A multi-delivery point grouping method, device, medium and computer equipment

Abstract

The present disclosure relates to a multi-delivery point grouping method, device, medium and computer equipment. The present disclosure obtains the center position of each group by grouping a plurality of delivery points; determines the corresponding goods quantity balance range of each group by using the center position of each group, and the goods quantity balance range is different from the coverage range of the group; selects a target delivery point from a target group to be balanced in goods quantity, so as to divide the target delivery point into a non-target group, and the target delivery point is in the goods quantity balance range of the non-target group, so as to realize the balance of the delivery goods quantity; and then the target delivery point is divided into the non-target group closest to the target delivery point, so that the delivery points of the non-target group are relatively concentrated, and the time wasted in the goods transportation is reduced.

Description

Technical Field

[0001] This disclosure relates to the field of logistics scheduling technology, specifically to a grouping device, medium, and computer equipment for multiple distribution points. Background Technology

[0002] With the development of internet technology, online shopping has gradually become an important part of people's daily lives. Typically, freight logistics will transport the user's online purchases to a delivery point near the user, where the user or delivery personnel will then pick up the goods.

[0003] Considering that freight drivers deliver goods to multiple delivery points during a single trip, in order to avoid freight drivers wasting too much time during the journey, it is necessary to have the same freight driver deliver goods to multiple delivery points that are relatively close together. Furthermore, the delivery volume of different freight drivers needs to be relatively balanced to avoid some drivers delivering too much or too little goods, which would lead to an unreasonable allocation of driver resources.

[0004] Currently, when planning freight logistics scheduling, density-based spatial clustering is commonly used to group multiple delivery points in different locations. While this can meet the clustering requirements, uneven density of delivery points can lead to significant differences in the volume of goods delivered to each cluster, resulting in unreasonable allocation of driver resources. Summary of the Invention

[0005] At least one embodiment of this disclosure provides a grouping method, apparatus, medium, and computer equipment for multiple distribution points.

[0006] In a first aspect, embodiments of this disclosure propose a grouping method for multiple delivery points, the method comprising:

[0007] Obtain information on multiple delivery points in different locations and the amount of goods to be delivered at each delivery point;

[0008] Multiple delivery points are clustered into groups to obtain the center location of each group;

[0009] For any group, the cargo volume balance range corresponding to the group is determined based on the center location of the group and the farthest distance between each delivery point in the group and the center location. The farthest distance between the center location and the boundary of the cargo volume balance range is less than or greater than the farthest distance between each delivery point in the group and the center location.

[0010] For any target group to balance the quantity of goods, determine at least one target delivery point in the target group to balance the quantity of goods, the sum of the quantities of goods to be delivered at at least one target delivery point is within a preset quantity range, the quantity range is obtained based on the quantity of goods to be balanced in the target group, and each target delivery point is within the quantity balance range of at least one non-target group.

[0011] For any target delivery point, the target delivery point is assigned to the non-target group that is closest to the central location, and the target delivery point is within the balance range of the cargo volume of the assigned non-target group.

[0012] Secondly, embodiments of this disclosure also propose a grouping device for multiple delivery points, the device comprising:

[0013] The acquisition unit is used to acquire multiple delivery points at different locations and the amount of goods to be delivered at each delivery point;

[0014] Grouping units are used to cluster multiple delivery points and obtain the center location of each group;

[0015] The first determining unit is used to determine the cargo quantity balance range corresponding to any group based on the center location of the group and the farthest distance between each delivery point in the group and the center location, wherein the farthest distance between the center location and the boundary of the cargo quantity balance range is less than or greater than the farthest distance between each delivery point in the group and the center location.

[0016] The second determining unit is used to determine at least one target delivery point in any target group for balancing the quantity of goods to be delivered, wherein the sum of the quantities of goods to be delivered at the at least one target delivery point is within a preset quantity range, the quantity range is obtained based on the quantity of goods to be balanced in the target group, and each target delivery point is within the quantity balance range of at least one non-target group.

[0017] The partitioning unit is used to assign any target delivery point to a non-target group that is closest to the central location of the target delivery point, and the target delivery point is within the balance range of the cargo volume of the assigned non-target group.

[0018] Thirdly, embodiments of this disclosure also provide a computer device, comprising at least one computing device and at least one storage device for storing instructions; the instructions, when executed by the at least one computing device, cause the at least one computing device to perform the steps of the grouping method for multiple distribution points as described in any embodiment of the first aspect.

[0019] Fourthly, embodiments of this disclosure also provide a computer-readable storage medium storing a program or instructions that cause a computer to perform the steps of the grouping method for multiple distribution points as described in any embodiment of the first aspect.

[0020] Fifthly, embodiments of this disclosure also provide a computer program product, wherein the computer program product includes a computer program stored in a computer-readable storage medium, and at least one processor of the computer reads from the storage medium and executes the computer program, causing the computer to perform the steps of the grouping method for multiple distribution points as described in any embodiment of the first aspect.

[0021] As can be seen, in at least one embodiment of this disclosure, multiple delivery points are clustered into groups to obtain the center position of each group; the center position of each group is used to determine the cargo volume balancing range corresponding to each group, which is different from the coverage range of the group; then, at least one target delivery point is selected from the target group to be balanced, and the sum of the cargo volume to be delivered at the at least one target delivery point is within a preset cargo volume range, which is based on the cargo volume to be balanced in the target group, so that the target delivery point is assigned to a non-target group, and each target delivery point is within the cargo volume balancing range of at least one non-target group, thus achieving cargo volume balancing. In addition, for any target delivery point, considering that the target delivery point may be within the cargo volume balancing range of at least one non-target group, the distance between the target delivery point and the center position of the different non-target groups in which it is located is different. The target delivery point is assigned to the non-target group whose center position is closest to the target delivery point, so that the target delivery point is relatively clustered with other delivery points in the non-target group, avoiding the truck driver wasting more time during transportation; and after the cargo volume balancing of all groups is completed, the cargo volume transported by each truck driver is also relatively balanced, solving the problem of unreasonable driver resource allocation. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings.

