CN112183954A

CN112183954A - Method and device for acquiring loading scheme of goods

Info

Publication number: CN112183954A
Application number: CN202010944782.XA
Authority: CN
Inventors: 童夏良; 胡骞; 张甡
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2020-09-10
Filing date: 2020-09-10
Publication date: 2021-01-05
Anticipated expiration: 2040-09-10

Abstract

The application provides a method and a related device for acquiring a loading scheme of cargos. According to the technical scheme, a double-layer loop search framework is used, the loading rate which the vehicles should reach is iterated through the outer layer loop, the number of the picking points which each vehicle corresponds to is iterated through the inner layer loop, and the path planning problem and the loading problem are solved through the related search algorithm, so that the optimal running route of the vehicles is achieved under the condition that the loading rate of the vehicles is guaranteed.

Description

Method and device for acquiring loading scheme of goods

Technical Field

The present application relates to the field of logistics freight and, more particularly, to a method and apparatus for obtaining loading schemes for cargo.

Background

Cargo loading and distribution refers to the process of distributing cargo from multiple pick-up points, such as cartons, wooden boxes, pallets or wooden axles, to the appropriate container vehicles. As the volume of cargo increases, the freight industry is increasingly concerned about the cost of cargo transportation. In particular, the freight industry desires that the cost of freight transportation be reduced.

The low cost freight transportation cost requires that the travel path of the vehicle is shorter on the basis of using fewer vehicles. Therefore, how to transport the goods at the pick-up point to the destination port by fewer vehicles through a shorter travel path is an urgent technical problem to be solved.

Disclosure of Invention

The application provides a method and a related device for acquiring a loading scheme of cargos. The loading scheme obtained by the technical scheme can use fewer vehicles to deliver goods in the goods pick-up point through a shorter driving path.

In a first aspect, the present application provides a method of obtaining a loading solution for cargo. The method comprises the following steps: initializing a goods pick-up point to be delivered to one or more goods pick-up points input by a user; initializing the loading rate which each vehicle in the vehicles required for transporting the goods in the goods pick-up point to be delivered should reach; initializing the number of the goods picking points corresponding to each vehicle in the vehicles required for transporting the goods in the goods picking points to be delivered; step four, determining a loading scheme of each vehicle according to the number of the corresponding goods picking points of each vehicle in the required vehicles; step five, judging whether the actual loading rate of at most one vehicle in the required vehicles for transporting the cargos according to the corresponding loading scheme is smaller than the loading rate which should be achieved, if so, executing step eight, otherwise, setting the pick-up points to be delivered as all pick-up points corresponding to all the vehicles with the actual loading rate smaller than the loading rate which should be achieved in the required vehicles, increasing the number of pick-up points corresponding to each vehicle in the vehicles for transporting the cargos in the pick-up points to be delivered, and executing step six; step six, judging whether the number of the added picking points is larger than the number of the picking points to be delivered, if so, executing the step seven, otherwise, executing the step four again; step seven, setting the goods taking points to be delivered as the one or more goods taking points, reducing the loading rate which each vehicle in the vehicles required for transporting the goods in the goods taking points to be delivered should reach, and starting to execute from the step three times; and step eight, outputting the loading scheme of each vehicle in the vehicles required for distributing the goods in the one or more pick-up points.

The method determines the loading scheme of the vehicles through two layers of loops, wherein the outer layer loop starts to iterate the loading rate of the vehicles from a larger loading rate, the loading rate of each vehicle is preferentially ensured, and the number of the required vehicles is minimized; the inner layer cycle starts iteration from fewer picking points corresponding to each vehicle, and the number of the picking points in each vehicle access path is ensured to be as small as possible, so that the running distance of the vehicle is minimized.

With reference to the first aspect, in a first possible implementation manner, between step four and step five, the method further includes: judging whether the actual loading rate of each vehicle in the required vehicles for transporting the goods according to the corresponding loading scheme is greater than the maximum loading rate, if so, executing the step nine, otherwise, executing the step five; and step nine, outputting prompt information of goods failure of the loading scheme.

With reference to the first aspect or the first possible implementation manner, in a second possible implementation manner, the determining a loading scheme for each vehicle according to the number of pick-up points corresponding to each vehicle in the required vehicles includes: determining a goods pick-up point corresponding to each vehicle and a path for each vehicle to visit the corresponding goods pick-up point according to a preset target of each vehicle and the number of the goods pick-up points corresponding to each vehicle through a dynamic planning algorithm; and determining the placement position of the goods in the pick-up point corresponding to each vehicle in each vehicle according to the size of the goods in the pick-up point corresponding to each vehicle and the path of each vehicle accessing the corresponding pick-up point.

With reference to the second possible implementation manner, in a third possible implementation manner, the preset target of each vehicle includes a shortest travel path of each vehicle accessing a corresponding pick-up point.

With reference to the second possible implementation manner or the third possible implementation manner, in a fourth possible implementation manner, the determining, according to the size of the goods in the pick-up point corresponding to each vehicle and the path of each vehicle accessing the corresponding pick-up point, the placement position of the goods in the pick-up point corresponding to each vehicle in each vehicle includes: and determining the placement position of each cargo in each pick-up point corresponding to each vehicle in each vehicle according to the size of the cargo in the pick-up point corresponding to each vehicle and the path of each vehicle accessing the corresponding pick-up point by using a three-dimensional loading algorithm.

With reference to the fourth possible implementation manner, in a fifth possible implementation manner, the three-dimensional loading algorithm includes any one of a tree search algorithm, a heuristic algorithm, a meta heuristic algorithm, and a reinforcement learning algorithm.

With reference to the fourth or fifth possible implementation manner, in a sixth possible implementation manner, the loading rate of each of the required vehicles when transporting goods according to the corresponding loading scheme is calculated by: calculating the loading space required by all goods in all the goods picking points corresponding to each vehicle according to the placing position of each goods in each goods picking point corresponding to each vehicle in each vehicle; and calculating the loading rate of each vehicle for transporting goods according to the corresponding loading scheme according to the required loading space and the loading space of each vehicle.

