Multi-product mixed three-dimensional boxing method, device and equipment and storage medium

Abstract

The invention provides a multi-product mixed three-dimensional boxing method, device and equipment and a storage medium, and the multi-product mixed three-dimensional boxing method comprises the steps that data information is read and preprocessed, and the data information comprises product constraint conditions, container sizes and carriage models; the stacking module is used for calling a stacking model to stack product containers layer by layer according to the data information to generate a plurality of stacks; calling a skyline model according to the compartment model based on the stacking module, and matching the non-stacked containers and the stacking module with stackable spaces in the compartments of different compartment models to generate a loading combination. According to the method, the stacking model and the skyline model are used iteratively, the stacking module is generated in the vertical direction of the three-dimensional space based on the stacking model, then the skyline model is called to dynamically find the stackable space in the two-dimensional space, and finally the loading combination with the maximum loading rate is generated.

Description

Technical Field

[0001] The present application relates to the technical field of automobile parts shipping, and in particular to a three-dimensional packing method, device, equipment and storage medium for mixed multi-products. Background Art

[0002] As the grid complexity of the automotive after-sales business continues to increase, the allocation, distribution and delivery of after-sales parts have become key links in the entire automotive supply chain. How to plan the path, pre-dispatch and vehicle loading of after-sales loading more efficiently, timely and accurately has become one of the key issues in reducing costs and increasing efficiency of after-sales parts. The main problem facing the after-sales parts allocation business is: how to increase the loading rate of after-sales parts, reduce the number of vehicle usage and vehicle usage costs, and achieve the long-term goal of reducing the transportation costs of after-sales parts. Summary of the invention

[0003] In view of the fact that in the prior art, product loading mainly relies on loaders to manually judge the stacking order and loading plan of product boxes, which has problems such as low loading efficiency and a lot of wasted space in the car, the present application provides a three-dimensional packing method, device, equipment and storage medium for mixed multiple products.

[0004] In a first aspect, an embodiment of the present application provides a three-dimensional packing method for mixed multiple products, the method comprising:

[0005] Reading data information and preprocessing the data information, the data information including: product constraints, cargo box dimensions and carriage model;

[0006] Calling a stacking model according to the data information to stack product boxes layer by layer to generate a stacking module with a certain number of stacks;

[0007] Based on the stacking module, the skyline model is called according to the car model, and the unstacked cargo boxes and the stacking modules are matched with the stackable spaces in the cars of different car models to generate a loading combination.

[0008] In a possible embodiment, the step of calling the stacking model according to the data information to stack the goods layer by layer to generate a plurality of stacking modules includes:

[0009] Calculate the wasted stacking space volume of each cargo box in the current stacking layer according to product constraints, cargo box size and car model, where the wasted stacking space volume includes: the volume of unusable space generated between two cargo boxes in adjacent stacking layers in the vertical space and / or between the cargo box and the car;

[0010] A stacking module is generated according to the information of the cargo boxes placed on all the stacking layers, and cargo boxes with the smallest wasted volume of the stacking space are placed on all the stacking layers in the stacking module.

[0011] In a possible embodiment, the step of calculating the wasted volume of the stacking space of each cargo box in the current stacking layer includes:

[0012] Get the orthographic projection area of ​​the cargo box in the current stacking layer;

[0013] The wasted stacking space volume is obtained by calculating the product of the orthographic projection area and the height of the stacked cargo boxes below the current stacking layer, and then subtracting the volume of the cargo boxes of the adjacent stacking layer below the current stacking layer.

[0014] In a possible embodiment, the step of calling the skyline model based on the stacking module according to the carriage model, matching the unstacked cargo box and the stacking module with the stackable space in the carriage of different carriage models, and generating a loading combination includes:

[0015] Obtain the boundary contour of the cargo stacked in each carriage model;

[0016] Matching stackable stacking modules and / or unstacked containers according to the boundary contour lines to generate at least one stacking combination;

[0017] Calculating the loading rate of each stacking combination relative to each carriage model respectively;

[0018] The stacking combination and carriage with the largest loading rate are selected to generate a loading combination.

