresponding to each of the k occurrence times from the multiple evaluation values ​​to obtain k reference evaluation value sets;

[0093] Determine the mean of each reference evaluation value set in the k reference evaluation value sets to obtain k means;

[0094] Performing a weighted operation according to the k means and the k weight values ​​to obtain a first evaluation value;

[0095] determining a target deviation between the first evaluation value and the target evaluation value;

[0096] Determining a target fine-tuning coefficient corresponding to the target deviation;

[0097] The reference preference information is optimized according to the target fine-tuning coefficient to obtain the target preference information.

[0098] It can be seen that the electronic device described in the embodiment of the present application obtains the target product order of the target object and the target delivery address of the target product order, the target product order includes n kinds of products, each product corresponds to at least one product, n is an integer greater than 1, obtains the source address of each of the n kinds of products, and obtains n source address sets, each product corresponds to a source address set, and each source address set corresponds to at least one source address, determines the express path corresponding to each of the n kinds of products according to the n source address sets and the target delivery address, and obtains n express path sets, each product corresponds to an express path set, determines the logistics information corresponding to each express path set in the n express path sets, and obtains n logistics information sets, the logistics information sets include estimated arrival time and cost information, obtains the target preference information of the target object, and obtains the target The preference information includes at least one of the following: express time preference information, express fee preference information, and express security preference information. The target source address of each of the n commodities is determined according to the n logistics information sets and the target preference information to obtain n target source addresses. The logistics information corresponding to each target source information in the n target source addresses is obtained from the n logistics information sets to obtain n logistics information. Logistics orders are generated according to the n target source addresses and the n logistics information to obtain m logistics orders. M logistics orders are initiated, where m is a positive integer less than or equal to n. The required commodities can be selected at one time through one platform, and the source of commodities can be decentralized. In addition, orders can be dynamically optimized based on user preferences and actual supply conditions to improve the intelligence of order management, thereby improving the intelligence of order management and improving user experience.

[0099] Figure 3 : is a functional unit composition block diagram of an order management device 300 involved in an embodiment of the present application, and the order management device 300 includes:

[0100] The acquisition unit 301 is used to acquire a target commodity order of a target object and a target delivery address of the target commodity order, wherein the target commodity order includes n commodities, each of which corresponds to at least one commodity, and n is an integer greater than 1; acquire a source address of each of the n commodities to obtain n source address sets, each of which corresponds to a source address set, and each source address set corresponds to at least one source address;

[0101] The determining unit 302 is configured to determine the express path corresponding to each of the n types of goods according to the n source address sets and the target delivery address, to obtain n express path sets, one express path set corresponding to each type of goods; determine the logistics information corresponding to each of the n express path sets, to obtain n logistics information sets, the logistics information sets including estimated arrival time and cost information;

[0102] The acquisition unit 301 is further used to acquire target preference information of the target object, wherein the target preference information includes at least one of the following: express time preference information, express fee preference information, and express security preference information;

[0103] The determining unit 302 is further configured to determine a target source address of each of the n types of commodities according to the n logistics information sets and the target preference information, to obtain n target source addresses;

[0104] The acquisition unit 301 is further configured to acquire the logistics information corresponding to each target source information in the n target source addresses from the n logistics information sets to obtain n logistics information;

[0105] The generation unit 303 is used to generate logistics orders according to the n target source addresses and the n logistics information, obtain m logistics orders, and initiate the m logistics orders, where m is a positive integer less than or equal to n.

[0106] Optionally, in the aspect of acquiring the target preference information of the target object, the acquiring unit 301 is specifically used to:

[0107] Obtaining historical order records of the target object to obtain multiple historical order records;

[0108] Obtaining a piece of logistics information corresponding to each of the plurality of historical order records, to obtain a plurality of logistics information; the logistics information includes at least one of the following: logistics time, logistics cost, and logistics service evaluation parameter;

[0109] Determining the reference preference information according to the plurality of logistics information;

[0110] Obtaining attribute information of the n types of commodities to obtain n pieces of attribute information;

[0111] The reference preference information is optimized according to the n attribute information to obtain the target preference information.

