Box loading method

Abstract

The invention provides a box loading method, which can be realized in a modularized manner, can be internally integrated in a system and can also be independently deployed, and the system integration is flexible. And irregular loading containers and various loading rules are supported, including threshold conditions of height limitation, load, loading rate and the like of the loading containers, and rule conditions of non-pressing light weight, non-pressing small size, cross stacking, layer number limitation, load bearing limitation, priority level and the like of target loading boxes. And meanwhile, the method can be realized based on Java codes, and has excellent performance in the aspects of large data volume and concurrency control.

Description

Technical Field

[0001] The present application relates to the field of loading technology, and in particular to a box loading method. Background Art

[0002] During logistics transportation or material stacking, boxes need to be loaded into designated containers (such as containers, racks, pallets, etc.). During loading, it is also necessary to consider how to maximize the container space to accommodate more boxes. However, current loading technology uses stand-alone application software, which is not suitable for system integration. Furthermore, the stability and data processing performance of current loading technology are mediocre, failing to meet user expectations. Summary of the Invention

[0003] In view of the above-mentioned shortcomings of the prior art, the purpose of this application is to provide a box loading method for solving the technical problems existing in the prior art.

[0004] To achieve the above-mentioned and other related purposes, the present application provides a box loading method, comprising the following steps:

[0005] Obtaining information about a box to be loaded, information about a loading container, and loading rule information, wherein the loading container is used to simulate carrying the box to be loaded according to the information about the box to be loaded;

[0006] Group the boxes to be loaded in the box information by type and sort them randomly;

[0007] Based on the random sorting results, the boxes to be loaded are grouped and loaded, and it is determined whether the loading results meet the preset assembly conditions. When the loading results do not meet the preset assembly conditions, all the boxes to be loaded are re-circulated to be grouped and randomly sorted by type, and all the boxes to be loaded are loaded according to the random sorting results after the re-circulation until the loading is completed; wherein the preset assembly conditions include that the number of assemblies of the same assembly scheme exceeds the preset number.

[0008] Optionally, the process of grouping the boxes to be loaded and performing loading based on the random sorting result includes:

[0009] A three-dimensional coordinate system is established with a vertex of the loading container as the origin, and the origin is recorded as the P1 placement point, and the vertex located in the X-axis coordinate is recorded as the P2 placement point, the vertex located in the Y-axis coordinate is recorded as the P4 placement point, the vertex located in the Z-axis coordinate is recorded as the P5 placement point, and the intersection vertex located in the XY plane is recorded as the P3 placement point, the intersection vertex located in the XZ plane is recorded as the P6 placement point, the intersection vertex located in the YZ plane is recorded as the P8 placement point, and the intersection vertex located in the XYZ space is recorded as the P7 placement point;

[0010] Based on the random sorting result, a box to be loaded is selected as the target box, and the target box is rotated so that the target box traverses each placement point in the three-dimensional coordinate system;

[0011] Calculate the fitness score of the target box at each placement point, and load the target box based on the fitness score, remove the target box from the box information to be loaded, and reselect the box to be loaded from the remaining box information to be loaded as the new target box to be loaded.

[0012] Optionally, the process of loading the to-be-loaded box in the to-be-loaded box information based on the fitness score includes:

[0013] Obtain the fitness score of the box to be loaded at each placement point and select the maximum fitness score; among them, if the fitness scores are the same, select the larger one based on the ratio of the volume to weight of the box to be loaded;

[0014] The box to be loaded is loaded according to the maximum fitness score until the loading container can no longer fit into the box to be loaded.

[0015] Optionally, the process of determining whether the loading result meets the preset assembly conditions includes:

[0016] When the loading container cannot be loaded into the box to be loaded, the loading rate of the loading container is calculated and the loading rate is used as the corresponding loading result;

[0017] Compare the loading rate with the current best assembly solution;

[0018] If the loading rate is greater than the current best assembly plan, the loading result is marked as not meeting the preset assembly conditions, and the current best assembly plan is replaced, and the assembly times of the current best assembly plan are reset to zero, and all boxes to be loaded are grouped and randomly sorted by type in a recycle, and all boxes to be loaded are loaded according to the random sorting results after the recycle until the loading is completed;

[0019] If the loading rate is greater than the current best assembly solution and the number of assemblies of the current best assembly solution exceeds the preset number, the current best assembly solution is selected.