[0019] In a possible embodiment, the step of respectively calculating the loading rate of each stacking combination relative to each carriage model includes:

[0020] Calculate the volume of all cargo boxes in each feasible stacking combination in the front compartment model;

[0021] Calculating the ratio of the volume of all cargo boxes in the stacking combination to the volume of the current carriage to obtain the loading rate of the stacking combination relative to the current carriage;

[0022] The stacking combination with the largest loading rate is allocated to the current carriage model for loading.

[0023] In a possible embodiment, the product constraints include: heavy does not crush light, large does not crush small and self-overlapping constraints, and the priority of the product constraints is: heavy does not crush light takes precedence over large does not crush small, and large does not crush small takes precedence over self-overlapping constraints.

[0024] In a possible embodiment, after generating the loading combination, the method further includes:

[0025] Output the result of the loading combination, the result of the loading combination includes: train number, product loading details, a three-dimensional loading static diagram in the carriage, and a three-dimensional loading dynamic diagram in the carriage.

[0026] In a second aspect, the present application also provides a three-dimensional packaging device for mixing multiple products, including:

[0027] A reading unit, used to read data information and perform preprocessing, wherein the data information includes: product constraints, cargo box dimensions and carriage model;

[0028] A stacking unit, configured to call a stacking model according to the data information to stack product boxes layer by layer to generate a plurality of stacking modules;

[0029] The loading unit is used to call the skyline model according to the carriage model based on the stacking module, match the unstacked cargo box and the stacking module with the stackable space in the carriage of different carriage models, and generate a loading combination.

[0030] In a third aspect, an embodiment of the present application further provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0031] The memory stores computer-executable instructions;

[0032] The processor executes the computer-executable instructions stored in the memory to implement the method in any possible implementation manner of the first aspect.

[0033] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer execution instructions, and when the computer execution instructions are executed by a processor, they are used to implement the method in any possible implementation of the above-mentioned first aspect.

[0034] The present application provides a three-dimensional packing method, device, equipment and storage medium for mixed multiple products, wherein the three-dimensional packing method for mixed multiple products includes: reading data information and preprocessing, the data information includes: product constraints, cargo box size and car model; calling the stacking model according to the data information to stack product cargo boxes layer by layer to generate stacking modules with a number of stacks; calling the skyline model according to the car model based on the stacking module, matching the unstacked cargo boxes and the stacking modules with the stackable space in the car of different car models, and generating a loading combination. The present application adopts the iterative use of the stacking model and the skyline model. After generating the stacking module in the vertical direction of the three-dimensional space based on the stacking model, the skyline model is called to dynamically search for the stackable space in the two-dimensional space, and finally the loading combination with the maximum loading rate is generated. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0036] Figure 1 This is a schematic diagram of an application scenario of a three-dimensional packing method for multiple mixed products in this application;

[0037] Figure 2 A flow chart of a three-dimensional packing method for mixing multiple products provided in an embodiment of the present application;

[0038] Figure 3 A schematic diagram of a stacking module provided in an embodiment of the present application;

[0039] Figure 4 A schematic diagram of obtaining a boundary contour line provided in an embodiment of the present application;

[0040] Figure 5 A schematic diagram of the unit structure of a three-dimensional packaging device for mixing multiple products provided in an embodiment of the present application;

[0041] Figure 6 A hardware structure diagram of an electronic device provided in an embodiment of the present application.

[0042] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0043] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0044] In order to clearly describe the technical solutions of the embodiments of the present application, some terms and technologies involved in the embodiments of the present application are briefly introduced below:

[0045] Product constraints: refers to the restrictions on the packaging and placement of auto parts to avoid damage to the parts during the process of packing and stacking them in the carriage for transportation.

[0046] Box size: refers to the length, width and height of the box used to pack certain parts.

