Order concentration degree determination method and device, electronic equipment and storage medium

Abstract

The invention relates to an order concentration degree determination method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the aggregation and grouping of a plurality of order positions, and obtaining an aggregation result, the aggregation result comprises at least one order aggregation cluster and / or at least one unaggregated order position, and the order aggregation cluster comprises at least two order positions; for each order cluster, constructing a fan-shaped area which takes the merchant position as a circle center and covers the order cluster according to the relative position between each order position and the merchant position in the order cluster; for at least one non-aggregated order position, at least one fan-shaped area with the merchant position as the circle center is constructed according to the relative position between each non-aggregated order position and the merchant position, and the fan-shaped area at least covers one non-aggregated order position; and according to the area of each constructed fan-shaped region and the order position number, determining the concentration ratio of the plurality of orders to which the plurality of order positions belong.

Description

Technical Field

[0001] This disclosure relates to the field of logistics and distribution technology, and in particular to a method and apparatus for determining order concentration, electronic equipment and storage medium. Background Technology

[0002] In recent years, delivery services such as food delivery and express delivery have brought great convenience to people's lives. Delivery service systems need to evaluate the distribution of orders within a merchant's delivery area based on the merchant's order concentration, and then use this evaluation to perform tasks such as delivery personnel estimation, order delivery time estimation, and merchant on-time performance assessment. However, in related technologies, the determination of a merchant's order concentration in delivery service systems is rather coarse, resulting in an inability to objectively and accurately evaluate the merchant's order distribution. Summary of the Invention

[0003] This disclosure provides a method, apparatus, electronic device, and storage medium for determining order concentration, in order to address the deficiencies in related technologies.

[0004] According to a first aspect of the present disclosure, a method for determining order concentration is provided, the method comprising:

[0005] Multiple order locations are clustered and grouped to obtain clustering results, wherein the clustering results include at least one order cluster and / or at least one unclustered order location, and the order cluster includes at least two order locations;

[0006] For each order cluster, a sector-shaped region centered on the merchant's location and covering the order cluster is constructed based on the relative position between each order location and the merchant's location within the order cluster.

[0007] For the at least one non-aggregated order location, at least one sector area centered on the merchant location is constructed based on the relative position between each non-aggregated order location and the merchant location, wherein the sector area covers at least one non-aggregated order location;

[0008] Based on the area of ​​each constructed sector and the number of order locations, the concentration of the multiple orders to which the multiple order locations belong is determined.

[0009] In one embodiment of this disclosure, the fan-shaped area centered on the merchant's location and covering the order cluster includes:

[0010] The smallest sector-shaped area centered on the merchant's location and covering all order locations within the order cluster.

[0011] In one embodiment of this disclosure, constructing a fan-shaped region centered on the merchant location and covering the order cluster based on the relative positions of each order location and the merchant location within the order cluster includes:

[0012] Determine the delivery distance and delivery angle for each order location within the order cluster, wherein the delivery distance is the distance between the order location and the merchant location, and the delivery angle is the angle between the order location and the merchant location;

[0013] The fan-shaped region is constructed by taking the delivery angle of the order position with the smallest delivery angle as the angle of one boundary of the fan, the delivery angle of the order position with the largest delivery angle as the angle of the other boundary of the fan, and the delivery distance of the order position with the largest delivery distance as the radius of the fan.

[0014] In one embodiment of this disclosure, constructing at least one sector centered on the merchant location for each of the at least one unaggregated order locations based on the relative position between each unaggregated order location and the merchant location includes:

[0015] Determine the delivery distance and delivery angle for each of the at least one non-aggregated order locations, wherein the delivery distance is the distance between the order location and the merchant location, and the delivery angle is the angle between the order location and the merchant location;

[0016] Each un-marked covered un-aggregated order location among the at least one un-aggregated order locations is sequentially taken as the center location, and after each center location is determined, the following steps are performed:

[0017] If there are non-aggregated order locations whose delivery angle difference from the central location is less than a preset threshold and which are not marked as covered, then the non-aggregated order locations whose delivery angle difference from the central location is less than the preset threshold are marked as covered, and a fan-shaped area centered on the merchant location is determined that covers the central location and the non-aggregated order locations whose delivery angle difference from the central location is less than the preset threshold.

[0018] If there is no non-aggregated order location whose delivery angle difference from the center location is less than a preset threshold and is not marked as covered, then a sector area is constructed using the difference between the delivery angle of the center location and the preset threshold as the angle of one boundary of the sector, the sum of the delivery angle of the center location and the preset threshold as the angle of the other boundary of the sector, and the delivery distance of the center location as the radius of the sector.

[0019] In one embodiment of this disclosure, determining a fan-shaped area centered on the merchant's location and covering the location of non-aggregated orders where the difference between the center location and the delivery angle from the center location is less than a preset threshold includes:

[0020] In the non-aggregated order locations where the difference between the center location and the delivery angle from the center location is less than a preset threshold, the delivery angle of the order location with the smallest delivery angle is used as the angle of one boundary of the sector, the delivery angle of the order location with the largest delivery angle is used as the angle of the other boundary of the sector, and the delivery distance of the order location with the largest delivery distance is used as the radius of the sector to construct a sector region.

