Distribution range adjusting method, electronic equipment and medium

Abstract

The invention discloses a distribution range adjustment method, electronic equipment and a medium. The method comprises the steps of determining a potential interest surface located outside a current distribution range of a target merchant; the potential interest surface is a geographic area where the user has the potential of placing an order for the target merchant; generating a new delivery range for the target merchant according to the potential interest surface and the interest surface included in the current delivery range; and according to the performance change degree of the new delivery range relative to the current delivery range and the business circle to which the target merchant belongs, determining whether to apply the new delivery range to the target merchant, thereby expanding the delivery scale of the merchant and promoting the improvement of the user scale while satisfying the logistics performance efficiency. And the mined potential interest surface is the interest surface of the user with the ordering potential for the commercial tenant, so that more reasonable and accurate distribution range adjustment and optimization can be realized by utilizing the potential interest surface.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method for adjusting a delivery range, an electronic device, and a medium. Background Art

[0002] After users place an order for goods purchased online, merchants need to deliver the goods offline. Usually, merchants have a certain delivery range and will not deliver goods over unlimited distances. In order to increase the user base, the delivery range will be adjusted, such as by expanding the delivery range to cover more users.

[0003] In practical applications, logistics fulfillment efficiency and expansion of distribution scale are two major indicators that need to be considered to increase user scale. However, there is a conflict between fulfillment efficiency and expansion of distribution scale. That is, expanding the distribution range of merchants will often lead to a decrease in fulfillment efficiency. As the distribution scale expands, the delivery distance of the delivery staff becomes longer and the delivery is not timely.

[0004] Therefore, optimizing and adjusting the merchant delivery range becomes a challenge to increase the user scale. Summary of the invention

[0005] The purpose of this application is to propose a delivery range adjustment method, device, electronic device, medium and program product to address the deficiencies of the above-mentioned prior art, and this purpose is achieved through the following technical solutions.

[0006] The first aspect of the present application provides a method for adjusting a delivery range, the method comprising:

[0007] Determine a potential interest area outside the current delivery range of the target merchant; the potential interest area is a geographical area where the user has the potential to place an order with the target merchant;

[0008] Generating a new delivery range for the target merchant according to the potential interest faces and the interest faces included in the current delivery range;

[0009] Whether to apply the new delivery range to the target merchant is determined based on the degree of change in the performance of the new delivery range relative to the current delivery range and the business district to which the target merchant belongs.

[0010] In some embodiments, determining the potential interest groups outside the current delivery range of the target merchant includes:

[0011] Acquire target merchants that meet the range adjustment conditions; determine candidate interest surfaces that are outside the current delivery range of the target merchant and within a preset distance; determine the delivery time from the target merchant to the candidate interest surfaces; and select potential interest surfaces from the candidate interest surfaces based on the delivery time and the user's historical order records on the candidate interest surfaces.

[0012] In some embodiments, selecting a potential interest facet from the candidate interest facets according to the delivery time of the candidate interest facets and the historical order records of the user on the candidate interest facets includes:

[0013] Based on the historical order records of users on the candidate interest surface, the order potential of the candidate interest surface is determined; the order potential reflects the probability of the user placing an order to the target merchant; and the candidate interest surface whose order potential exceeds a preset potential value and whose delivery time does not exceed a preset time is selected as the potential interest surface.

[0014] In some embodiments, obtaining target merchants that meet the scope adjustment conditions includes:

[0015] Merchants adopting the target delivery type are obtained from the merchant database; merchants having user order records within a preset time range are selected from the obtained merchants as target merchants.

[0016] In some embodiments, generating a new delivery range for the target merchant according to the potential interest facets and the interest faces included in the current delivery range includes:

[0017] Determine the attribute indicators of the potential interest surface and the attribute indicators of the interest surface included in the current delivery range; obtain an interest surface combination that meets the target constraint conditions based on the attribute indicators of the potential interest surface and the attribute indicators of the interest surface included in the current delivery range; and generate a new delivery range for the target merchant using the interest surface combination.

[0018] In some embodiments, the attribute indicator includes future order volume and at least one of the following: delivery time and delivery distance; the step of obtaining an interest face combination that meets the target constraint condition based on the attribute indicator of the potential interest face and the attribute indicator of the interest face included in the current delivery range includes:

[0019] The potential interest faces and the interest faces included in the current delivery range are combined to obtain a set of interest faces that the target merchant can cover; according to the attribute indicators of each interest face in the interest face set, the interest face set is optimized by operations combination to obtain an interest face combination that meets the target constraint conditions; the target constraint conditions are maximizing the order quantity and the delivery time and / or delivery distance does not exceed a threshold.

[0020] In some embodiments, the determining whether to apply the new delivery range to the target merchant according to the degree of change in the performance of the new delivery range relative to the current delivery range and the business district to which the target merchant belongs includes:

[0021] Determine the degree of change in the performance of the new delivery range relative to the current delivery range; apply the new delivery range to the target merchant if the proportion of merchants eligible for range adjustment included in the business district to which the target merchant belongs exceeds a preset proportion and the degree of change in performance does not exceed a preset value; apply the new delivery range to the target merchant if the proportion of merchants eligible for range adjustment included in the business district to which the target merchant belongs does not exceed a preset proportion.

[0022] In some embodiments, determining the degree of change in the fulfillment of the new delivery range relative to the current delivery range includes:

[0023] Based on the attribute indicators of the interest areas included in the new delivery range, a first fulfillment risk value of the new delivery range is determined; the first fulfillment risk value represents the logistics fulfillment of the target merchant using the new delivery range; based on the attribute indicators of the interest areas included in the current delivery range, a second fulfillment risk value of the current delivery range is determined; the second fulfillment risk value represents the logistics fulfillment of the target merchant using the current delivery range; the difference between the first fulfillment risk value and the second fulfillment risk value is used as the degree of fulfillment change.