[0020] Optionally, the method further comprises: grouping and randomly sorting all boxes to be loaded by type using a probabilistic optimization algorithm; and, based on the random sorting result, grouping the boxes to be loaded using an allocation strategy algorithm for loading.

[0021] Optionally, the probability optimization algorithm is a simulated annealing algorithm, and the allocation strategy algorithm is a Best Fit algorithm.

[0022] Optionally, before obtaining the box information to be loaded, the loading container information and the loading rule information, the method further includes: initializing the simulated annealing algorithm parameters, including setting the maximum temperature value of the simulated annealing algorithm to 1000, the minimum temperature value to 10, and the cooling rate value to 0.98.

[0023] Optionally, when the loading result meets the preset assembly conditions, the simulated annealing algorithm is exited, and the temperature is lowered according to the set cooling rate, and when the current temperature is lower than the minimum temperature, the current best assembly solution is selected.

[0024] Optionally, the loading rule information includes that the bottom of the box to be loaded is not suspended in the air, is not placed on a box with a smaller volume than the box to be loaded, and is not placed on a box with a lighter weight than the box to be loaded.

[0025] Optionally, when calculating the fitness score of the target box at each placement point, the method further includes: classifying the fitness scores according to the loading rule information.

[0026] As described above, the present application provides a box loading method with the following beneficial effects: the present application has good scalability and can be implemented in a modular manner. It can be integrated within the system or deployed independently, and the system integration is flexible. The present application has good functionality and supports irregular loading containers and various loading rules, including threshold conditions such as height limit, load, and loading rate of loading containers, as well as rule conditions such as heavy not pressing light, large not pressing small, cross stacking, layer number limit, load-bearing limit, priority level, etc. of the target loading box. The present application has good stability and performance, can be implemented based on Java code, and performs well in terms of large data volume and concurrency control. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A schematic diagram of the process of box loading method provided in this application;

[0028] Figure 2 for Figure 1 Flowchart of loading calculation;

[0029] Figure 3 A schematic diagram of a three-dimensional coordinate system provided in this application, with a vertex of the loading container as the origin;

[0030] Figure 4 Schematic diagram of the box loading effect provided for this application;

[0031] Figure 5 A timing diagram of the box loading method provided in this application. DETAILED DESCRIPTION

[0032] The following describes the embodiments of the present application through specific examples. Those skilled in the art can easily understand the other advantages and effects of the present application from the content disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments. The details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other unless they conflict.

[0033] It should be noted that the illustrations provided in this embodiment only illustrate the basic concept of the present application in a schematic manner. Therefore, the illustrations only show components related to the present application and are not drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component can be changed at will, and the component layout type may also be more complicated.

[0034] See also Figures 1 to 3 As shown, the present application provides a box loading method, comprising the following steps:

[0035] Obtaining information about a box to be loaded, information about a loading container, and loading rule information, wherein the loading container is used to simulate carrying the box to be loaded according to the information about the box to be loaded;

[0036] Use a probabilistic optimization algorithm to group the boxes to be loaded in the loading box information by type and randomly sort them;

[0037] Based on the random sorting results, the allocation strategy algorithm is used to group the boxes to be loaded and load them, and it is determined whether the loading results meet the preset assembly conditions. When the loading results do not meet the preset assembly conditions, the probability optimization algorithm is recycled to group and randomly sort all the boxes to be loaded by type, and load all the boxes to be loaded according to the random sorting results after recycling until the loading is completed; wherein, the preset assembly conditions include that the number of assemblies of the same assembly scheme exceeds the preset number.