[0023] Figure 1 A flowchart illustrating a grouping method for multiple delivery points provided in an embodiment of this disclosure;

[0024] Figure 2 This is a schematic diagram illustrating a clustering and grouping of multiple delivery points according to an embodiment of this disclosure;

[0025] Figure 3 A flowchart illustrating a method for determining a target group for balancing the quantity of goods to be transported, provided as an embodiment of this disclosure;

[0026] Figure 4A flowchart illustrating a process for determining the balance range of cargo volume corresponding to a group, as provided in an embodiment of this disclosure;

[0027] Figure 5 A schematic diagram illustrating a cargo quantity balance range corresponding to a grouping, provided in an embodiment of this disclosure;

[0028] Figure 6 This is a schematic diagram of a process for determining at least one target delivery point in a target group to balance the amount of goods to be delivered, as provided in an embodiment of the present disclosure.

[0029] Figure 7 for Figure 5 A schematic diagram showing at least one target delivery point in the target group where the amount of goods to be delivered is balanced;

[0030] Figure 8 This is a schematic diagram of a grouping device with multiple delivery points provided in an embodiment of this disclosure;

[0031] Figure 9 An exemplary block diagram of a computer device provided in an embodiment of this disclosure. Detailed Implementation

[0032] To better understand the above-described objectives, features, and advantages of this disclosure, the present disclosure will be further described in detail below with reference to the accompanying drawings and embodiments. It is to be understood that the described embodiments are only some, not all, of the embodiments of this disclosure. The specific embodiments described herein are merely for explaining this disclosure and are not intended to limit it. All other embodiments obtained by those skilled in the art based on the described embodiments of this disclosure are within the scope of protection of this disclosure.

[0033] It should be noted that in this article, relational terms such as “first” and “second” are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0034] This disclosure provides a method, apparatus, medium, or computer device for grouping multiple delivery points. The method involves clustering multiple delivery points to obtain the center location of each group; using the center location of each group to determine the cargo volume balancing range corresponding to each group, where the cargo volume balancing range differs from the coverage range of the group; then selecting at least one target delivery point from the target group to be balanced, where the sum of the cargo volumes to be delivered at at least one target delivery point is within a preset cargo volume range, which is based on the cargo volumes to be balanced in the target group. This allows the target delivery points to be assigned to non-target groups, and each target delivery point is within the cargo volume balancing range of at least one non-target group, thereby achieving cargo volume balancing. In addition, for any target delivery point, considering that the target delivery point may be within the balance range of cargo volume of at least one non-target group, the distance between the target delivery point and the center location of the different non-target groups in which it is located is different. The target delivery point is divided into the non-target group whose center location is closest to the target delivery point, so that the target delivery point is relatively clustered with other delivery points in the non-target group, avoiding truck drivers wasting more time during transportation; and after the cargo volume balance of all groups is completed, the cargo volume transported by each truck driver is also relatively balanced, solving the problem of unreasonable allocation of driver resources.

[0035] Figure 1 This is a flowchart illustrating a grouping method for multiple delivery points provided in an embodiment of the present disclosure. The execution subject of this grouping method for multiple delivery points is an electronic device, including but not limited to smartphones, PDAs, tablets, wearable devices with displays, desktop computers, laptops, all-in-one computers, smart home devices, servers, etc. The server can be an independent server or a cluster of multiple servers, and can include servers built locally and servers set up in the cloud.

[0036] like Figure 1 As shown, the grouping method for multiple delivery points may include, but is not limited to, steps 101 to 105:

[0037] In step 101, multiple delivery points at different locations and the quantity of goods to be delivered at each delivery point are obtained.

[0038] In this embodiment of the disclosure, the delivery point is the unloading node of freight logistics and the smallest sorting place of freight logistics. A delivery point covers a certain area around it. That is, goods with any location in the area as the delivery address will be delivered to the corresponding delivery point in the area, and then the user or delivery personnel will pick up the goods from the delivery point.

[0039] In this embodiment, the location of delivery points can be reported to the distribution center by the management personnel of the delivery points. The distribution center manages information such as the location of multiple delivery points and the quantity of goods to be delivered. The distribution center receives and processes user order information, sorts various types of goods delivered by suppliers, performs picking, processing, and assembly operations according to user order requirements, and dispatches truck drivers to deliver goods to the facilities and institutions of each delivery point. Distribution centers can be classified based on their delivery range, such as city distribution centers and regional distribution centers. City distribution centers are those whose delivery range is within a city, while regional distribution centers are those with stronger radiation capabilities and inventory preparation, delivering to users across provinces (states), the country, or even internationally.

[0040] In this embodiment of the disclosure, if the electronic device executing the grouping method of multiple delivery points is part of a distribution center, the electronic device obtains multiple delivery points at different locations and the quantity of goods to be delivered at each delivery point from the distribution center; if the electronic device is part of a distribution center, the electronic device can directly obtain multiple delivery points at different locations and the quantity of goods to be delivered at each delivery point from the database of the distribution center.