[0024] A second aspect of the present application provides a delivery range adjustment device, the device comprising:

[0025] A potential point determination module is used to determine potential interest areas outside the current delivery range of the target merchant; the potential interest areas are geographical areas where users have the potential to place orders with the target merchant;

[0026] A range generation module, used for generating a new delivery range for the target merchant according to the potential interest face and the interest face included in the current delivery range;

[0027] The range evaluation module is used to determine whether to apply the new delivery range to the target merchant based on the degree of change in the performance of the new delivery range relative to the current delivery range and the business district to which the target merchant belongs.

[0028] The third aspect of the present application proposes an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described in the first aspect above.

[0029] A fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the program is executed by a processor to implement the method described in the first aspect above.

[0030] An embodiment of the fifth aspect of the present application provides a computer program product, including a computer program, wherein the computer program is executed by a processor to implement the method described in the first aspect above.

[0031] Based on the above-mentioned delivery range adjustment method, device, electronic device, medium and program product, the present application has at least the following beneficial effects or advantages:

[0032] By mining potential interest groups with order potential outside the merchant's existing delivery range, a new delivery range is obtained based on the mined potential interest groups and the interest groups already included in the existing delivery range. Then, based on the degree of change in the new delivery range relative to the existing delivery range and the business district to which the merchant belongs, it is determined whether the new delivery range is applied to the merchant, thereby expanding the merchant's delivery scale and promoting the increase in user scale while meeting the logistics fulfillment efficiency. And because the mined potential interest groups are the interest groups of users with the potential to place orders for the merchant, using potential interest groups can achieve more reasonable and accurate delivery range optimization.

[0033] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0035] Figure 1 The present invention is a flow chart of an embodiment of a method for adjusting a delivery range according to an exemplary embodiment;

[0036] Figure 2 The present invention is a flowchart showing an overall implementation of a distribution range adjustment according to an exemplary embodiment;

[0037] Figure 3 is a structural schematic diagram of a delivery range adjustment device according to an exemplary embodiment;

[0038] Figure 4 is a schematic diagram of a hardware structure of an electronic device according to an exemplary embodiment;

[0039] Figure 5 The figure is a schematic diagram of the structure of a storage medium according to an exemplary embodiment. DETAILED DESCRIPTION

[0040] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of systems and methods consistent with some aspects of the present application as detailed in the appended claims.

[0041] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0042] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0043] In addition, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0044] In the experience of online commodity management, there is often a conflict between the increase in distribution scale and logistics fulfillment. That is to say, if the distribution scale is expanded by adjusting the merchant's distribution range, it will often lead to a decrease in logistics fulfillment efficiency. There is a contradiction between the two.

[0045] In order to improve the effective population coverage of merchants while meeting the logistics fulfillment efficiency, this application proposes a distribution range adjustment method, which mines potential interest areas with order potential outside the merchant's existing distribution range, obtains a new distribution range based on the mined potential interest areas and the interest areas already included in the existing distribution range, and then determines whether the new distribution range is applied to the merchant based on the degree of change in the performance of the new distribution range relative to the existing distribution range and the business district to which the merchant belongs, thereby expanding the merchant's distribution scale and promoting the increase in user scale while meeting the logistics fulfillment efficiency. And because the mined potential interest areas are the interest areas of users with the potential to place orders for merchants, using potential interest areas can achieve more reasonable and accurate distribution range optimization.

[0046] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The several specific embodiments listed can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0047] Embodiment 1

[0048] Figure 1 FIG. 1 is a flow chart of an embodiment of a method for adjusting a delivery range according to an exemplary embodiment. Figure 1 As shown, the following steps 101 to 103 are included:

[0049] Step 101: Determine a potential interest area outside the current delivery range of a target merchant; the potential interest area is a geographical area where the user has the potential to place an order with the target merchant;

[0050] Step 102: Generate a new delivery range for the target merchant based on the potential interest face and the interest face included in the current delivery range;

[0051] Step 103: Determine whether to apply the new delivery range to the target merchant based on the degree of change in the new delivery range relative to the current delivery range and the business district to which the target merchant belongs.

[0052] This embodiment can be applied to an application, website, mini-program or cloud application with a merchant delivery range adjustment function. By deploying the application, website, mini-program or cloud application in an electronic device, the merchant delivery range can be optimized.

[0053] The target merchant is the merchant whose delivery range is to be adjusted, and can also be called a merchant. The target merchant can be a merchant object with a certain delivery distance. For example, different merchants purchase different types of delivery service packages, which can be mainly divided into special delivery, express delivery, and city-wide delivery. Among these three types, merchants who purchase special delivery or express delivery service packages can be used as target merchants. The target merchant can also be a merchant object specified by the user. For example, the user believes that some merchants or a certain merchant can increase the user scale, and thus specifies these merchants or this merchant to adjust the delivery range.

[0054] The current delivery range can be understood as the existing delivery range of the target merchant, that is, the geographical range that the target merchant can currently cover. The geographical range can be a geographical boundary defined by a geo-fence. In other words, only users within the merchant's delivery range can purchase the target merchant's products. Usually, the merchant's delivery range is divided based on human experience, common sense, and the geographical information around the merchant, such as static attributes such as roads, rivers, viaducts, and subway lines.