[0038] According to the above description, in an exemplary embodiment, the process of grouping and loading boxes using an allocation strategy algorithm based on the random sorting results includes:

[0039] A three-dimensional coordinate system is established with a vertex of the loading container as the origin, and the origin is recorded as P1 placement point, and the vertex located in the X-axis coordinate is recorded as P2 placement point, the vertex located in the Y-axis coordinate is recorded as P4 placement point, the vertex located in the Z-axis coordinate is recorded as P5 placement point, and the intersection vertex located in the XY plane is recorded as P3 placement point, the intersection vertex located in the XZ plane is recorded as P6 placement point, the intersection vertex located in the YZ plane is recorded as P8 placement point, and the intersection vertex located in the XYZ space is recorded as P7 placement point. Specifically, a schematic diagram of the three-dimensional coordinate system established with a vertex of the loading container as the origin is shown as follows Figure 3 shown.

[0040] Based on the random sorting result, a box to be loaded is selected as the target box, and the target box is rotated so that the target box traverses each placement point in the three-dimensional coordinate system;

[0041] Calculate the fitness score of the target box at each placement point, and load the target box based on the fitness score, remove the target box from the box information to be loaded, and reselect the box to be loaded from the remaining box information to be loaded as the new target box to be loaded.

[0042] According to the above description, in an exemplary embodiment, the process of loading the to-be-loaded box in the to-be-loaded box information based on the fitness score includes:

[0043] Obtain the fitness score of the box to be loaded at each placement point and select the maximum fitness score; among them, if the fitness scores are the same, select the larger one based on the ratio of the volume to weight of the box to be loaded;

[0044] The box to be loaded is loaded according to the maximum fitness score until the loading container can no longer fit into the box to be loaded.

[0045] According to the above description, in an exemplary embodiment, the process of determining whether the loading result meets the preset assembly conditions includes:

[0046] When the loading container cannot be loaded into the box to be loaded, the loading rate of the loading container is calculated and the loading rate is used as the corresponding loading result;

[0047] Compare the loading rate with the current best assembly solution;

[0048] If the loading rate is greater than the current best assembly plan, the loading result is marked as not meeting the preset assembly conditions, and the current best assembly plan is replaced. The assembly times of the current best assembly plan are reset to zero, and the probability optimization algorithm is recycled to group and randomly sort all boxes to be loaded by type, and all boxes to be loaded are loaded according to the random sorting results after recycling until the loading is completed;

[0049] If the loading rate is greater than the current best assembly solution and the number of assemblies of the current best assembly solution exceeds the preset number, the current best assembly solution is selected.

[0050] According to the above description, in an exemplary embodiment, the container loading method may further include: utilizing a probabilistic optimization algorithm to group all containers to be loaded by type and randomly sorting them; and, based on the random sorting results, utilizing an allocation strategy algorithm to group the containers to be loaded and perform loading. For example, the probabilistic optimization algorithm may be a simulated annealing algorithm, and the allocation strategy algorithm may be a Best Fit algorithm (BF algorithm).

[0051] According to the above records, in an exemplary embodiment, before obtaining the box information to be loaded, the loading container information and the loading rule information, the box loading method may further include: initializing the simulated annealing algorithm parameters, including setting the maximum temperature value of the simulated annealing algorithm to 1000, the minimum temperature value to 10, and the cooling rate value to 0.98.

[0052] According to the above description, in an exemplary embodiment, when the loading result meets the preset assembly conditions, the simulated annealing algorithm is exited, and cooling is performed according to the set cooling rate, and when the current temperature is lower than the minimum temperature, the current optimal assembly solution is selected.

[0053] According to the above records, in an exemplary embodiment, the loading rule information includes heavy items not pressing light items, large items not pressing small items, cross stacking, layer number restrictions, load-bearing restrictions, and priority levels. For example, it may include that the bottom of the box to be loaded is not suspended in the air, it is not placed on a box with a smaller volume than the box to be loaded, and it is not placed on a box with a lighter weight than the box to be loaded.

[0054] According to the above description, in an exemplary embodiment, when calculating the fitness score of the target box at each placement point, the box loading method may further include: classifying the fitness scores according to the loading rule information. Specifically, the fitness score classification results are shown in Table 1 below.

[0055] Table 1

[0056]

[0057] The intersection rate represents the sum of the overlapping areas of the face and other boxes / the area of the face.