With reference to the fourth or fifth possible implementation manner, in a sixth possible implementation manner, the loading rate of each of the required vehicles when transporting goods according to the corresponding loading scheme is calculated by: calculating the loading space required by all goods in each goods picking point corresponding to each vehicle and the contact area between the goods in each goods picking point and the goods in the adjacent goods picking points; calculating the loading space required by all goods in all the pick-up points corresponding to each vehicle according to the loading space required by the goods in each pick-up point corresponding to each vehicle and the contact area between the goods in each pick-up point and the goods in the adjacent pick-up points; and calculating the loading rate of each vehicle for transporting the cargos according to the corresponding loading scheme according to the loading space required by all cargos in all the pick-up points corresponding to each vehicle and the loading space of each vehicle.

The implementation mode is based on the number of the loaded meters of the goods in the vehicle, and a three-dimensional loading method is not used, so that the loading rate of the vehicle can be calculated more quickly, and the calculation efficiency of the loading scheme of the goods at the goods pick-up point can be improved.

In a second aspect, the present application provides an apparatus for obtaining a loading scheme for cargo, the apparatus comprising a processing module and an output module. The processing module is used for executing steps one to seven of the following steps, and the output module is used for executing step eight of the following steps: initializing a goods pick-up point to be delivered to one or more goods pick-up points input by a user; initializing the loading rate which each vehicle in the vehicles required for transporting the goods in the goods pick-up point to be delivered should reach; initializing the number of the goods picking points corresponding to each vehicle in the vehicles required for transporting the goods in the goods picking points to be delivered; step four, determining a loading scheme of each vehicle according to the number of the corresponding goods picking points of each vehicle in the required vehicles; step five, judging whether the actual loading rate of at most one vehicle in the required vehicles for transporting the cargos according to the corresponding loading scheme is smaller than the loading rate which should be achieved, if so, executing step eight, otherwise, setting the pick-up points to be delivered as all pick-up points corresponding to all the vehicles with the actual loading rate smaller than the loading rate which should be achieved in the required vehicles, increasing the number of pick-up points corresponding to each vehicle in the vehicles for transporting the cargos in the pick-up points to be delivered, and executing step six; step six, judging whether the number of the added picking points is larger than the number of the picking points to be delivered, if so, executing the step seven, otherwise, executing the step four again; step seven, setting the goods taking points to be delivered as the one or more goods taking points, reducing the loading rate which each vehicle in the vehicles required for transporting the goods in the goods taking points to be delivered should reach, and starting to execute from the step three times; and step eight, outputting the loading scheme of each vehicle in the vehicles required for distributing the goods in the one or more pick-up points.

With reference to the first aspect, in a first possible implementation manner, between step four and step five, the method further includes: judging whether the actual loading rate of each vehicle in the required vehicles for transporting the goods according to the corresponding loading scheme is greater than the maximum loading rate, if so, executing the step nine, otherwise, executing the step five; and step nine, outputting prompt information of goods failure of the loading scheme. Wherein, the processing module is further configured to execute the above steps, and the output module is further configured to execute the step nine.

With reference to the first aspect or the first possible implementation manner, in a second possible implementation manner, the processing module is specifically configured to: determining a goods pick-up point corresponding to each vehicle and a path for each vehicle to visit the corresponding goods pick-up point according to a preset target of each vehicle and the number of the goods pick-up points corresponding to each vehicle through a dynamic planning algorithm; and determining the placement position of the goods in the pick-up point corresponding to each vehicle in each vehicle according to the size of the goods in the pick-up point corresponding to each vehicle and the path of each vehicle accessing the corresponding pick-up point.

With reference to the second possible implementation manner or the third possible implementation manner, in a fourth possible implementation manner, the processing module is specifically configured to: and determining the placement position of each cargo in each pick-up point corresponding to each vehicle in each vehicle according to the size of the cargo in the pick-up point corresponding to each vehicle and the path of each vehicle accessing the corresponding pick-up point by using a three-dimensional loading algorithm.

With reference to the fourth or fifth possible implementation manner, in a sixth possible implementation manner, the loading rate of each of the required vehicles when transporting goods according to the corresponding loading scheme is calculated by the processing module by executing the following method: calculating the loading space required by all goods in all the goods picking points corresponding to each vehicle according to the placing position of each goods in each goods picking point corresponding to each vehicle in each vehicle; and calculating the loading rate of each vehicle for transporting goods according to the corresponding loading scheme according to the required loading space and the loading space of each vehicle.

With reference to the fourth or fifth possible implementation manner, in a sixth possible implementation manner, the loading rate of each of the required vehicles when transporting goods according to the corresponding loading scheme is calculated by the processing module by executing the following method: calculating the loading space required by all goods in each goods picking point corresponding to each vehicle and the contact area between the goods in each goods picking point and the goods in the adjacent goods picking points; calculating the loading space required by all goods in all the pick-up points corresponding to each vehicle according to the loading space required by the goods in each pick-up point corresponding to each vehicle and the contact area between the goods in each pick-up point and the goods in the adjacent pick-up points;

and calculating the loading rate of each vehicle for transporting the cargos according to the corresponding loading scheme according to the loading space required by all cargos in all the pick-up points corresponding to each vehicle and the loading space of each vehicle.

In a third aspect, an apparatus for obtaining a loading solution for a vehicle is provided, the apparatus comprising a processor; the processor is used for executing the program stored in the memory; the processor and the transceiver are adapted to perform the method of the first aspect or any one of its implementations when the program stored in the memory is executed.

Optionally, the apparatus may further comprise the memory.

In a fourth aspect, there is provided a computer readable medium storing program code for execution by a device, the program code for performing the method of the first aspect or any one of its implementations.

In a fifth aspect, there is provided a computer program product comprising instructions which, when run on a computer, cause the computer to perform the method of the first aspect or any one of its implementations.