[0047] Carriage model: refers to the number set for each type of car based on the size and shape of the space in the car, in order to facilitate the allocation of loaded products.

[0048] Stacking module: refers to a stack of cargo boxes stacked layer by layer in a vertical space, with one cargo box stacked on each stacking layer in the stacking module.

[0049] Unstacked Cartons: refers to independent cartons that cannot be stacked because they do not meet the stacking model input conditions.

[0050] Stacking combination: refers to the combination of stacking modules and stacking modules based on two-dimensional space for interlaced stacking, or the combination of stacking modules and unstacked cartons, or the combination of unstacked cartons and unstacked cartons.

[0051] Heavy items should not be placed under light items: This means that heavier items should be placed under lighter items.

[0052] The big shall not crush the small: it means that overhanging stacking is allowed, but the overhanging length in each direction when the product cartons are stacked shall not exceed 1 times the length of the product cartons of the next stacking layer.

[0053] Self-stacking constraint: refers to whether similar products are allowed to be stacked together due to product attribute restrictions.

[0054] As the grid complexity of the automotive after-sales business continues to increase, the allocation, distribution and delivery of after-sales parts have become key links in the entire automotive supply chain. How to more efficiently, timely and accurately plan the path, pre-scheduling and vehicle loading of after-sales loading has become one of the key issues in reducing costs and increasing efficiency of after-sales parts. This application mainly focuses on the allocation business. In order to achieve the long-term goal of reducing the transportation costs of after-sales parts, algorithm technology is used to increase the loading rate of after-sales parts, reduce the number of vehicle usage, reduce vehicle usage costs, and improve overall delivery efficiency. The business characteristics of the allocation business include:

[0055] (1) Wide variety of goods

[0056] There are many types of goods and many sizes of goods, which is an extremely complex scenario with box types. There are hundreds of thousands of types of goods, and the sizes of goods vary. The smallest goods are 1mm*1mm*1mm, and the largest goods are 1000mm*1000mm*1000mm.

[0057] (2) Wide range of product categories

[0058] There are many categories of goods, and different categories of goods have different constraints, which is a very complex scenario. Including but not limited to gearboxes, glass, batteries, oils, radiators, seats, bumpers, four doors and two covers, single-throw parts, side panels, four-sided panels, and whole pallet & box parts. Different accessory number categories correspond to different business rules.

[0059] (3) Many business rules

[0060] The constraints are mainly divided into heavy items not pressing light items, whether self-stacking is allowed, large items not pressing small items, orientation constraints, placement constraints and pallet usage rules.

[0061] (4) Large scale of the problem

[0062] The scale of the problems in the transfer business is a large-scale three-dimensional packing problem.

[0063] The transfer business in the existing technology is mainly based on the automatic box closing of the product packing system, and the loading business personnel load the product boxes according to their personal loading experience, which leads to problems such as failure to more comprehensively consider the constraints of the products, the matching between different models and boxes, and failure to dynamically adjust the packing strategy in real time. Especially for the loading scenarios of multiple types of products and multiple models, the existence of the above problems will greatly reduce the loading efficiency and increase the vehicle cost of product transportation.

[0064] like Figure 1 , which is a schematic diagram of an application scenario provided by an embodiment of the present application. In the schematic diagram of the application scenario, a terminal device 101 and a server 102 are included. The terminal device 101 and the server 102 communicate with each other through a communication network.

[0065] The terminal device 101 is an electronic device used by the target object, and the electronic device may be a personal computer, a mobile phone, a tablet computer, a notebook, an e-book reader, a vehicle-mounted terminal, etc. In addition, a client for generating a loading combination plan may be installed on the terminal device 101, and the client may be a software (for example, an APP, a browser, etc.), or a web page, a small program, etc. The target object may use the client for generating a loading combination plan through the terminal device 101 to input product data information and receive the output loading combination result.

[0066] The server 102 may be an independent physical server or an edge device 102 in the field of cloud computing. It may also be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud storage, cloud functions, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (English name: Content Delivery Network, abbreviated as CDN), as well as big data and artificial intelligence platforms.

