CN113792902A - Commodity ex-warehouse method and related equipment - Google Patents
Commodity ex-warehouse method and related equipment Download PDFInfo
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- CN113792902A CN113792902A CN202011370883.7A CN202011370883A CN113792902A CN 113792902 A CN113792902 A CN 113792902A CN 202011370883 A CN202011370883 A CN 202011370883A CN 113792902 A CN113792902 A CN 113792902A
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
Abstract
The embodiment of the disclosure provides a commodity ex-warehouse method and device, a computer readable storage medium and electronic equipment, and belongs to the technical field of computers and communication. The method comprises the following steps: acquiring order data; acquiring shelf information; acquiring the least ex-warehouse shelf set of each type of commodity in the order data according to the order data and the shelf information; determining the ex-warehouse shelf set of each type of commodities according to the minimum ex-warehouse shelf set of each type of commodities; acquiring the ex-warehouse shelf set of the order data according to the ex-warehouse shelf set of each type of commodity in the order data; and delivering the commodities according to the delivery shelf set of the order data. The technical scheme of the disclosed embodiment provides a commodity ex-warehouse method, which can optimize the picking efficiency and cost.
Description
Technical Field
The present disclosure relates to the field of computer and communication technologies, and in particular, to a method and an apparatus for delivering commodities from a warehouse, a computer-readable storage medium, and an electronic device.
Background
The goods delivery system is different from the traditional goods delivery system of 'people arrive at goods', the goods delivery system of 'people arrive at people' without a warehouse can reduce the time for people to search goods, and the delivery efficiency is greatly improved. The selection of the unmanned warehouse-out method usually needs to be considered together with the problems of commodity layout, order combination and the like, and the common method is to take commodities, shelves and orders together as input, construct an integer programming model and give a warehouse-out scheme through an accurate solution or a heuristic method. However, in consideration of the complexity of the commodity types and the requirement of order instantaneity, the unmanned warehouse commodity sorting and delivery method cannot optimize multiple types of targets at the same time.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
The embodiment of the disclosure provides a commodity ex-warehouse method and device, a computer-readable storage medium and an electronic device, which can optimize sorting efficiency and cost.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.
According to one aspect of the present disclosure, there is provided a method for delivering commodities, including:
acquiring order data, wherein the order data comprises the types and the quantity of commodities;
the method comprises the steps of obtaining shelf information, wherein the shelf information comprises the types and the quantity of commodities stored in each shelf in a warehouse;
acquiring the least ex-warehouse shelf set of each type of commodity in the order data according to the order data and the shelf information, wherein the least ex-warehouse shelf set of each type of commodity is the shelf set which meets the requirement that the least number of shelves are used when the commodity is ex-warehouse;
when the least ex-warehouse shelf set of a certain type of commodity in the order data is one, enabling the least ex-warehouse shelf set of the certain type of commodity to be the ex-warehouse shelf set of the certain type of commodity;
when the least ex-warehouse shelf set of a certain type of commodity in the order data is multiple, sorting the shelves of the multiple least ex-warehouse shelf sets of the commodity according to the commodity type stored by each shelf in the least ex-warehouse shelf set of the commodity and the ex-warehouse cost of each shelf, and determining the ex-warehouse shelf set of the commodity according to the sorting;
acquiring the ex-warehouse shelf set of the order data according to the ex-warehouse shelf set of each type of commodity in the order data;
and delivering the commodities according to the delivery shelf set of the order data.
In one embodiment, the sorting the shelves of the minimum ex-warehouse shelf set of the type of goods according to the type of goods stored on each shelf in the minimum ex-warehouse shelf set of the type of goods and the ex-warehouse cost of each shelf comprises:
and sorting the shelves of the least warehouse-out shelf set of the commodities according to the numerical value of each shelf from large to small by taking the number of the commodity types stored by each shelf as a numerator and the warehouse-out cost of each shelf as a denominator.
In one embodiment, determining the set of ex-warehouse shelves for the type of item according to the ranking comprises:
and summing the sequencing serial numbers of the shelves included in each of the plurality of least ex-warehouse shelf sets of the commodity, and taking the least ex-warehouse shelf set with the smallest summed value as the ex-warehouse shelf set of the commodity.
In one embodiment, when determining the ex-warehouse shelf set of a certain type of goods in the order data, if one or more shelves in a least ex-warehouse shelf set of the type of goods are shelves in ex-warehouse shelf sets of other types of goods, making the least ex-warehouse shelf set of the type of goods as the ex-warehouse shelf set of the type of goods includes:
when a plurality of least warehouse-out shelf sets exist and one or more shelves are shelves in the warehouse-out shelf sets of other kinds of commodities, the shelves of the least warehouse-out shelf sets are sequenced, and the warehouse-out shelf sets of the commodities are determined according to the sequencing.