A sixth aspect provides a chip, where the chip includes a processor and a data interface, and the processor reads instructions stored in a memory through the data interface to execute the method in the first aspect or any one of the implementation manners.

Optionally, as an implementation manner, the chip may further include a memory, where instructions are stored in the memory, and the processor is configured to execute the instructions stored in the memory, and when the instructions are executed, the processor is configured to execute the method in the first aspect or any one of the implementation manners.

In a seventh aspect, a computing device is provided, the computing device comprising: a memory for storing a program; a processor for executing the program stored in the memory, the processor being configured to perform the method of the first aspect or any one of the implementations when the program stored in the memory is executed.

The method in the embodiment of the application determines the loading scheme of the vehicle through two layers of loops, wherein the outer layer loop iterates the loading rate of the vehicle from a larger loading rate, the loading rate of each vehicle is preferentially ensured, and the number of required vehicles is minimized; the inner layer cycle starts iteration from fewer picking points corresponding to each vehicle, and the number of the picking points in each vehicle access path is ensured to be as small as possible, so that the running distance of the vehicle is minimized.

Drawings

Fig. 1 is a schematic diagram of an application scenario to which the technical solution of the embodiment of the present application may be applied.

Fig. 2 is a schematic flow chart of a method of acquiring a loading scheme of cargo according to an embodiment of the present application.

FIG. 3 is an illustration of a quick load of one embodiment of the present application.

Fig. 4 is a schematic flow chart of a method of acquiring a loading scheme of cargo according to another embodiment of the present application.

Fig. 5 is a schematic diagram illustrating a correspondence relationship between a vehicle loading rate and a number of pick-up points accessed by a vehicle according to an embodiment of the present application.

Fig. 6 is a schematic block diagram of an apparatus for acquiring a loading scheme of cargo according to an embodiment of the present application.

Fig. 7 is a schematic block diagram of an apparatus for acquiring a loading scheme of goods according to another embodiment of the present application.

FIG. 8 is a schematic diagram of a computer program product of one embodiment of the present application.

Detailed Description

In order to facilitate understanding of the technical solutions in the present application, some terms or phrases referred to in the embodiments of the present application will be described below.

Cargo: the product packaged in a packaging material, such as a carton or wooden box, is the lowermost shipping or delivery unit.

A goods picking point: a warehouse or factory for storing goods to be delivered.

Freight note: which may also be referred to as a shipping manifest, contains identifying information (e.g., name and/or location) of the pick points contained in the current shipping task and information (e.g., size, shape of each item) of the items in each pick point.

The loading scheme is as follows: including the path of the vehicle to access the pick-up points and the spatial placement of each cargo in each pick-up point in the container being transported by the vehicle.

Loading rate of vehicle: refers to the volume of the cargo as a percentage of the rated volume of the vehicle or the weight of the cargo as a percentage of the rated load of the vehicle.

Loading the rice number: the length of the cargo in the container transported by the vehicle is seen from the direction of the vehicle head to the direction of the parking space.

Destination port: the transportation destination of the cargo may be, for example, a port, an airport, a train station, or the like.

Fig. 1 is a schematic diagram of an application scenario of the technical solution of the embodiment of the present application. The application scenario may include multiple pick-up points and a destination port. It can be understood that this application scenario is only an example, and other application scenarios of the technical solution of the embodiment of the present application may include fewer pick-up points or more destination ports.

The technical scheme of the embodiment of the application aims to obtain a loading scheme which uses less vehicles and enables each vehicle to pass through a shorter path as much as possible so as to transport all goods in the goods taking points to be delivered to the destination port.

In view of the transportation requirements, the application provides a double-layer circular search framework capable of automatically integrating the delivery points to be delivered, and preferentially searches the solution space of the high-quality part, namely preferentially searches from a small number of vehicles and a short path so as to obtain a high-quality loading scheme.

In the double-layer cyclic search framework provided by the application, the loading rate which the outer-layer cyclic iteration vehicle should reach, the number of the picking points which the inner-layer cyclic iteration vehicle corresponds to are used for solving the path planning problem and the loading problem by using the related search algorithm, so that the optimal driving route of the vehicle is realized under the condition of ensuring the loading rate of the vehicle. In the embodiment of the present application, the pick-up point corresponding to each vehicle refers to a pick-up point where the vehicle transports goods, or a pick-up point corresponds to which vehicle, goods in the pick-up point are transported by the vehicle, and the pick-up point corresponding to one vehicle may be one or multiple.

Specifically, the outer loop iterates the loading rates of the vehicles from a larger loading rate, the loading rate of each vehicle is preferentially ensured, and the number of required vehicles is minimized; the inner layer cycle starts iteration from fewer picking points corresponding to each vehicle, and the number of the picking points in each vehicle access path is ensured to be as small as possible, so that the running distance of the vehicle is minimized.

In the inner-layer loop, a picking point combination corresponding to the vehicle can be obtained by clustering through algorithms such as a dynamic programming algorithm, a heuristic algorithm or a meta-heuristic algorithm and the like according to a preset target (for example, the shortest driving path of the vehicle) based on the number of picking points corresponding to the vehicle, wherein the picking point combination refers to which picking points the vehicle corresponds and a path for accessing the corresponding picking points, and the path for accessing the corresponding picking points by the vehicle can also be understood as the sequence for accessing the corresponding picking points; and in the inner loop, the three-dimensional loading scheme of the goods in the goods taking points corresponding to the vehicle in the container of the vehicle can be solved through algorithms such as a tree search algorithm, a heuristic algorithm, a meta-heuristic algorithm or a reinforcement learning algorithm.

Fig. 2 is a schematic flow chart of a method of obtaining a shipping scheme for a cargo according to one embodiment of the present application. As shown in fig. 2, the method may include S210 to S270.

And S210, initializing the pick-up points to be delivered to one or more pick-up points input by the user.