[0067] There is no restriction on the number of the terminal devices 101 and / or servers 102 .

[0068] It should be noted that the three-dimensional packing method for mixed multiple products in the embodiment of the present application can be executed by the terminal device 101 or the server 102 alone, or can be executed jointly by the terminal device 101 and the server 102. For example, when executed jointly by the terminal device 101 and the server 102, the server 102 can receive data information including product constraints, cargo box dimensions, and car model input by the target object; then, according to the data information, the stacking model is called to stack the goods layer by layer to generate a number of stacking modules; then, based on the stacking module, the skyline model is called according to the car model, and the unstacked cargo box and the stacking module are respectively matched with the stackable space in the car of different car models to generate a loading combination. The terminal device 102 can receive the loading combination and present the result of the loading combination to the target object, so that the target object performs actual packing operations according to the position of each product and its cargo box.

[0069] Combined with the above application scenarios, Figure 2 This is a flow chart of a three-dimensional packing method for multiple mixed products provided in an embodiment of the present application. Figure 2 As shown, the three-dimensional packing method for multi-product mixture is applied to Figure 1 The server 102 shown, the method specifically includes:

[0070] S210: Reading data information and preprocessing the data information, wherein the data information includes: product constraints, cargo box dimensions and vehicle compartment model.

[0071] In this embodiment, the preprocessing of data information mainly refers to the loading personnel inputting information such as box number details, parts BOM, parts category, vehicle model, pallet, constraint parameters, etc. into the system. After the stacking model and skyline model of this application read the input data information, they check the input basic data information and then convert the data into the data form restricted by the model. Among them, the data check may include but is not limited to screening the validity of the data information, screening the missing of the data information, etc. The data information includes but is not limited to the following data: the car model and the length, width, and height dimension values ​​of the car corresponding to each car model; the length, width, and height values ​​of the parts BOM; the attributes of the parts category, and the product constraints are recorded according to the part category; the length, width, and height values ​​of each box number in the box number details; the configuration items and parameter items of the constraints.

[0072] In a feasible embodiment, the product constraints include: heavy not pressing light, large not pressing small and self-stacking constraints, and the priority of the product constraints is: heavy not pressing light takes precedence over large not pressing small, and large not pressing small takes precedence over self-stacking constraints. By giving priority to the constraint of heavy not pressing light, the weight distribution of the cargo boxes in the stacking module can be balanced to avoid vehicle instability caused by center offset. Further considering the constraint of large not pressing small can increase the stability of the stacking module and reduce the waste of stacking volume.

[0073] S220: calling a stacking model according to the data information to stack product boxes layer by layer to generate a plurality of stacking modules;

[0074] The algorithm of the stacking model described in this embodiment is as follows: each time a product box is tried to be placed in the stacking layer, until there is not enough space left between the top stacking layer and the top of the carriage to place any other product boxes, at which time a complete stacking module is generated. At this time, the product constraints in the data information have been considered, so all product boxes in the generated stacking module meet the restrictions of the product constraints, ensuring the rationality and stability of the placement of the stacked goods layer by layer in the vertical space.

[0075] In a preferred embodiment, the specific steps of calling the stacking model according to the data information to stack product boxes layer by layer to generate a plurality of stacking modules include:

[0076] S221: Calculate the wasted stacking space volume of each cargo box in the current stacking layer according to the product constraint conditions, cargo box size and vehicle compartment model, wherein the wasted stacking space volume includes: the volume of unusable space generated between two cargo boxes in adjacent stacking layers in the vertical space and / or between the cargo box and the vehicle compartment;

[0077] S222: generating a stacking module according to information of cargo boxes placed on all stacking layers, wherein cargo boxes with the smallest wasted volume of the stacking space are placed on all stacking layers in the stacking module.

