Automatic container separation method and system
Through the automatic container binning method, a packing solution is generated using a three-dimensional space algorithm, which solves the problem of inefficiency in traditional loading methods, and realizes efficient and accurate cargo binning, reducing labor costs.
Patent Information
- Application Number
- CN202411586503.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-08
- Publication Date
- 2025-03-04
AI Technical Summary
Traditional container loading methods are inefficient, have high labor costs, and cannot quickly make container decisions when handling unfamiliar cargo or containers, resulting in excessive time consumption.
The automatic container binning method is adopted to obtain the basic information of goods by defining the classification and sorting of goods, and a three-dimensional spatial algorithm is used to generate a packing scheme, reducing manual intervention and improving the efficiency of boxing.
It has achieved the reduction of manual intervention, improved binning efficiency, ensured the accuracy and reliability of binning schemes, and supported automatic binning of various cargo types and transportation needs.
Smart Images
Figure CN119558745A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to a container sorting method, and in particular to an automatic container sorting method and system. Background Art
[0002] With the continuous development of global trade, sea container transportation has become one of the main modes of cargo transportation. However, the traditional container loading method has problems such as low efficiency and high labor costs. There is an urgent need for an automated container sorting system to improve loading efficiency and reduce costs. At this stage, the relevant personnel are handling the preparation and packing based on past experience. If the attributes and specifications of the goods in the order, the capacity and loadable tonnage of the container are familiar, the processing will be faster. However, when encountering unfamiliar goods and containers, it is impossible to make quick packing and placement decisions based on experience, which will cause more time consumption.
[0003] Furthermore, when there are many types or quantities of goods, it takes a lot of time to manually handle the sorting and packing of goods. In addition, each employee has different experience and processing methods, and the results of sorting will also vary greatly. At the same time, it is impossible to quickly provide the company with an automatic packing solution. How to save time for packing and preparing goods and promote the company's operational efficiency is an issue that needs to be urgently addressed. Summary of the invention
[0004] In view of the low efficiency and high labor cost of the current traditional container loading method, the present invention provides a container automatic box separation method, which can reduce manual intervention and improve the box separation efficiency.
[0005] To achieve the above object, the embodiments of the present invention adopt the following technical solutions:
[0006] A method for automatically sorting containers comprises the following steps:
[0007] Define the classification and sorting of goods and obtain basic information about the goods;
[0008] Classify the goods according to the defined categories and sort the classified goods;
[0009] Obtain basic information of containers, and allocate containers to classified and sorted goods based on the basic information of containers;
[0010] Generate packing solutions using a three-dimensional space algorithm.
[0011] According to one aspect of the present invention, the classification of the cargo includes at least: conventional cargo, refrigerated cargo, dangerous goods, and live cargo.
[0012] According to one aspect of the present invention, the basic information of the cargo includes at least size and weight.
[0013] According to one aspect of the present invention, the basic information of the container includes at least: quantity, length, width, height, and load-bearing capacity.
[0014] According to one aspect of the present invention, allocating containers to classified and sequenced goods includes: allocating goods classified into the same category to the same container, and loading the sequenced goods into the container in sequence according to the established sequence until the container is full, until all containers are full or all goods are loaded.
[0015] According to one aspect of the present invention, the generating of a packing solution using a three-dimensional space algorithm comprises:
[0016] Get all the matching goods for each container;
[0017] Get basic information of containers and all cargoes;
[0018] Based on the three-dimensional space algorithm, a packing plan is generated for each container.
[0019] According to one aspect of the present invention, the method of generating a packing plan using a three-dimensional space algorithm further includes: evaluating the safety and feasibility of the packing plan, and optimizing and adjusting packing plans with lower safety or lower feasibility.
[0020] According to one aspect of the present invention, the automatic container sorting method further includes: optimizing the automatic container sorting method using a deep learning algorithm.
[0021] According to one aspect of the present invention, the method of optimizing the automatic container sorting method using a deep learning algorithm includes:
[0022] Obtain historical data of completed automatic container sorting;
[0023] Clean and organize the acquired historical data to form a data set to be processed;
[0024] Use deep learning algorithms to process data sets, realize automatic distribution of goods, and obtain packing solutions;
[0025] The packing solution is further optimized based on the deep learning algorithm and the final packing solution is output.