[0021] In one embodiment of this disclosure, determining the concentration of multiple orders to which the multiple order locations belong, based on the area of ​​each constructed sector region and the number of order locations, includes:

[0022] The total number of orders is determined by summing the number of order locations in all constructed sector regions, the total area of ​​the sector is determined by summing the areas of all constructed sector regions, and the order distribution density is determined by the quotient of the total number of orders and the total area of ​​the sector.

[0023] The average order density is determined by the ratio of the number of order locations to the area of ​​the merchant's delivery area.

[0024] The quotient of the order distribution density and the order average density is determined as the concentration of the multiple orders to which the multiple order locations belong.

[0025] In one embodiment of this disclosure, the multiple orders to which the multiple order locations belong are all orders placed by the merchant within a preset time period.

[0026] According to a second aspect of the present disclosure, an order concentration determination apparatus is provided, the apparatus comprising:

[0027] The aggregation module is used to aggregate and group multiple order locations to obtain aggregation results, wherein the aggregation results include at least one order aggregation cluster and / or at least one unaggregated order location, and the order aggregation cluster includes at least two order locations;

[0028] The first construction module is used to construct, for each order cluster, a fan-shaped region centered on the merchant's position and covering the order cluster, based on the relative position between each order position and the merchant's position within the order cluster;

[0029] The second construction module is used to construct at least one sector-shaped region centered on the merchant location for each unaggregated order location based on the relative position between each unaggregated order location and the merchant location, wherein the sector-shaped region covers at least one unaggregated order location;

[0030] The determination module is used to determine the concentration of multiple orders to which the multiple order locations belong, based on the area of ​​each constructed sector region and the number of order locations.

[0031] In one embodiment of this disclosure, the fan-shaped area centered on the merchant's location and covering the order cluster includes:

[0032] The smallest sector-shaped area centered on the merchant's location and covering all order locations within the order cluster.

[0033] In one embodiment of this disclosure, the first building module is configured to:

[0034] Determine the delivery distance and delivery angle for each order location within the order cluster, wherein the delivery distance is the distance between the order location and the merchant location, and the delivery angle is the angle between the order location and the merchant location;

[0035] The fan-shaped region is constructed by taking the delivery angle of the order position with the smallest delivery angle as the angle of one boundary of the fan, the delivery angle of the order position with the largest delivery angle as the angle of the other boundary of the fan, and the delivery distance of the order position with the largest delivery distance as the radius of the fan.

[0036] In one embodiment of this disclosure, the second building module is used for:

[0037] Determine the delivery distance and delivery angle for each of the at least one non-aggregated order locations, wherein the delivery distance is the distance between the order location and the merchant location, and the delivery angle is the angle between the order location and the merchant location;

[0038] Each un-marked covered un-aggregated order location among the at least one un-aggregated order locations is sequentially taken as the center location, and after each center location is determined, the following steps are performed:

[0039] If there are non-aggregated order locations whose delivery angle difference from the central location is less than a preset threshold and which are not marked as covered, then the non-aggregated order locations whose delivery angle difference from the central location is less than the preset threshold are marked as covered, and a fan-shaped area centered on the merchant location is determined that covers the central location and the non-aggregated order locations whose delivery angle difference from the central location is less than the preset threshold.

[0040] If there is no non-aggregated order location whose delivery angle difference from the center location is less than a preset threshold and is not marked as covered, then a sector area is constructed using the difference between the delivery angle of the center location and the preset threshold as the angle of one boundary of the sector, the sum of the delivery angle of the center location and the preset threshold as the angle of the other boundary of the sector, and the delivery distance of the center location as the radius of the sector.

[0041] In one embodiment of this disclosure, when the second construction module determines a fan-shaped area centered on the merchant's location and covering the location of non-aggregated orders whose difference between the center location and the delivery angle from the center location is less than a preset threshold, it is used to:

[0042] In the non-aggregated order locations where the difference between the center location and the delivery angle from the center location is less than a preset threshold, the delivery angle of the order location with the smallest delivery angle is used as the angle of one boundary of the sector, the delivery angle of the order location with the largest delivery angle is used as the angle of the other boundary of the sector, and the delivery distance of the order location with the largest delivery distance is used as the radius of the sector to construct a sector region.

[0043] In one embodiment of this disclosure, the determining module is used for:

[0044] The total number of orders is determined by summing the number of order locations in all constructed sector regions, the total area of ​​the sector is determined by summing the areas of all constructed sector regions, and the order distribution density is determined by the quotient of the total number of orders and the total area of ​​the sector.

[0045] The average order density is determined by the ratio of the number of order locations to the area of ​​the merchant's delivery area.

[0046] The quotient of the order distribution density and the order average density is determined as the concentration of the multiple orders to which the multiple order locations belong.

[0047] In one embodiment of this disclosure, the multiple orders to which the multiple order locations belong are all orders placed by the merchant within a preset time period.

[0048] According to a third aspect of the present disclosure, an electronic device is provided, the device including a memory and a processor, the memory being configured to store computer instructions executable on the processor, and the processor being configured to implement the method described in the first aspect when executing the computer instructions.

[0049] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect.