[0041] In some embodiments, the quantity of goods may be the weight of goods, the number of goods, or a unit of measurement related to the goods. Those skilled in the art can set the specific measurement method of the quantity of goods according to actual needs.

[0042] In step 102, multiple delivery points are clustered into groups to obtain the center location of each group.

[0043] In this embodiment of the disclosure, based on the location of multiple delivery points, a distance clustering algorithm is used to cluster the multiple delivery points into multiple groups and the center location of each group. The distance clustering algorithm is, for example, the k-means clustering algorithm. The k-means clustering algorithm is a conventional technology in the art and will not be described in detail to avoid repetition.

[0044] For example, Figure 2 This is a schematic diagram illustrating clustering and grouping of multiple delivery points according to an embodiment of this disclosure. Figure 2 In the process, after clustering multiple delivery points using the k-means clustering algorithm, four groups were obtained: circular groups (each delivery point is marked with a circle), square groups (each delivery point is marked with a square), diamond groups (each delivery point is marked with a diamond), and triangular groups (each delivery point is marked with a triangle). The center positions of each group are as follows: Figure 2 The small dashed circles shown.

[0045] In step 103, for any group, the cargo volume balance range corresponding to the group is determined based on the center location of the group and the farthest distance between each delivery point in the group and the center location. The farthest distance between the center location and the boundary of the cargo volume balance range is less than or greater than the farthest distance between each delivery point in the group and the center location.

[0046] In this embodiment of the disclosure, multiple delivery points in each group are delivered by the same freight driver. In order to avoid the problem of unreasonable allocation of driver resources caused by some drivers delivering too much or too little cargo, this embodiment determines the cargo volume balance range corresponding to each group in order to balance the cargo volume to be delivered for different groups.

[0047] In this embodiment, the logic for balancing the volume of goods to be delivered for different groups is as follows: For groups with a large volume of goods to be delivered, at least one delivery point in that group needs to be reassigned to other groups; for groups with a small volume of goods to be delivered, at least one delivery point in other groups needs to be assigned. Therefore, to achieve the above balancing logic, in this embodiment, a volume balancing range is determined for each group. This volume balancing range is either smaller or larger than the coverage area of ​​the group; that is, the furthest distance between the center and the boundary of the volume balancing range is smaller or greater than the furthest distance between each delivery point in the group and the center of the group.

[0048] In this embodiment of the disclosure, if the balance range of cargo volume is smaller than the coverage range of the group, then when the group carries the delivery points of other groups, the distance between the newly carried delivery point and the center position of the group will not exceed the distance between the farthest delivery point in the group and the center position of the group, so as to realize the relative aggregation of the delivery points of the same group and avoid the freight driver wasting more time during transportation.

[0049] In this embodiment of the disclosure, if the cargo volume balancing range is greater than the coverage range of the group, the group can accommodate more of the delivery points of other groups, thereby achieving cargo volume balancing and improving balancing efficiency.

[0050] In step 104, for any target group to be balanced, at least one target delivery point to be balanced is determined in the target group. The sum of the goods to be delivered at at least one target delivery point is within a preset goods quantity range. The goods quantity range is obtained based on the goods quantity to be balanced in the target group, and each target delivery point is within the goods quantity balance range of at least one non-target group.

[0051] In this embodiment of the disclosure, since the target group is a group with balanced cargo volume, that is, the sum of the cargo volume to be delivered of all delivery points in the target group is large, it is necessary to divide at least one delivery point in the target group into a non-target group to achieve balanced cargo volume. The non-target group is a group that does not need to be balanced, and the sum of the cargo volume to be delivered of all delivery points in the non-target group is small, which can accommodate at least one delivery point of the target group.

[0052] In this embodiment of the disclosure, at least one delivery point is selected from the target group as the target delivery point for balancing the amount of goods to be delivered. The selected at least one target delivery point satisfies the following conditions: the sum of the amount of goods to be delivered is within a preset range of the amount of goods, so as to divide at least one target delivery point in the target group into a non-target group, and each target delivery point is within the range of the amount of goods to be delivered of at least one non-target group, thereby achieving balancing of the amount of goods delivered.

[0053] In some embodiments, the upper limit of the cargo quantity range is the sum of the cargo quantity to be balanced in the target group and a preset cargo quantity increment, while the lower limit of the cargo quantity range is the cargo quantity to be balanced in the target group or no lower limit is set. The preset cargo quantity increment can be set according to actual needs, and this embodiment does not limit its specific value. Therefore, in this embodiment, the actual cargo quantity balanced in the target group (i.e., the sum of the cargo quantities to be delivered at at least one target delivery point) can exceed the cargo quantity to be balanced in the target group. In other embodiments, the upper limit of the cargo quantity range is the cargo quantity to be balanced in the target group, while the lower limit of the cargo quantity range is the cargo quantity to be balanced in the target group or no lower limit is set.

[0054] For non-target groups, since the cargo volume balancing range is smaller than the coverage area of ​​the non-target group, that is, the farthest distance between the center of the cargo volume balancing range and the boundary of the cargo volume balancing range is smaller than the farthest distance between each delivery point in the non-target group and the center position of the non-target group, it is ensured that when each group carries delivery points of other groups, the distance between the newly carried delivery point and the center position of the group will not exceed the distance between the farthest delivery point in the group and the center position of the group. This achieves relative clustering of delivery points in the same group and avoids freight drivers wasting more time during transportation.

[0055] In step 105, for any target delivery point, the target delivery point is assigned to the non-target group that is closest to the central location, and the target delivery point is within the balance range of the cargo volume of the assigned non-target group.