[0112] Optionally, in determining the reference preference information according to the plurality of logistics information, the acquiring unit 301 is specifically configured to:

[0113] Determine an evaluation value corresponding to each piece of logistics information in the plurality of logistics information to obtain a plurality of evaluation values;

[0114] Determining a target mean and a target mean square error of the plurality of evaluation values;

[0115] Dynamically adjust the target mean value according to the target mean square error to obtain a target evaluation value;

[0116] The reference preference information corresponding to the target evaluation value is determined.

[0117] Optionally, in the aspect of optimizing the reference preference information according to the n attribute information to obtain the target preference information, the acquiring unit 301 is specifically used to:

[0118] Classify the n attribute information to obtain k attribute information sets, where k is a positive integer less than or equal to n;

[0119] Obtaining the number of occurrences of attribute information corresponding to each attribute information set in the k attribute information sets from the multiple historical order records, and obtaining k occurrence numbers; each historical order corresponds to one attribute information;

[0120] Determine k weight values ​​according to the k occurrence times;

[0121] Obtaining an evaluation value corresponding to each of the k occurrence times from the multiple evaluation values ​​to obtain k reference evaluation value sets;

[0122] Determine the mean of each reference evaluation value set in the k reference evaluation value sets to obtain k means;

[0123] Performing a weighted operation according to the k means and the k weight values ​​to obtain a first evaluation value;

[0124] determining a target deviation between the first evaluation value and the target evaluation value;

[0125] Determining a target fine-tuning coefficient corresponding to the target deviation;

[0126] The reference preference information is optimized according to the target fine-tuning coefficient to obtain the target preference information.

[0127] It can be seen that the order management device described in the embodiment of the present application obtains the target product order of the target object and the target delivery address of the target product order, the target product order includes n kinds of products, each of which corresponds to at least one product, and n is an integer greater than 1. The source address of each of the n kinds of products is obtained to obtain n source address sets, each of which corresponds to a source address set, and each source address set corresponds to at least one source address. The express delivery path corresponding to each of the n kinds of products is determined according to the n source address sets and the target delivery address to obtain n express delivery path sets, each of which corresponds to an express delivery path set, and the logistics information corresponding to each of the n express delivery path sets is determined to obtain n logistics information sets, the logistics information sets include estimated arrival time and cost information, and the target preference information of the target object is obtained. The target preference information includes at least one of the following: express time preference information, express fee preference information, and express security preference information. The target source address of each of the n commodities is determined according to the n logistics information sets and the target preference information to obtain n target source addresses. The logistics information corresponding to each target source information in the n target source addresses is obtained from the n logistics information sets to obtain n logistics information. Logistics orders are generated according to the n target source addresses and the n logistics information to obtain m logistics orders. M logistics orders are initiated, where m is a positive integer less than or equal to n. The required commodities can be selected at one time through one platform, and the source of commodities can be decentralized. In addition, orders can be dynamically optimized based on user preferences and actual supply conditions to improve the intelligence of order management, thereby improving the intelligence of order management and improving user experience.

[0128] It can be understood that the functions of each program module of the order management device of this embodiment can be specifically implemented according to the method in the above method embodiment. The specific implementation process can refer to the relevant description of the above method embodiment, which will not be repeated here.

[0129] The embodiment of the present application also provides an order management device, which includes: Figure 3 The order management device shown can be used to implement all the functions of the above-mentioned order management devices.

[0130] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any method recorded in the above method embodiments.

[0131] The present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps of any method described in the above method embodiment. The computer program product may be a software installation package.

[0132] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0133] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0134] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0135] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0136] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0137] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the above-mentioned methods of each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or CD-ROM and other media that can store program codes.

[0138] A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (English: Read-Only Memory, abbreviated as: ROM), a random access memory (English: Random Access Memory, abbreviated as: RAM), a magnetic disk or an optical disk, etc.