[0078] S223: Based on the stacking module, the skyline model is called according to the car model, and the unstacked cargo boxes and the stacking modules are matched with the stackable spaces in the cars of different car models to generate a loading combination.

[0079] It should be noted that the current stacking layer starts from the first layer at the bottom of the carriage and ends when no more cargo boxes can be placed on the top of the carriage. When the current stacking layer is the first layer, the stacking space waste volume of all cargo boxes only includes: the volume of the unusable space between the cargo box and the carriage. If the height of the cargo box is so high that the space between it and the top of the carriage cannot be stacked with other cargo boxes, at this time, the stacking space waste volume of the cargo box is equal to the volume of the unusable space between the cargo box and the carriage.

[0080] In the process of generating stacking modules using the stacking model, only the stacking strategy of the cargo box in the vertical space needs to meet the constraints of the products in each cargo box and ensure that the stacking space waste volume of all cargo boxes constituting the stacking module is minimized. The minimum stacking space waste volume means the optimal stacking plan and the highest loading efficiency.

[0081] In a preferred embodiment, the step of calculating the wasted volume of stacking space of each cargo box in the current stacking layer includes:

[0082] Get the orthographic projection area of ​​the cargo box in the current stacking layer;

[0083] The wasted stacking space volume is obtained by calculating the product of the orthographic projection area and the height of the cargo box below the current stacking layer, and then subtracting the volume of the cargo box of the adjacent stacking layer below the current stacking layer.

[0084] See attached Figure 3 The schematic diagram of the stacked modules is shown in Figure 3 The diagram shows a partial structure of a stacking module. The calculation process of the wasted volume of the stacking space is explained by taking the stacking layer N in the stacking module as an example, which specifically includes:

[0085] First, if Figure 3 The stacking space wasted volume of the cargo box of the current stacking layer N shown includes three parts: V1, V2 and V3. In practice, the stacking space wasted volume of the current stacking layer N may only include V1 or V2 or V3 or both V1 and V2. That is, there may be a case where the volume of V3 is 0, at which time the current stacking layer is stacked just in place on the top of the carriage; there may also be a case where the volume of V1 or V2 is 0, at which time, when stacking layer N is stacked according to the constraints of the cargo box, one side is aligned with the stacking layer below, and the other side bulges out; or there is a case where the volume value V1=V2=0, in addition, the stacking surface size of the cargo box of stacking layer N is exactly the same as that of the stacking layer below.

[0086] Then, the orthographic projection area of ​​the current stacking layer N cargo box is calculated. The projection area can be understood as the area of ​​the bottom stacking surface of the stacking layer N cargo box protruding from the stacking layer below (such as stacking layer 1 to stacking layer N-1).

[0087] Secondly, the product of the orthographic projection area and the height of the stacked cargo boxes below the current stacking layer N is calculated.

[0088] Finally, the volume of all stacked cargo boxes below the current stacking layer N is subtracted from the above product to obtain the wasted stacking space volume of the cargo boxes stacked in the current stacking layer N.

[0089] In this embodiment, through the application of the stacking model, each product box is tried to be stacked and the wasted volume of the stacking space is calculated. Finally, each stacking layer selects the product box with the smallest wasted volume of the stacking space for stacking. That is, the final optimization goal is measured by the wasted volume of the stacking space. When the wasted volume of the stacking space is minimized, the total number of stacking modules obtained in the end is the smallest, and the total stacking area occupied in the two-dimensional plane is the smallest, which is conducive to improving the final carriage loading rate.

[0090] S230: Based on the stacking module, the skyline model is called according to the car model, and the unstacked cargo boxes and the stacking modules are matched with the stackable spaces in the cars of different car models to generate a loading combination.

[0091] The algorithm idea of ​​the skyline model described in this embodiment is: the current state of the carriage is described by the skyline, the boundary contour of the currently stacked product boxes in the carriage is obtained, and the space for further stacking of product boxes is selected based on the boundary contour, and the stacking modules and unstacked boxes of all generated stacks are matched cyclically until all product boxes are loaded or there is no more available space in the carriage to stack any product boxes. At this time, after screening out all feasible combinations, they are matched with the carriage model to obtain the optimal loading combination. Each carriage of the optimization target can achieve the optimal loading rate.