As an example, a pick-up order input by a user may be stored in a memory, and when the method according to the embodiment of the present application is executed, the relevant information of the pick-up point in the pick-up order may be read from the memory, and the pick-up point where the goods need to be transported in the current transportation task is initialized or set as the pick-up point recorded in the pick-up order. The pick-up point of the goods to be transported in the transportation task can be called as the final pick-up point to be delivered.

Alternatively, the user-entered bill of lading may be received by the means for obtaining a delivery plan for the cargo from another device or means via the communication interface.

S220, initializing the loading rate which each vehicle in the vehicles needed for transporting the goods in the goods taking point to be delivered should reach.

That is, the loading rate that each vehicle should reach for transporting all the goods in the final delivery pick-up point to be delivered is set in advance. Generally, a larger expected loading rate is initially set for each vehicle so as to search from the larger expected loading rate, so that the number of required vehicles can be reduced as much as possible, and the transportation cost can be reduced.

As an example, an initial loading rate that each vehicle should reach may be set in advance, so that the loading rate that each vehicle should reach may be initialized according to the initial loading rate. For example, the user may input an initial loading rate for each vehicle so that, upon initialization, the loading rate that each vehicle should achieve may be initialized to the initial loading rate.

For example, the loading rate that each vehicle should achieve may be initialized to 100%.

And S230, initializing the number of the pick-up points corresponding to each vehicle in the vehicles required for transporting the goods in the pick-up points to be delivered.

That is, the number of pick-up points corresponding to each vehicle for carrying all the cargos in the pick-up points to be finally delivered is set in advance. Generally speaking, a smaller number of pick-up points is initially set for each vehicle, so that a search is performed from the smaller number of pick-up points, and thus the travel route of the vehicle can be reduced as much as possible, and the transportation cost can be reduced.

As an example, an initial number of pick-up points corresponding to each vehicle may be preset, so that the number of pick-up points corresponding to each vehicle may be initialized according to the initial number of pick-up points. For example, the user may input an initial pick-up point number corresponding to each vehicle, so that, at the time of initialization, the pick-up point number corresponding to each vehicle may be initialized to the initial pick-up point number.

For example, the number of pick-up points corresponding to each vehicle may be initialized to 1.

S240, determining a loading scheme of each vehicle according to the number of the pick-up points corresponding to each vehicle in the required vehicles.

That is, based on the number of pick-up points corresponding to each vehicle, it is determined which pick-up points each vehicle should visit, the route of each vehicle visiting the pick-up points (or, so to speak, the sequence of visiting the pick-up points), and how the cargo of each pick-up point is placed in the container of the vehicle when each vehicle visits the pick-up points.

When determining the loading scheme of each vehicle according to the number of pick-up points corresponding to each vehicle in the required vehicles, clustering the pick-up points to be currently allocated according to a preset target and the number of pick-up points corresponding to each vehicle to obtain a pick-up point combination corresponding to each vehicle and a path of the vehicle accessing the pick-up points, and then determining the placement position of the goods in the pick-up points in the vehicle according to the sequence of the pick-up point combination corresponding to each vehicle and the access pick-up points, wherein the pick-up point combination corresponding to each vehicle, the path of the access pick-up point combination and the placement position of the goods in the pick-up point combination can form the loading scheme of the vehicle, and the preset target can comprise the shortest travel path of each vehicle and/or the shortest travel time of each vehicle.

As an example, clustering the currently-to-be-delivered pick-up points according to a preset target and the number of pick-up points corresponding to each vehicle to obtain a pick-up point combination corresponding to each vehicle and a route of the vehicle to access the pick-up points may include: and determining the goods pick-up points corresponding to the vehicles and the paths of the vehicles accessing the corresponding goods pick-up points according to the preset target of each vehicle and the number of the goods pick-up points corresponding to the vehicles by a dynamic planning algorithm.

An exemplary method for determining the pick-up point corresponding to each vehicle and the route for each vehicle to visit the pick-up point is given below by taking the shortest route as an example.

Firstly, the number of the pick-up points corresponding to one vehicle is recorded as p, and for any two pick-up points i and j, the shortest path distance d (i, j, p) from i to j through the total p pick-up points (including the pick-up point i and the pick-up point j) is calculated by using a dynamic programming algorithm.

d(i,j,2)＝d_ijThe vehicle passes the shortest distance of 2 pick-up points. The shortest distance from the pickup point i to the pickup point j through a total of 2 pickup points (including the pickup point i and the pickup point j) is shown, which is the distance between the pickup point i and the pickup point j, and no other pickup point is shown in the middle.

d(i,j,p)＝min_{k,k≠i,k≠j}{d(i,k,p-1)+d_kjAnd the calculation formula of the shortest path when the vehicle passes through 2 or more pickup points. For example, d (i, j,3) ═ min_{k,k≠i,k≠j}{d(i,k,3-1)+d_kj}＝min_{k,k≠i,k≠j}{d_ik+d_kj}, 3 indicates that the vehicle has passed 3 pick-up points in total, but subtracted the pick-up pointi and a goods picking point j, wherein the middle of the vehicle only passes through 1 goods picking point, the set k only has the one goods picking point, the shortest driving distance of the vehicle is from the goods picking point i to the goods picking point k to the goods picking point j, and the shortest path is d_ik+d_kjI.e. the distance from the pick-up point i to the pick-up point k plus the distance from the pick-up point k to the pick-up point j. And analogizing the calculation mode of the shortest path of more than 3 goods picking points in turn.

Then, the pick-up point combination corresponding to the shortest path d (i, j, p) from the pick-up point i to the pick-up point j through total p pick-up points (including the pick-up point i and the pick-up point j) is calculated, wherein p is more than or equal to 2 and less than or equal to N.

S (i, j,2) ═ i, j, i.e., the vehicles pass through only 2 pick-up points, and the corresponding shortest path combination is themselves.