[0050] As described in the above embodiments, multiple order locations can be clustered and grouped to obtain clustering results. For each order cluster in the clustering results, a sector-shaped region centered on the merchant location and covering the order cluster is constructed based on the relative position between each order location and the merchant location within the cluster. For at least one non-clustered order location in the clustering results, at least one sector-shaped region centered on the merchant location is constructed based on the relative position between each non-clustered order location and the merchant location. Finally, the concentration of multiple orders belonging to the multiple order locations can be determined based on the area of ​​each constructed sector-shaped region and the number of order locations. This method constructs sector-shaped regions for each order cluster and for at least one non-clustered order location that does not enter an order cluster. The order concentration is determined based on the area of ​​the sector-shaped region and the number of order locations. This ensures that the area of ​​the order cluster and its distance from the merchant, as well as the distance between the non-clustered order location and the merchant, and the relative positions between different non-clustered order locations are all reflected in the order concentration, thus enabling the order concentration to objectively and accurately reflect the distribution of orders.

[0051] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0052] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0053] Figures 1 to 4 This is a schematic diagram of the aggregation and grouping results in related technologies;

[0054] Figure 5 This is a flowchart illustrating a method for determining order concentration according to an embodiment of this disclosure;

[0055] Figure 6 This is a schematic diagram illustrating multiple order locations according to an embodiment of this disclosure;

[0056] Figure 7 This is a schematic diagram illustrating the clustering and grouping results of multiple order locations according to an embodiment of this disclosure;

[0057] Figure 8 This is a schematic diagram illustrating a horizontal coordinate system and a polar coordinate system according to an embodiment of this disclosure;

[0058] Figure 9 This is a schematic diagram of an order cluster shown in one embodiment of the present disclosure;

[0059] Figure 10 This is a schematic diagram illustrating the construction of a sector-shaped region based on an order cluster according to an embodiment of this disclosure;

[0060] Figure 11 This is an embodiment of the present disclosure showing a method based on Figure 7 A schematic diagram of a fan-shaped region constructed from multiple order clusters;

[0061] Figure 12 This is a schematic diagram illustrating a sector region constructed based on at least one non-aggregated order location, according to an embodiment of this disclosure;

[0062] Figure 13 This is an embodiment of the present disclosure showing a method based on Figure 7 A schematic diagram of a fan-shaped area constructed from multiple non-aggregated order locations;

[0063] Figure 14 This is a schematic diagram illustrating different overlaps of adjacent sector regions according to an embodiment of this disclosure;

[0064] Figure 15 This is a schematic diagram of the order concentration determination device according to an embodiment of the present disclosure;

[0065] Figure 16 This is a schematic diagram of the structure of an electronic device shown in an embodiment of this disclosure. Detailed Implementation

[0066] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0067] The terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The singular forms “a,” “the,” and “the” as used in this disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

[0068] It should be understood that although the terms first, second, third, etc., may be used in this disclosure to describe various information, such information should not be limited to these terms. These terms are used only to distinguish information of the same type from one another. For example, without departing from the scope of this disclosure, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0069] In recent years, delivery services such as food delivery and express delivery have brought great convenience to people's lives. Delivery service systems need to evaluate the distribution of orders within a merchant's delivery area based on the merchant's order concentration, and then use this evaluation to perform tasks such as delivery personnel estimation, order delivery time estimation, and merchant on-time performance assessment. However, in related technologies, the determination of a merchant's order concentration in delivery service systems is rather coarse, resulting in an inability to objectively and accurately evaluate the merchant's order distribution.

[0070] Generally speaking, the more concentrated a merchant's orders are, the more orders a delivery person can carry per delivery, the fewer delivery personnel the merchant needs, and the higher the merchant's delivery efficiency. Conversely, the more dispersed a merchant's orders are, the fewer orders a delivery person can carry per delivery, the more delivery personnel the merchant needs, and the lower the merchant's delivery efficiency.

[0071] Generally, when assessing delivery personnel, merchants can estimate the number of orders they will need over a future period and thus estimate the number of delivery personnel required. However, for the same number of estimated orders, the number of delivery personnel required will vary depending on the location distribution; that is, the distribution of orders affects the matching relationship between the number of orders and the number of delivery personnel.

[0072] Generally speaking, when estimating order delivery time, the exact time when customers will receive the goods can be predicted based on the merchant's order distribution.

[0073] Generally speaking, when evaluating a merchant's on-time delivery rate, if two merchants have the same number of orders, the on-time delivery rate can be accurately and objectively assessed based on the distribution of their orders.

[0074] For example, in related technologies, the order locations of all a merchant's orders are aggregated. Multiple order locations that are close together can form an order cluster, while order locations that are far away from other order locations will not enter the order cluster and will exist in isolation. The proportion of order locations that enter the order cluster to all order locations in the aggregation result is used as the order concentration.

[0075] The above method for determining order concentration does not take into account the area of ​​the order cluster and its distance from the merchant, as well as the distance and distribution of orders that have not entered the order cluster from the merchant. Therefore, order concentration cannot accurately reflect the distribution of order locations.

[0076] For example, appendix Figure 1 , 2 In sections 3 and 4, the black squares represent merchant locations, and the hollow circles represent order locations. The above method for determining order concentration is attached. Figure 1 , 2 The order concentration in categories 3 and 4 is 80%, but the attached Figure 2 With appendix Figure 1 Compared to order clusters, which have smaller area, more concentrated orders, and are easier to deliver; (Attached) Figure 3 With appendix Figure 1 Compared to order clusters, which are closer to the merchant, delivery is easier; Figure 4 With appendix Figure 1 Orders not included in the order cluster are closer to the merchant and more concentrated, making delivery easier. Therefore, the method described above for determining order concentration cannot distinguish between orders with attached... Figure 1 , 2 The different order distributions in categories 3 and 4 do not accurately reflect the overall order distribution.

