CN114091740A - Boxing task processing method, device and equipment - Google Patents
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Abstract
The application belongs to the technical field of logistics, and particularly relates to a boxing task processing method, device and equipment, wherein the method comprises the following steps: acquiring packing task information, determining a first packing scheme of the front N-m trucks through a greedy algorithm and a tree search algorithm according to the cargo box information and the truck information, and obtaining the total volume of the remaining cargo boxes to be loaded corresponding to the first packing scheme, determining a plurality of truck combinations according to the total volume of the containers to be loaded, wherein each truck combination comprises m trucks, determining a plurality of second packing schemes corresponding to each truck combination through a tree search algorithm, determining at least one third packing scheme from the plurality of second packing schemes, combining the at least one third packing scheme with the first packing scheme respectively to obtain a final packing scheme, the method can determine the boxing scheme in different modes according to the total volume of the containers to be loaded in the boxing process, and can obtain the boxing scheme with higher boxing rate in limited time.
Description
Technical Field
The application belongs to the technical field of logistics, and particularly relates to a boxing task processing method, device and equipment.
Background
With the rapid development of industries such as logistics, storage and the like, the problem of boxing is very common in the fields of daily life and industry.
In practice, when containers are loaded, the types and the number of containers are increased, and when containers of different types are loaded, the packing rate is greatly reduced compared with the case where containers of the same type are loaded. In the prior art, a packing scheme is determined by a tree search-based method, and when the number of containers to be loaded is large, the number of nodes of a search tree is large. Wherein each node represents a packing scheme for a container and each leaf node represents a complete packing scheme or a scheme that cannot be continued. When the nodes of the search tree are more, all the nodes of the search tree cannot be traversed in limited time, and the obtained packing scheme is only a local optimal scheme and cannot meet the service requirement.
The conventional boxing task processing method cannot obtain a boxing scheme with high boxing rate in limited time under the condition that containers to be loaded are more, and cannot meet business requirements.
Disclosure of Invention
In order to solve the problems in the prior art, namely to solve the problem that the conventional packing task processing method cannot obtain a packing scheme with high packing rate in a limited time under the condition that more packing boxes to be loaded exist, and cannot meet the business requirements, the application provides a packing task processing method, a device and equipment
In a first aspect, an embodiment of the present application provides a method for processing a boxing task, where the method includes:
acquiring boxing task information; the boxing task information comprises: container information and truck information;
determining a first packing scheme of the first N-m trucks through a greedy algorithm and a tree search algorithm according to the cargo box information and the truck information, and obtaining the total volume of the remaining cargo boxes to be loaded corresponding to the first packing scheme; n is the number of trucks required for loading all containers; the N-m trucks are the N-m trucks with the largest available capacity at present; the tree search algorithm represents a tree search algorithm meeting the limited search width under the preset container placement rule;
determining a plurality of truck combinations according to the total volume of the remaining containers to be loaded, wherein each truck combination comprises m trucks, determining a plurality of second loading schemes corresponding to each truck combination through a tree search algorithm, and determining at least one third loading scheme from the plurality of second loading schemes; the third boxing scheme is a boxing scheme meeting preset conditions in the second boxing scheme;
and combining at least one third packing scheme with the first packing scheme respectively to obtain at least one final packing scheme.
Optionally, the container information includes a total volume of containers to be loaded currently, and the truck information includes a volume of each truck available currently; determining a first packing scheme of the front N-m trucks through a greedy algorithm and a tree search algorithm according to the cargo box information and the truck information, wherein the first packing scheme comprises the following steps:
repeatedly executing the following steps until the total volume of the current cargo containers to be loaded is smaller than the preset volume, and obtaining a first loading scheme of the front N-m trucks:
if the total volume of the containers to be loaded is larger than or equal to the preset volume, determining a target vehicle; the preset volume is the sum of the volumes of m trucks with the maximum current volume;
and determining the packing scheme of the target vehicle through the greedy algorithm and the tree search algorithm.
Optionally, determining the packing scheme of the target vehicle through the greedy algorithm and the tree search algorithm includes:
determining a packing mode of a first container to be loaded and establishing a corresponding node;
repeatedly executing the following steps until no new node exists, and obtaining a boxing scheme of the target vehicle according to a plurality of nodes which are created currently:
selecting a next container to be loaded according to the available space of the target vehicle, determining the loading mode of the currently selected container to be loaded, and creating a corresponding node for each loading mode, wherein the created nodes belong to child nodes of the corresponding node of the previous container to be loaded; the number of the created nodes is less than the search width;
and selecting the node with the highest priority from the plurality of nodes of the currently selected containers to be loaded.
Optionally, the method further includes:
determining the total volume of wasted space, the average volume of loaded containers and the component of the center coordinates of the loaded containers along the direction of a preset axis under the local packing scheme corresponding to each node;
weighting and summing the total volume of the wasted space, the average volume of the loaded containers and the component of the center coordinates of the loaded containers along the direction of a preset axis to obtain the score of the node;
determining the node with the highest or lowest priority according to the score of each node; wherein the priority of the node is positively correlated with the score of the node.
Optionally, the method further includes:
when the target vehicle has available space for accommodating at least one container, judging whether a first type of container exists in the containers to be loaded; the first type of container is a sleeve machine;
if the first type of container to be loaded exists, stacking a plurality of containers to be loaded in the length direction and the height direction of the container to obtain stacked complex blocks;
placing the complex block in the available space, and if the complex block is successfully placed, determining the complex block as a child node of a corresponding node of a previous cargo box to be loaded; and if the placement is unsuccessful, regenerating the complex block.
Optionally, the method further includes:
if the first type of container to be loaded does not exist, judging whether a second type of container to be loaded exists or not; the second type of container is a discrete piece;
if a second type of container to be loaded exists, stacking a plurality of containers to be loaded in the length and height direction of the container to obtain stacked simple blocks;
placing the simple block in the available space, and if the simple block is successfully placed, determining the simple block as a child node of a corresponding node of the previous container to be loaded; and if the placement is unsuccessful, regenerating the simple block.
Optionally, determining at least one third packing scenario from the plurality of second packing scenarios comprises:
determining the space utilization rate and the geometric center position of the container corresponding to each second packing scheme according to the placement mode of the container in each second packing scheme;
determining at least one third packing scheme according to the space utilization rate and/or the geometric center position of the packing box; the third packing scheme is a second packing scheme which meets preset requirements in terms of space utilization rate and/or geometric center position of the packing box.