[0026] A container automatic sorting system, comprising:
[0027] Data collection module, used to obtain basic information of goods and containers;
[0028] The data processing module is used to define the classification and sorting of goods, classify the goods according to the defined classification, and sort the classified goods;
[0029] The data calculation module is used to allocate containers for classified and sorted goods and generate packing plans using three-dimensional space algorithms.
[0030] Advantages of the implementation of the present invention: The automatic container sorting method described in the present invention includes the following steps: defining the classification and sorting of goods, and obtaining basic information of goods; classifying goods according to the defined classification, and sorting the classified goods; obtaining basic information of containers, and allocating containers to the classified and sorted goods based on the basic information of containers; and generating packing plans using three-dimensional space algorithms. By defining the classification and sorting of goods, batch acquisition, processing, and optimization of cargo information can be achieved, reducing manual intervention; based on big data and artificial intelligence technology, the accuracy and reliability of the sorting plan are ensured, and automatic sorting of various cargo types, specifications, and transportation requirements is supported to meet the actual needs of different customers; it also includes an automatic container sorting system, which is modularly designed for easy integration and convenient connection to other logistics management systems to achieve data sharing and exchange. BRIEF DESCRIPTION OF THE DRAWINGS
[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0032] Figure 1 This is a flow chart of a method for automatically separating containers according to Embodiment 1 of the present invention;
[0033] Figure 2 This is a flow chart of a method for automatically sorting containers according to the second embodiment of the present invention;
[0034] Figure 3 This is a structural diagram of an automatic container sorting system according to Embodiment 3 of the present invention;
[0035] Figure 4 This is a structural diagram of an automatic container sorting device described in Example 4 of the present invention. DETAILED DESCRIPTION
[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0037] The terms "including" and "having" and any variations thereof in the embodiments of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product or equipment comprising a series of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products or equipment.
[0038] The naming or numbering of the steps in the embodiments of the present invention does not mean that the steps in the method flow must be executed in the time / logical sequence indicated by the naming or numbering. The execution order of the named or numbered process steps can be changed according to the technical purpose to be achieved, as long as the same or similar technical effects can be achieved.
[0039] Reference to an "embodiment" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.
[0040] Embodiment 1
[0041] like Figure 1 As shown, a method for automatically sorting containers comprises the following steps:
[0042] Step S1: define the classification and sorting of goods and obtain basic information of goods;
[0043] Among them, the classification of goods includes conventional goods (such as household appliances, shoes and clothing, daily necessities, etc.), refrigerated goods (such as meat, fish, fruits and vegetables, etc.), dangerous goods (such as flammable, explosive, and toxic goods), live goods (such as animals and plants that require special care and transportation conditions), etc.
[0044] In the actual transportation process, there are also contaminated goods (goods that may cause pollution during transportation but do not cause danger), liquid goods (such as oil, etc.), bulk goods (such as grain, ore, coal, etc. transported in bulk), etc.
[0045] Defining the order of goods means prioritizing them according to their categories. Goods with high priority will be given priority when they are divided into containers. When goods of the same type are divided into containers, the priority is determined by time and / or size, and goods of the same type are divided into the same container as much as possible.
[0046] The basic information of the goods includes at least the size and weight. The size of the goods, namely the length, width and height of the goods, determines the size of the container required for packing the goods. The weight of the goods is used to calculate whether the goods loaded in the container exceed the weight limit. In addition, the basic information of the goods also includes fragility, which is used to make requirements on the loading position of the goods; the shelf life of the goods, for which priority can be given to packing of goods with a near shelf life; the properties of the goods, such as regular shape, liquid, solid powder, etc., are used to determine whether the goods need to be packed separately.
[0047] In this embodiment, the cargo sorting method includes:
[0048] 1. Prioritize the cargo according to its volume. The larger the cargo, the higher its priority. It will be given priority when it is divided into boxes and packed. If the cargo has the same volume, the length, width and height of the cargo will be further considered. The cargo whose length, width and height meet the dimensions of most containers will be given priority.