[0092] In a preferred embodiment, the step of calling the skyline model based on the stacking module according to the carriage model, matching the unstacked cargo box and the stacking module with the stackable space in the carriage of different carriage models, and generating a loading combination specifically includes:

[0093] S231: Obtaining the boundary contour lines of the product boxes stacked in the carriage of each carriage model;

[0094] S232: Matching stackable stacking modules and / or unstacked containers according to the boundary contour line to generate at least one stacking combination;

[0095] S233: Calculating the loading rate of each stacking combination relative to each carriage model respectively;

[0096] S234: Select the stacking combination and carriage with the maximum loading rate to generate a loading combination.

[0097] In a preferred embodiment, the step of respectively calculating the loading rate of each stacking combination relative to each carriage model comprises:

[0098] Calculate the volume of all cargo boxes in each feasible stacking combination in the front compartment model;

[0099] Calculating the ratio of the volume of all cargo boxes in the stacking combination to the volume of the current carriage to obtain the loading rate of the stacking combination relative to the current carriage;

[0100] The stacking combination with the largest loading rate is allocated to the current carriage model for loading.

[0101] See attached Figure 4 The schematic diagram of obtaining the boundary contour line is shown in Figure 4 The illustration shows the boundary contour lines of a certain carriage model obtained by using the skyline model. Figure 4 Take the following as an example to illustrate the specific implementation process of generating a loading combination:

[0102] First, obtain the boundary contours of the product boxes stacked in the carriage. Figure 4 In the skyline model shown, the stacked containers are composed of five stacking modules. Specifically, the boundary contour line 12 is the boundary contour line of the first stacking module, the boundary contour line 23 is the boundary contour line of the second stacking module, the boundary contour line 34 is the boundary contour line of the third stacking module, the boundary contour line 45 is the boundary contour line of the fourth stacking module, and the boundary contour line 56 is the boundary contour line of the fifth stacking module. The boundary contour line of all stacked product containers in the carriage is the area surrounded by the dotted lines 12345, which is the stackable space.

[0103] Then, the other stacking modules and other unstacked cargo boxes that are not stacked in the carriage are tried in turn to see whether they can be stacked in the above-mentioned opposite spaces, and a feasible stacking combination is screened out.

[0104] Finally, calculate the loading rates of all feasible stacking combinations relative to all optional carriage models, select the solution with the largest loading rate, and obtain the optimal loading combination.

[0105] This embodiment uses the algorithm of the skyline model to consider the selection of stacking modules and unstacked containers to be stacked and their stacking positions in the carriage based on the boundary contours of the stacked product containers. Figure 4 The stacking strategy of the space can be used in the middle dotted box. By comparing the loading rates of various stacking combinations, the stacking combination and car matching solution with the highest loading rate can be selected.

[0106] In another embodiment, the three-dimensional packing method for multi-product mixing described in the present application further includes:

[0107] After the loading combination is generated, the result of the loading combination is output, and the result of the loading combination includes: train number, product loading details, three-dimensional loading static diagram in the carriage, and three-dimensional loading dynamic diagram in the carriage. Through the output result, the loaders can accurately select product boxes and stack the product boxes in the optimal position according to the output result.

[0108] Figure 5 This is a schematic diagram of the unit structure of a three-dimensional packaging device for multiple products provided in an embodiment of the present application. The device can be in the form of software and / or hardware, such as Figure 5 As shown, a three-dimensional packing device 500 for mixing multiple products includes: a reading unit 501, a stacking unit 502 and a loading unit 503.