In a second aspect, an embodiment of the present application further provides a boxing task processing apparatus, where the apparatus includes:
the acquisition module is used for acquiring boxing task information; the boxing task information comprises: container information and truck information;
the first determining module is used for determining a first packing scheme of the front N-m trucks through a greedy algorithm and a tree search algorithm according to the cargo box information and the truck information, and obtaining the total volume of the remaining cargo boxes to be loaded corresponding to the first packing scheme; n is the number of trucks required for loading all containers; the N-m trucks are the N-m trucks with the largest available capacity at present; the tree search algorithm represents a tree search algorithm meeting the limited search width under the preset container placement rule;
the second determining module is used for determining a plurality of truck combinations according to the total volume of the remaining to-be-loaded cargo containers, wherein each truck combination comprises m trucks, determining a plurality of second loading schemes corresponding to each truck combination through a tree search algorithm, and determining at least one third loading scheme from the plurality of second loading schemes; the third boxing scheme is a boxing scheme meeting preset conditions in the second boxing scheme;
and the combination module is used for combining at least one third boxing scheme with the first boxing scheme respectively to obtain at least one final boxing scheme.
Optionally, the container information includes a total volume of containers to be loaded currently, and the truck information includes a volume of each truck available currently; when the first determining module determines the first packing scheme of the front N-m trucks through a greedy algorithm and a tree search algorithm according to the cargo box information and the truck information, the first determining module is specifically configured to:
repeatedly executing the following steps until the volume of the current container to be loaded is smaller than the preset volume, and obtaining a first container loading scheme of the front N-m trucks:
if the total volume of the containers to be loaded is larger than or equal to the preset volume, determining a target vehicle; the preset volume is the sum of the volumes of m trucks with the maximum current volume;
and determining the packing scheme of the target vehicle through the greedy algorithm and the tree search algorithm.
Optionally, when the first determining module determines the container loading scheme of the target vehicle through the greedy algorithm and the tree search algorithm, the first determining module is specifically configured to:
determining a packing mode of a first container to be loaded and establishing a corresponding node;
repeatedly executing the following steps until no new node exists, and obtaining a boxing scheme of the target vehicle according to a plurality of nodes which are created currently:
selecting a next container to be loaded according to the available space of the target vehicle, determining the loading mode of the currently selected container to be loaded, and creating a corresponding node for each loading mode, wherein the created nodes belong to child nodes of the corresponding node of the previous container to be loaded; the number of the created nodes is less than the search width;
and selecting the node with the highest priority from the plurality of nodes of the currently selected containers to be loaded.
Optionally, the apparatus further comprises: a score calculation module to:
and determining the total volume of the wasted space, the average volume of the loaded containers and the component of the center coordinates of the loaded containers along the direction of the preset axis under the local packing scheme corresponding to each node.
Weighting and summing the total volume of the wasted space, the average volume of the loaded containers and the component of the center coordinates of the loaded containers along the direction of a preset axis to obtain the score of the node;
determining the node with the highest or lowest priority according to the score of each node; wherein the priority of the node is positively correlated with the score of the node.
Optionally, the apparatus further includes a blocking module, configured to:
when the target vehicle has available space for accommodating at least one container, judging whether a first type of container exists in the containers to be loaded; the first type of container is a sleeve machine;
if the first type of container to be loaded exists, stacking a plurality of containers to be loaded in the length direction and the height direction of the container to obtain stacked complex blocks;
placing the complex block in the available space, and if the complex block is successfully placed, determining the complex block as a child node of a corresponding node of a previous cargo box to be loaded; and if the placement is unsuccessful, regenerating the complex block.
Optionally, the blocking module is further configured to:
if the first type of container to be loaded does not exist, judging whether a second type of container to be loaded exists or not; the second type of container is a discrete piece;
if a second type of container to be loaded exists, stacking a plurality of containers to be loaded in the length and height direction of the container to obtain stacked simple blocks;
placing the simple block in the available space, and if the simple block is successfully placed, determining the simple block as a child node of a corresponding node of the previous container to be loaded; and if the placement is unsuccessful, regenerating the simple block.
Optionally, when the second determining module determines at least one third packing scheme from the plurality of second packing schemes, the second determining module is specifically configured to:
determining the space utilization rate and the geometric center position of the container corresponding to each second packing scheme according to the placement mode of the container in each second packing scheme;
determining at least one third packing scheme according to the space utilization rate and/or the geometric center position of the packing box; the third packing scheme is a second packing scheme which meets preset requirements in terms of space utilization rate and/or geometric center position of the packing box.
In a third aspect, an embodiment of the present application further provides a boxing task processing apparatus, including: a memory and at least one processor;
the memory stores computer-executable instructions;
the at least one processor executes the computer-executable instructions stored by the memory, so that the at least one processor performs the boxing task processing method provided by any corresponding embodiment of the first aspect of the application.
In a fourth aspect, the present application further provides a computer-readable storage medium, where a computer executing instruction is stored in the computer-readable storage medium, and when a processor executes the computer executing instruction, the method for processing a casing task provided in any embodiment corresponding to the first aspect of the present application is implemented.
As can be understood by those skilled in the art, the method, the device and the equipment for processing the boxing task provided by the embodiment of the application acquire the information of the boxing task; the boxing task information comprises: container information and truck information; determining a first packing scheme of the first N-m trucks through a greedy algorithm and a tree search algorithm according to the cargo box information and the truck information, and obtaining the total volume of the remaining cargo boxes to be loaded corresponding to the first packing scheme; n is the number of trucks required for loading all containers; the N-m trucks are the N-m trucks with the largest available capacity at present; the tree search algorithm represents a tree search algorithm meeting the limited search width under the preset container placement rule; determining a plurality of truck combinations according to the total volume of the remaining containers to be loaded, wherein each truck combination comprises m trucks, determining a plurality of second loading schemes corresponding to each truck combination through a tree search algorithm, and determining at least one third loading scheme from the plurality of second loading schemes; the third boxing scheme is a boxing scheme meeting preset conditions in the second boxing scheme; and combining at least one third packing scheme with the first packing scheme to obtain at least one final packing scheme, wherein the first packing scheme can be determined by adopting a local optimization mode for the first N-m trucks, the third packing scheme can be determined by adopting a global optimization mode for the last m trucks, the packing scheme with high packing rate can be obtained within limited time, and the business requirements can be met.