[0056] In this embodiment of the disclosure, for any target delivery point, considering that the target delivery point may be within the balance range of cargo volume of at least one non-target group, the distance between the target delivery point and the center position of the different non-target groups in which it is located is different. The target delivery point is divided into the non-target group whose center position is closest to the target delivery point, so that the target delivery point is relatively clustered with other delivery points in the non-target group, avoiding the truck driver wasting more time during transportation.

[0057] For example, for any target delivery point, firstly, based on the cargo volume balance range of at least one non-target group to which the target delivery point is located, the center position of each of the at least one non-target group is obtained; then, the distance between the target delivery point and the center position of each of the at least one non-target group is calculated to obtain the non-target group whose center position is closest to the target delivery point; then, the target delivery point is assigned to the non-target group whose center position is closest to the target delivery point, and the target delivery point is within the cargo volume balance range of the assigned non-target group.

[0058] It should be noted that after the target delivery point is assigned to the non-target group, the target delivery point is removed from the target group.

[0059] As can be seen, this embodiment of the disclosure clusters multiple delivery points to obtain the center location of each group; uses the center location of each group to determine the cargo volume balancing range corresponding to each group, the cargo volume balancing range is different from the coverage range of the group; then selects at least one target delivery point from the target group to be balanced, the sum of the cargo volume to be delivered at at least one target delivery point is within a preset cargo volume range, the cargo volume range is obtained based on the cargo volume to be balanced of the target group, so as to classify the target delivery point into non-target groups, and each target delivery point is within the cargo volume balancing range of at least one non-target group, thus achieving cargo volume balancing. In addition, for any target delivery point, considering that the target delivery point may be within the cargo volume balancing range of at least one non-target group, the distance between the target delivery point and the center location of different non-target groups is different. The target delivery point is classified into the non-target group whose center location is closest to the target delivery point, so that the target delivery point is relatively clustered with other delivery points in the non-target group, avoiding the truck drivers wasting more time during transportation; and after the cargo volume balancing of all groups is completed, the cargo volume transported by each truck driver is also relatively balanced, solving the problem of unreasonable driver resource allocation.

[0060] Based on the above embodiments, Figure 1 Before "for any target group for balancing the quantity of goods to be balanced, determine at least one target delivery point in the target group for balancing the quantity of goods to be balanced" in step 104 shown, the grouping method for multiple delivery points also includes Figure 3 The following steps 301 and 302 are shown for determining the target group for balancing the quantity of goods to be transported:

[0061] In step 301, for any group, the sum of the quantities of goods to be delivered to all delivery points in the group is determined.

[0062] In this embodiment of the disclosure, after obtaining the quantity of goods to be delivered for each delivery point, a correspondence between delivery point identifiers and the quantities of goods to be delivered can be established. The delivery point identifiers include, but are not limited to, one or more combinations of the following: delivery point name, address, ID, etc. Therefore, for any group, by determining the identifier of each delivery point included in that group, and based on the correspondence between the delivery point identifiers and the quantities of goods to be delivered, the quantity of goods to be delivered for each delivery point in that group can be determined, and thus the sum of the quantities of goods to be delivered for all delivery points in that group can be calculated.

[0063] In step 302, if the sum of the quantities of goods to be delivered is greater than the pre-calculated threshold for the quantity of goods to be delivered, then the group is determined as the target group for balancing the quantities of goods to be delivered.

[0064] In this embodiment, the threshold for the amount of goods to be delivered is a pre-calculated fixed value. The calculation method is as follows: 1) Calculate the demand for goods at multiple delivery points in different locations obtained in step 101; 2) Calculate the sum of the demand for goods at multiple delivery points; 3) Determine the number of groups obtained after clustering the multiple delivery points in step 102; 4) Determine the ratio between the sum of the demand for goods at multiple delivery points and the number of groups as the threshold for the amount of goods to be delivered. Depending on the different business scenarios, the calculation method for the demand for goods at each delivery point varies. For example, if the delivery point is a warehouse, meaning freight logistics delivers goods to the warehouse, then the demand for goods at each delivery point is the warehouse capacity; if the delivery point is a service point, which can be understood as a node providing receiving and delivery services, then the demand for goods at each delivery point is the number of orders.

[0065] In this embodiment of the disclosure, for any group, if the sum of the goods to be delivered to all delivery points in the group is greater than a pre-calculated threshold for the goods to be delivered, it indicates that the demand for goods in the group is overweight and requires goods balancing. Otherwise, the freight drivers would need to make multiple trips to the distribution center to pick up the goods, resulting in a significant waste of time. If the sum of the goods to be delivered to all delivery points in the group is less than or equal to the pre-calculated threshold for the goods to be delivered, it indicates that the demand for goods in the group is neither overweight nor over-limit. After picking up the goods from the distribution center, the freight drivers can deliver the goods to each delivery point in the group without making multiple trips to the distribution center, thus eliminating the need for goods balancing.

[0066] Based on the above embodiments, Figure 1Step 103, as shown, "For any group, determine the balance range of cargo volume corresponding to the group based on the group's central location and the farthest distance between each delivery point in the group and the central location," includes, for example: Figure 4 Steps 401 and 402 are shown below:

[0067] In step 401, for any group, the farthest distance between each delivery point in the group and the central location is determined.

[0068] In this embodiment of the disclosure, for any group, the central location of the group can be determined based on the location distribution of each delivery point in the group. Alternatively, the central location of the group can be obtained by clustering multiple delivery points using a distance clustering algorithm. After determining the central location of the group, the farthest distance between each delivery point in the group and the central location can be further determined.