[0109] A reading unit 501 is configured to read data information and perform preprocessing, wherein the data information includes: product constraints, cargo box dimensions, and vehicle compartment model;

[0110] A stacking unit 502, configured to call a stacking model according to the data information to stack product boxes layer by layer to generate a plurality of stacking modules;

[0111] The loading unit 503 is used to call the skyline model according to the car model based on the stacking module, match the unstacked cargo box and the stacking module with the stackable space in the car of different car models, and generate a loading combination.

[0112] The three-dimensional packing device for mixing multiple products provided in the embodiment of the present application has the same implementation principle and technical effects as those in the aforementioned three-dimensional packing method embodiment for mixing multiple products. For the sake of brief description, for matters not mentioned in the device embodiment, reference may be made to the corresponding contents in the aforementioned three-dimensional packing method embodiment for mixing multiple products.

[0113] In some possible implementations, the three-dimensional packaging device for mixed multiple products according to the present application may include at least a processor and a memory. The memory stores program code, and when the program code is executed by the processor, the processor executes the steps of the three-dimensional packaging method for mixed multiple products according to various exemplary embodiments of the present application described in this specification. For example, the processor may execute the following steps: Figure 2 and Figure 3 Follow the steps shown in .

[0114] Based on the same inventive concept, an electronic device is also provided in the embodiment of the present application, and the electronic device can realize the functions of the aforementioned three-dimensional packing method and device for mixed multiple products, referring to Figure 6 , the electronic device comprises:

[0115] At least one processor 601, and a memory 602 connected to the at least one processor 601. The specific connection medium between the processor 601 and the memory 602 is not limited in the embodiment of the present application. Figure 6 In the example, the processor 601 and the memory 602 are connected via a bus 600. The bus 600 is Figure 6The connection between other components is shown by bold lines, and is not intended to be limiting. The bus 600 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 Only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus. Alternatively, the processor 601 can also be called a controller, and there is no limitation on the name.

[0116] In the embodiment of the present application, the memory 602 stores instructions that can be executed by at least one processor 601. The at least one processor 601 can execute the three-dimensional packing method for mixed multiple products discussed above by executing the instructions stored in the memory 602. The processor 601 can implement Figure 5 The functions of each module in the device shown.

[0117] Among them, the processor 601 is the control center of the device, and can use various interfaces and lines to connect the various parts of the entire control device. By running or executing instructions stored in the memory 602 and calling the data stored in the memory 602, the various functions of the device and processing data, the device can be monitored as a whole.

[0118] In one possible design, the processor 601 may include one or more processing units, and the processor 601 may integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the modem processor may not be integrated into the processor 601. In some embodiments, the processor 601 and the memory 602 may be implemented on the same chip, and in some embodiments, they may also be implemented separately on separate chips.

[0119] Processor 601 can be a general-purpose processor, such as a central processing unit (CPU), a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, and can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor can be a microprocessor or any conventional processor, etc. The steps of the three-dimensional packing method for mixing multiple products disclosed in the embodiments of the present application can be directly embodied as a hardware processor, or can be executed by a combination of hardware and software modules in the processor.

[0120] The memory 602 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The memory 602 may include at least one type of storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory, a random access memory (Random Access Memory, RAM), a static random access memory (Static Random Access Memory, SRAM), a programmable read-only memory (Programmable Read Only Memory, PROM), a read-only memory (Read Only Memory, ROM), an electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), a magnetic memory, a disk, an optical disk, etc. The memory 602 is any other medium that can be used to carry or store a desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory 602 in the embodiment of the present application can also be a circuit or any other device that can realize a storage function, for storing program instructions and / or data.

[0121] By programming the processor 601, the code corresponding to the three-dimensional packing method for multiple products introduced in the above embodiment can be fixed into the chip, so that the chip can execute the code when running. Figure 2 The steps of the three-dimensional packing method for multiple mixed products in the embodiment shown are as follows: How to design and program the processor 601 is a technology well known to those skilled in the art and will not be described in detail here.

[0122] Based on the same inventive concept, an embodiment of the present application further provides a storage medium storing computer instructions. When the computer instructions are executed on a computer, the computer executes the three-dimensional packing method for mixed multiple products as described above.