Drawings
Preferred embodiments of the packing task processing method, apparatus, and device of the present application are described below with reference to the accompanying drawings. The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the application. The attached drawings are as follows:
fig. 1 is an application scenario diagram of a method for processing a boxing task according to an embodiment of the present application;
fig. 2 is a schematic flowchart of a method for processing a boxing task according to an embodiment of the present application;
FIG. 3 is a schematic flow chart illustrating a process for determining a first packing scenario for the first N-m trucks according to an embodiment of the present disclosure;
FIG. 4 is a schematic flow chart illustrating a method for determining a loading scheme of a target vehicle according to an embodiment of the present disclosure;
FIG. 5 is a schematic structural diagram of a search tree according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of a boxing task processing device according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of a boxing task processing device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the embodiments of the present application, and it is obvious that the described embodiments are some but not all of the embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The following describes the technical solutions of the present application and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
The following explains an application scenario of the embodiment of the present application:
fig. 1 is an application scenario diagram of a method for handling a packing task according to an embodiment of the present application, and as shown in fig. 1, in the logistics industry, it is often necessary to load containers of a plurality of different sizes into different types of trucks, where each container has a certain length, width, and height, and occupies a certain volume, and each container has a corresponding placement requirement, such as vertical placement or horizontal placement, and how to obtain a packing strategy according to the placement requirements of the containers, so that all containers are placed into a truck, and it is satisfied that as few trucks as possible are selected, and a packing rate of the truck is highest.
For the truck, a coordinate system can be constructed, the point o represents the upper left corner of the bottom surface of the cargo box, the axis a represents the direction in which the origin of coordinates extends horizontally towards the cargo discharge port, the axis b represents the direction in which the origin of coordinates extends horizontally towards the right, the axis c represents the direction in which the origin of coordinates extends upwards, the lengths of the axis a, the axis b and the axis c can represent the length width and the height of the truck, the three coordinate axes can represent the truck space, and after the truck space is determined, a plurality of cargo boxes can be sequentially placed in the truck space. Wherein, the packing strategy refers to which truck the packing box is placed to and the placing mode in the truck.
In the prior art, a packing scheme is usually determined by a tree search method, when containers to be loaded are large, nodes of a search tree are more, each leaf node can represent a complete packing scheme or a scheme which cannot be performed, if all leaf nodes of the search tree are traversed, the calculation amount is large, the packing scheme cannot be obtained within a limited time, and the business requirement cannot be met.
In view of the above problems, the boxing task processing method provided by the embodiment of the application has the main concept that: in the process of loading N-m trucks before loading, a greedy strategy is adopted to realize when the packing mode of each container to be loaded is searched, a local packing scheme which is optimized as much as possible can be obtained when each container to be loaded is loaded based on the greedy strategy, when the last m trucks are loaded, the total volume of the containers to be loaded is small, all packing schemes can be traversed, a packing scheme with a high packing rate is obtained, the packing scheme of the first N-m trucks and the packing scheme of the last m trucks are combined, a final packing scheme is obtained, and the final packing scheme meets the approximate maximization of the whole packing rate.
Fig. 2 is a schematic flow diagram of a boxing task processing method provided in an embodiment of the present application, where the boxing task processing method provided in the embodiment of the present application is applied to boxing task processing equipment, and as shown in fig. 2, the boxing task processing method includes the following steps:
step S201, acquiring boxing task information; the boxing task information comprises: container information and truck information.
In this step, it is necessary to determine container information and truck information, wherein the container information and truck information may be information input by a user based on actual conditions of the container and truck to be loaded, and may also be determined based on received order information. For example, in a shop selling home appliances, the order includes the type, model, and number of home appliances purchased by the user, and the container information for each home appliance can be determined based on the information.
In practice, according to information such as the volume and the size of a plurality of available trucks, orders can be merged or split, for example, a large order including a large number of containers to be loaded can be split, and a small order including a small number of containers to be loaded can be merged, so that the containers to be loaded of the split or combined order can be loaded in a truck with a preset number.
Step S202, determining a first packing scheme of the first N-m trucks through a greedy algorithm and a tree search algorithm according to the cargo box information and the truck information, and obtaining the total volume of the remaining cargo boxes to be loaded corresponding to the first packing scheme; n is the number of trucks required for loading all containers; the N-m trucks are the N-m trucks with the largest available capacity at present; the tree search algorithm represents a tree search algorithm satisfying a limited search width under a preset container placement rule.
The first packing scheme is used for representing a plurality of containers respectively loaded by the first N-m trucks and the placement mode of each container in the trucks. When the packing scheme of the first N-m trucks is determined, because more containers to be loaded exist, a greedy algorithm is adopted for determining the packing mode of each container to be loaded through a tree search algorithm. The greedy algorithm is a packing mode which takes a packing mode corresponding to the current optimal solution as a local packing scheme when any packing box to be loaded is loaded, and receives a packing box to be loaded when the packing mode of the next packing box to be loaded is determined. Where N represents the number of trucks loading all of the containers to be loaded.
When the number of the containers to be loaded is large or the size of the containers is large, a container loading mode based on a greedy algorithm is adopted; during loading, when the containers to be loaded are fewer or have smaller volume, the loading mode of each container to be loaded is not determined based on the greedy algorithm.
Wherein, satisfying the preset rule means: and (4) presetting container placement rules. For example, when a container is loaded in a truck, the container is always placed at the position of the lower left corner of the available space of the container, and after the position of the container is determined, the placement scheme of the container is reduced as much as possible, so that the calculation amount of subsequent tree search is reduced. Furthermore, due to the nature of the containers, there may be certain requirements on the manner of placement, for example, there is vertical space available for a currently unfilled truck, but the containers to be loaded may only be placed laterally, and the containers may not be loaded in the truck. Or the container A has certain requirements on load bearing, and when the weight of the container B exceeds the load bearing, the container B cannot be placed above the container A.
When the front N-m trucks are selected, the truck with the largest volume needs to be selected preferentially, and when the volume of the truck is larger, the required number of trucks is smaller, so that the freight cost is reduced.