[0055] Area of ​​Interest (AOI) refers to the geographical area where the user has the potential to place an order with the target merchant. The user may be a user whose location is on the potential interest area, that is, the user on the potential interest area has a preference for placing an order with the target merchant. Exemplarily, the potential interest area may be a residential area, a university, an office building, an industrial park, a shopping mall, a hospital or a scenic spot. It should be noted that the potential interest area may be one or more.

[0056] The new delivery range can be understood as a geographical range that is optimized and expanded based on the current delivery range. The new delivery range includes both the interests within the existing delivery range and the potential interests. The new delivery range can also be a geographical boundary defined by using a geo-fence.

[0057] The degree of fulfillment change can be understood as the changes in logistics fulfillment of the new delivery range relative to the current delivery range. The greater the degree of fulfillment change, the higher the overall fulfillment change risk.

[0058] A business district can be understood as a commercial area of ​​a certain scale. Usually, a business district will have a large number of shops, shopping centers, restaurants, entertainment venues and other businesses, which can attract users to come for shopping, consumption and entertainment. It can be seen that a business district will include multiple businesses.

[0059] Exemplarily, assuming that the target merchants to be adjusted for the delivery range are merchant A, the potential interest surfaces outside the current delivery range of merchant A are mined: AOI 1, AOI 2, AOI 3, and a new delivery range is generated for merchant A based on AOI 1, AOI 2, AOI 3 and the interest surfaces AOI 4, AOI 5, AOI 6 included in the current delivery range. Then, based on the degree of fulfillment change of the new delivery range relative to the current delivery range and the business district to which merchant A belongs, it is determined whether to apply the new delivery range to merchant A.

[0060] At this point, the above Figure 1 The delivery range adjustment process shown in the figure is to mine potential interest groups with order potential outside the merchant's existing delivery range, obtain a new delivery range based on the mined potential interest groups and the interest groups already included in the existing delivery range, and then determine whether the new delivery range is applied to the merchant based on the degree of change in the fulfillment of the new delivery range relative to the existing delivery range and the business district to which the merchant belongs, thereby expanding the merchant's delivery scale and promoting the increase in user scale while meeting the logistics fulfillment efficiency. And because the mined potential interest groups are the interest groups of users with order potential for the merchant, using the potential interest groups can achieve more reasonable and accurate delivery range optimization.

[0061] In an optional embodiment of the present application, the above step 101 of determining the potential interest areas outside the current delivery range of the target merchant includes the following specific steps:

[0062] Obtain target merchants that meet the scope adjustment conditions;

[0063] Determine candidate interest areas that are outside the current delivery range of the target merchant and within a preset distance;

[0064] Determine the delivery time from the target merchant to the candidate interest surface;

[0065] According to the delivery time and the historical order records of users on the candidate interest surfaces, potential interest surfaces are selected from the candidate interest surfaces.

[0066] The range adjustment conditions can be understood as the conditions that merchants suitable for delivery range adjustment need to meet, and are used to screen target merchants for delivery range adjustment from all merchants. The range adjustment conditions can be set in advance based on actual needs or experience.

[0067] The preset distance can be understood as the farthest delivery distance corresponding to the target merchant, that is, the target merchant is taken as the starting point and the delivery destination is taken as the end point. The distance from the starting point to the end point cannot exceed the preset distance. It should be noted that the farthest delivery distances corresponding to different delivery types may be different. For example, the farthest delivery distance corresponding to special delivery is 6 kilometers, and the farthest delivery distance corresponding to express delivery is 8 kilometers.

[0068] Candidate interest surfaces can be understood as interest surfaces mined from the existing delivery range, that is, interest surfaces mined from the spatial dimension.

[0069] The delivery time can be understood as the length of time required to deliver the goods from the target merchant to the candidate interest surface, and the delivery time can reflect the time dimension of potential interest surface screening. It should be noted here that the determination of the delivery time needs to consider many factors such as the distance from the starting point to the end point, the order rate, and the order density on the interest surface. The determination method can be analyzed and estimated using deep learning technology or time estimation method, and this application does not make specific restrictions on this.

[0070] The historical order records are the order records of the user within a previous period of time. The order records can reflect the user's order preferences for merchants, that is, they can reflect the user experience dimension of potential interest screening. Specifically, the historical order records of merchants belonging to the same category as the target merchant can be used.

[0071] Exemplarily, for the target merchant A, assuming that the candidate interest surfaces outside the current delivery range of merchant A and within the preset distance are: AOI 1, AOI 2, and AOI 3, determine the delivery time from merchant A to AOI 1, the delivery time from merchant A to AOI 2, and the delivery time from merchant A to AOI 3, and then select AOI 2 and AOI 3 as potential interest surfaces from these candidate interest surfaces based on these delivery times, the historical order records of users on AOI 1, the historical order records of users on AOI 2, and the historical order records of users on AOI 3.

[0072] In this embodiment, merchants that meet certain conditions are obtained as target merchants for range adjustment, and then the business conditions and existing delivery range of the target merchants are analyzed, and potential interests with the potential to place orders with the target merchants are mined from the spatial dimension, time dimension and user experience dimension, so as to achieve more reasonable and accurate delivery range adjustment.

[0073] Based on the above implementation, the mining of potential interest aspects can also be considered from a single dimension or any combination of dimensions, such as considering the combination of time dimension and space dimension to mine potential interest aspects, or considering the combination of user experience dimension and time dimension to mine potential interest aspects.

[0074] In an optional embodiment of the present application, obtaining target merchants that meet the range adjustment conditions specifically includes: obtaining merchants that adopt the target delivery type from the merchant database, and selecting merchants that have user order records within a preset time range from the obtained merchants as target merchants.