[0139] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. An order management method, characterized in that: The method comprises: Obtain a target commodity order of a target object and a target delivery address of the target commodity order, wherein the target commodity order includes n commodities, each of which corresponds to at least one commodity, and n is an integer greater than 1; Obtaining the supply address of each of the n types of goods to obtain n supply address sets, each of which corresponds to a supply address set, and each supply address set corresponds to at least one supply address; when the required quantity of goods exceeds the remaining quantity in stock of a certain supply address, dispatching a certain quantity of goods from other supply addresses to meet the needs of the user; Determine the express delivery path corresponding to each of the n types of goods according to the n source address sets and the target delivery address, and obtain n express delivery path sets, where each type of goods corresponds to one express delivery path set; Determine the logistics information corresponding to each of the n express path sets to obtain n logistics information sets, wherein the logistics information sets include estimated arrival time and cost information; Acquire target preference information of the target object, wherein the target preference information includes at least one of the following: express time preference information, express fee preference information, and express security preference information; Determine the target source address of each of the n commodities according to the n logistics information sets and the target preference information to obtain n target source addresses; Obtaining logistics information corresponding to each target source of goods information in the n target source of goods addresses from the n logistics information sets to obtain n logistics information; Generate logistics orders according to the n target source addresses and the n logistics information, obtain m logistics orders, and initiate the m logistics orders, where m is a positive integer less than or equal to n; If the target source addresses are the same, the corresponding logistics orders will be merged; Wherein, the acquiring target preference information of the target object includes: Obtaining historical order records of the target object to obtain multiple historical order records; Obtaining logistics information corresponding to each of the multiple historical order records, to obtain multiple logistics information; the logistics information includes: logistics time, logistics cost, and logistics service evaluation parameters; Determine the reference preference information according to the plurality of logistics information; the reference preference information includes: express time preference information, express fee preference information, and express safety preference information; Acquire the attribute information of the n kinds of commodities to obtain n pieces of attribute information; the attribute information of the commodities includes: commodity name, commodity type, commodity classification number, commodity price range, and commodity brand; Optimizing the reference preference information according to the n attribute information to obtain the target preference information; Wherein, determining the reference preference information according to the plurality of logistics information includes: Determine an evaluation value corresponding to each piece of logistics information in the plurality of logistics information to obtain a plurality of evaluation values; Determine a target mean and a target mean square error of the plurality of evaluation values; wherein the mean reflects the user's normalized preference, and the variance reflects the user's preference fluctuation; Dynamically adjust the target mean value according to the target mean square error to obtain a target evaluation value, specifically: determine the target fluctuation parameter corresponding to the target mean square error according to the preset corresponding relationship between the mean square error and the fluctuation parameter, and calculate the target evaluation value according to the following formula: target evaluation value = (1 + target fluctuation parameter) * evaluation value; the range of the fluctuation parameter is -0.2~0.2; Determining the reference preference information corresponding to the target evaluation value; The step of optimizing the reference preference information according to the n attribute information to obtain the target preference information includes: Classify the n attribute information to obtain k attribute information sets, where k is a positive integer less than or equal to n; Obtaining the number of occurrences of attribute information corresponding to each attribute information set in the k attribute information sets from the multiple historical order records, and obtaining k occurrence numbers; each historical order corresponds to one attribute information; Determine k weight values ​​according to the k occurrence times, specifically: determine the proportion of each occurrence time to obtain k weight values; Obtaining an evaluation value corresponding to each of the k occurrence times from the multiple evaluation values ​​to obtain k reference evaluation value sets; Determine the mean of each reference evaluation value set in the k reference evaluation value sets to obtain k means; Performing a weighted operation according to the k means and the k weight values ​​to obtain a first evaluation value; Determine a target deviation between the first evaluation value and the target evaluation value, that is, target deviation=(first evaluation value-target evaluation value) / target evaluation value; Determining a target fine-tuning coefficient corresponding to the target deviation, specifically: determining the target fine-tuning coefficient corresponding to the target deviation based on a preset mapping relationship between the deviation and the fine-tuning coefficient; The reference preference information is optimized according to the target fine-tuning coefficient to obtain the target preference information, that is, the target preference information = (1 + target fine-tuning coefficient) * reference preference information.