In one embodiment, further comprising:
when determining the ex-warehouse shelf set of a certain type of goods in the order data, if one or more shelves in the least ex-warehouse shelf set of the type of goods are shelves in the ex-warehouse shelf sets of other types of goods, enabling the least ex-warehouse shelf set of the type of goods to be the ex-warehouse shelf set of the type of goods;
in one embodiment, further comprising:
according to the order statistics of the customers, the commodities which are frequently purchased by the customers at the same time are placed on the same shelf.
In one embodiment, further comprising:
the distance between each shelf and the goods picking platform is used as one of the established standards of the delivery cost of the shelf, and the distance between the unmanned carrier and each shelf is used as one of the established standards of the delivery cost of the shelf.
According to an aspect of the present disclosure, there is provided a delivery apparatus for goods, including:
the system comprises an acquisition module, a storage module and a display module, wherein the acquisition module is configured to acquire order data and shelf information, the order data comprises the types and the quantity of commodities, and the shelf information comprises the types and the quantity of the commodities stored in each shelf;
the least ex-warehouse shelf set determining module is configured to obtain a least ex-warehouse shelf set of each type of commodity in the order data according to the order data and the shelf information, wherein the least ex-warehouse shelf set of each type of commodity is a shelf set which meets the requirement that the commodity uses the least number of shelves when being ex-warehouse;
the selection module is configured to enable the least ex-warehouse shelf set of a certain type of commodity to be the ex-warehouse shelf set of the certain type of commodity when the least ex-warehouse shelf set of the certain type of commodity in the order data is one; when the least ex-warehouse shelf set of a certain type of commodity in the order data is multiple, sorting the shelves of the multiple least ex-warehouse shelf sets of the commodity according to the commodity type stored by each shelf in the least ex-warehouse shelf set of the commodity and the ex-warehouse cost of each shelf, and determining the ex-warehouse shelf set of the commodity according to the sorting;
the ex-warehouse shelf set determining module is configured to acquire an ex-warehouse shelf set of the order data according to the ex-warehouse shelf set of each type of commodity in the order data; and
and the ex-warehouse module is configured to ex-warehouse the commodities according to the ex-warehouse shelf set of the order data.
According to an aspect of the present disclosure, there is provided an electronic device including:
one or more processors;
a storage device configured to store one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the method of any of the above embodiments.
According to an aspect of the present disclosure, there is provided a computer readable storage medium storing a computer program which, when executed by a processor, implements the method of any one of the above embodiments.
In the technical scheme provided by some embodiments of the present disclosure, the commodity ex-warehouse method of the present disclosure optimizes the shelf cost and the picking cost at the same time, and designs an efficient heuristic method for solving, thereby optimizing the picking efficiency and cost.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The following figures depict certain illustrative embodiments of the invention in which like reference numerals refer to like elements. These described embodiments are to be considered as exemplary embodiments of the disclosure and not limiting in any way.
Fig. 1 is a schematic diagram illustrating an exemplary system architecture of a commodity discharge method or a commodity discharge apparatus to which the embodiments of the present disclosure may be applied;
FIG. 2 illustrates a schematic structural diagram of a computer system suitable for use with the electronic device implementing embodiments of the present disclosure;
FIG. 3 schematically shows a flow chart of a commodity ex-warehouse model building and solving method according to an embodiment of the disclosure;
FIG. 4 schematically illustrates a flow diagram of a heuristic commodity ex-warehouse method, in accordance with an embodiment of the present disclosure;
FIG. 5 schematically illustrates a block diagram of an ex-warehouse facility for merchandise, according to an embodiment of the present disclosure;
FIG. 6 schematically illustrates a block diagram of an apparatus for the ex-warehouse of articles according to another embodiment of the present invention;
fig. 7 schematically shows a block diagram of an apparatus for delivering goods from a warehouse according to another embodiment of the present invention.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations, or operations have not been shown or described in detail to avoid obscuring aspects of the disclosure.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
Fig. 1 shows a schematic diagram of an exemplary system architecture 100 of a method or apparatus for ex-warehouse of goods to which embodiments of the present disclosure may be applied.
As shown in fig. 1, the system architecture 100 may include one or more of terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation. For example, server 105 may be a server cluster comprised of multiple servers, or the like.
A staff member or a client may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may be various electronic devices having display screens including, but not limited to, smart phones, tablets, portable and desktop computers, digital cinema projectors, and the like.