[0077] Based on this, at least one embodiment of this disclosure provides a method for determining order concentration. This method can be applied to delivery service systems, such as food delivery systems and express delivery systems, so that the delivery service system can accurately and objectively assess the order distribution of merchants by determining order concentration, and then perform services such as delivery personnel estimation, order delivery time estimation, and merchant on-time rate assessment.

[0078] Please refer to the appendix. Figure 5 The example illustrates the flow of the order concentration determination method, including steps S501 to S503.

[0079] In step S501, multiple order locations are clustered and grouped to obtain clustering results, wherein the clustering results include at least one order cluster and / or at least one unclustered order location, and the order cluster includes at least two order locations.

[0080] For example, this method can statistically analyze the order locations of a merchant's historical orders within a preset time period to determine the merchant's order concentration. That is, the multiple orders belonging to the multiple order locations represent all orders placed by the merchant within the preset time period.

[0081] For example, this step can use the DBSCAN clustering algorithm to group multiple order locations together to obtain the clustering results.

[0082] Please refer to the appendix. Figure 6 The order locations for all orders placed by the merchant within the preset time period are shown as hollow circles in the image, and the merchant's location is shown as a black square in the image. Please refer to the attached document. Figure 7 , attached Figure 5 After being grouped together, multiple order locations were formed into 4 clusters and 7 ungrouped order locations.

[0083] In step S502, for each order cluster, a sector-shaped region centered on the merchant location and covering the order cluster is constructed based on the relative position between each order location and the merchant location within the order cluster.

[0084] The fan-shaped area centered on the merchant's location and covering the order cluster can be the smallest possible fan-shaped area covering all order locations within the order cluster. In actual delivery, orders within the same cluster that are close to each other often mean that delivery personnel can carry multiple orders for delivery at once, making delivery easier; while delivery to more distant areas requires traversing the closer area between the delivery personnel and the merchant. This fan-shaped area covers all order locations within the order cluster and all order locations within the area that needs to be traversed to deliver these orders, closely resembling the grouping of orders in the actual delivery process (i.e., groups assigned to different delivery personnel). It is suitable for evaluating the distribution of orders, and its area and the number of order locations reflect the delivery difficulty.

[0085] For example, the relative position between the order location and the merchant location can include delivery distance and delivery angle, where the delivery distance is the distance between the order location and the merchant location, and the delivery angle is the angle between the order location and the merchant location. Preferably, a polar coordinate system can be established with the merchant location as the pole and a ray extending from the merchant location in a certain direction as the polar axis, with the polar angle of the order location in the polar coordinate system as the delivery angle and the polar radius of the order location in the polar coordinate system as the delivery distance. Please refer to the appendix. Figure 8 The diagram shows schematics of a horizontal coordinate system and a polar coordinate system. The polar coordinate system includes a pole and a polar axis. The polar axis is a ray originating from the pole. The coordinates of each point in the polar coordinate system include the polar radius ρ and the polar angle θ. The polar radius is the distance between the point and the pole, and the polar angle is the angle between the line connecting the point and the pole and the polar axis.

[0086] Based on this example, this step can construct a sector-shaped region centered on the merchant's location and covering the order cluster as follows: First, determine the delivery distance and delivery angle of each order location within the order cluster; next, construct the sector-shaped region by using the delivery angle of the order location with the smallest delivery angle as the angle of one boundary of the sector, the delivery angle of the order location with the largest delivery angle as the angle of the other boundary of the sector, and the delivery distance of the order location with the largest delivery distance as the radius of the sector.

[0087] If the i-th order cluster contains n i For each order location, the delivery angle of the j-th order location within the i-th order cluster is... j = 1, 2, ..., n i The delivery distance of the j-th order location within the i-th order cluster is j = 1, 2, ..., n i When constructing a sector-shaped region for the i-th order cluster, the angle of one boundary of the sector can be set to... The angle of the other boundary of the sector is The radius of the sector is

[0088] Please refer to the appendix. Figure 9 The order cluster represented by the dashed line has 7 order locations. Order location 1 has the smallest delivery angle, order location 2 has the largest delivery angle, and order location 3 has the largest delivery distance. Therefore, we can construct a sector with the delivery angle of order location 1 as one boundary angle, the delivery angle of order location 2 as the other boundary angle, and the delivery distance of order location 3 as the radius. Figure 10 The sector-shaped area shown.

[0089] The sector-shaped region constructed in this step can cover all order locations within the order cluster, and may also cover other order locations outside the order cluster. That is, the number of order locations m covered by the sector-shaped region constructed based on the i-th order cluster. i The number of order positions n that is greater than or equal to the number of order locations within the i-th order cluster. i For example, attached Figure 10 The fan-shaped area shown not only covers all order positions within the order cluster, but also covers the non-clustered order positions, namely order position 4.

[0090] Please refer to the appendix. Figure 11 This step is an appendix. Figure 7 The four order clusters shown construct sector regions sector1, sector2, sector3, and sector4, respectively.

[0091] In step S503, for the at least one non-aggregated order location, at least one sector area centered on the merchant location is constructed based on the relative position between each non-aggregated order location and the merchant location, wherein the sector area covers at least one non-aggregated order location.

[0092] The sector-shaped area constructed in this step can cover one or more order locations. In actual delivery, if multiple order locations are within a certain angle centered on the merchant's location, delivery personnel can deliver multiple orders simultaneously, making delivery easier. This sector-shaped area can cover the order locations suitable for simultaneous delivery of multiple orders, and its area and number of order locations can reflect the delivery difficulty, thus making it suitable for evaluating the distribution of orders.