In addition, the tree search algorithm refers to a packing scheme for determining each container to be loaded by searching nodes in the tree. When the boxing mode of the front N-m trucks is determined, one tree can represent the whole boxing scheme of the front N-m trucks and can also represent the whole boxing scheme of the N trucks. Wherein a tree comprises a plurality of nodes, each node represents a packing scheme for a packing case, and the leaf nodes represent a complete packing scheme or a scheme that cannot be continued. When tree searching is carried out, searching is carried out in a mode of limiting the searching width, namely the number of nodes is kept in a certain range, so that a boxing scheme with high potential can be searched in a limited time.
When the first N-m trucks are loaded, the total volume of the remaining to-be-loaded cargo containers can be determined, and the truck combination of the remaining m trucks can be determined according to the total volume of the remaining to-be-loaded cargo containers.
S203, determining a plurality of truck combinations according to the total volume of the remaining containers to be loaded, wherein each truck combination comprises m trucks, determining a plurality of second packing schemes corresponding to each truck combination through a tree search algorithm, and determining at least one third packing scheme from the plurality of second packing schemes; the third packing scheme is a packing scheme meeting preset conditions in the second packing scheme.
After the total volume of the containers to be loaded is determined, m trucks are selected from the currently available trucks according to the total volume of the containers to be loaded, wherein the sum of the volumes of the m trucks needs to be larger than the total volume of the containers to be loaded.
However, when m trucks are selected, the truck with the largest capacity is not selected, and since there are fewer trucks to be loaded at this time, if the truck with the largest capacity is selected, a large amount of truck space is wasted, and therefore, it is considered to load the remaining trucks with a plurality of smaller trucks. Meanwhile, when the loading schemes of the remaining m trucks are determined, a global optimization mode is adopted, namely, a plurality of achievable second packing schemes are determined based on each container combination, and then a third packing scheme meeting preset conditions is determined from the second packing schemes corresponding to all the packing combinations. And the second packing scheme is determined by traversing all nodes of the search tree. For example, where there are three truck combinations of containers of different volumes, and there are four achievable packing solutions for each truck combination, there are 12 packing solutions for the remaining containers to be loaded, from which the third packing solution can be selected that meets the conditions.
In determining the third packing scenario, the determination may be made based on the space utilization and/or the geometric center position of each second packing scenario, so as to determine the packing scenario of the m rear vehicles with higher packing rates.
And S204, combining at least one third boxing scheme with the first boxing scheme respectively to obtain at least one final boxing scheme.
After the first filling plan of the first N-m trucks and the at least one third filling plan of the last m trucks are determined, the first filling plan and the third filling plan are combined to obtain a plurality of final filling plans. After the multiple final boxing schemes are obtained, the multiple final boxing schemes can be displayed to a user, so that the user can select a boxing scheme suitable for the boxing habit of the user according to the requirement.
The boxing task processing method provided by the embodiment of the application can obtain local boxing schemes optimized as much as possible by obtaining the boxing task information, determining the first boxing scheme of the front N-m trucks through a greedy algorithm and a tree search algorithm according to the cargo box information and the cargo box information, obtaining the total volume of the remaining cargo boxes to be loaded corresponding to the first boxing scheme, determining a plurality of cargo box combinations according to the total volume of the remaining cargo boxes to be loaded, wherein each cargo box combination comprises m trucks, determining a plurality of second boxing schemes corresponding to each cargo box combination through the tree search algorithm, determining at least one third boxing scheme from the plurality of second boxing schemes, determining the third boxing scheme of the last m trucks through a global optimization mode, obtaining the final boxing scheme, enabling the final boxing scheme to meet the approximate maximization of the overall boxing rate, and obtaining the boxing scheme with higher boxing rate in a limited time, the actual business requirements can be met.
FIG. 3 is a schematic flow chart illustrating a process for determining a first packing scenario for the first N-m trucks according to an embodiment of the present disclosure; as shown in fig. 3, the method includes:
and repeatedly executing the step S301 and the step S302 until the total volume of the containers to be loaded is smaller than the preset volume, and obtaining a first packing scheme of the first N-m trucks:
s301, if the total volume of the container to be loaded is larger than or equal to a preset volume, determining a target vehicle; the preset volume is the sum of the volumes of m trucks with the maximum current volume.
When the first packing scheme of the front N-m trucks is determined, the size relation between the total volume of the current to-be-loaded cargo containers and the preset volume needs to be determined. And the preset volume is the sum of the volumes of m trucks with the maximum current volume. The m can be set according to the needs of a user, and when the numerical value set by the m is larger, the corresponding calculated amount is larger than that when the numerical value is smaller, and the m can be selected based on the data processing speed of the equipment. For example, m may be set to 2.
The judgment of the size relationship between the total volume of the current container to be loaded and the preset volume is to determine the state of the current container to be loaded, if the total volume of the current container to be loaded is larger than the preset volume, more containers to be loaded are represented, and if the total volume of the current container to be loaded is smaller than the preset volume, less containers to be loaded are represented. The preset volume is the sum of the volumes of m trucks with the largest volume in the trucks which can be used currently.
When the volume is larger than the preset volume, the next container to be loaded needs to be placed in the front N-m trucks, and the target vehicle needs to be determined firstly. And the determined target vehicle is the vehicle with the largest current volume.
And S302, determining a packing scheme of the target vehicle through the greedy algorithm and the tree search algorithm.
After the target vehicle is determined, a container loading scheme of the target vehicle can be determined by adopting a greedy algorithm and a tree search algorithm. The packing scheme determined based on the greedy algorithm indicates that when a container to be loaded is placed in a truck, the currently optimal placement mode of the container is selected, and after the placement mode is determined, the placement mode of the next container to be loaded is determined based on the placement mode of the previous container, that is, the placement mode of the previous container is not considered secondarily. The placing mode of each container to be loaded can be the local optimal placing mode through a greedy algorithm.
By the method, the boxing scheme of the front N-m trucks can be determined based on the greedy algorithm, and the boxing scheme can be determined as soon as possible under the condition that a large number of trucks to be loaded exist.
The following describes in detail a process of determining a packaging scheme of a target vehicle based on a greedy algorithm and a tree search algorithm.
FIG. 4 is a schematic flow chart illustrating a method for determining a loading scheme of a target vehicle according to an embodiment of the present disclosure; as shown in fig. 4, the method includes:
step S401, determining a packing mode of a first container to be loaded, and creating a corresponding node.