[0049] 2. Based on sorting method 1, the volume is divided into interval volumes. For goods in the same interval volume, the priority is sorted according to the weight of the goods. The heavier the weight, the higher the priority, and the higher the priority is when sorting and packing;
[0050] 3. Based on sorting method 2, the shelf life of the goods and / or the scheduled date of the transportation task are taken into comprehensive consideration. Goods with a near shelf life and / or scheduled date of transportation task will be given priority for packing;
[0051] 4. Based on sorting method 3, the properties of the goods are taken into consideration. For example, dangerous goods are packed first, powders, liquids and other goods have a higher priority than general goods, and fragile goods among general goods have a higher priority for packing.
[0052] Step S2: Classify the goods according to the defined categories and sort the classified goods;
[0053] The goods type is defined in step S1, and all goods are classified into the defined goods type according to their basic information, and the classified goods are sorted according to the established priority sorting rules.
[0054] Step S3: obtaining basic information of the container, and allocating the container to the classified and sorted goods based on the basic information of the container;
[0055] The basic information of the container includes the number, length, width and height of the container, wherein the length, width and height in this embodiment refer to the length, width and height inside the container, which can be used to calculate the volume of the container.
[0056] Goods classified into the same category are assigned to the same container, and the sorted goods are loaded into the container in sequence according to the established sequence until it is full, until all containers are full or all goods are loaded.
[0057] A full container means that the weight of all the goods allocated to the container reaches the upper limit of the container's load-bearing capacity or the volume of all the goods allocated to the container is greater than the capacity of the container.
[0058] Step S4: Generate a packing solution using a three-dimensional space algorithm.
[0059] Step S41: Obtain all goods matched by each container;
[0060] In step S3, all goods are assigned to containers after classification and sorting, that is, the goods are matched with the containers, and all goods matching each container are obtained, and the container and its matching goods are taken as analysis objects.
[0061] Step S42: Obtain basic information of the container and basic information of all goods;
[0062] Obtain basic information of the container, including at least the length, width, height and load-bearing capacity of the container; basic information of the cargo includes at least the size and weight; and pre-process the acquired information, such as unifying the measurement units of all containers and cargoes.
[0063] Step S43: generating a packing plan for each container based on a three-dimensional space algorithm;
[0064] A packing plan is generated for each container using a three-dimensional space algorithm. The three-dimensional space algorithms available include a greedy algorithm, a simulated annealing algorithm, a genetic algorithm, etc. Based on the three-dimensional space algorithm, the analysis object in step S41 is calculated to obtain a packing plan.
[0065] In this embodiment, a box packing greedy algorithm is used, and the specific steps of the algorithm are as follows:
[0066] Step S431: obtaining container data and cargo data for the greedy packing algorithm and performing preprocessing;
[0067] The basic information of the container and the basic information of all goods obtained in step S42 are obtained, the basic information of the container is converted into a large set of containers to be loaded, and the basic information of all goods is represented by a list of goods to be loaded.
[0068] The preprocessing is to use a sorting algorithm to sort the containers and goods in positive order. The positive order of the goods in the sorting is the goods sorting defined in step S1, and the sorting of the containers is the sorting corresponding to the goods sorting, that is, the containers are sorted according to the types of goods that can be loaded in the containers. The containers that can load goods with higher priorities have higher priorities. When the priorities of loading goods are the same, the containers that can load more goods have higher priorities.
[0069] Step S432: traverse the pre-processed container data and cargo data, and pack the cargo according to the greedy algorithm;
[0070] Specifically, the cargo to be loaded is traversed, and the cargo is packed according to the priority. It is determined whether the cargo exceeds the maximum volume of the container. If not, the cargo is loaded into the container and bound to the container. Then the next cargo is loaded until the cargo cannot be loaded into the container. That is, when the current cargo volume exceeds the remaining volume of the container, the next container is switched for loading.