[0075] Among them, the merchant database can be understood as a database that records all merchants on the platform. In the merchant database, different merchants use different delivery types according to their actual needs. The delivery types may include special delivery, express delivery, city-wide delivery, etc.

[0076] The target delivery type can be understood as one of the conditions that need to be met to screen merchants suitable for delivery range adjustment from the delivery type dimension. For example, the target delivery type can be dedicated delivery and / or express delivery.

[0077] The preset time range can be understood as a time range closest to the current time. User order records within a time range can be used as the second condition that needs to be met to screen merchants that are suitable for delivery range adjustment from the perspective of business conditions.

[0078] In this embodiment, by selecting merchants suitable for distribution range adjustment as target merchants from the dimensions of distribution type and merchant business status, unnecessary calculations can be reduced and the accuracy and rationality of optimization objects can be improved.

[0079] In an optional embodiment of the present application, according to the delivery time and the historical order records of the user in the candidate interest surface, selecting a potential interest surface from the candidate interest surface specifically includes the following steps:

[0080] Based on the historical order records of users on the candidate interest facets, determine the order potential of the candidate interest facets; the order potential reflects the probability of the user placing an order with the target merchant;

[0081] Candidate interest groups whose order potential exceeds a preset potential value and whose delivery time does not exceed a preset time are selected as potential interest groups.

[0082] The order potential reflects the probability of users placing an order to the target merchant on the candidate interest surface. The greater the order potential, the higher the corresponding order probability.

[0083] Based on the historical order records of users on the candidate interest surface, the order potential of the candidate interest surface is determined, specifically in the following manner: the order potential of each user on the candidate interest surface is estimated by using the historical order records of each user on the candidate interest surface, and then the order potential of each user is aggregated to obtain the order potential of the candidate interest surface. Among them, the order potential of a single user can be estimated by deep learning technology or probability estimation method, which is not specifically limited in this application.

[0084] Exemplarily, assuming that there are users A, B and C on the candidate interest surface, it is estimated that user A has 1 order, user B has 0 order, and user C has 2 order. Thus, the order potential of the candidate interest surface is 1+0+2=3 orders.

[0085] It should be noted that the above-mentioned method for estimating the order potential of the candidate interest faces is only an exemplary description, and other methods can also be used to achieve the estimation of the order potential of the candidate interest faces, and this application does not make any specific limitations on this.

[0086] The preset potential value can be understood as a potential threshold value set in advance according to actual experience. The potential threshold value can be set based on the city's business conditions, for example, set to 3 orders or 4 orders.

[0087] The preset duration can be understood as the longest delivery time corresponding to the target merchant, that is, the target merchant is taken as the starting point and the delivery destination is taken as the end point. The time from the starting point to the end point cannot exceed the preset duration. It should be noted that the longest delivery time corresponding to different delivery types may be different. For example, the longest delivery time corresponding to special delivery is 30 minutes, and the longest delivery time corresponding to express delivery is 40 minutes.

[0088] In this embodiment, the order potential of the candidate interest faces is determined by using historical order records, so that the candidate interest faces whose order potential exceeds a preset potential value and whose delivery time does not exceed a preset time are selected as potential interest faces, so as to improve the accuracy of potential interest face mining and ensure that the mined potential interest faces can also meet the logistics fulfillment requirements.

[0089] In an optional embodiment of the present application, step 102 generates a new delivery range for the target merchant according to the potential interest face and the interest face included in the current delivery range, including the following specific steps:

[0090] Determine the attribute indicators of potential interest areas and the attribute indicators of interest areas included in the current delivery range;

[0091] According to the attribute indicators of the potential interest surfaces and the attribute indicators of the interest surfaces included in the current delivery range, a combination of interest surfaces that meets the target constraint conditions is obtained;

[0092] Utilize this interest face combination to generate a new delivery range for the target merchants.

[0093] Attribute indicators reflect different aspects of interest, which may include future order volume, delivery time, delivery distance, etc. Future order volume refers to the future orders placed by target merchants for interest, delivery time refers to the time required for target merchants to deliver to interest, and delivery distance refers to the length of the delivery route from target merchants to interest.

[0094] It should be noted that the determination method of the attribute index can be implemented by deep learning technology or algorithm, and this application does not make specific restrictions on this. For example, the future order volume of the interest surface can be obtained by inputting the order potential of the user on the interest surface and the label information of the target merchant into a preset estimation model, and the estimation model outputs the future order volume of the interest surface.

[0095] The target constraint condition can be understood as the requirement condition for the attribute index of the interest surface, which is used to obtain the most appropriate combination of interest surfaces.

[0096] The interest face combination can be understood as a set of potential interest faces and interest faces included in the current delivery range that meet the target constraints.

[0097] The interest face combination is used to generate a new delivery range for the target merchant, specifically by obtaining the geo-fence information of each interest face in the interest face combination, merging the geo-fence information of each interest face using a range generation method, and obtaining an overall delivery range, i.e., a new delivery range for the target merchant. Furthermore, in order to ensure that the new delivery range includes the current delivery range, the new delivery range can also be adjusted in combination with the current delivery range, so that the finally generated new delivery range includes the current delivery range.

[0098] In this embodiment, by determining the attribute indicators of potential interest surfaces and the attribute indicators of interest surfaces included in the current delivery range, an interest surface combination that meets the target constraint conditions is obtained based on the attribute indicators of these interest surfaces, so that an accurate and reasonable new delivery range is generated using the interest surface combination.