[0093] For example, the relative position between the order location and the merchant location can include delivery distance and delivery angle, where the delivery distance is the distance between the order location and the merchant location, and the delivery angle is the angle between the order location and the merchant location. Preferably, a polar coordinate system can be established with the merchant location as the pole and a ray extending from the merchant location in a certain direction as the polar axis, with the polar angle of the order location in the polar coordinate system as the delivery angle and the polar radius of the order location in the polar coordinate system as the delivery distance. Please refer to the appendix. Figure 8 The diagram shows schematics of a horizontal coordinate system and a polar coordinate system. The polar coordinate system includes a pole and a polar axis. The polar axis is a ray originating from the pole. The coordinates of each point in the polar coordinate system include the polar radius ρ and the polar angle θ. The polar radius is the distance between the point and the pole, and the polar angle is the angle between the line connecting the point and the pole and the polar axis.

[0094] Based on this example, this step can construct at least one sector-shaped region centered on the merchant's location for the at least one unaggregated order location as follows:

[0095] First, determine the delivery distance and delivery angle for each of the at least one non-aggregated order locations.

[0096] Next, each un-marked covered un-aggregated order location among the at least one un-aggregated order locations is sequentially taken as the center location, and after each center location is determined, the following steps are performed:

[0097] If there are non-aggregated order locations whose delivery angle difference from the central location is less than a preset threshold and which are not marked as covered, then these non-aggregated order locations are marked as covered, and a fan-shaped region is determined with the merchant location as the center, covering both the central location and the non-aggregated order locations whose delivery angle difference from the central location is less than the preset threshold. For example, among the central location and the non-aggregated order locations whose delivery angle difference from the central location is less than the preset threshold, the delivery angle of the order location with the smallest delivery angle is used as the angle of one boundary of the fan, the delivery angle of the order location with the largest delivery angle is used as the angle of the other boundary of the fan, and the delivery distance of the order location with the largest delivery distance is used as the radius of the fan, thus constructing a fan-shaped region.

[0098] If there is no non-aggregated order location whose delivery angle difference from the center location is less than a preset threshold and is not marked as covered, then a sector area is constructed using the difference between the delivery angle of the center location and the preset threshold as the angle of one boundary of the sector, the sum of the delivery angle of the center location and the preset threshold as the angle of the other boundary of the sector, and the delivery distance of the center location as the radius of the sector.

[0099] If the location of the kth unaggregated order is marked as covered, its delivery angle is θ. k The preset threshold is θ thl Then it is possible to operate within the angular range [θ] k -θ thl ,θ k +θ thl Within [θ], determine if there are any unmarked, non-aggregated order locations that are not covered; if so, then assign the k-th non-aggregated order location and its angle range [θ]. k -θ thl ,θ k +θ thl The unmarked, non-clustered order locations within the specified area are treated as a single order set, and a sector is constructed for this order set in the same manner as constructing a sector for an order cluster; if no such sector exists, then the sector is constructed within the angular range [θ]. k -θ thl ,θ k +θ thl Let ] be the angular range of the sector, and let the delivery location of the kth non-aggregated order location be the radius of the sector to construct the sector region.

[0100] For example, the preset threshold can be 24°.

[0101] Please refer to the appendix. Figure 12 In the diagram, the hollow circles represent the locations of unaggregated orders, namely order positions 1, 2, and 3. When order position 1 is the center, order position 2 is not marked as a covered unaggregated order position, and the difference in delivery angle between it and the center is less than a preset threshold. Therefore, a sector region, sector 7, is constructed with the delivery angle of order position 1 as one boundary angle, the delivery angle of order position 2 as another boundary angle, and the delivery distance of order position 2 as the radius. When order position 3 is the center, there are no unaggregated order positions whose delivery angle difference from the center is less than the preset threshold and which are not marked as covered. Therefore, a sector region, sector 8, is constructed with the difference between the delivery angle of the center and the preset threshold as one boundary angle, the sum of the delivery angle of the center and the preset threshold as the other boundary angle, and the delivery distance of the center as the radius.

[0102] Please refer to the appendix. Figure 13 This step is an appendix. Figure 7 The seven order clusters shown construct sector regions sector5, sector6, sector7, and sector8, respectively.

[0103] In step S504, the concentration of the multiple orders to which the multiple order locations belong is determined based on the area of ​​each constructed sector region and the number of order locations.

[0104] The number of order locations within a sector refers to the number of order locations within that sector, i.e., the number of order locations covered by the sector.

[0105] For example, the concentration of multiple orders belonging to the multiple order locations is determined in the following manner:

[0106] First, the sum of the number of order locations in all constructed sector regions is determined as the total number of orders, the sum of the areas of all constructed sector regions is determined as the total sector area, and the quotient of the total number of orders and the total sector area is determined as the order distribution density.