[0058] In a specific embodiment, a container is provided as a loading container for use in the container loading method described in the above embodiment. The goal of the container is to maximize the total volume of boxes loaded into the container (maximize the loading rate) without overloading. Specifically, using the container as a loading container for use in the container loading method described in the above embodiment includes the following steps:

[0059] 1. Obtain information about containers and boxes to be loaded, as well as loading rules;

[0060] 2. Initialize the simulated annealing algorithm parameters (maximum temperature: 1000, minimum temperature: 10, cooling rate: 0.98)

[0061] 3. Loading and execution (simulated annealing algorithm)

[0062] 3.1 Group all boxes to be packed by type and sort them randomly;

[0063] 3.2 Group Execution Loading (Best Fit Algorithm)

[0064] 3.21) Loop through each box;

[0065] 3.22) Obtain a set of placement points, including the container origin and the projection points of the bottom surface of the obstacle in the container;

[0066] 3.23) Rotate the boxes, for example, swapping length and width, and placing each box twice;

[0067] 3.24) Traverse each placement point

[0068] a) Calculate the fitness score of the box at the placement point:

[0069] b) Determine the best fitness (except for scores of 0). If the scores are the same, sort by volume or weight and take the larger one;

[0070] c) Select the box with the best fitness and put it into the container, and remove the box from the set of boxes to be packed;

[0071] d) Repeat step 3.21) until there is nothing left to pack into the box;

[0072] 3.3 Evaluate the loading plan:

[0073] 3.31) If the loading rate is greater than the current best solution, replace the current best solution, reset the number of times of the current best assembly solution, and repeat step 3.1;

[0074] 3.32) If the loading rate is less than or equal to the current optimal solution, and the current optimal solution has been used for 50 times (configurable), the current optimal solution is selected and the simulated annealing algorithm is exited.

[0075] 3.4 Execute cooling, cooling rate (0.98), if the current temperature is less than the minimum temperature, select the current optimal loading plan and exit the simulated annealing algorithm;

[0076] 3.5 Repeat step 3.1;

[0077] 4. After the loading is completed, the calculation results are assembled.

[0078] According to the above records, the container is used as a loading container and the box loading method described in the above embodiment is applied to the box loading effect diagram as shown in FIG. Figure 4 shown.

[0079] According to the above records, in an exemplary embodiment, the present application further provides a task controller, a task service, a loading executor and a container object, and the above-mentioned box loading method is implemented through the timing coordination between the task controller, the task service, the loading executor and the container object, such as Figure 5 shown.

[0080] In summary, this application provides a container loading method that can be implemented in a modular manner, allowing for both internal system integration and independent deployment, with flexible system integration. It also supports irregular loading containers and a variety of loading rules, including threshold conditions such as height limits, load capacity, and loading rate for loading containers, as well as rules for target loading containers such as heavy containers not crushing light containers, large containers not crushing small containers, cross-stacking, layer number limits, load-bearing limits, and priority levels. Furthermore, it can be implemented in Java code, demonstrating excellent performance in large data volumes and concurrency control.

[0081] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by one of ordinary skill in the art without departing from the spirit and technical concepts disclosed in this application shall be covered by the claims of this application.

[0082] The structures, proportions, sizes, etc. illustrated in the drawings in this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by those familiar with this technology. They are not intended to limit the conditions for implementation of this application and therefore have no substantial technical significance. Any structural modifications, changes in proportional relationships, or adjustments in size should still fall within the scope of the technical contents disclosed in this application without affecting the effects and objectives that can be achieved by this application. At the same time, terms such as "upper," "lower," "left," "right," "center," and "one" cited in this specification are only for the convenience of description and are not intended to limit the scope of implementation of this application. Changes or adjustments in their relative relationships should also be considered as the scope of implementation of this application without substantially changing the technical contents.