[0069] In step 402, a circular area with the center of the group as the center and the target distance as the radius is determined as the cargo quantity balance range corresponding to the group; wherein, the target distance is the distance calculated based on a preset reduction coefficient and the farthest distance between each delivery point in the group and the center, 0 < reduction coefficient < 1; or, the target distance is the distance calculated based on a preset amplification coefficient and the farthest distance between each delivery point in the group and the center, amplification coefficient > 1.

[0070] For example, for any group i, the center position of group i is denoted as Oi, such as Figure 2 The dashed circles shown represent the farthest distance between each delivery point in group i and the center location Oi, denoted as Ri. A preset reduction coefficient is denoted as a, where 0 < a < 1. Therefore, the target distance = a × Ri. The circular area defined by Oi as the center and the target distance as the radius represents the cargo quantity balance range corresponding to group i. Figure 5 The large dashed circle shown in the diagram illustrates this. It can be seen that because the cargo volume balance range (i.e., the circular area with center Oi and radius a×Ri, where 0 < a < 1) is smaller than the group's coverage range (i.e., the circular area with center Oi and radius Ri), when a group carries delivery points from other groups, the distance between the newly carried delivery point and the center of the group will not exceed the distance between the farthest delivery point in the group and the center of the group. This achieves relative clustering of delivery points within the same group, avoiding excessive time wasted by truck drivers during transport.

[0071] For example, for any group i, the center position of group i is denoted as Oi, the farthest distance between each delivery point in group i and the center position Oi is denoted as Ri, and the preset magnification factor is denoted as b, where b > 1. Then, the target distance = b × Ri. The circular area with Oi as the center and the target distance as the radius is the cargo volume balance range corresponding to group i. It can be seen that since the cargo volume balance range (i.e., the circular area with Oi as the center and b × Ri as the radius, where b > 1) is greater than the coverage range of the group (i.e., the circular area with Oi as the center and Ri as the radius), the group can carry more delivery points of other groups, achieve cargo volume balance, and improve balance efficiency.

[0072] Based on the above embodiments, Figure 1 Step 104, as shown, "For any target group where the quantity of goods to be balanced is to be determined, at least one target delivery point in the target group where the quantity of goods to be balanced is to be determined", includes, for example, Figure 6 The following steps 601 to 603 are shown:

[0073] In step 601, for any target group to be balanced, the quantity of goods to be balanced in the target group is determined. The quantity of goods to be balanced is the difference between the sum of the quantities of goods to be delivered at all delivery points in the target group and the pre-calculated threshold for the quantity of goods to be delivered.

[0074] For example, for any target group j to balance the amount of goods to be delivered, the sum of the amount of goods to be delivered at all delivery points in target group j is denoted as Wj, the pre-calculated threshold for the amount of goods to be delivered is denoted as Wave, Wj > Wave, and the amount of goods to be balanced in target group j is denoted as Wbalancej, Wbalancej = Wj - Wave.

[0075] In step 602, for delivery points in the target group that are within the balance range of at least one non-target group, the minimum distance corresponding to the delivery point is obtained based on the distance between the delivery point and the center position of the at least one non-target group in which it is located.

[0076] For example, in Figure 7 In the diagram, the target group for achieving quantity balancing is the diamond group, while the non-target groups that do not require quantity balancing are the circular, square, and triangular groups. Delivery points A and B within the diamond group are located within the quantity balancing range of the circular group. Since A and B are only within the quantity balancing range of the circular group, the minimum distance between A and B is as follows: Figure 7 The dashed line connects the center of the circular group to the center of the square group; the delivery points C and D in the rhombus group are within the balance range of the square group's goods volume. C is only within the balance range of the square group's goods volume. Therefore, the minimum distance corresponding to C is as follows: Figure 7The dashed line connecting C to the center of the square group; while D is not only within the equilibrium range of the square group's goods volume, but also within the equilibrium range of the triangular group's goods volume, such as... Figure 7 As shown, the distance between D and the center of the triangle group is less than the distance between D and the center of the square group. Therefore, the minimum distance corresponding to D is as follows: Figure 7 The dashed line connecting D to the center of the triangle group.

[0077] In step 603, at least one target delivery point is determined based on the delivery points in the target group that are within the balance range of the cargo volume of at least one non-target group; wherein, the sum of the cargo volumes to be delivered at at least one target delivery point is within a preset cargo volume range, and the maximum value of the minimum distances corresponding to at least one target delivery point is less than any non-target delivery point.

[0078] In this embodiment of the disclosure, the minimum distances corresponding to different delivery points in the target group can be sorted from smallest to largest, and then the delivery points can be determined as target delivery points in sequence until the sum of the quantities of goods to be delivered at all target delivery points is less than or equal to the quantities of goods to be balanced, thus completing the determination of the target delivery points.

[0079] For example Figure 7 In the diagram, the diamond group represents the target group for balancing the quantity of goods, while the circular, square, and triangular groups are non-target groups for which quantity balancing is not required. The delivery points A, B, C, and D in the diamond group have the following minimum distances: Figure 7 The minimum distance between point A and the center of the circular group is shown by the dashed line connecting point B and point B. Figure 7 The minimum distance between point B and the center of the circular group is shown by the dashed line connecting point B and the center of the circular group. Figure 7 The minimum distance corresponding to the dashed line connecting C and the center of the square group is as follows: Figure 7 The dashed lines connecting point D to the center of the triangular group are used to sort the points by minimum distance in ascending order, for example: minimum distance for A < minimum distance for C < minimum distance for D < minimum distance for B. If the sum of the quantities of goods to be delivered for A, C, and D is less than the quantity of goods to be balanced, and the sum of the quantities of goods to be delivered for A, B, C, and D is greater than the quantity of goods to be balanced, then A, C, and D are determined as the target delivery points for balancing the quantity of goods in the diamond group. Then, A is assigned to the circular group, C to the square group, and D to the triangular group, thus achieving the balancing of the quantity of goods in the diamond group.