S(i,j,p)＝S(i,k^-P-1) U { j }, where k is^-＝min{d(i,k,p-1)+d_kjAnd k is not equal to i, k is not equal to j, when the vehicle passes through 2 or more pickup points, the shortest path corresponds to a calculation formula of the pickup point combination, namely the actual optimal access pickup point combination and the access sequence of the vehicle can be calculated through the formula. For example, S (i, j,3) ═ S (i, k)^-,3-1)∪{j}＝S(i,k^-,2)∪{j}＝{i,k^-}∪{j}＝{i,k^-J,3 means that the vehicle passes through 3 delivery points in total, and two delivery points of a delivery point i and a delivery point j are subtracted, and only 1 delivery point actually passes through the middle of the vehicle, and then the set k is obtained^-Only at the pick-up point, the shortest driving distance of the vehicle is from the pick-up point i to the pick-up point k^-Then to the picking point j, the corresponding picking point combination is { i, k }^-J) the 3 pick points. And analogizing the calculation mode of the shortest path of more than 3 goods picking points in turn.

As an example, determining the placement position of the goods in the pick-up point in the vehicle according to the pick-up point combination corresponding to each vehicle and the sequence of accessing the pick-up point may include: and determining the placement position of the goods in the pick-up point corresponding to each vehicle in each vehicle according to the size of the goods in the pick-up point corresponding to each vehicle and the path of each vehicle accessing the corresponding pick-up point.

The prior art can be referred to in an implementation manner of determining the placement position of the goods in the pick-up point corresponding to each vehicle in each vehicle according to the size of the goods in the pick-up point corresponding to each vehicle and the path of each vehicle accessing the corresponding pick-up point.

For example, the determining the placement position of the goods in the pick-up point corresponding to each vehicle in each vehicle according to the size of the goods in the pick-up point corresponding to each vehicle and the path of each vehicle accessing the corresponding pick-up point may include: and determining the placement position of each cargo in each pick-up point corresponding to each vehicle in each vehicle according to the size of the cargo in the pick-up point corresponding to each vehicle and the path of each vehicle accessing the corresponding pick-up point by using a three-dimensional loading algorithm.

Optionally, the three-dimensional loading algorithm may include any one of a tree search algorithm, a heuristic algorithm, a meta heuristic algorithm, and a reinforcement learning algorithm.

In the following, an implementation manner of determining a placement position of each cargo in each pick-up point corresponding to each vehicle in the vehicle is described by taking a three-dimensional loading algorithm including a tree search algorithm as an example.

Firstly, initializing a three-dimensional space with a container of the vehicle as L _ k × W _ k × H _ k, and establishing a coordinate system with the left front lower corner of the three-dimensional space as an origin and with the length, width and height as X, Y, Z axes respectively.

The items to be loaded for each pick-up point or two pick-up points adjacent in succession are then constructed as simple pieces (for example cubes of the same size) and as complex pieces (for example cubes of different sizes), wherein the goods of the preceding pick-up point are below and the goods of the following pick-up point are above.

And finally, determining the loading sequence of the simple blocks and/or the complex blocks formed in the last step based on business constraints and rules, and determining specific coordinates of the blocks in the container by using algorithms such as tree search and the like, so as to obtain the placement position of the goods in each goods pick-up point.

One example of a business constraint and rule may include: when loading goods, the cylindrical goods are loaded firstly, and the carton goods are loaded finally; another example may include: the weight of the cargo on which it may be stacked.

And S250, judging whether the actual loading rate of at most one vehicle in the required vehicles for conveying the cargos according to the corresponding loading scheme is less than the loading rate to be reached, if so, executing S280, otherwise, setting the pick-up points to be distributed as all pick-up points corresponding to all the vehicles with the actual loading rate less than the loading rate to be reached in the required vehicles, increasing the number of the pick-up points corresponding to each vehicle in the vehicles required for conveying the cargos in the pick-up points to be distributed, and executing S260.

When the number of the pick-up points corresponding to each vehicle in the vehicles required for transporting the goods in the pick-up points to be delivered is increased, the increased number may be configured in advance, for example, 1 pick-up point may be added each time.

In this step, if the loading rates of at least two of the vehicles in the required vehicles for transporting the goods according to the corresponding loading schemes are smaller than the loading rates that should be achieved, it is indicated that the number of pickup points allocated to each of the at least two vehicles is too small, the number of pickup points corresponding to each of the vehicles in the required vehicles for transporting the goods in the pickup points to be delivered should be increased, the loading schemes of the vehicles with the other loading rates satisfying the requirement are recorded, the pickup points corresponding to the vehicles satisfying the requirement are deleted from the pickup points to be delivered, that is, the pickup points to be delivered are set as all the pickup points corresponding to the at least two vehicles, and S260 is performed.

If the loading rate of at most one of the required vehicles for transporting the goods according to the corresponding loading scheme is less than the loading rate to be achieved, it means that the current loading scheme of each vehicle can make the running cost as low as possible and the loading rate as large as possible, and then S280 can be executed.

In this embodiment, when calculating the actual loading rate of each vehicle, the actual loading rate of the vehicle may be calculated by using a three-dimensional loading method. For example, the loading rate of the vehicle when the goods in all the pick-up points corresponding to the vehicle are loaded in the vehicle can be calculated according to the placing position of each goods in each pick-up point recorded in the loading scheme.

Alternatively, in the present embodiment, the actual loading rate of each vehicle may be calculated using a quick loading method. The fast loading method is realized according to the following principle: in actual loading, the goods in different delivery points, except the goods at the interface, are not stacked in a crossed manner, so that the loading meters of the goods in the delivery point in the vehicle container can be calculated once for the goods in each delivery point, and thus when the actual loading rate of the goods in the delivery point accessed by each vehicle is calculated, the upper and lower bounds (namely the maximum value and the minimum value) of the actual loading rate of each vehicle can be quickly obtained by adding the loading meters of the delivery points.

As shown in fig. 3, the pick-up points to be delivered include a pick-up point a and a pick-up point B. The loading meter number of the goods in the pick-up point A is denoted as LM _ A, the meter number of the interface of the pick-up point A is denoted as C _ A, the loading meter number of the goods in the pick-up point B is denoted as LM _ B, and the meter number of the interface of the pick-up point B is denoted as C _ B, so that when the loading meter number of the goods after the combination of the pick-up point A and the pick-up point B is calculated, the upper bound and the lower bound of the loading rate of the combination of the pick-up point A and the pick-up point B can be quickly calculated by the following method.