[0071] If all the goods have been loaded, the packing is deemed to be completed. If the goods have not been loaded but all containers have been put into use, the first round of packing is deemed to be completed.
[0072] After the first round of packing is completed, containers with remaining volume and unloaded goods are obtained by traversing, and the goods that have been loaded are excluded. The remaining unloaded goods are packed again until all the goods are loaded or the container can no longer be loaded with goods.
[0073] The algorithm code for reference is as follows:
[0074]
[0075]
[0076] Step S44: Evaluate the safety and feasibility of the packing solutions, and optimize and adjust the packing solutions with lower safety or lower feasibility.
[0077] In practical applications, relatively optimal packing solutions can be obtained based on three-dimensional space algorithms. However, it is difficult for these solutions to take the loaded goods into comprehensive consideration. For example, some goods are fragile and afraid of squeezing. Therefore, it is necessary to evaluate the safety and feasibility of the packing solutions. Based on the evaluation results, the packing solutions with lower safety or weaker feasibility should be optimized and adjusted, and the optimal packing solution should be found after comprehensive consideration.
[0078] This embodiment provides a method for automatic container sorting, which defines the classification and sorting of goods, obtains basic information of goods; classifies goods according to the defined classification, and sorts the classified goods; obtains basic information of containers, and allocates containers to the classified and sorted goods based on the basic information of containers; and generates a packing plan using a three-dimensional space algorithm. By defining the classification and sorting of goods, it is possible to achieve batch acquisition, processing, and optimization of cargo information, reducing manual intervention; based on big data and artificial intelligence technology, the accuracy and reliability of the sorting plan are ensured, and automatic sorting of various cargo types, specifications, and transportation requirements is supported to meet the actual needs of different customers.
[0079] Embodiment 2
[0080] like Figure 1 As shown, a method for automatically sorting containers comprises the following steps:
[0081] Step S1: define the classification and sorting of goods and obtain basic information of goods;
[0082] Among them, the classification of goods includes conventional goods (such as household appliances, shoes and clothing, daily necessities, etc.), refrigerated goods (such as meat, fish, fruits and vegetables, etc.), dangerous goods (such as flammable, explosive, and toxic goods), live goods (such as animals and plants that require special care and transportation conditions), etc.
[0083] In the actual transportation process, there are also contaminated goods (goods that may cause pollution during transportation but do not cause danger), liquid goods (such as oil, etc.), bulk goods (such as grain, ore, coal, etc. transported in bulk), etc.
[0084] Defining the order of goods means prioritizing them according to their categories. Goods with high priority will be given priority when they are divided into containers. When goods of the same type are divided into containers, the priority is determined by time and / or size, and goods of the same type are divided into the same container as much as possible.
[0085] The basic information of the goods includes at least the size and weight. The size of the goods, namely the length, width and height of the goods, determines the size of the container required for packing the goods. The weight of the goods is used to calculate whether the goods loaded in the container exceed the weight limit. In addition, the basic information of the goods also includes fragility, which is used to make requirements on the loading position of the goods; the shelf life of the goods, for which priority can be given to packing of goods with a near shelf life; the properties of the goods, such as regular shape, liquid, solid powder, etc., are used to determine whether the goods need to be packed separately.
[0086] In this embodiment, the cargo sorting method includes:
[0087] 1. Prioritize the cargo according to its volume. The larger the cargo, the higher its priority. It will be given priority when it is divided into boxes and packed. If the cargo has the same volume, the length, width and height of the cargo will be further considered. The cargo whose length, width and height meet the dimensions of most containers will be given priority.
[0088] 2. Based on sorting method 1, the volume is divided into interval volumes. For goods in the same interval volume, the priority is sorted according to the weight of the goods. The heavier the weight, the higher the priority, and the higher the priority is when sorting and packing;
[0089] 3. Based on sorting method 2, the shelf life of the goods and / or the scheduled date of the transportation task are taken into comprehensive consideration. Goods with a near shelf life and / or scheduled date of transportation task will be given priority for packing;
[0090] 4. Based on sorting method 3, the properties of the goods are taken into consideration. For example, dangerous goods are packed first, powders, liquids and other goods have a higher priority than general goods, and fragile goods among general goods have a higher priority for packing.