The server 105 may be a server that provides various services. For example, the staff sends a delivery request of the product to the server 105 by using the terminal device 103 (or the terminal device 101 or 102). The server 105 may obtain order data, wherein the order data includes the type and quantity of the goods; the method comprises the steps of obtaining shelf information, wherein the shelf information comprises the types and the quantity of commodities stored in each shelf in a warehouse; acquiring the least ex-warehouse shelf set of each type of commodity in the order data according to the order data and the shelf information, wherein the least ex-warehouse shelf set of each type of commodity is the shelf set which meets the requirement that the least number of shelves are used when the commodity is ex-warehouse; when the least ex-warehouse shelf set of a certain type of commodity in the order data is one, enabling the least ex-warehouse shelf set of the certain type of commodity to be the ex-warehouse shelf set of the certain type of commodity; when the least ex-warehouse shelf set of a certain type of commodity in the order data is multiple, sorting the shelves of the multiple least ex-warehouse shelf sets of the commodity according to the commodity type stored by each shelf in the least ex-warehouse shelf set of the commodity and the ex-warehouse cost of each shelf, and determining the ex-warehouse shelf set of the commodity according to the sorting; when determining the ex-warehouse shelf set of a certain type of goods in the order data, if one or more shelves in the least ex-warehouse shelf set of the type of goods are shelves in the ex-warehouse shelf sets of other types of goods, enabling the least ex-warehouse shelf set of the type of goods to be the ex-warehouse shelf set of the type of goods; acquiring the ex-warehouse shelf set of the order data according to the ex-warehouse shelf set of each type of commodity in the order data; and delivering the commodities according to the delivery shelf set of the order data. The server 105 may send the ex-warehouse shelf set of the order data to the terminal device 103, so as to display the ex-warehouse shelf set of the order data on the terminal device 103, and further, the staff may view the corresponding ex-warehouse shelf set of the current order data based on the content displayed on the terminal device 103.
Also, for example, the terminal device 103 (also may be the terminal device 101 or 102) may be a smart tv, a VR (Virtual Reality)/AR (Augmented Reality) helmet display, or a mobile terminal such as a smart phone, a tablet computer, etc. on which a navigation, a network appointment, an instant messaging, a video Application (APP) and the like are installed, and a worker may send a warehouse-out request of a commodity to the server 105 through the smart tv, the VR/AR helmet display or the navigation, the network appointment, the instant messaging, the video APP. The server 105 may obtain the warehouse-out shelf set of the commodity warehouse-out based on the warehouse-out request of the commodity, and return the warehouse-out shelf set of the commodity warehouse-out to the smart television, the VR/AR helmet display or the navigation, network appointment, the instant messaging, and the video APP, so as to display the warehouse-out shelf set of the returned commodity warehouse-out through the smart television, the VR/AR helmet display or the navigation, network appointment, the instant messaging, and the video APP.
FIG. 2 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present disclosure.
It should be noted that the computer system 200 of the electronic device shown in fig. 2 is only an example, and should not bring any limitation to the functions and the scope of the application of the embodiments of the present disclosure.
As shown in fig. 2, the computer system 200 includes a Central Processing Unit (CPU)201 that can perform various appropriate actions and processes in accordance with a program stored in a Read-Only Memory (ROM) 202 or a program loaded from a storage section 208 into a Random Access Memory (RAM) 203. In the RAM 203, various programs and data necessary for system operation are also stored. The CPU 201, ROM 202, and RAM 203 are connected to each other via a bus 204. An input/output (I/O) interface 205 is also connected to bus 204.
The following components are connected to the I/O interface 205: an input portion 206 including a keyboard, a mouse, and the like; an output section 207 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 208 including a hard disk and the like; and a communication section 209 including a Network interface card such as a LAN (Local Area Network) card, a modem, or the like. The communication section 209 performs communication processing via a network such as the internet. A drive 210 is also connected to the I/O interface 205 as needed. A removable medium 211, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like, is mounted on the drive 210 as necessary, so that a computer program read out therefrom is installed into the storage section 208 as necessary.
In particular, the processes described below with reference to the flowcharts may be implemented as computer software programs, according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable storage medium, the computer program containing program code for performing the method illustrated by the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via the communication section 209 and/or installed from the removable medium 211. The computer program, when executed by a Central Processing Unit (CPU)201, performs various functions defined in the methods and/or apparatus of the present application.
It should be noted that the computer readable storage medium shown in the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM) or flash Memory), an optical fiber, a portable compact disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer-readable signal medium may include a propagated data signal with computer-readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable storage medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF (Radio Frequency), etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of methods, apparatus, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules and/or units and/or sub-units described in the embodiments of the present disclosure may be implemented by software, or may be implemented by hardware, and the described modules and/or units and/or sub-units may also be disposed in a processor. Wherein the names of such modules and/or units and/or sub-units in some cases do not constitute a limitation on the modules and/or units and/or sub-units themselves.
As another aspect, the present application also provides a computer-readable storage medium, which may be contained in the electronic device described in the above embodiment; or may exist separately without being assembled into the electronic device. The computer-readable storage medium carries one or more programs which, when executed by an electronic device, cause the electronic device to implement the method described in the embodiments below. For example, the electronic device may implement the steps shown in fig. 4.