FIG. 5 is a schematic structural diagram of a search tree according to an embodiment of the present disclosure; as shown in fig. 5, the search tree includes a root node, a plurality of first child nodes exist below the root node, each first child node represents a container packing manner of the 1 st container, wherein the container packing manner of one container may be multiple, and the container packing manner of the 1 st container may be determined through a greedy policy. And a second sub-node exists under the first sub-node, and the like, so that various packing modes of each packing box are obtained. After the placement mode of the 1 st container is determined, the node is determined to be created from the plurality of first child nodes.
Repeatedly executing the following steps S402 and S403 until no new node exists, and obtaining a packing scheme of the target vehicle according to the plurality of nodes created currently:
s402, selecting a next container to be loaded according to the available space of the target vehicle, determining the loading modes of the currently selected container to be loaded, and creating a corresponding node for each loading mode, wherein the created nodes belong to child nodes of the corresponding node of the previous container to be loaded; the number of created nodes is less than the search width.
After the node corresponding to the 1 st container is determined, the nodes corresponding to the 2 nd container, the 3 rd container and the like can be sequentially determined. When the corresponding nodes of the containers are determined, the loading modes of the containers to be loaded at present are determined, and one node is created for each loading mode. For example, when the node corresponding to the 2 nd container is determined, if there are 5 loading methods, one node may be created for each loading method.
It should be noted that the number of nodes created for each bin to be loaded cannot exceed the search width. When the number of nodes is larger than the search width, the node with the lowest priority needs to be determined and deleted. For example, if the number is limited to 4, only the packing schemes corresponding to the first 4 nodes that are preferentially searched are considered, so that a better packing scheme corresponding to the to-be-packed box is obtained within a limited time. Wherein, when searching, always give priority to the bigger packing box, therefore, can obtain better packing scheme preferentially.
And S403, selecting a node with the highest priority from the plurality of nodes of the currently selected containers to be loaded.
When the node corresponding to the container to be loaded is determined from the plurality of nodes, the priorities of the plurality of nodes are compared, and the node with the highest priority is determined as the node corresponding to the container to be loaded. The highest priority indicates that the partial binning scheme is the current optimal scheme.
When the newly added node does not exist, the target vehicle is full, and the loading mode of the container corresponding to each node can be determined based on the determined node each time.
After the node corresponding to a certain container is determined, the greedy algorithm indicates that the packing scheme corresponding to the container is determined, and other packing modes corresponding to the container are not considered.
The method can determine the packing mode of the target vehicle, can determine the local optimal packing scheme at a higher speed based on a greedy algorithm, can reduce the calculated data amount by limiting the search width, and preferentially searches the packing scheme with higher potential.
On the basis of the above-described embodiments, a process of determining a node with the highest or lowest priority is described in detail.
Optionally, the method further includes:
and determining the total volume of the wasted space, the average volume of the loaded containers and the component of the center coordinates of the loaded containers along the direction of the preset axis under the local packing scheme corresponding to each node.
After a certain node is determined through a search algorithm, the container corresponding to the node and the placement mode of the container placed before the container can be determined, so that the total volume of the wasted space under the current local packing scheme can be determined, and the total volume can be the difference between the volume of the truck and the sum of the volumes of all containers. It is also possible to calculate the average volume of all containers loaded, which can be calculated on the basis of the volume of each container. It is also possible to calculate the component of the centre coordinates of the loaded container in the direction of a predetermined axis, where the predetermined axis here represents the a-axis, i.e. the direction in which the origin of coordinates extends horizontally towards the discharge opening.
And weighting and summing the total volume of the wasted space, the average volume of the loaded containers and the component of the center coordinates of the loaded containers along the direction of the preset axis to obtain the grade of the node.
By setting different weights for the total volume of the wasted space, the average volume of the loaded containers, and the component of the center coordinates of the loaded containers in the direction of the preset axis, respectively, and summing, the score of the node can be obtained. The set weight can be adjusted according to actual conditions. When the value of the weight is set higher, it indicates that the corresponding influence factor is more emphasized. If the value of the weight corresponding to the total volume of the wasted space is higher, the influence of the total volume of the wasted space on the priority is emphasized.
Determining the node with the highest or lowest priority according to the score of each node; wherein the priority of the node is positively correlated with the score of the node.
After the grade of each node is determined, the node with the highest grade is determined as the node with the highest priority, and the node with the lowest grade is determined as the node with the lowest priority.
The priority of the nodes is determined by the mode of determining the node scores, so that the priority of each node can be visually measured, and the node with the highest or lowest priority can be quickly determined.
The following describes in detail a process of determining child nodes of the current node.
Optionally, the method further includes:
when the target vehicle has available space for accommodating at least one container, judging whether a first type of container exists in the containers to be loaded; the first type of container is a sleeve machine; if the first type of container to be loaded exists, stacking a plurality of containers to be loaded in the length direction and the height direction of the container to obtain stacked complex blocks; placing the complex block in the available space, and if the complex block is successfully placed, determining the complex block as a child node of a corresponding node of a previous cargo box to be loaded; and if the placement is unsuccessful, regenerating the complex block.
When the child node is determined, whether available space exists in the current container is judged, and if the available space exists, the next container to be loaded can be determined from the containers to be loaded. When the next container to be loaded is determined, the set of machines is preferably considered, for example, an air conditioner comprises an outdoor machine and an indoor machine which form one set of machines. The sleeving machine needs to be placed together and has a large volume, so that the sleeving machine can be placed preferentially. If a container with a small volume is placed in advance, the available container space can be cut up, so that a container with a large volume cannot be placed, and the space utilization rate is improved.
When the containers of the first type such as the nesting machine exist, a plurality of containers can be stacked in the length direction and the height direction of the containers to obtain stacked complex blocks. Since the cargo box is usually in a slender state, the length of the cargo box is far greater than the width value, and therefore the width of the combined complex blocks has a greater influence on the whole volume. And when less containers are placed in the width direction, the space can be left for placing other types of containers, so that the space utilization rate is improved. Wherein, when stacking, the scheme of stacking more containers is preferably selected.
And if the placement is unsuccessful, the containers are continuously stacked to obtain the complex blocks again.