[0080] In some embodiments, for any target group to be balanced, after all target delivery points in the target group are divided into non-target groups, the target group is marked as balanced; wherein, the non-target group is a group that is not marked as balanced.

[0081] For example Figure 7In this model, the diamond-shaped group is the target group for load balancing, while the circular, square, and triangular groups are non-target groups that do not require load balancing and are not marked as balanced. Delivery points A, C, and D in the diamond-shaped group are the target delivery points for load balancing. A is assigned to the circular group, C to the square group, and D to the triangular group, thus achieving load balancing for the diamond-shaped group and marking it as balanced. In this embodiment, marking the target group that has achieved load balancing as balanced facilitates skipping balanced groups when balancing other unmarked groups later, preventing balanced groups from becoming overweight again.

[0082] In some embodiments, if all target groups have been balanced, the center position of any non-target group that has been divided into delivery points is updated; and the target group to be balanced is re-determined from all unmarked balanced groups.

[0083] For example Figure 7 In this process, the only target group for balancing the cargo volume is the diamond group. The circular, square, and triangular groups are non-target groups that do not require cargo volume balancing, and they are not marked as balanced. After balancing the cargo volume of the diamond group, for the circular group (divided into A), the center position of the circular group is updated; for the square group (divided into C), the center position of the square group is updated; and for the triangular group (divided into D), the center position of the triangular group is updated. After updating the center positions of the circular, square, and triangular groups, since none of them are marked as balanced, the target group for cargo volume balancing is re-determined from these groups, using a method similar to... Figure 3 The process for determining the target group for balancing the quantity of goods shown will not be repeated here to avoid duplication.

[0084] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art will understand that the embodiments of this disclosure are not limited to the described order of actions, because according to the embodiments of this disclosure, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art will understand that the embodiments described in the specification are all optional embodiments.

[0085] Figure 8This is a schematic diagram of a multi-delivery-point grouping device provided in an embodiment of this disclosure. This multi-delivery-point grouping device can be applied to electronic devices, including but not limited to smartphones, PDAs, tablets, wearable devices with displays, desktop computers, laptops, all-in-one computers, smart home devices, servers, etc. The server can be a standalone server or a cluster of multiple servers, and can include locally located servers and cloud-based servers. The multi-delivery-point grouping device provided in this disclosure can execute the processing flows provided in various embodiments of the multi-delivery-point grouping method, such as... Figure 8 As shown, the grouping device for multiple delivery points includes: an acquisition unit 801, a grouping unit 802, a first determination unit 803, a second determination unit 804, and a division unit 805.

[0086] The acquisition unit 801 is used to acquire multiple delivery points at different locations and the amount of goods to be delivered at each delivery point;

[0087] Grouping unit 802 is used to cluster multiple delivery points into groups and obtain the center location of each group;

[0088] The first determining unit 803 is used to determine the cargo quantity balance range corresponding to any group based on the center location of the group and the farthest distance between each delivery point in the group and the center location, wherein the farthest distance between the center location and the boundary of the cargo quantity balance range is less than or greater than the farthest distance between each delivery point in the group and the center location.

[0089] The second determining unit 804 is used to determine at least one target delivery point in any target group to be balanced, wherein the sum of the goods to be delivered at the at least one target delivery point is within a preset goods quantity range, the goods quantity range is obtained based on the goods quantity to be balanced in the target group, and each target delivery point is within the goods quantity balance range of at least one non-target group.

[0090] The partitioning unit 805 is used to partition any target delivery point into the non-target group that is closest to the central location, and the target delivery point is within the balance range of the cargo volume of the partitioned non-target group.

[0091] In some embodiments, the grouping device for multiple delivery points further includes a target grouping determination unit, configured to:

[0092] For any group, determine the sum of the quantities of goods to be delivered to all delivery points in the group; if the sum of the quantities of goods to be delivered is greater than the pre-calculated threshold for the quantities of goods to be delivered, then the group is determined as the target group for balancing the quantities of goods to be delivered.

[0093] In some embodiments, the first determining unit 803 is configured to: determine the farthest distance between each delivery point in the group and the center location for any group; determine a circular area with the center location of the group as the center and the target distance as the radius as the cargo volume balance range corresponding to the group, wherein the target distance is a distance calculated based on a preset reduction coefficient and the farthest distance between each delivery point in the group and the center location, where 0 < reduction coefficient < 1; or, the target distance is a distance calculated based on a preset magnification coefficient and the farthest distance between each delivery point in the group and the center location, where the magnification coefficient > 1.

[0094] In some embodiments, the second determining unit 804 is configured to:

[0095] For any target group to balance the quantity of goods to be delivered, determine the quantity of goods to be delivered in the target group. The quantity of goods to be delivered is the difference between the sum of the quantities of goods to be delivered at all delivery points in the target group and the pre-calculated threshold for the quantity of goods to be delivered.

[0096] For delivery points in the target group that are within the balance range of at least one non-target group, the minimum distance corresponding to the delivery point is obtained based on the distance between the delivery point and the center position of the at least one non-target group in which it is located.