[0107] For example, the angles of the two boundaries of the sector region are θ. min θ max The radius of the sector is r max Then the area s of the sector is:

[0108] For example, the area of ​​the sector region constructed based on the i-th order cluster is s. i The number of order locations is m i The area of ​​the k-th sector constructed based on the at least one non-aggregated order location is s. k The number of order locations is m k Then the order distribution density ρ distri for:

[0109]

[0110] Order distribution density ρ distri This reflects the distribution density of all orders within a merchant's delivery area. The more clusters formed by the order distribution, the smaller the cluster area, the closer the clusters are to the merchant, the closer the non-clustered orders are to the merchant, and the smaller the angle between non-clustered orders, the easier the delivery and the higher the order distribution density. Conversely, the fewer clusters formed by the order distribution, the larger the cluster area, the farther the clusters are from the merchant, the farther the non-clustered orders are from the merchant, and the larger the angle between non-clustered orders, the more difficult the delivery and the lower the order distribution density.

[0111] Next, the average order density is determined by the ratio of the number of order locations to the area of ​​the merchant's delivery area.

[0112] The merchant's delivery area refers to the area of ​​the region formed by the merchant's delivery range.

[0113] For example, if the number of order locations is N and the merchant's delivery area is S, then the average order density ρ mean for:

[0114]

[0115] Average order density ρ mean This reflects the average order density across all orders within a merchant's delivery area, regardless of order distribution, whether the distribution is concentrated or dispersed. mean All are constant values.

[0116] Finally, the quotient of the order distribution density and the order average density is determined as the concentration of the multiple orders to which the multiple order locations belong.

[0117] For example, the concentration c of the multiple orders to which the multiple order locations belong. distri for:

[0118]

[0119] Concentration c distri The larger the value, the more concentrated the order distribution; concentration c distri The smaller the size, the more dispersed the orders.

[0120] It should be noted that the multiple sector regions constructed by this method may overlap. When overlap occurs, some order positions will be counted repeatedly, meaning that some order positions may be included in the order position count of multiple sector regions. Figure 12 and Figure 13 In the calculation, there are two duplicate order positions between sector 1 and sector 2, and one duplicate order position between sector 3 and sector 6. However, when calculating the average order density, the number of orders without duplicates, N, is used, i.e., ∑m i +∑m k ≥N.

[0121] In this case, there's no need to deduplicate the repeatedly calculated locations. This is because order locations covered by multiple sector areas tend to have higher delivery efficiency and a more concentrated order location distribution. The more overlapping order locations within the sector areas, the easier the delivery. Therefore, repeated calculations can improve the order distribution density ρ of merchants whose order locations are covered by multiple sector areas. distri Larger.

[0122] With attachment Figure 14Taking the distribution of two sector regions, sector1 and sector2, under three scenarios (a, b, and c) as an example, in scenario a, the two sector regions do not overlap; in scenario b, the two sector regions have a small overlap, with two overlapping order positions; and in scenario c, the two sector regions have a large overlap, with four overlapping order positions. Clearly, scenario c has the most concentrated order positions, while scenario a has the most dispersed order positions.

[0123] The parameters for the two sector regions, sector1 and sector2, under case a are shown in Table 1 below:

[0124] Table 1: Statistics of the sector-shaped region under case a

[0125]

[0126] In case b, the parameters of the two sector regions, sector1 and sector2, are shown in Table 2 below:

[0127] Table 2: Statistics of the sector-shaped region under case b

[0128]

[0129]

[0130] The parameters of the two sector regions, sector1 and sector2, under case c are shown in Table 3 below:

[0131] Table 3: Statistics of the sector-shaped region under case c

[0132]

[0133] It is evident that the order distribution density in case a is lower than that in case b, and the order distribution density in case b is lower than that in case c. This method, without deduplicating duplicate order locations, calculates an order distribution density that does not accurately reflect the actual order distribution. Conversely, if duplicate order locations are deduplicated before calculating the order distribution density, the differences in order location distribution across cases a, b, and c cannot be accurately represented.

[0134] An exemplary embodiment of this method is as follows:

[0135] Appendix Figure 6 The merchant's location and the order locations of 25 orders within a preset time period, as shown, are aggregated and grouped to obtain the attached data. Figure 7 The diagram shows four order clusters and seven unclustered order locations. An appendix is ​​constructed based on the four order clusters. Figure 11 The four sector regions shown (sectors 1, 2, 3, and 4) are constructed based on seven non-aggregated order locations. Figure 13 The four sector regions, sectors 5, 6, 7, and 8, are shown below. The parameters for each of these eight sector regions are listed in Table 4.

[0136] Table 1: Statistics of the sector-shaped region under case a

[0137]

[0138]

[0139] That is, the order distribution density ρ is obtained. distri It is 4.23km -2 .

[0140] The merchant's delivery area is a rectangle of 4.6km * 4.2km, with an area S of 19.32. What is the average order density ρ? mean The distance is N / S = 25 / 19.32 = 1.29 km. -2 .

[0141] The concentration c of the merchant's 25 orders distri For ρ distri / ρ mean =4.23 / 1.29 = 2.27.

[0142] As described in the above embodiments, multiple order locations can be clustered and grouped to obtain clustering results. For each order cluster in the clustering results, a sector-shaped region centered on the merchant location and covering the order cluster is constructed based on the relative position between each order location and the merchant location within the cluster. For at least one non-clustered order location in the clustering results, at least one sector-shaped region centered on the merchant location is constructed based on the relative position between each non-clustered order location and the merchant location. Finally, the concentration of multiple orders belonging to the multiple order locations can be determined based on the area of ​​each constructed sector-shaped region and the number of order locations. This method constructs sector-shaped regions for each order cluster and for at least one non-clustered order location that does not enter an order cluster. The order concentration is determined based on the area of ​​the sector-shaped region and the number of order locations. This ensures that the area of ​​the order cluster and its distance from the merchant, as well as the distance between the non-clustered order location and the merchant, and the relative positions between different non-clustered order locations are all reflected in the order concentration, thus enabling the order concentration to objectively and accurately reflect the distribution of orders.