Claims

1. A box loading method, characterized in that: The method comprises the following steps: Obtaining information about a box to be loaded, information about a loading container, and loading rule information, wherein the loading container is used to simulate carrying the box to be loaded according to the information about the box to be loaded; Group the boxes to be loaded in the box information by type and sort them randomly; Based on the random sorting results, the boxes to be loaded are grouped and loaded, and it is determined whether the loading results meet the preset assembly conditions. When the loading results do not meet the preset assembly conditions, all the boxes to be loaded are re-circulated to be grouped and randomly sorted by type, and all the boxes to be loaded are loaded according to the random sorting results after the re-circulation until the loading is completed; wherein the preset assembly conditions include that the number of assemblies of the same assembly scheme exceeds the preset number.

2. The box loading method according to claim 1, characterized in that: The process of grouping and loading boxes based on the random sorting results includes: A three-dimensional coordinate system is established with a vertex of the loading container as the origin, and the origin is recorded as the P1 placement point, and the vertex located in the X-axis coordinate is recorded as the P2 placement point, the vertex located in the Y-axis coordinate is recorded as the P4 placement point, the vertex located in the Z-axis coordinate is recorded as the P5 placement point, and the intersection vertex located in the XY plane is recorded as the P3 placement point, the intersection vertex located in the XZ plane is recorded as the P6 placement point, the intersection vertex located in the YZ plane is recorded as the P8 placement point, and the intersection vertex located in the XYZ space is recorded as the P7 placement point; Based on the random sorting result, a box to be loaded is selected as the target box, and the target box is rotated so that the target box traverses each placement point in the three-dimensional coordinate system; Calculate the fitness score of the target box at each placement point, and load the target box based on the fitness score, remove the target box from the box information to be loaded, and reselect the box to be loaded from the remaining box information to be loaded as the new target box to be loaded.

3. The box loading method according to claim 2, characterized in that: The process of loading the box to be loaded in the box to be loaded information based on the fitness score includes: Obtain the fitness score of the box to be loaded at each placement point and select the maximum fitness score; among them, if the fitness scores are the same, select the larger one based on the ratio of the volume to weight of the box to be loaded; The box to be loaded is loaded according to the maximum fitness score until the loading container can no longer fit into the box to be loaded.

4. The box loading method according to claim 3, characterized in that: The process of judging whether the loading result meets the preset assembly conditions includes: When the loading container cannot be loaded into the box to be loaded, the loading rate of the loading container is calculated and the loading rate is used as the corresponding loading result; Compare the loading rate with the current best assembly solution; If the loading rate is greater than the current best assembly plan, the loading result is marked as not meeting the preset assembly conditions, and the current best assembly plan is replaced, and the assembly times of the current best assembly plan are reset to zero, and all boxes to be loaded are grouped and randomly sorted by type in a recycle, and all boxes to be loaded are loaded according to the random sorting results after the recycle until the loading is completed; If the loading rate is greater than the current best assembly solution and the number of assemblies of the current best assembly solution exceeds the preset number, the current best assembly solution is selected.

5. The box loading method according to any one of claims 1 to 4, characterized in that: The method further includes: grouping and randomly sorting all boxes to be loaded by type using a probability optimization algorithm; and, based on the random sorting result, grouping the boxes to be loaded using an allocation strategy algorithm and performing loading.

6. The box loading method according to claim 5, characterized in that: The probability optimization algorithm is a simulated annealing algorithm, and the allocation strategy algorithm is a Best Fit algorithm.

7. The box loading method according to claim 6, characterized in that: Before obtaining the box information to be loaded, the loading container information and the loading rule information, the method further includes: initializing the simulated annealing algorithm parameters, including setting the maximum temperature value of the simulated annealing algorithm to 1000, the minimum temperature value to 10, and the cooling rate value to 0.

98.

8. The box loading method according to claim 7, characterized in that: When the loading result meets the preset assembly conditions, the simulated annealing algorithm is exited, and the cooling is performed according to the set cooling speed. When the current temperature is lower than the minimum temperature, the current best assembly solution is selected.

9. The box loading method according to claim 1, characterized in that: The loading rule information includes that the bottom of the box to be loaded is not suspended in the air, it is not placed on a box with a smaller volume than the box to be loaded, and it is not placed on a box with a lighter weight than the box to be loaded.

10. The box loading method according to claim 2, characterized in that: When calculating the fitness score of the target box at each placement point, the method further includes: classifying the fitness scores according to the loading rule information.

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