[0097] Based on the delivery points in the target group that are within the balance range of the cargo volume of at least one non-target group, at least one target delivery point is determined; wherein, the sum of the cargo volume to be delivered at at least one target delivery point is within a preset cargo volume range, and the maximum value of the minimum distance corresponding to at least one target delivery point is less than any non-target delivery point.

[0098] In some embodiments, the grouping device for multiple delivery points further includes a marking unit for:

[0099] For any target group, after all target delivery points in the target group are assigned to non-target groups, the target group is marked as balanced; among them, non-target groups are groups that are not marked as balanced.

[0100] In some embodiments, the grouping device for multiple delivery points further includes an updating unit for: if all target groups have been balanced, updating the center position of any non-target group that has been divided into delivery points;

[0101] The target group determination unit is also used to redetermine the target group to be balanced from all unmarked balanced groups after the update unit has completed the update.

[0102] In some embodiments, the partitioning unit 805 is used for:

[0103] For any target delivery point, based on the cargo volume balance range of at least one non-target group in which the target delivery point is located, the center position of each of the at least one non-target group is obtained;

[0104] Calculate the distance between the target delivery point and the center location of at least one non-target group, and obtain the non-target group whose center location is closest to the target delivery point;

[0105] The target delivery point is assigned to the non-target group that is closest to the central location, and the target delivery point is within the balance range of the cargo volume of the assigned non-target group.

[0106] In at least one embodiment of this disclosure, multiple delivery points are clustered into groups to obtain the center location of each group. The center location of each group is used to determine the cargo volume balancing range corresponding to each group, which differs from the coverage area of ​​the group. Then, at least one target delivery point is selected from the target groups to be balanced, where the sum of the cargo volumes to be delivered at the at least one target delivery point falls within a preset cargo volume range. This cargo volume range is based on the cargo volumes to be balanced in the target groups, allowing the target delivery points to be assigned to non-target groups. Each target delivery point is within the cargo volume balancing range of at least one non-target group, thus achieving cargo volume balancing. Furthermore, considering that any target delivery point may fall within the cargo volume balancing range of at least one non-target group, the distance between the target delivery point and the center locations of its different non-target groups varies. The target delivery point is assigned to the non-target group whose center location is closest to it, allowing the target delivery point to be relatively clustered with other delivery points in that non-target group, avoiding excessive time wasted by truck drivers during transport. Moreover, after balancing the cargo volumes of all groups, the cargo volume transported by each truck driver is also relatively balanced, solving the problem of unreasonable driver resource allocation.

[0107] For details of the various embodiments of the grouping device for multiple delivery points disclosed above, please refer to the details of the various embodiments of the grouping method for multiple delivery points described above. To avoid repetition, these details will not be repeated.

[0108] Figure 9 This is an exemplary block diagram of a computer device provided in an embodiment of this disclosure. Figure 9 As shown, the computer device includes: at least one computing device 901 and at least one storage device 902 for storing instructions. It is understood that the storage device 902 in this embodiment may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.

[0109] In some implementations, storage device 902 stores elements such as executable modules or data structures, or subsets thereof, or extended sets thereof: operating systems and applications.

[0110] The operating system includes various system programs, such as the framework layer, core library layer, and driver layer, used to implement various basic tasks and handle hardware-based tasks. The application programs include various applications, such as media players and browsers, used to implement various application tasks. The program implementing the multi-delivery-point grouping method provided in this disclosure can be included in the application programs.

[0111] In this embodiment of the disclosure, at least one computing device 901 executes the steps of various embodiments of the grouping method for multiple distribution points provided in this disclosure by calling a program or instruction stored in at least one storage device 902, specifically, a program or instruction stored in an application.

[0112] The grouping method for multiple delivery points provided in this disclosure can be applied to, or implemented by, a computing device 901. The computing device 901 can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by integrated logic circuits in the hardware or by instructions in software within the computing device 901. The computing device 901 can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor can be a microprocessor or any conventional processor.

[0113] The steps of the grouping method for multiple distribution points provided in this disclosure can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in storage device 902, and computing device 901 reads information from storage device 902 and combines it with hardware to complete the steps of the method.

[0114] This disclosure also proposes a computer-readable storage medium storing a program or instructions that cause a computer to perform steps, such as those in the various embodiments of the multi-distribution-point grouping method, which will not be repeated here to avoid repetition. The computer-readable storage medium can be a non-transitory computer-readable storage medium.

[0115] This disclosure also proposes a computer program product, wherein the computer program product includes a computer program stored in a non-transitory computer-readable storage medium, and at least one processor of the computer reads from the storage medium and executes the computer program, causing the computer to perform the steps of various embodiments of the grouping method for multiple distribution points, which will not be repeated here to avoid repetition.

[0116] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0117] Those skilled in the art will understand that although some embodiments described herein include certain features included in other embodiments but not others, combinations of features from different embodiments are meant to be within the scope of this disclosure and form different embodiments.

[0118] Those skilled in the art will understand that the descriptions of the various embodiments have different focuses, and for parts not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0119] Although embodiments of the present disclosure have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present disclosure, and all such modifications and variations fall within the scope defined by the appended claims.