[0143] This method considers cluster area when determining order concentration; that is, the smaller the cluster area, the greater the order concentration, and the larger the cluster area, the smaller the order concentration.

[0144] This method considers the distance between clusters and merchants when determining order concentration; the smaller the distance, the greater the order concentration; the greater the distance, the smaller the order concentration.

[0145] This method considers the distribution of non-aggregated order locations when determining order concentration. The smaller the distance from the merchant and the smaller the angle between non-aggregated order locations, the greater the order concentration; the greater the distance from the merchant and the larger the angle between non-aggregated order locations, the smaller the order concentration.

[0146] According to a second aspect of the embodiments of this disclosure, an order concentration determination apparatus is provided. Please refer to the appendix. Figure 15 The device includes:

[0147] The aggregation module 1501 is used to aggregate and group multiple order locations to obtain aggregation results, wherein the aggregation results include at least one order aggregation cluster and / or at least one unaggregated order location, and the order aggregation cluster includes at least two order locations;

[0148] The first construction module 1502 is used to construct, for each order cluster, a fan-shaped region centered on the merchant position and covering the order cluster, based on the relative position between each order position and the merchant position within the order cluster.

[0149] The second construction module 1503 is used to construct at least one sector area centered on the merchant location for the at least one non-aggregated order location based on the relative position between each non-aggregated order location and the merchant location, wherein the sector area covers at least one non-aggregated order location;

[0150] The determination module 1504 is used to determine the concentration of multiple orders to which the multiple order locations belong, based on the area of ​​each constructed sector region and the number of order locations.

[0151] In one embodiment of this disclosure, the fan-shaped area centered on the merchant's location and covering the order cluster includes:

[0152] The smallest sector-shaped area centered on the merchant's location and covering all order locations within the order cluster.

[0153] In one embodiment of this disclosure, the first building module is configured to:

[0154] Determine the delivery distance and delivery angle for each order location within the order cluster, wherein the delivery distance is the distance between the order location and the merchant location, and the delivery angle is the angle between the order location and the merchant location;

[0155] The fan-shaped region is constructed by taking the delivery angle of the order position with the smallest delivery angle as the angle of one boundary of the fan, the delivery angle of the order position with the largest delivery angle as the angle of the other boundary of the fan, and the delivery distance of the order position with the largest delivery distance as the radius of the fan.

[0156] In one embodiment of this disclosure, the second building module is used for:

[0157] Determine the delivery distance and delivery angle for each of the at least one non-aggregated order locations, wherein the delivery distance is the distance between the order location and the merchant location, and the delivery angle is the angle between the order location and the merchant location;

[0158] Each un-marked covered un-aggregated order location among the at least one un-aggregated order locations is sequentially taken as the center location, and after each center location is determined, the following steps are performed:

[0159] If there are non-aggregated order locations whose delivery angle difference from the central location is less than a preset threshold and which are not marked as covered, then the non-aggregated order locations whose delivery angle difference from the central location is less than the preset threshold are marked as covered, and a fan-shaped area centered on the merchant location is determined that covers the central location and the non-aggregated order locations whose delivery angle difference from the central location is less than the preset threshold.

[0160] If there is no non-aggregated order location whose delivery angle difference from the center location is less than a preset threshold and is not marked as covered, then a sector area is constructed using the difference between the delivery angle of the center location and the preset threshold as the angle of one boundary of the sector, the sum of the delivery angle of the center location and the preset threshold as the angle of the other boundary of the sector, and the delivery distance of the center location as the radius of the sector.

[0161] In one embodiment of this disclosure, when the second construction module determines a fan-shaped area centered on the merchant's location and covering the location of non-aggregated orders whose difference between the center location and the delivery angle from the center location is less than a preset threshold, it is used to:

[0162] In the non-aggregated order locations where the difference between the center location and the delivery angle from the center location is less than a preset threshold, the delivery angle of the order location with the smallest delivery angle is used as the angle of one boundary of the sector, the delivery angle of the order location with the largest delivery angle is used as the angle of the other boundary of the sector, and the delivery distance of the order location with the largest delivery distance is used as the radius of the sector to construct a sector region.

[0163] In one embodiment of this disclosure, the determining module is used for:

[0164] The total number of orders is determined by summing the number of order locations in all constructed sector regions, the total area of ​​the sector is determined by summing the areas of all constructed sector regions, and the order distribution density is determined by the quotient of the total number of orders and the total area of ​​the sector.

[0165] The average order density is determined by the ratio of the number of order locations to the area of ​​the merchant's delivery area.

[0166] The quotient of the order distribution density and the order average density is determined as the concentration of the multiple orders to which the multiple order locations belong.

[0167] In one embodiment of this disclosure, the multiple orders to which the multiple order locations belong are all orders placed by the merchant within a preset time period.

[0168] At least one embodiment of this disclosure also provides an electronic device, please refer to the appendix. Figure 16 The diagram illustrates the structure of the device, which includes a memory and a processor. The memory stores computer instructions that can run on the processor, and the processor processes orders based on the method described in the first aspect when executing the computer instructions.

[0169] At least one embodiment of this disclosure also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect.