In the above-mentioned step, through constituteing the packing box of the same type complex piece, can reduce and place the number of times, improve the efficiency that generates the vanning scheme, through preferentially placing the complex piece that the cover machine is constituteed, can improve the space utilization of freight train.
Optionally, the method further includes:
if the first type of container to be loaded does not exist, judging whether a second type of container to be loaded exists or not; the second type of container is a discrete piece; if a second type of container to be loaded exists, stacking a plurality of containers to be loaded in the length and height direction of the container to obtain stacked simple blocks; placing the simple block in the available space, and if the simple block is successfully placed, determining the simple block as a child node of a corresponding node of the previous container to be loaded; and if the placement is unsuccessful, regenerating the simple block.
Wherein, when the first type container does not exist, the container can be continuously loaded with parts, such as a refrigerator, a washing machine, a water heater and the like in the electric appliance. When considering the parts, the containers with larger volume are also considered preferentially and combined into a simple block. For example, a simple block consisting of several refrigerators can be loaded with priority. The process of combining the parts into the simple block is similar to the process of combining the complete machine into the complex block, and the description is omitted here. The process of determining the simple block as the child node of the corresponding node of the previous container to be loaded is also similar to the process of determining the complex block as the child node of the corresponding node of the previous container to be loaded, and details are not repeated here.
The process of determining at least one third packing scenario for the last m vehicles is described in detail below.
Optionally, the determining at least one third packing scenario from the plurality of second packing scenarios comprises:
determining the space utilization rate and the geometric center position of the container corresponding to each second packing scheme according to the placement mode of the container in each second packing scheme; determining at least one third packing scheme according to the space utilization rate and/or the geometric center position of the packing box; the third packing scheme is a second packing scheme which meets preset requirements in terms of space utilization rate and/or geometric center position of the packing box.
Wherein after determining a plurality of second packing plans for the last m trucks, a third packing plan can be determined therefrom, the third packing plan being at least one plan in which the space utilization and/or the geometric center position of the cargo box in the second packing plan meets the preset requirements. When determining the third packing plan, the space utilization rate and the geometric center of the packing boxes under the arrangement mode of all the packing boxes in each second packing plan can be determined. Wherein the geometric centre of the container represents the geometric centre of all containers already loaded in the vehicle. And comparing the space utilization rate and/or the geometric center of the container corresponding to each second packing scheme to obtain a third packing scheme with the space utilization rate and/or the geometric center of the container meeting the preset requirement. The number of the third packing schemes can be multiple.
The space utilization rate and/or the geometric center of the container meet the preset requirement, the space utilization rate is larger than the preset space utilization rate, and the geometric center of the container is close to the lower left corner of the container space.
The packing schemes of the last m trucks subjected to global optimization can be obtained by comparing the space utilization rate of each second packing scheme and/or the geometric center position of the packing box, and the packing rate is improved.
Fig. 6 is a schematic structural diagram of a boxing task processing apparatus 60 according to an embodiment of the present application, and as shown in fig. 6, the apparatus includes:
an obtaining module 610, configured to obtain boxing task information; the boxing task information comprises: container information and truck information;
the first determining module 620 is configured to determine a first packing scheme of the first N-m trucks through a greedy algorithm and a tree search algorithm according to the truck information and the truck information, and obtain a total volume of remaining trucks to be loaded corresponding to the first packing scheme; n is the number of trucks required for loading all containers; the N-m trucks are the N-m trucks with the largest available capacity at present; the tree search algorithm represents a tree search algorithm meeting the limited search width under the preset container placement rule;
a second determining module 630, configured to determine multiple truck combinations according to the total volume of remaining containers to be loaded, where each truck combination includes m trucks, determine multiple second loading schemes corresponding to each truck combination through a tree search algorithm, and determine at least one third loading scheme from among the multiple second loading schemes; the third boxing scheme is a boxing scheme meeting preset conditions in the second boxing scheme;
and the combining module 640 is used for combining the at least one third boxing scheme with the first boxing scheme respectively to obtain at least one final boxing scheme.
Optionally, the container information includes a total volume of containers to be loaded currently, and the truck information includes a volume of each truck available currently; when the first determining module 620 determines the first packing scheme of the first N-m trucks through the greedy algorithm and the tree search algorithm according to the cargo box information and the truck information, it is specifically configured to:
repeatedly executing the following steps until the volume of the current container to be loaded is smaller than the preset volume, and obtaining a first container loading scheme of the front N-m trucks:
if the total volume of the containers to be loaded is larger than or equal to the preset volume, determining a target vehicle; the preset volume is the sum of the volumes of m trucks with the maximum current volume;
and determining the packing scheme of the target vehicle through the greedy algorithm and the tree search algorithm.
Optionally, when determining the container loading scheme of the target vehicle through the greedy algorithm and the tree search algorithm, the first determining module 620 is specifically configured to:
determining a packing mode of a first container to be loaded and establishing a corresponding node;
repeatedly executing the following steps until no new node exists, and obtaining a boxing scheme of the target vehicle according to a plurality of nodes which are created currently:
selecting a next container to be loaded according to the available space of the target vehicle, determining the loading mode of the currently selected container to be loaded, and creating a corresponding node for each loading mode, wherein the created nodes belong to child nodes of the corresponding node of the previous container to be loaded; the number of the created nodes is less than the search width;
and selecting the node with the highest priority from the plurality of nodes of the currently selected containers to be loaded.
Optionally, the apparatus further comprises: a score calculation module to:
and determining the total volume of the wasted space, the average volume of the loaded containers and the component of the center coordinates of the loaded containers along the direction of the preset axis under the local packing scheme corresponding to each node.
Weighting and summing the total volume of the wasted space, the average volume of the loaded containers and the component of the center coordinates of the loaded containers along the direction of a preset axis to obtain the score of the node;
determining the node with the highest or lowest priority according to the score of each node; wherein the priority of the node is positively correlated with the score of the node.
Optionally, the apparatus further includes a blocking module, configured to:
when the target vehicle has available space for accommodating at least one container, judging whether a first type of container exists in the containers to be loaded; the first type of container is a sleeve machine;
if the first type of container to be loaded exists, stacking a plurality of containers to be loaded in the length direction and the height direction of the container to obtain stacked complex blocks;
placing the complex block in the available space, and if the complex block is successfully placed, determining the complex block as a child node of a corresponding node of a previous cargo box to be loaded; and if the placement is unsuccessful, regenerating the complex block.