LM _ a + LM _ B;

the lower bound is LM _ a + LM _ B-min { C _ a, C _ B }, where min { } denotes a minimum value operation.

And calculating the upper and lower bounds of the actual loading rate of the vehicle according to the upper and lower bounds obtained by the calculation and the size of the container of the vehicle. Because the calculation processes are all arithmetic calculation, compared with three-dimensional loading, the time can be ignored, and therefore, the calculation time can be saved.

And S260, judging whether the number of the increased picking points is larger than that of the picking points to be distributed or not, if so, executing S270, otherwise, starting to execute from S240.

That is, if the number of pick-up points allocated per vehicle is greater than the number of remaining pick-up points to be allocated, it is said that for these remaining pick-up points to be allocated, a suitable loading solution cannot be found for each vehicle such that the loading rate of each vehicle satisfies the currently specified achievable loading rate. In this case, S270 is executed to reduce the loading rate that each vehicle should reach and to newly allocate pick-up points from all the pick-up points input by the user to acquire the loading plan, otherwise S240 is executed to newly acquire the loading plan of each vehicle according to the increased number of pick-up points of each vehicle.

S270, setting the pick-up points to be delivered as the one or more pick-up points, reducing a loading rate that each of the vehicles required for transporting the goods in the pick-up points to be delivered should reach, and resuming execution from S230.

The loading rate per reduction may be preset. For example, the loading rate per reduction may be set to 5%.

And S280, outputting a loading scheme of each vehicle in the vehicles required for distributing the goods in the one or more pick-up points.

For example, the loading scheme of each vehicle may be transmitted to other devices or apparatuses through a communication interface or a transmitter, or may be output through an output port of a display apparatus, a voice output apparatus, or the like.

Optionally, the method of this embodiment may further include the following operations between S240 and S250: judging whether the actual loading rate of each vehicle in the required vehicles for transporting the goods according to the corresponding loading scheme is greater than the maximum loading rate, if so, executing the step nine, otherwise, executing the step five; and step nine, outputting prompt information of goods failure of the loading scheme.

That is, if the opportunity loading rate of each vehicle in all the vehicles is greater than the maximum loading rate that can be achieved by the vehicle, no matter whether the pick-up point corresponding to the vehicle is continuously increased or the loading rate that the vehicle should achieve is reduced, it is impossible to search for a satisfactory loading scheme, and at this time, the search may be ended, and a prompt message indicating that the search failed may be output. The method can know the allocation failure in advance, and avoid useless search, thereby avoiding the waste of computing resources.

Fig. 4 is a schematic flow chart of a method of acquiring a loading scheme of cargo according to another embodiment of the present application. As shown in fig. 4, the method includes S410 to S495. The steps in the protocol are performed sequentially, unless otherwise specified.

S410, initializing the loading rate theta and descending step length steppheta which each vehicle should reach, and initializing the number P of accessible pick-up points and ascending step length steppckup of each vehicle.

For example, the loading rate that should be achieved may be initialized to 100% and the step down may be set to 5%. For example, the number of pick-up points accessible to each vehicle is initialized to 0 and the up-step is set to 1.

And S420, controlling the loading rate of the vehicle by the outer layer circulation. Specifically, the load rate to be achieved is reset according to the load rate to be achieved and the descent step that are currently set. For example, in the first off-cycle, the loading rate θ that the vehicle should achieve is 100% -5% -95%, and in the second off-cycle, the loading rate θ that the vehicle should achieve is 95% -5% -90%.

And S430, circularly controlling the number of the goods picking points visited by each vehicle by the inner layer. Specifically, the number of the pickup points is reset according to the currently set number of the pickup points and the descending step length. For example, in the first round of the inner cycle, the number P of the picking points is 0+ 1-1, and in the second round of the inner cycle, the number P of the picking points is 1+ 1-2.

And S440, carrying out cargo lifting point clustering and three-dimensional loading according to the loading rate of the vehicles and the number of the accessed cargo lifting points to obtain a loading scheme of each vehicle.

The implementation manner of performing the picking point clustering and the three-dimensional loading to obtain the loading scheme of each vehicle can refer to the foregoing contents, and details are not described herein.

For example, if there are 3 pick-up points to be delivered, respectively A, B and C, and each pick-up point can be loaded by one vehicle, then the loading rates of the 3 vehicles, respectively RateA, RateB and RateC, can be obtained.

S450, judging whether the actual loading rate of the vehicle is larger than the loading rate theta to be achieved. If the actual loading rate of the vehicle is larger than theta, executing S460; otherwise, S480 is performed.

For example, RateA is greater than θ, but RateB and RateC are less than θ, the loading scheme corresponding to RateA may be output, and pick-up point a may be deleted from the to-be-delivered supply points. At this time, the remaining B and C of the pick-up points are to be delivered, and returning to S430, setting P + 1+ 2, i.e., attempting to load two pick-up points of B and C using one vehicle.

At this time, since P is already equal to the number 2 of remaining pick-up points to be delivered, regardless of whether a vehicle can be loaded or not, the loading rate can be directly outputted, that is, a vehicle is loaded with the goods in the two pick-up points, and the process is ended. In other words, this is because the P value cannot be increased at this time, and lowering the loading rate threshold does not change the loading result, so the search can be ended directly. However, if the number of remaining pick-up points to be delivered is greater than 2, it is possible to proceed back to S430, trying the loading scheme when P +1 is 3.

And S460, recording the loading scheme of the vehicle with the actual loading rate larger than theta, and deleting the pick-up point corresponding to the vehicle from the to-be-loaded pick-up point list.

S470, judging whether the delivery points to be delivered are not loaded, namely whether the remaining delivery points exist, if so, executing S480, otherwise, executing S495.