Claims

1. A method for grouping multiple delivery points, the method comprising: obtaining multiple delivery points at different locations and the amount of goods to be delivered at each of the delivery points; grouping the multiple delivery points into clusters to obtain a center location of each cluster; for any of the clusters, determining a goods amount balancing range corresponding to the cluster according to the center location of the cluster and the farthest distance between each of the delivery points in the cluster and the center location, wherein the goods amount balancing range is different from the coverage range of the cluster, and the farthest distance between the center location and the boundary of the goods amount balancing range is less than or greater than the farthest distance between each of the delivery points in the cluster and the center location; for any target cluster to be balanced in goods amount, determining at least one target delivery point in the target cluster to be balanced in goods amount, wherein the sum of the amount of goods to be delivered at the at least one target delivery point is within a preset goods amount range, the goods amount range is based on the amount of goods to be balanced in the target cluster, and each of the target delivery points is within the goods amount balancing range of at least one non-target cluster; for any of the target delivery points, dividing the target delivery point into the non-target cluster closest to the target delivery point, and the target delivery point is within the goods amount balancing range of the divided non-target cluster.

2. The method of claim 1, wherein, Before the step of, for any target cluster to be balanced in goods amount, determining at least one target delivery point in the target cluster to be balanced in goods amount, the method further comprises: for any of the clusters, determining the sum of the amount of goods to be delivered at all of the delivery points in the cluster; if the sum of the amount of goods to be delivered is greater than a pre-calculated threshold of the amount of goods to be delivered, determining the cluster as a target cluster to be balanced in goods amount.

3. The method of claim 1 or 2, wherein, The step of, for any of the clusters, determining a goods amount balancing range corresponding to the cluster according to the center location of the cluster and the farthest distance between each of the delivery points in the cluster and the center location, comprises: for any of the clusters, determining the farthest distance between each of the delivery points in the cluster and the center location; determining a circular region with the center location of the cluster as the center and a target distance as the radius as the goods amount balancing range corresponding to the cluster, wherein the target distance is a distance calculated based on a preset reduction coefficient and the farthest distance between each of the delivery points in the cluster and the center location, and 0 < the reduction coefficient < 1, or the target distance is a distance calculated based on a preset expansion coefficient and the farthest distance between each of the delivery points in the cluster and the center location, and the expansion coefficient > 1.

4. The method of claim 1 or 2, wherein, The step of, for any target cluster to be balanced in goods amount, determining at least one target delivery point in the target cluster to be balanced in goods amount, comprises: for any target cluster to be balanced in goods amount, determining the amount of goods to be balanced in the target cluster, wherein the amount of goods to be balanced is the difference between the sum of the amount of goods to be delivered at all of the delivery points in the target cluster and a pre-calculated threshold of the amount of goods to be delivered. For the delivery point in the target group within the cargo amount balance range of at least one non-target group, a minimum distance corresponding to the delivery point is obtained based on the distance between the delivery point and the center position of at least one non-target group where the delivery point is located; Based on the delivery point in the target group within the cargo amount balance range of at least one non-target group, at least one target delivery point is determined; wherein the sum of the to-be-delivered cargo amount of the at least one target delivery point is within a preset cargo amount range, and the maximum value of the minimum distances corresponding to the at least one target delivery point is less than any non-target delivery point.

5. The method of claim 1, wherein, The method further comprises: For any target group, after all target delivery points in the target group are divided into non-target groups, the target group is marked as balanced; wherein the non-target group is a group that is not marked as balanced.

6. The method of claim 5, wherein, The method further comprises: If all target groups are balanced, for any non-target group to which a delivery point is divided, the center position of the non-target group is updated; From all groups that are not marked as balanced, the target group to be balanced is re-determined.

7. The method of claim 1, wherein, For any target delivery point, the target delivery point is divided into a non-target group closest to the center position and the target delivery point, and the target delivery point is within the cargo amount balance range of the divided non-target group, comprising: For any target delivery point, based on the cargo amount balance range of at least one non-target group where the target delivery point is located, the center position of each of the at least one non-target group is obtained; The distance between the target delivery point and the center position of each of the at least one non-target group is calculated to obtain a non-target group closest to the center position and the target delivery point; The target delivery point is divided into a non-target group closest to the center position and the target delivery point, and the target delivery point is within the cargo amount balance range of the divided non-target group.

8. A grouping device for multiple delivery points, the device comprising: An acquisition unit configured to acquire a plurality of delivery points at different positions and a to-be-delivered cargo amount of each of the delivery points; A grouping unit configured to cluster and group the plurality of delivery points to obtain a center position of each group; A first determination unit configured to, for any group, determine a cargo amount balance range corresponding to the group according to the center position of the group and the farthest distance between each delivery point in the group and the center position, wherein the cargo amount balance range is different from the coverage range of the group, and the farthest distance between the center position and the boundary of the cargo amount balance range is less than or greater than the farthest distance between each delivery point in the group and the center position. a second determining unit configured to determine at least one target distribution point in a target group for which the amount of goods to be balanced is balanced, wherein the sum of the amount of goods to be distributed at the at least one target distribution point is within a preset range of the amount of goods, and the range of the amount of goods is based on the amount of goods to be balanced in the target group, and each of the target distribution points is within the range of the amount of goods to be balanced in at least one non-target group; a dividing unit configured to divide each of the target distribution points into a non-target group closest to the target distribution point in terms of distance between the center position and the target distribution point, and the target distribution point is within the range of the amount of goods to be balanced in the non-target group into which the target distribution point is divided.

9. A computer readable storage medium, wherein, The computer readable storage medium stores programs or instructions, which cause the computer to execute the steps of the grouping method of multiple distribution points according to any one of claims 1 to 7.

10. A computer device, wherein, The computer readable storage medium stores programs or instructions, which cause the computer to execute the steps of the grouping method of multiple distribution points according to any one of claims 1 to 7. The computer readable storage medium stores programs or instructions, which cause the computer to execute the steps of the grouping method of multiple distribution points according to any one of claims 1 to 7.

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