[0099] In an optional embodiment of the present application, when the attribute index includes the future order volume and at least one of the following: delivery time and delivery distance; obtaining an interest face combination that meets the target constraint condition according to the attribute index of the potential interest face and the attribute index of the interest face included in the current delivery range includes the following specific steps:

[0100] Merge the potential interests with the interests included in the current delivery range to obtain the set of interests that the target merchant can cover;

[0101] According to the attribute index of each interest face in the interest face set, the interest face set is optimized by operations combination to obtain an interest face combination that meets the target constraint condition.

[0102] Among them, the interest set is the largest set that the target merchant can cover.

[0103] The objective constraint is to maximize the order quantity and ensure that the delivery time and / or delivery distance does not exceed the threshold. Operations Research and Combinatorial Optimization (ORCO) is used to find the interest face combination that maximizes the order quantity but does not exceed the threshold in the delivery time and / or delivery distance.

[0104] Exemplarily, assuming that the interest surface set includes AOI 1, AOI 2, and AOI 3, four interest surface combinations {AOI 1, AOI 2, AOI 3}, {AOI 1, AOI 2}, {AOI 1, AOI 3}, and {AOI 2, AOI 3} can be obtained from these three interest surfaces, among which the delivery time of the interest surface combination {AOI 1, AOI 2, AOI 3} exceeds the threshold and can be eliminated. The sum of the future order quantities of the remaining three groups {AOI 1, AOI 2}, {AOI 1, AOI 3}, and {AOI 2, AOI 3} are calculated to be 12, 24, and 16 respectively, and the interest surface combination {AOI 1, AOI 3} with the largest sum of future order quantities is selected.

[0105] It should be noted that the above is only an exemplary description of the operations research combinatorial optimization method and does not constitute a limitation on the protection scope of the embodiments of the present application.

[0106] In this embodiment, the potential interests of the target merchant and the interests already included in the current delivery range are merged to obtain the maximum set of interests that the target merchant can cover, and then a set of interest combinations that maximize the order volume and whose delivery time and / or delivery distance do not exceed a threshold are found through operations combinatorial optimization, so that the generated new delivery range is more reasonable and accurate.

[0107] In an optional embodiment of the present application, step 103 determines whether to apply the new delivery range to the target merchant according to the degree of change in the performance of the new delivery range relative to the current delivery range and the business district to which the target merchant belongs, including the following specific steps:

[0108] Determine the degree of change in fulfillment of the new delivery range relative to the current delivery range;

[0109] If the proportion of merchants eligible for scope adjustment in the business district to which the target merchant belongs exceeds the preset proportion and the degree of change in fulfillment does not exceed the preset value, the new delivery scope will be applied to the target merchant;

[0110] If the proportion of merchants in the business district to which the target merchant belongs that are eligible for scope adjustment does not exceed the preset proportion, the new delivery scope will be applied to the target merchant.

[0111] Among them, the degree of fulfillment change refers to the change in logistics fulfillment of the new delivery range relative to the current delivery range, which is used to indicate the risk of fulfillment change after applying the new delivery range.

[0112] The preset ratio can be pre-set based on practical experience, for example, 30%. When the proportion of merchants eligible for range adjustment in a business district exceeds the preset ratio, it means that there are a large number of merchants in the business district whose delivery range needs to be adjusted. In general, the configuration of the delivery personnel's capacity is based on the business district. Therefore, if the number of merchants whose delivery range needs to be adjusted is large and the delivery capacity configured in the business district is constant, then it is necessary to evaluate the performance change risk of the target merchants to ensure that the logistics performance efficiency will not change significantly after the target merchants apply the new delivery range. If the number of merchants whose delivery range needs to be adjusted in the business district is small, the performance change risk of the target merchants can be ignored, because the range adjustment of a small number of merchants does not have a great impact on the delivery capacity of the business district, and the logistics performance efficiency of the target merchants can be ensured. In addition, the generation of the new delivery range also comprehensively considers the various attribute indicators of delivery time, delivery distance, and future order volume.

[0113] For example, assuming that the proportion of merchants eligible for range adjustment in the business district to which target merchant A belongs is 1%, since the merchant proportion of 1% does not exceed the preset proportion of 30%, it means that the number of merchants in the business district that need to adjust the delivery range is relatively small. The degree of change in the performance of target merchant A can be ignored, and the new delivery range can be directly applied to target merchant A, so that the wearing scale of target merchant A can be improved.

[0114] In this embodiment, the degree of change in the fulfillment of the new delivery range relative to the current delivery range is determined, and the proportion of merchants in the business district to which the target merchant belongs that meet the requirements of the range adjustment is combined to determine whether the new delivery range should be applied to the target merchant, so as to ensure that the merchant's logistics fulfillment efficiency will not be reduced and the delivery scale will be improved.

[0115] In an optional embodiment of the present application, determining the degree of change in the performance of the new delivery range relative to the current delivery range specifically includes the following steps:

[0116] Determine the first fulfillment risk value of the new delivery range according to the attribute indicators of the interest areas included in the new delivery range;

[0117] Determine the second fulfillment risk value of the current delivery range according to the attribute indicators of the interest areas included in the current delivery range;

[0118] The difference between the first performance risk value and the second performance risk value is taken as the degree of performance change.

[0119] Among them, the first fulfillment risk value represents the logistics fulfillment of the target merchant using the new delivery range, and the second fulfillment risk value represents the logistics fulfillment of the target merchant using the current delivery range.

[0120] Attribute indicators reflect information on different aspects of interest, which may include future order volume, delivery time, delivery distance, etc.