2. An order management device, characterized in that: The device comprises: an acquisition unit, configured to acquire a target commodity order of a target object and a target delivery address of the target commodity order, wherein the target commodity order includes n commodities, each of which corresponds to at least one commodity, and n is an integer greater than 1; acquire a source address of each of the n commodities to obtain n source address sets, each of which corresponds to a source address set, and each source address set corresponds to at least one source address; when the required quantity of commodities exceeds the remaining quantity in stock of a certain source address, a certain quantity of commodities is dispatched from other source addresses to meet the needs of the user; a determination unit, configured to determine a courier route corresponding to each of the n types of goods according to the n source address sets and the target delivery address, to obtain n courier route sets, one courier route set corresponding to each type of goods; determine logistics information corresponding to each courier route set in the n courier route sets, to obtain n logistics information sets, the logistics information sets including estimated arrival time and cost information; The acquisition unit is further used to acquire target preference information of the target object, wherein the target preference information includes at least one of the following: express time preference information, express fee preference information, and express security preference information; The determination unit is further configured to determine a target source address of each of the n types of commodities according to the n logistics information sets and the target preference information, to obtain n target source addresses; The acquisition unit is further used to acquire the logistics information corresponding to each target source information in the n target source addresses from the n logistics information sets to obtain n logistics information; A generating unit, configured to generate logistics orders according to the n target source addresses and the n logistics information, obtain m logistics orders, and initiate the m logistics orders, where m is a positive integer less than or equal to n; If the target source addresses are the same, the corresponding logistics orders will be merged; Wherein, in the aspect of acquiring the target preference information of the target object, the acquiring unit is specifically used for: Obtaining historical order records of the target object to obtain multiple historical order records; Obtaining a piece of logistics information corresponding to each of the plurality of historical order records, to obtain a plurality of logistics information; the logistics information includes at least one of the following: logistics time, logistics cost, and logistics service evaluation parameter; Determine the reference preference information according to the plurality of logistics information; the reference preference information includes: express time preference information, express fee preference information, and express safety preference information; Acquire the attribute information of the n kinds of commodities to obtain n pieces of attribute information; the attribute information of the commodities includes: commodity name, commodity type, commodity classification number, commodity price range, and commodity brand; Optimizing the reference preference information according to the n attribute information to obtain the target preference information; Wherein, in determining the reference preference information according to the plurality of logistics information, the acquisition unit is specifically used for: Determine an evaluation value corresponding to each piece of logistics information in the plurality of logistics information to obtain a plurality of evaluation values; Determine a target mean and a target mean square error of the plurality of evaluation values; wherein the mean reflects the user's normalized preference, and the variance reflects the user's preference fluctuation; Dynamically adjust the target mean value according to the target mean square error to obtain a target evaluation value, specifically: determine the target fluctuation parameter corresponding to the target mean square error according to the preset corresponding relationship between the mean square error and the fluctuation parameter, and calculate the target evaluation value according to the following formula: target evaluation value = (1 + target fluctuation parameter) * evaluation value; the range of the fluctuation parameter is -0.2~0.2; Determining the reference preference information corresponding to the target evaluation value; Wherein, in the aspect of optimizing the reference preference information according to the n attribute information to obtain the target preference information, the acquisition unit is specifically used for: Classify the n attribute information to obtain k attribute information sets, where k is a positive integer less than or equal to n; Obtaining the number of occurrences of attribute information corresponding to each attribute information set in the k attribute information sets from the multiple historical order records, and obtaining k occurrence numbers; each historical order corresponds to one attribute information; Determine k weight values ​​according to the k occurrence times, specifically: determine the proportion of each occurrence time to obtain k weight values; Obtaining an evaluation value corresponding to each of the k occurrence times from the multiple evaluation values ​​to obtain k reference evaluation value sets; Determine the mean of each reference evaluation value set in the k reference evaluation value sets to obtain k means; Performing a weighted operation according to the k means and the k weight values ​​to obtain a first evaluation value; Determine a target deviation between the first evaluation value and the target evaluation value, that is, target deviation=(first evaluation value-target evaluation value) / target evaluation value; Determining a target fine-tuning coefficient corresponding to the target deviation, specifically: determining the target fine-tuning coefficient corresponding to the target deviation based on a preset mapping relationship between the deviation and the fine-tuning coefficient; The reference preference information is optimized according to the target fine-tuning coefficient to obtain the target preference information, that is, the target preference information = (1 + target fine-tuning coefficient) * reference preference information.

3. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory is used to store one or more programs and is configured to be executed by the processor, wherein the programs include instructions for executing the steps in the method according to claim 1.

4. An order management system, characterized in that: The order management system is the device as claimed in claim 2.

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