Optionally, the blocking module is further configured to:
if the first type of container to be loaded does not exist, judging whether a second type of container to be loaded exists or not; the second type of container is a discrete piece;
if a second type of container to be loaded exists, stacking a plurality of containers to be loaded in the length and height direction of the container to obtain stacked simple blocks;
placing the simple block in the available space, and if the simple block is successfully placed, determining the simple block as a child node of a corresponding node of the previous container to be loaded; and if the placement is unsuccessful, regenerating the simple block.
Optionally, when the second determining module determines at least one third packing scheme from the plurality of second packing schemes, the second determining module is specifically configured to:
determining the space utilization rate and the geometric center position of the container corresponding to each second packing scheme according to the placement mode of the container in each second packing scheme;
determining at least one third packing scheme according to the space utilization rate and/or the geometric center position of the packing box; the third packing scheme is a second packing scheme which meets preset requirements in terms of space utilization rate and/or geometric center position of the packing box.
The boxing task processing device provided by the embodiment of the application can execute the boxing task processing method provided by any embodiment of the application, and has the corresponding functional modules and beneficial effects of the execution method.
Fig. 7 is a schematic structural diagram of a boxing task processing apparatus 70 provided in an embodiment of the present application, and as shown in fig. 7, the boxing task processing apparatus includes: a memory 710 and at least one processor 720.
Wherein the memory 710 stores computer-executable instructions;
the at least one processor 720 executes the computer-executable instructions stored in the memory 710, so that the at least one processor 720 executes the method for processing the boxing task according to any embodiment of the present application corresponding to fig. 2 to 5.
Wherein the memory 710 and the processor 720 are connected by a bus 730.
The relevant description may be understood by referring to the relevant description and effect corresponding to the steps in fig. 2 to fig. 5, and redundant description is not repeated here.
The present application further provides a readable storage medium, in which an execution instruction is stored, and when the execution instruction is executed by at least one processor of the air conditioner control device, the computer execution instruction, when executed by the processor, implements the boxing task processing method in the above embodiments.
The present application also provides a program product comprising executable instructions stored in a readable storage medium. The at least one processor of the boxing task processing device may read the execution instruction from the readable storage medium, and the execution of the execution instruction by the at least one processor causes the boxing task processing device to implement the boxing task processing method provided by the various embodiments described above.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of modules is merely a division of logical functions, and an actual implementation may have another division, for example, a plurality of modules or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.
Modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present application may be integrated into one processing module, or each of the modules may exist alone physically, or two or more modules are integrated into one module. The integrated module can be realized in a hardware form, and can also be realized in a form of hardware and a software functional module.
The integrated module implemented in the form of a software functional module may be stored in a computer-readable storage medium. The software functional module is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present application. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: it is readily understood by the person skilled in the art that the scope of protection of the present application is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the present application, and the technical scheme after the changes or substitutions will fall into the protection scope of the present application.
Claims (10)
1. A method for handling a boxing task, the method comprising:
acquiring boxing task information; the boxing task information comprises: container information and truck information;
determining a first packing scheme of the first N-m trucks through a greedy algorithm and a tree search algorithm according to the cargo box information and the truck information, and obtaining the total volume of the remaining cargo boxes to be loaded corresponding to the first packing scheme; n is the number of trucks required for loading all containers; the N-m trucks are the N-m trucks with the largest available capacity at present; the tree search algorithm represents a tree search algorithm meeting the limited search width under the preset container placement rule;
determining a plurality of truck combinations according to the total volume of the remaining containers to be loaded, wherein each truck combination comprises m trucks, determining a plurality of second loading schemes corresponding to each truck combination through a tree search algorithm, and determining at least one third loading scheme from the plurality of second loading schemes; the third boxing scheme is a boxing scheme meeting preset conditions in the second boxing scheme;
and combining at least one third packing scheme with the first packing scheme respectively to obtain at least one final packing scheme.
2. The method of claim 1, wherein the container information includes a total volume of containers currently to be loaded, and the truck information includes a volume of each truck currently available for use; determining a first packing scheme of the front N-m trucks through a greedy algorithm and a tree search algorithm according to the cargo box information and the truck information, wherein the first packing scheme comprises the following steps:
repeatedly executing the following steps until the total volume of the current cargo containers to be loaded is smaller than the preset volume, and obtaining a first loading scheme of the front N-m trucks:
if the total volume of the containers to be loaded is larger than or equal to the preset volume, determining a target vehicle; the preset volume is the sum of the volumes of m trucks with the maximum current volume;
and determining the packing scheme of the target vehicle through the greedy algorithm and the tree search algorithm.
3. The method of claim 2, wherein determining the target vehicle's packing scheme via the greedy algorithm and the tree search algorithm comprises:
determining a packing mode of a first container to be loaded and establishing a corresponding node;
repeatedly executing the following steps until no new node exists, and obtaining a boxing scheme of the target vehicle according to a plurality of nodes which are created currently:
selecting a next container to be loaded according to the available space of the target vehicle, determining the loading mode of the currently selected container to be loaded, and creating a corresponding node for each loading mode, wherein the created nodes belong to child nodes of the corresponding node of the previous container to be loaded; the number of the created nodes is less than the search width;
and selecting the node with the highest priority from the plurality of nodes of the currently selected containers to be loaded.
4. The method of claim 3, further comprising:
determining the total volume of wasted space, the average volume of loaded containers and the component of the center coordinates of the loaded containers along the direction of a preset axis under the local packing scheme corresponding to each node;
weighting and summing the total volume of the wasted space, the average volume of the loaded containers and the component of the center coordinates of the loaded containers along the direction of a preset axis to obtain the score of the node;
determining the node with the highest or lowest priority according to the score of each node; wherein the priority of the node is positively correlated with the score of the node.
5. The method of claim 3, further comprising:
when the target vehicle has available space for accommodating at least one container, judging whether a first type of container exists in the containers to be loaded; the first type of container is a sleeve machine;
if the first type of container to be loaded exists, stacking a plurality of containers to be loaded in the length direction and the height direction of the container to obtain stacked complex blocks;
placing the complex block in the available space, and if the complex block is successfully placed, determining the complex block as a child node of a corresponding node of a previous cargo box to be loaded; and if the placement is unsuccessful, regenerating the complex block.