[0123] In some possible embodiments, various aspects of the three-dimensional packing method for mixed multiple products provided in the present application can also be implemented in the form of a program product, which includes a program code. When the program product is run on an apparatus, the program code is used to enable the control device to execute the steps of the three-dimensional packing method for mixed multiple products according to various exemplary embodiments of the present application described above in this specification.

[0124] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0125] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0126] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0127] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0128] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A three-dimensional packing method for mixed multiple products, characterized in that: The method comprises: Reading data information and preprocessing the data information, the data information including: product constraints, cargo box dimensions and carriage model; Calling a stacking model according to the data information to stack product boxes layer by layer to generate a stacking module with a certain number of stacks; Based on the stacking module, the skyline model is called according to the car model, and the unstacked cargo boxes and the stacking modules are matched with the stackable spaces in the cars of different car models to generate a loading combination.

2. The method according to claim 1, characterized in that The step of calling the stacking model according to the data information to stack product boxes layer by layer to generate a plurality of stacking modules comprises: Calculate the wasted stacking space volume of each cargo box in the current stacking layer according to product constraints, cargo box size and car model, where the wasted stacking space volume includes: the volume of unusable space generated between two cargo boxes in adjacent stacking layers in the vertical space and / or between the cargo box and the car; A stacking module is generated according to the information of the cargo boxes placed on all the stacking layers, and cargo boxes with the smallest wasted volume of the stacking space are placed on all the stacking layers in the stacking module.

3. The method according to claim 2, characterized in that The step of calculating the wasted volume of stacking space of each cargo box in the current stacking layer includes: Get the orthographic projection area of ​​the current stacking layer cargo box; The wasted stacking space volume is obtained by calculating the product of the orthographic projection area and the height of the stacked cargo boxes below the current stacking layer, and then subtracting the volume of the cargo boxes of the adjacent stacking layer below the current stacking layer.

4. The method according to claim 1, characterized in that: The calling of the skyline model based on the stacking module according to the carriage model, matching the unstacked cargo box and the stacking module with the stackable space in the carriage of different carriage models respectively, and generating a loading combination, includes: Obtain the boundary contour of the cargo stacked in each carriage model; Matching stackable stacking modules and / or unstacked containers according to the boundary contour lines to generate at least one stacking combination; Calculating the loading rate of each stacking combination relative to each carriage model respectively; The stacking combination and carriage with the largest loading rate are selected to generate a loading combination.

5. The method according to claim 4, characterized in that The step of respectively calculating the loading rate of each stacking combination relative to each carriage model comprises: Calculate the volume of all cargo boxes in each feasible stacking combination in the front compartment model; Calculating the ratio of the volume of all cargo boxes in the stacking combination to the volume of the current carriage to obtain the loading rate of the stacking combination relative to the current carriage; The stacking combination with the largest loading rate is allocated to the current carriage model for loading.

6. The method according to claim 1, characterized in that The product constraints include: heavy does not crush light, large does not crush small and self-overlapping constraints, and the priority of the product constraints is: heavy does not crush light takes precedence over large does not crush small, and large does not crush small takes precedence over self-overlapping constraints.

7. The method according to claim 1, characterized in that The generating of the loading combination further includes: Output the result of the loading combination, the result of the loading combination includes: train number, product loading details, a three-dimensional loading static diagram in the carriage, and a three-dimensional loading dynamic diagram in the carriage.

8. A three-dimensional packaging device for mixed products, characterized in that: include: A reading unit, used to read data information and perform preprocessing, wherein the data information includes: product constraints, cargo box dimensions and carriage model; A stacking unit, configured to call a stacking model according to the data information to stack product boxes layer by layer to generate a plurality of stacking modules; The loading unit is used to call the skyline model according to the carriage model based on the stacking module, match the unstacked cargo box and the stacking module with the stackable space in the carriage of different carriage models, and generate a loading combination.

9. An electronic device, comprising: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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