[0091] Step S2: Classify the goods according to the defined categories and sort the classified goods;
[0092] The goods type is defined in step S1, and all goods are classified into the defined goods type according to their basic information, and the classified goods are sorted according to the established priority sorting rules.
[0093] Step S3: obtaining basic information of the container, and allocating the container to the classified and sorted goods based on the basic information of the container;
[0094] The basic information of the container includes the number, length, width and height of the container, wherein the length, width and height in this embodiment refer to the length, width and height inside the container, which can be used to calculate the volume of the container.
[0095] Goods classified into the same category are assigned to the same container, and the sorted goods are loaded into the container in sequence according to the established sequence until it is full, until all containers are full or all goods are loaded.
[0096] A full container means that the weight of all the goods allocated to the container reaches the upper limit of the container's load-bearing capacity or the volume of all the goods allocated to the container is greater than the capacity of the container.
[0097] Step S4: Generate a packing solution using a three-dimensional space algorithm;
[0098] Step S41: Obtain all goods matched by each container;
[0099] In step S3, all goods are assigned to containers after classification and sorting, that is, the goods are matched with the containers, and all goods matching each container are obtained, and the container and its matching goods are taken as analysis objects.
[0100] Step S42: Obtain basic information of the container and basic information of all goods;
[0101] Obtain basic information of the container, including at least the length, width, height and load-bearing capacity of the container; basic information of the cargo includes at least the size and weight; and pre-process the acquired information, such as unifying the measurement units of all containers and cargoes.
[0102] Step S43: generating a packing plan for each container based on a three-dimensional space algorithm;
[0103] A packing plan is generated for each container using a three-dimensional space algorithm. The three-dimensional space algorithms available include a greedy algorithm, a simulated annealing algorithm, a genetic algorithm, etc. Based on the three-dimensional space algorithm, the analysis object in step S41 is calculated to obtain a packing plan.
[0104] In this embodiment, a box packing greedy algorithm is used, and the specific steps of the algorithm are as follows:
[0105] Step S431: obtaining container data and cargo data for the greedy packing algorithm and performing preprocessing;
[0106] The basic information of the container and the basic information of all goods obtained in step S42 are obtained, the basic information of the container is converted into a large set of containers to be loaded, and the basic information of all goods is represented by a list of goods to be loaded.
[0107] The preprocessing is to use a sorting algorithm to sort the containers and goods in positive order. The positive order of the goods in the sorting is the goods sorting defined in step S1, and the sorting of the containers is the sorting corresponding to the goods sorting, that is, the containers are sorted according to the types of goods that can be loaded in the containers. The containers that can load goods with higher priorities have higher priorities. When the priorities of loading goods are the same, the containers that can load more goods have higher priorities.
[0108] Step S432: traverse the pre-processed container data and cargo data, and pack the cargo according to the greedy algorithm;
[0109] Specifically, the cargo to be loaded is traversed, and the cargo is packed according to the priority. It is determined whether the cargo exceeds the maximum volume of the container. If not, the cargo is loaded into the container and bound to the container. Then the next cargo is loaded until the cargo cannot be loaded into the container. That is, when the current cargo volume exceeds the remaining volume of the container, the next container is switched for loading.
[0110] If all the goods have been loaded, the packing is deemed to be completed. If the goods have not been loaded but all containers have been put into use, the first round of packing is deemed to be completed.
[0111] After the first round of packing is completed, containers with remaining volume and unloaded goods are obtained by traversing, and the goods that have been loaded are excluded. The remaining unloaded goods are packed again until all the goods are loaded or the container can no longer be loaded with goods.
[0112] The algorithm code for reference is as follows:
[0113]
[0114]
[0115]
[0116] Step S44: Evaluate the safety and feasibility of the packing solutions, and optimize and adjust the packing solutions with lower safety or lower feasibility.