And S480, judging whether the number of the pick-up points accessed by each vehicle is greater than the total number N of the pick-up points to be delivered, if so, executing S490, otherwise, returning to S430, namely increasing the number P of the pick-up points accessed by each vehicle, and continuing to generate a loading scheme and judging.

S490, the number of pick-up points visited by each vehicle is reset to 0, and the process is repeated from S420. Wherein previously recorded loading scenarios can be emptied.

And S495, ending the search and outputting the loading scheme.

Aiming at the defects that the loading rate is improved iteratively/the transportation distance is reduced to cause longer running time and the effect cannot be guaranteed by continuously searching different loading schemes in the conventional scheme, the embodiment preferentially searches the solution space of a high-quality part by a double-layer cyclic search framework and target driving, so that a high-quality solution is obtained in a shorter time.

As shown in fig. 5, according to the technical solution of the present application, a solution space with a high loading rate and a small number of visited pick-up points can be preferentially searched, so that a loading solution with a high loading rate and a small number of visited pick-up points can be searched in a shorter time.

Further, the scheme of the embodiment is based on the number of the loaded goods in the vehicle, time-consuming three-dimensional loading is not needed, and the arithmetic time of the loading rate of the vehicle is rapidly calculated.

Fig. 6 is a schematic block diagram of an apparatus 600 for acquiring a loading scheme of cargo according to an embodiment of the present application. The apparatus 600 may include a processing module 610 and an output module 620. Wherein the processing module 610 may be implemented by a processor, and the output module 620 may be implemented by a communication interface, a transmitter or a display, or a voice output device (e.g., a microphone or a speaker).

In some examples, the apparatus 600 may be configured to perform the method shown in fig. 2, for example, the processing module 610 may be configured to perform S210 to S270, and the output module 620 may be configured to perform S280.

In another example, the apparatus 600 may be configured to perform the method shown in fig. 4, for example, the processing module 610 may be configured to perform S410 to S490, and the output module 620 may be configured to perform S495.

Fig. 7 is a schematic block diagram of an apparatus 800 for acquiring a loading scheme of cargo according to an embodiment of the present application. The apparatus 800 includes a processor 802, a communication interface 803, and a memory 804. One example of the apparatus 800 is a chip and another example of the apparatus 800 is a computing device.

The processor 802, memory 804, and communication interface 803 may communicate over a bus. The memory 804 has executable code stored therein, and the processor 802 reads the executable code in the memory 804 to perform a corresponding method. The memory 804 may also include other software modules required to run processes, such as an operating system. The operating system may be LINUX^TM，UNIX^TM，WINDOWS^TMAnd the like.

For example, executable code in memory 804 is used to implement the steps or operations in FIG. 2; the processor 802 reads the executable code in the memory 804 to perform S210 to S270 in fig. 2, and the communication interface 803 may perform S280.

For another example, the executable code in memory 804 is used to perform the method shown in FIG. 4; the processor 802 reads the executable code in the memory 804 to perform S410 to S490 in the method shown in fig. 4, and the communication interface 803 may perform S495.

The processor 802 may be a CPU, among others. The memory 804 may include volatile memory (volatile memory), such as Random Access Memory (RAM). The memory 804 may also include a non-volatile memory (2 NVM), such as a read-only memory (2 ROM), a flash memory, a Hard Disk Drive (HDD) or a Solid State Drive (SSD).

In some embodiments of the present application, the disclosed methods may be implemented as computer program instructions encoded on a computer-readable storage medium in a machine-readable format or encoded on other non-transitory media or articles of manufacture. Fig. 8 schematically illustrates a conceptual partial view of an example computer program product comprising a computer program for executing a computer process on a computing device, arranged in accordance with at least some embodiments presented herein. In one embodiment, the example computer program product 900 is provided using a signal bearing medium 901. The signal bearing medium 9018 may include one or more program instructions 902 that, when executed by one or more processors, may provide the functions or portions of the functions described above with respect to the methods shown in fig. 2 or fig. 4. Thus, for example, in the embodiment shown in fig. 2, one or more features of S210-S280 may be undertaken by one or more instructions associated with the signal bearing medium 901. As another example, referring to the embodiment shown in fig. 4, one or more features of S410-S495 may be undertaken by one or more instructions associated with the signal bearing medium 901.

In some examples, signal bearing medium 901 may comprise a computer readable medium 903, such as, but not limited to, a hard disk drive, a Compact Disc (CD), a Digital Video Disc (DVD), a digital tape, a memory, a read-only memory (ROM), a Random Access Memory (RAM), or the like. In some embodiments, the signal bearing medium 901 may comprise a computer recordable medium 904 such as, but not limited to, a memory, a read/write (R/W) CD, a R/W DVD, and the like. In some implementations, the signal bearing medium 901 may include a communication medium 905, such as, but not limited to, a digital and/or analog communication medium (e.g., a fiber optic cable, a waveguide, a wired communications link, a wireless communication link, etc.). Thus, for example, the signal bearing medium 901 may be communicated by a wireless form of communication medium 905 (e.g., a wireless communication medium conforming to the IEEE 802.11 standard or other transmission protocol). The one or more program instructions 902 may be, for example, computer-executable instructions or logic-implementing instructions. In some examples, the aforementioned computing devices may be configured to provide various operations, functions, or actions in response to program instructions 902 conveyed to the computing device by one or more of computer-readable medium 903, computer-recordable medium 904, and/or communication medium 905. It should be understood that the arrangements described herein are for illustrative purposes only. Thus, those skilled in the art will appreciate that other arrangements and other elements (e.g., machines, interfaces, functions, orders, and groupings of functions, etc.) can be used instead, and that some elements may be omitted altogether depending upon the desired results. In addition, many of the described elements are functional terms that may be implemented as discrete or distributed components or in conjunction with other components, in any suitable combination and location.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units 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 units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: u disk, removable hard disk, read only memory, random access memory, magnetic or optical disk, etc. for storing program codes.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method of obtaining a loading scheme for cargo, comprising:

initializing a goods pick-up point to be delivered to one or more goods pick-up points input by a user;

initializing the loading rate which each vehicle in the vehicles required for transporting the goods in the goods pick-up point to be delivered should reach;

initializing the number of the goods picking points corresponding to each vehicle in the vehicles required for transporting the goods in the goods picking points to be delivered;

step four, determining a loading scheme of each vehicle according to the number of the corresponding goods picking points of each vehicle in the required vehicles;

step five, judging whether the actual loading rate of at most one vehicle in the required vehicles for transporting the cargos according to the corresponding loading scheme is smaller than the loading rate which should be achieved, if so, executing step eight, otherwise, setting the pick-up points to be delivered as all pick-up points corresponding to all the vehicles with the actual loading rate smaller than the loading rate which should be achieved in the required vehicles, increasing the number of pick-up points corresponding to each vehicle in the vehicles for transporting the cargos in the pick-up points to be delivered, and executing step six;

step six, judging whether the number of the added picking points is larger than the number of the picking points to be delivered, if so, executing the step seven, otherwise, executing the step four again;

step seven, setting the goods taking points to be delivered as the one or more goods taking points, reducing the loading rate which each vehicle in the vehicles required for transporting the goods in the goods taking points to be delivered should reach, and starting to execute from the step three times;

and step eight, outputting the loading scheme of each vehicle in the vehicles required for distributing the goods in the one or more pick-up points.

2. The method of claim 1, further comprising, between step four and step five:

judging whether the actual loading rate of each vehicle in the required vehicles for transporting the goods according to the corresponding loading scheme is greater than the maximum loading rate, if so, executing the step nine, otherwise, executing the step five;

and step nine, outputting prompt information of goods failure of the loading scheme.

3. The method of claim 1 or 2, wherein determining the loading plan for each of the required vehicles based on the number of pick-up points corresponding to each vehicle comprises:

determining a goods pick-up point corresponding to each vehicle and a path for each vehicle to visit the corresponding goods pick-up point according to a preset target of each vehicle and the number of the goods pick-up points corresponding to each vehicle through a dynamic planning algorithm;

and determining the placement position of the goods in the pick-up point corresponding to each vehicle in each vehicle according to the size of the goods in the pick-up point corresponding to each vehicle and the path of each vehicle accessing the corresponding pick-up point.

4. The method of claim 3, wherein the predetermined goal for each vehicle comprises a shortest travel path for each vehicle to visit a corresponding pick-up point.

5. The method of claim 3 or 4, wherein the determining the placement position of the goods in the pick-up point corresponding to each vehicle in each vehicle according to the size of the goods in the pick-up point corresponding to each vehicle and the path of each vehicle accessing the corresponding pick-up point comprises:

and determining the placement position of each cargo in each pick-up point corresponding to each vehicle in each vehicle according to the size of the cargo in the pick-up point corresponding to each vehicle and the path of each vehicle accessing the corresponding pick-up point by using a three-dimensional loading algorithm.

6. The method of claim 5, wherein the three-dimensional loading algorithm comprises any one of a tree search algorithm, a heuristic algorithm, a meta heuristic algorithm, and a reinforcement learning algorithm.

7. The method according to claim 5 or 6, wherein the loading rate of each of the desired vehicles for transporting the cargo according to the corresponding loading scheme is calculated by:

calculating the loading space required by all goods in all the goods picking points corresponding to each vehicle according to the placing position of each goods in each goods picking point corresponding to each vehicle in each vehicle;

and calculating the loading rate of each vehicle for transporting goods according to the corresponding loading scheme according to the required loading space and the loading space of each vehicle.

8. The method according to claim 5 or 6, wherein the loading rate of each of the desired vehicles for transporting the cargo according to the corresponding loading scheme is calculated by:

calculating the loading space required by all goods in each goods picking point corresponding to each vehicle and the contact area between the goods in each goods picking point and the goods in the adjacent goods picking points;

calculating the loading space required by all goods in all the pick-up points corresponding to each vehicle according to the loading space required by the goods in each pick-up point corresponding to each vehicle and the contact area between the goods in each pick-up point and the goods in the adjacent pick-up points;

9. An apparatus for acquiring a loading scheme of goods, comprising a processing module for performing steps one to seven of the following steps and an output module for performing step eight of the following steps:

10. The apparatus of claim 9, further comprising, between step four and step five: judging whether the actual loading rate of each vehicle in the required vehicles for transporting the goods according to the corresponding loading scheme is greater than the maximum loading rate, if so, executing the step nine, otherwise, executing the step five; step nine, outputting prompt information of goods failure of the loading scheme;

wherein, the processing module is further configured to execute the above steps, and the output module is further configured to execute the step nine.

11. The apparatus according to claim 9 or 10, wherein the processing module is specifically configured to:

12. The apparatus of claim 11, wherein the predetermined goal for each vehicle comprises a shortest travel path for each vehicle to visit a corresponding pick-up point.

13. The apparatus according to claim 11 or 12, wherein the processing module is specifically configured to:

14. The apparatus of claim 13, wherein the three-dimensional loading algorithm comprises any one of a tree search algorithm, a heuristic algorithm, a meta heuristic algorithm, and a reinforcement learning algorithm.

15. The apparatus of claim 13 or 14, wherein the loading rate of each of the desired vehicles for transporting the cargo according to the corresponding loading scheme is calculated by the processing module by performing the following method:

16. The apparatus of claim 13 or 14, wherein the loading rate of each of the desired vehicles for transporting the cargo according to the corresponding loading scheme is calculated by the processing module by performing the following method:

17. An apparatus for obtaining a loading scheme for cargo, comprising: a processor coupled with a memory;

the memory is to store instructions;

the processor is configured to execute instructions stored in the memory to cause the network device to implement the method of any of claims 1-8.

18. A computer-readable medium comprising instructions that, when executed on a processor, cause the processor to implement the method of any one of claims 1 to 8.