[0170] In this disclosure, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. The term "a plurality" means two or more unless expressly defined otherwise. Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims. It should be understood that this disclosure is not limited to the precise structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for determining order concentration, characterized in that, The method includes: Multiple order locations are clustered and grouped to obtain clustering results, wherein the clustering results include at least one order cluster and / or at least one unclustered order location, and the order cluster includes at least two order locations; For each order cluster, a sector-shaped region centered on the merchant's location and covering the order cluster is constructed based on the relative position between each order location and the merchant's location within the order cluster. For the at least one non-aggregated order location, at least one sector area centered on the merchant location is constructed based on the relative position between each non-aggregated order location and the merchant location, wherein the sector area covers at least one non-aggregated order location; Based on the area of ​​each constructed sector and the number of order locations, the concentration of the multiple orders to which the multiple order locations belong is determined.

2. The method for determining order concentration according to claim 1, characterized in that, The fan-shaped area centered on the merchant's location and covering the order cluster includes: The smallest sector-shaped area centered on the merchant's location and covering all order locations within the order cluster.

3. The method for determining order concentration according to claim 2, characterized in that, The step of constructing a fan-shaped region centered on the merchant's location and covering the order cluster based on the relative position between each order location and the merchant's location within the order cluster includes: Determine the delivery distance and delivery angle for each order location within the order cluster, wherein the delivery distance is the distance between the order location and the merchant location, and the delivery angle is the angle between the order location and the merchant location; The fan-shaped region is constructed by taking the delivery angle of the order position with the smallest delivery angle as the angle of one boundary of the fan, the delivery angle of the order position with the largest delivery angle as the angle of the other boundary of the fan, and the delivery distance of the order position with the largest delivery distance as the radius of the fan.

4. The method for determining order concentration according to claim 1, characterized in that, For each of the at least one non-aggregated order locations, at least one sector-shaped region centered on the merchant location is constructed based on the relative position between each non-aggregated order location and the merchant location, including: Determine the delivery distance and delivery angle for each of the at least one non-aggregated order locations, wherein the delivery distance is the distance between the order location and the merchant location, and the delivery angle is the angle between the order location and the merchant location; Each un-marked covered un-aggregated order location among the at least one un-aggregated order locations is sequentially taken as the center location, and after each center location is determined, the following steps are performed: If there are non-aggregated order locations whose delivery angle difference from the central location is less than a preset threshold and which are not marked as covered, then the non-aggregated order locations whose delivery angle difference from the central location is less than the preset threshold are marked as covered, and a fan-shaped area centered on the merchant location is determined that covers the central location and the non-aggregated order locations whose delivery angle difference from the central location is less than the preset threshold. If there is no non-aggregated order location whose delivery angle difference from the center location is less than a preset threshold and is not marked as covered, then a sector area is constructed using the difference between the delivery angle of the center location and the preset threshold as the angle of one boundary of the sector, the sum of the delivery angle of the center location and the preset threshold as the angle of the other boundary of the sector, and the delivery distance of the center location as the radius of the sector.

5. The method for determining order concentration according to claim 4, characterized in that, The determination of a fan-shaped area centered on the merchant's location and covering the locations of non-aggregated orders where the difference between the center location and the delivery angle from the center location is less than a preset threshold includes: In the non-aggregated order locations where the difference between the center location and the delivery angle from the center location is less than a preset threshold, the delivery angle of the order location with the smallest delivery angle is used as the angle of one boundary of the sector, the delivery angle of the order location with the largest delivery angle is used as the angle of the other boundary of the sector, and the delivery distance of the order location with the largest delivery distance is used as the radius of the sector to construct a sector region.

6. The method for determining order concentration according to claim 1, characterized in that, The step of determining the concentration of multiple orders belonging to the multiple order locations based on the area of ​​each constructed sector region and the number of order locations includes: The total number of orders is determined by summing the number of order locations in all constructed sector regions, the total area of ​​the sector is determined by summing the areas of all constructed sector regions, and the order distribution density is determined by the quotient of the total number of orders and the total area of ​​the sector. The average order density is determined by the ratio of the number of order locations to the area of ​​the merchant's delivery area. The quotient of the order distribution density and the order average density is determined as the concentration of the multiple orders to which the multiple order locations belong.

7. The method for determining order concentration according to claim 1, characterized in that, The multiple orders to which the multiple order locations belong are all the orders placed by the merchant within a preset time period.

8. An order concentration determination device, characterized in that, The device includes: The aggregation module is used to aggregate and group multiple order locations to obtain aggregation results, wherein the aggregation results include at least one order aggregation cluster and / or at least one unaggregated order location, and the order aggregation cluster includes at least two order locations; The first construction module is used to construct, for each order cluster, a fan-shaped region centered on the merchant's position and covering the order cluster, based on the relative position between each order position and the merchant's position within the order cluster; The second construction module is used to construct at least one sector-shaped region centered on the merchant location for each unaggregated order location based on the relative position between each unaggregated order location and the merchant location, wherein the sector-shaped region covers at least one unaggregated order location; The determination module is used to determine the concentration of multiple orders to which the multiple order locations belong, based on the area of ​​each constructed sector region and the number of order locations.

9. An electronic device, characterized in that, The device includes a memory and a processor, the memory being used to store computer instructions that can be executed on the processor, and the processor being used to implement the method of any one of claims 1 to 7 when executing the computer instructions.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method described in any one of claims 1 to 7.

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