[0117] In practical applications, relatively optimal packing solutions can be obtained based on three-dimensional space algorithms. However, it is difficult for these solutions to take the loaded goods into comprehensive consideration. For example, some goods are fragile and afraid of squeezing. Therefore, it is necessary to evaluate the safety and feasibility of the packing solutions. Based on the evaluation results, the packing solutions with lower safety or weaker feasibility should be optimized and adjusted, and the optimal packing solution should be found after comprehensive consideration.
[0118] Step S5: Use a deep learning algorithm to optimize the automatic container sorting method.
[0119] Step S51: Acquire historical data of completed automatic container sorting;
[0120] Step S52: cleaning and sorting the acquired historical data to form a data set to be processed;
[0121] Step S53: Use a deep learning algorithm to process the data set, realize automatic distribution of goods, and obtain a packing plan;
[0122] Step S54: further optimize the packing solution based on the deep learning algorithm and output the final packing solution.
[0123] Historical data can be used to form a training set based on the rules summarized from manual loading. For example, 180kg goods use 20GP containers; the number of goods with "fluid bags" or "BULK" specifications is fixed to 20GP assembly; 200L barrels of goods, 20GP containers are fully loaded with 80, and 40GP containers are fully loaded with 124; 17kg PAILS barrels of goods, 20GP containers are fully loaded with 600, and 40GP containers are fully loaded with 1200. According to the training set, by identifying the above goods and matching them with the corresponding specifications first, the number of containers occupied first is locked, and the remaining specifications of goods are loaded through algorithms.
[0124] Set up the training set: collect data, prepare data, select models, train, evaluate, adjust parameters, and evaluate the test set to get some final evaluation indicators, such as accuracy, precision, etc.
[0125] Then, through the K-cross validation method, the data set is divided into a training set and a test set. The test set is set aside and the training set is divided into k parts. One of the k parts is used as a validation set each time, and the rest are used as training sets. After k trainings, we get k different models. Evaluate the effects of the k models, select the best hyperparameters, use the optimal hyperparameters, and then retrain the model using all the k parts of data as training sets to get the final model, so as to achieve a result closer to the expected result.
[0126] Based on the first embodiment, this embodiment combines the deep learning algorithm with the automatic container sorting method, and uses big data and artificial intelligence technology to further ensure the accuracy and reliability of the sorting solution and accelerate the calculation speed of the automatic container sorting method in actual application.
[0127] Embodiment 3
[0128] like Figure 3 As shown, a container automatic box sorting system 2 includes:
[0129] The data collection module 21 is used to obtain basic information of goods and containers;
[0130] The data processing module 22 is used to define the classification and sorting of goods, classify the goods according to the defined classification, and sort the classified goods;
[0131] The data calculation module 23 is used to allocate containers to the classified and sorted goods and generate a packing plan using a three-dimensional space algorithm.
[0132] The automatic container sorting system also includes: an optimization algorithm module 24, which automatically distributes and optimizes the goods based on advanced technologies such as deep learning and genetic algorithms;
[0133] The result output module 25 is used to display the optimization results to the customer in the form of a table or other methods.
[0134] Furthermore, in order to facilitate customer interaction, a friendly user operation interface can be provided to customers to facilitate users to input data and view results.
[0135] Embodiment 4
[0136] like Figure 4 As shown, a container automatic box sorting device includes:
[0137] A memory 100, used for storing computer programs;
[0138] The processor 200 is used to execute the computer program to implement the steps of the method for automatic container separation as described in the first embodiment and the second embodiment.
[0139] Embodiment 5
[0140] A readable storage medium for automatic container sorting, wherein a computer program is stored on the readable storage medium, and when the computer program is executed, the steps of the method for automatic container sorting as described in Embodiment 1 and Embodiment 2 are implemented.
[0141] The present invention may be a system, method and / or computer program product. The computer program product may include a computer-readable storage medium (or medium) having computer-readable program instructions thereon, the computer-readable program instructions being used to cause a processor to perform aspects of the present invention.
[0142] The readable storage medium is a computer-readable storage medium, which can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer-readable storage medium can be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of computer-readable storage media includes the following: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device (such as a punch card or a raised structure in a groove with instructions recorded thereon), and any suitable combination of the above.