[0121] The method for determining the first performance risk value and the second performance risk value can be implemented using deep learning technology or algorithms, and this application does not make any specific limitations on this.

[0122] In this embodiment, by determining a first fulfillment risk value of a new delivery range and a second fulfillment risk value of a current delivery range, the first fulfillment risk value and the second fulfillment risk value are used to implement an assessment of the degree of fulfillment change.

[0123] Embodiment 2

[0124] Based on the above embodiment 1, Figure 2 The overall implementation flow chart of a delivery range adjustment is shown according to an exemplary embodiment, and includes the following steps:

[0125] Step 1: Screen target merchants

[0126] In step 1, merchants that use the target delivery type and have user order records within a preset time range are selected from the merchant database as target merchants. It can be understood that the number of target merchants can be one or more.

[0127] Step 2: Explore potential interests

[0128] In step 2, for each target merchant, the candidate interest surfaces that are outside the current delivery range of the target merchant and within the preset distance are determined, and the delivery time from the target merchant to the candidate interest surfaces is determined, and the order potential of the candidate interest surfaces is determined based on the historical order records of users on the candidate interest surfaces. The candidate interest surfaces whose order potential exceeds the preset potential value and whose delivery time does not exceed the preset time are selected as potential interest surfaces, thereby realizing the mining of potential order opportunity points from the time and space dimensions and the user experience dimensions.

[0129] Step 3: Merge to generate the largest set of interests that the target merchant can cover

[0130] In step 3, the interest faces included in the existing delivery range of the target merchant are merged with the potential interest faces mined for the target merchant to obtain the interest face set of the target merchant.

[0131] Step 4: Estimate the attribute index of each interest face in the interest face set

[0132] In step 4, deep learning technology can be used to estimate the attribute indicators of each interest facet in the interest facet set, such as future order volume, delivery time, and delivery distance.

[0133] Step 5: Generate a new delivery area

[0134] In step 5, based on the attribute indicators of each interest facet in the interest facet set, the interest facet set is optimized through operations combinatorial optimization to obtain an interest facet combination that maximizes the order volume and does not exceed a threshold value in the delivery time and / or delivery distance, and a new delivery range is generated using the interest facet combination.

[0135] Step 6: Evaluate new delivery areas

[0136] In step 6, the degree of change in the performance of the new delivery range relative to the current delivery range is determined. When the proportion of merchants in the business district to which the target merchant belongs that are eligible for range adjustment exceeds a preset proportion and the degree of change in performance does not exceed a preset value, the new delivery range is applied to the target merchant. When the proportion of merchants in the business district to which the target merchant belongs that are eligible for range adjustment does not exceed a preset proportion, the new delivery range is applied to the target merchant.

[0137] The present application embodiments and the above Figure 1 The embodiments are based on the same inventive concept, and the specific implementation of steps 1 to 6 can refer to the relevant description of steps 101 to 103, which will not be repeated here.

[0138] Based on the above-mentioned embodiment 2, potential interest groups with order potential outside the existing delivery range of the target merchant are explored from the time and space dimensions and the user experience dimension, and the interest groups within the existing delivery range are merged with the potential interest groups, and the attribute indicators of each interest group are estimated. In combination with the estimated attribute indicators, operations combinatorial optimization is used to obtain an interest group combination that meets the target constraint conditions, so that an accurate and reasonable new delivery range is generated using the interest group combination, and further a judgment is made as to whether the new delivery range should be applied to the target merchant based on the degree of change in the fulfillment of the new delivery range relative to the existing delivery range and the proportion of merchants whose range is adjusted in the business district to which the target merchant belongs, so as to ensure that the logistics fulfillment efficiency of the merchant will not be reduced, while the delivery scale is improved.

[0139] The execution subject of the embodiment of the present application may be an application, service, instance, software-based functional module, virtual machine (VM), container or cloud server, etc., or a hardware device (such as a server or terminal device) or hardware chip (such as CPU, GPU, FPGA, NPU, AI acceleration card or DPU) with data processing function. The device for implementing the distribution range adjustment can be deployed on the computing device of the application party that provides the corresponding service or on the cloud computing platform that provides computing power, storage and network resources. The mode of providing services to the outside world by the cloud computing platform may be IaaS (Infrastructure as a Service), PaaS (Platform as a Service), SaaS (Software as a Service) or DaaS (Data as a Service). Taking the platform providing SaaS software as a service (Software as a Service) as an example, the cloud computing platform can use its own computing resources to provide the training of the distribution range adjustment model or the functional execution of the distribution range adjustment module, and the specific application architecture can be built according to the service requirements. For example, the platform can provide construction services based on the above model to applications or individuals using platform resources, and further call the above model and implement online or offline delivery range adjustment functions based on delivery range adjustment requests submitted by relevant clients or servers and other devices.

[0140] Corresponding to the above-mentioned embodiment of the delivery range adjustment method, the present application also provides an embodiment of the delivery range adjustment device.

[0141] Figure 3 FIG. 1 is a schematic diagram of a structure of a delivery range adjustment device according to an exemplary embodiment. The device is used to execute the delivery range adjustment method provided in any of the above embodiments, such as Figure 3 As shown, the delivery range adjustment device includes:

[0142] The potential point determination module 310 is used to determine the potential interest area outside the current delivery range of the target merchant; the potential interest area is the geographical area where the user has the potential to place an order with the target merchant;

[0143] A range generation module 320, configured to generate a new delivery range for the target merchant according to the potential interest facets and the interest facets included in the current delivery range;

[0144] The range evaluation module 330 is used to determine whether to apply the new delivery range to the target merchant based on the degree of change in the performance of the new delivery range relative to the current delivery range and the business district to which the target merchant belongs.