6. The method of claim 5, further comprising:
if the first type of container to be loaded does not exist, judging whether a second type of container to be loaded exists or not; the second type of container is a discrete piece;
if a second type of container to be loaded exists, stacking a plurality of containers to be loaded in the length and height direction of the container to obtain stacked simple blocks;
placing the simple block in the available space, and if the simple block is successfully placed, determining the simple block as a child node of a corresponding node of the previous container to be loaded; and if the placement is unsuccessful, regenerating the simple block.
7. The method according to any one of claims 1-6, wherein determining at least one third binning scheme from the plurality of second binning schemes comprises:
determining the space utilization rate and the geometric center position of the container corresponding to each second packing scheme according to the placement mode of the container in each second packing scheme;
determining at least one third packing scheme according to the space utilization rate and/or the geometric center position of the packing box; the third packing scheme is a second packing scheme which meets preset requirements in terms of space utilization rate and/or geometric center position of the packing box.
8. A boxing task processing apparatus, comprising:
the acquisition module is used for acquiring boxing task information; the boxing task information comprises: container information and truck information;
the first determining module is used for determining a first packing scheme of the front N-m trucks through a greedy algorithm and a tree search algorithm according to the cargo box information and the truck information, and obtaining the total volume of the remaining cargo boxes to be loaded corresponding to the first packing scheme; n is the number of trucks required for loading all containers; the N-m trucks are the N-m trucks with the largest available capacity at present; the tree search algorithm represents a tree search algorithm meeting the limited search width under the preset container placement rule;
the second determining module is used for determining a plurality of truck combinations according to the total volume of the remaining to-be-loaded cargo containers, wherein each truck combination comprises m trucks, determining a plurality of second loading schemes corresponding to each truck combination through a tree search algorithm, and determining at least one third loading scheme from the plurality of second loading schemes; the third boxing scheme is a boxing scheme meeting preset conditions in the second boxing scheme;
and the combination module is used for combining at least one third boxing scheme with the first boxing scheme respectively to obtain at least one final boxing scheme.
9. A boxing task processing apparatus, comprising: a memory and at least one processor;
the memory stores computer-executable instructions;
the at least one processor executing the computer-executable instructions stored by the memory causes the at least one processor to perform the method of binning task processing according to any of claims 1-7.
10. A computer-readable storage medium having stored thereon computer-executable instructions which, when executed by a processor, implement the method of casing task processing according to any one of claims 1-7.
Priority Applications (2)
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|---|---|---|---|
| CN202111320411.5A CN114091740A (en) | 2021-11-09 | 2021-11-09 | Boxing task processing method, device and equipment |
| PCT/CN2022/110321 WO2023082728A1 (en) | 2021-11-09 | 2022-08-04 | Container loading task processing method and apparatus, and device |
Applications Claiming Priority (1)
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| CN202111320411.5A CN114091740A (en) | 2021-11-09 | 2021-11-09 | Boxing task processing method, device and equipment |
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| WO (1) | WO2023082728A1 (en) |
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| CN114684626A (en) * | 2022-04-25 | 2022-07-01 | 阿帕数字科技有限公司 | Three-dimensional boxing method and device for regular objects and electronic equipment |
| CN114819426A (en) * | 2022-07-01 | 2022-07-29 | 深圳市海清视讯科技有限公司 | Cargo loading scheme determining method, device, equipment and storage medium |
| WO2023082728A1 (en) * | 2021-11-09 | 2023-05-19 | 青岛海尔科技有限公司 | Container loading task processing method and apparatus, and device |
| CN116228838A (en) * | 2023-05-10 | 2023-06-06 | 深圳大学 | Object boxing reinforcement learning method and related device based on visual detection |
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| CN103761635A (en) * | 2014-01-14 | 2014-04-30 | 大连理工大学 | Three-dimensional multi-box specially-structured cargo loading optimizing method |
| CN104915817A (en) * | 2015-05-26 | 2015-09-16 | 亿赞普(北京)科技有限公司 | Loading method and apparatus for container |
| CN106022506A (en) * | 2016-05-04 | 2016-10-12 | 浙江大学 | Portable light sensing currency detector |
| US11111090B2 (en) * | 2019-03-08 | 2021-09-07 | Verizon Connect Development Limited | Load planning optimization using automated 3D packing |
| CN110077772B (en) * | 2019-05-27 | 2020-10-23 | 上海维祥信息技术有限公司 | Pallet assembling method and application thereof |
| CN111047100B (en) * | 2019-12-17 | 2020-10-09 | 广东工业大学 | Method and system for packing logistics containers |
| CN111768151A (en) * | 2020-06-28 | 2020-10-13 | 战马物流(苏州)有限公司 | Vehicle loading method and system for loading cargoes |
| CN114091740A (en) * | 2021-11-09 | 2022-02-25 | 青岛海尔科技有限公司 | Boxing task processing method, device and equipment |
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2021
- 2021-11-09 CN CN202111320411.5A patent/CN114091740A/en active Pending
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- 2022-08-04 WO PCT/CN2022/110321 patent/WO2023082728A1/en unknown
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| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2023082728A1 (en) * | 2021-11-09 | 2023-05-19 | 青岛海尔科技有限公司 | Container loading task processing method and apparatus, and device |
| CN114684626A (en) * | 2022-04-25 | 2022-07-01 | 阿帕数字科技有限公司 | Three-dimensional boxing method and device for regular objects and electronic equipment |
| CN114684626B (en) * | 2022-04-25 | 2024-04-09 | 阿帕数字科技有限公司 | Three-dimensional boxing method and device for regular objects and electronic equipment |
| CN114819426A (en) * | 2022-07-01 | 2022-07-29 | 深圳市海清视讯科技有限公司 | Cargo loading scheme determining method, device, equipment and storage medium |
| CN114819426B (en) * | 2022-07-01 | 2022-12-09 | 深圳市海清数字技术有限公司 | Cargo loading scheme determining method, device, equipment and storage medium |
| CN116228838A (en) * | 2023-05-10 | 2023-06-06 | 深圳大学 | Object boxing reinforcement learning method and related device based on visual detection |
| CN116228838B (en) * | 2023-05-10 | 2024-03-08 | 深圳大学 | Object boxing reinforcement learning method and related device based on visual detection |
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| WO2023082728A1 (en) | 2023-05-19 |
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