[0143] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to a corresponding computing / processing device or downloaded to an external computer or external storage device via a network (e.g., the Internet, a local area network, a wide area network, and / or a wireless network). The network can include copper transmission cables, optical transmission fibers, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions to be stored in a computer-readable storage medium in the corresponding computing / processing device.
[0144] The computer programs described herein are computer-readable program instructions that can be downloaded from a computer-readable storage medium to a corresponding computing / processing device or downloaded to an external computer or external storage device via a network (e.g., the Internet, a local area network, a wide area network, and / or a wireless network). The network may include copper transmission cables, optical transmission fibers, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions to be stored in a computer-readable storage medium in the corresponding computing / processing device.
[0145] The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, an electronic circuit (including, for example, a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA)) may execute computer-readable program instructions to personalize the electronic circuit by utilizing state information of the computer-readable program instructions so as to perform aspects of the present invention.
[0146] Aspects of the present invention are described herein with reference to flowcharts of methods, systems, devices, and computer program products according to embodiments of the present invention and / or block diagrams. It should be understood that each box in the flowchart and / or block diagram and the combination of boxes in the flowchart and / or block diagram can be implemented by computer-readable program instructions.
[0147] These computer-readable program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine that, when executed by a processor of the computer or other programmable data processing apparatus, creates a device for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions may also be stored in a computer-readable storage medium that can instruct a computer, a programmable data processing apparatus, and / or other device to function in a particular manner, such that a computer-readable storage medium having instructions stored therein includes an article of manufacture that includes instructions for implementing various aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.
[0148] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with the art within the technical scope disclosed in the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.
Claims
1. A method for automatically sorting containers, characterized in that: The automatic container sorting method comprises the following steps: Define the classification and sorting of goods and obtain basic information about the goods; Classify the goods according to the defined categories and sort the classified goods; Obtain basic information of containers, and allocate containers to classified and sorted goods based on the basic information of containers; Generate packing solutions using a three-dimensional space algorithm.
2. The automatic container sorting method according to claim 1, characterized in that: The classification of goods includes at least: conventional goods, refrigerated goods, dangerous goods, and live goods.
3. The automatic container sorting method according to claim 1, characterized in that: The basic information of the goods includes at least size and weight.
4. The automatic container sorting method according to claim 1, characterized in that: The basic information of the container includes at least: quantity, length, width, height, and load-bearing capacity.
5. The automatic container sorting method according to claim 1, characterized in that: The allocating containers to the classified and sequenced goods includes: allocating goods classified into the same category to the same container, loading the sequenced goods into the container in sequence according to the established sequence until the container is full, until all containers are full or all goods are loaded.
6. The automatic container sorting method according to claim 1, characterized in that: The method of using a three-dimensional space algorithm to generate a packing solution includes: Get all the matching goods for each container; Get basic information of containers and all cargoes; Based on the three-dimensional space algorithm, a packing plan is generated for each container.
7. The automatic container sorting method according to claim 1, characterized in that: The method of generating a packing plan using a three-dimensional space algorithm also includes: evaluating the safety and feasibility of the packing plan, and optimizing and adjusting packing plans with lower safety or lower feasibility.
8. The automatic container sorting method according to any one of claims 1 to 7, characterized in that: The automatic container sorting method also includes: optimizing the automatic container sorting method using a deep learning algorithm.
9. The automatic container sorting method according to claim 8, characterized in that: The method of optimizing the automatic container sorting method using a deep learning algorithm includes: Obtain historical data of completed automatic container sorting; Clean and organize the acquired historical data to form a data set to be processed; Use deep learning algorithms to process data sets, realize automatic distribution of goods, and obtain packing solutions; The packing solution is further optimized based on the deep learning algorithm and the final packing solution is output.
10. An automatic container sorting system, characterized in that: The automatic container sorting system comprises: Data collection module, used to obtain basic information of goods and containers; The data processing module is used to define the classification and sorting of goods, classify the goods according to the defined classification, and sort the classified goods; The data calculation module is used to allocate containers for classified and sorted goods and generate packing plans using three-dimensional space algorithms.