[0145] In an optional implementation, the potential point determination module 310 is specifically used to obtain a target merchant that meets the range adjustment conditions; determine a candidate interest surface that is outside the current delivery range of the target merchant and within a preset distance; determine the delivery time from the target merchant to the candidate interest surface; and select a potential interest surface from the candidate interest surface based on the delivery time and the user's historical order records on the candidate interest surface.

[0146] In an optional implementation, the potential point determination module 310 is specifically used to determine the order potential of the candidate interest surface based on the historical order records of users on the candidate interest surface during the process of selecting potential interest surfaces from the candidate interest surfaces according to the delivery time of the candidate interest surface and the historical order records of users on the candidate interest surface; the order potential reflects the probability of the user placing an order for the target merchant; and select the candidate interest surface whose order potential exceeds a preset potential value and whose delivery time does not exceed a preset time as the potential interest surface.

[0147] In an optional implementation, the potential point determination module 310 is specifically used to obtain merchants that adopt the target delivery type from the merchant database during the process of obtaining target merchants that meet the range adjustment conditions; and select merchants that have user order records within a preset time range as target merchants from the obtained merchants.

[0148] In an optional implementation, the range generation module 320 is specifically used to determine the attribute indicators of the potential interest surface and the attribute indicators of the interest surface included in the current delivery range; obtain an interest surface combination that meets the target constraint conditions based on the attribute indicators of the potential interest surface and the attribute indicators of the interest surface included in the current delivery range; and use the interest surface combination to generate a new delivery range for the target merchant.

[0149] In an optional implementation, the attribute indicators include future order volume and at least one of the following: delivery time, delivery distance; the range generation module 320 is specifically used to merge the potential interest surfaces and the interest surfaces included in the current delivery range in the process of obtaining an interest surface combination that meets the target constraint conditions based on the attribute indicators of the potential interest surfaces and the attribute indicators of the interest surfaces included in the current delivery range, so as to obtain a set of interest surfaces that can be covered by the target merchant; according to the attribute indicators of each interest surface in the interest surface set, the interest surface set is operationally combinatorially optimized to obtain an interest surface combination that meets the target constraint conditions; the target constraint conditions are maximizing the order volume, and the delivery time and / or delivery distance does not exceed a threshold.

[0150] In an optional implementation, the range assessment module 330 is specifically used to determine the degree of change in the performance of the new delivery range relative to the current delivery range; when the proportion of merchants in the business district to which the target merchant belongs that are eligible for range adjustment exceeds a preset proportion and the degree of change in performance does not exceed a preset value, the new delivery range is applied to the target merchant; when the proportion of merchants in the business district to which the target merchant belongs that are eligible for range adjustment does not exceed a preset proportion, the new delivery range is applied to the target merchant.

[0151] In an optional implementation, the range assessment module 330 is specifically used to determine a first fulfillment risk value of the new delivery range according to the attribute indicators of the interest surface included in the new delivery range in the process of determining the degree of change in the performance of the new delivery range relative to the current delivery range; the first fulfillment risk value represents the logistics fulfillment of the target merchant using the new delivery range; the second fulfillment risk value is determined according to the attribute indicators of the interest surface included in the current delivery range; the second fulfillment risk value represents the logistics fulfillment of the target merchant using the current delivery range; and the difference between the first fulfillment risk value and the second fulfillment risk value is used as the degree of change in performance.

[0152] The implementation process of the functions and effects of each unit in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method, and will not be repeated here.

[0153] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiment described above is only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present application scheme. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0154] In the embodiment of the present application, by mining potential interest areas with order potential outside the existing delivery range of the merchant, a new delivery range is obtained based on the mined potential interest areas and the interest areas already included in the existing delivery range, and then based on the degree of change in the performance of the new delivery range relative to the existing delivery range and the business district to which the merchant belongs, it is determined whether the new delivery range is applied to the merchant, thereby expanding the merchant's delivery scale and promoting the increase in user scale while meeting the logistics performance efficiency. And because the mined potential interest areas are the interest areas of users with order potential for the merchant, using the potential interest areas can achieve more reasonable and accurate delivery range optimization.

[0155] The embodiment of the present application also provides an electronic device corresponding to the delivery range adjustment method provided in the above embodiment, so as to execute the above delivery range adjustment method.

[0156] Figure 4 6 is a hardware structure diagram of an electronic device according to an exemplary embodiment, the electronic device includes: a communication interface 601, a processor 602, a memory 603 and a bus 604; wherein the communication interface 601, the processor 602 and the memory 603 communicate with each other through the bus 604. The processor 602 can execute the delivery range adjustment method described above by reading and executing the machine executable instructions corresponding to the control logic of the delivery range adjustment method in the memory 603. The specific content of the method is referred to the above embodiment, which will not be repeated here.

[0157] The memory 603 mentioned in this application can be any electronic, magnetic, optical or other physical storage system, and can contain storage information, such as executable instructions, data, etc. Specifically, the memory 603 can be RAM (Random Access Memory), flash memory, storage drive (such as hard disk drive), any type of storage disk (such as optical disk, DVD, etc.), or similar storage medium, or a combination thereof. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 601 (which can be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. can be used.

[0158] The bus 604 may be an ISA bus, a PCI bus or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The memory 603 is used to store programs, and the processor 602 executes the programs after receiving execution instructions.

[0159] Processor 602 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in processor 602 or an instruction in software form. The above-mentioned processor 602 can be a general-purpose processor, including a network processor (Network Processor, referred to as NP), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a readily available programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The disclosed methods, steps and logic block diagrams in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present application can be directly embodied as a hardware decoding processor to execute, or the hardware and software modules in the decoding processor are combined to execute.

[0160] The electronic device provided in the embodiment of the present application and the delivery range adjustment method provided in the embodiment of the present application are based on the same inventive concept and have the same beneficial effects as the methods adopted, operated or implemented therein.

[0161] The present application also provides a computer-readable storage medium corresponding to the delivery range adjustment method provided in the above embodiment. Figure 5 As shown, the computer-readable storage medium shown is a CD 30 on which a computer program (ie, a program product) is stored. When the computer program is executed by a processor, the delivery range adjustment method provided by any of the aforementioned embodiments will be executed.

[0162] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which are not listed here one by one.

[0163] The computer-readable storage medium provided in the above-mentioned embodiments of the present application and the delivery range adjustment method provided in the embodiments of the present application are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.

[0164] An embodiment of the present application also provides a computer program product corresponding to the delivery range adjustment method provided in the aforementioned embodiment. The computer program product includes a computer program, and the computer program is executed by a processor to implement the delivery range adjustment method provided in the aforementioned embodiment.

[0165] The computer program product provided by the above-mentioned embodiments of the present application and the delivery range adjustment method provided by the embodiments of the present application are based on the same inventive concept and have the same beneficial effects as the method adopted, run or implemented by the application program stored therein.

[0166] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0167] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0168] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for adjusting a distribution range, characterized in that: The method comprises: Determine a potential interest area outside the current delivery range of the target merchant; the potential interest area is a geographical area where the user has the potential to place an order with the target merchant; Generating a new delivery range for the target merchant according to the potential interest faces and the interest faces included in the current delivery range; Whether to apply the new delivery range to the target merchant is determined based on the degree of change in the performance of the new delivery range relative to the current delivery range and the business district to which the target merchant belongs.

2. The method according to claim 1, characterized in that The determining of potential interests outside the current delivery range of the target merchant includes: Obtain target merchants that meet the scope adjustment conditions; Determine candidate interest surfaces that are outside the current delivery range of the target merchant and within a preset distance; Determining a delivery time from the target merchant to the candidate interest surface; A potential interest surface is selected from the candidate interest surfaces according to the delivery time and the historical order records of users on the candidate interest surfaces.

3. The method according to claim 2, characterized in that The selecting potential interest facets from the candidate interest facets according to the delivery time of the candidate interest facets and the historical order records of the users on the candidate interest facets comprises: Determine the order potential of the candidate interest facet based on the user's historical order records on the candidate interest facet; the order potential reflects the probability of the user placing an order for the target merchant; Candidate interest groups whose order potential exceeds a preset potential value and whose delivery time does not exceed a preset time are selected as potential interest groups.

4. The method according to claim 2, characterized in that: The obtaining of target merchants meeting the scope adjustment conditions includes: Obtain merchants that adopt the target delivery type from the merchant database; From the acquired merchants, merchants with user order records within a preset time range are selected as target merchants.

5. The method according to any one of claims 1 to 4, characterized in that: The generating a new delivery range for the target merchant according to the potential interest face and the interest face included in the current delivery range includes: Determining the attribute index of the potential interest surface and the attribute index of the interest surface included in the current delivery range; Obtaining a combination of interest surfaces that meets target constraint conditions according to the attribute indicators of the potential interest surfaces and the attribute indicators of the interest surfaces included in the current delivery range; The interest facet combination is used to generate a new delivery range for the target merchant.

6. The method according to claim 5, characterized in that The attribute indicators include future order volume and at least one of the following: delivery time and delivery distance; the attribute indicators of the potential interest surface and the attribute indicators of the interest surface included in the current delivery range are used to obtain a combination of interest surfaces that meets the target constraint conditions, including: Merging the potential interests with the interests included in the current delivery range to obtain a set of interests that the target merchant can cover; According to the attribute index of each interest facet in the interest facet set, the interest facet set is optimized through operations combinatorial optimization to obtain an interest facet combination that meets the target constraint condition; the target constraint condition is that the order quantity is maximized, and the delivery time and / or delivery distance does not exceed a threshold value.

7. The method according to any one of claims 1 to 4, characterized in that: The determining whether to apply the new delivery range to the target merchant according to the degree of change in the new delivery range relative to the current delivery range and the business district to which the target merchant belongs includes: Determining the degree of change in fulfillment of the new delivery range relative to the current delivery range; If the proportion of merchants eligible for range adjustment included in the business district to which the target merchant belongs exceeds a preset proportion and the degree of change in performance does not exceed a preset value, applying the new delivery range to the target merchant; When the proportion of merchants eligible for range adjustment included in the business circle to which the target merchant belongs does not exceed a preset proportion, the new delivery range is applied to the target merchant.

8. The method according to claim 7, characterized in that Determining the degree of change in the performance of the new delivery range relative to the current delivery range includes: Determining a first fulfillment risk value of the new delivery range according to the attribute indicators of the interest surface included in the new delivery range; the first fulfillment risk value represents the logistics fulfillment of the target merchant using the new delivery range; Determining a second fulfillment risk value of the current delivery range according to the attribute index of the interest surface included in the current delivery range; the second fulfillment risk value represents the logistics fulfillment situation of the target merchant using the current delivery range; The difference between the first performance risk value and the second performance risk value is used as the performance change degree.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: The processor executes the program to implement the method according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method according to any one of claims 1 to 8.

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