In the related art, for example, a machine learning method, a deep learning method, or the like may be used to deliver a product, and the range of application of different methods is different.
Fig. 3 schematically shows a flow chart of a commodity ex-warehouse model building and solving method according to an embodiment of the disclosure.
Referring to fig. 3, a flow diagram may include a read data processing module, a group aggregation single module, a build sort model module, and a model solution.
1. Read data processing module
Reading real-time order data, including commodities and commodity quantity contained in the order, order taking time information (commodity ex-warehouse time or commodity arrival time) and the like; reading shelf information, wherein the current shelf contains commodity quantity information; reading other information: storage location information (shelf position), AGV car (automated guided vehicle) information, and commodity information.
2. Group collection single module
The singleton module is a very important module of the unmanned bin sortation system. By combining orders into a large aggregate order according to certain rules, picking efficiency can be greatly increased. The group aggregated sheet may generally reconcile similar orders, such as items in the order, or predict in advance that items in the order are on the same shelf, etc. Combining these orders may increase picking efficiency.
3. Module for establishing sorting model
Description of variables
The set of all shelves R, a shelf is denoted by R. CrIndicating the cost required to select shelf r.
The set of categories of all products is denoted as I, and a product is denoted by I. DiIndicating the demand of commodity i.
SriIndicating the number of items i contained on shelf r.
xriRepresenting the number of items i picked from shelf r, is a non-negative integer variable. y isrThe variable is a 0 or 1 variable indicating whether or not the shelf r is used.
f represents the single-piece cost function of the same goods selected on the shelf, and assuming that the selected amount of a certain goods is x, the corresponding single-piece goods selection cost is f (x).
Integer programming model and building
xri≤yrSr1，r∈R，i∈I (4)
xriIs a non-negative integer, yr∈{0，1}
Description of the model
Equation (1) represents an integer programmed objective function. As can be seen from the goal, the present model minimizes the shelf cost and picking cost required to ex-warehouse these items given the number of each type of item. Cost per shelf CrIs constant, then min Σ in equation (1)rCryrIndicating that a minimum number of shelves are required. f (x)ri) When the article x is taken outriPiece by piece, the required picking cost per item. If the cost of picking a piece for any item is the same, f will be a linearly increasing function, then ∑r，ixrif(xri) Will be a constant value, the objective function equation (1) will degrade to minimize shelf cost, and the whole model is an integer linear programming model. In practice, the average picking cost of the items decreases with increasing picking number on the same shelf, for example, for the same item, the cost of picking 10 items in one shelf is obviously different from the cost of picking one item in 10 shelves, the former is definitely smaller than the latter. Therefore, in the objective function formula (1), f is a nonlinear function (similar to an increasing convex function), and the model becomes difficult to solve.
Equation (2) represents the actual business constraint, which means that the number of the commodities taken out of the shelf just meets the commodity demand (it is assumed here that the sum of all the commodities in the shelf can certainly meet the order demand).
Equations (3) and (4) represent the logical constraints of the model. When y isr0 means that no product is taken off the shelf r, so there is x from equation (4)ri0. If yrThe constraint of formula (3) is satisfied because at least one product is taken from the shelf r, and the requirement of formula (4) is satisfied because the total number of the products taken from the shelf cannot be exceeded.
4. Model solution
Exact solution
The model described above can be solved accurately by using an integer programming solver, such as cplex, gurobi or open source solver scip. While exact solution has global optimality, and can use less shelf and cost, solution to the model often cannot be completed in a short time due to the complexity of the integer programming, which is in part a generally NP problem, and the sorting cost function f.
Solving complexity: for 1000 kinds of shelves and 10000 kinds of commodities, it can be found from the constraint formula (4) that the model needs to solve an integer programming model with more than 1000 ten thousand integer variables, and considering that the target is a nonlinear function, the solver is difficult to give an optimal solution in a short time.
Unmanned storehouse real-time restriction: due to the instantaneity of ordering by a user and the timeliness requirement of commodity distribution, the unmanned storehouse algorithm needs to be called in real time, and the result is difficult to be given quickly by accurate solving.
Heuristic solution
When designing the heuristic algorithm, the method needs to consider not only the shelf cost but also the picking time, so the method designs the heuristic algorithm and mainly comprises the following steps (principles):
1) for each commodity, the shelf set which can be exported most is found. Through the processing, the method and the device can ensure that the quantity of each type of commodity taken down from one goods shelf is enough, so that the time for picking the commodity is reduced, and the picking cost is reduced.
2) The shelf to be delivered is preferably selected, so that the number of used shelves is reduced, and the cost of the shelf is reduced.
3) For other candidate shelves, the number of types of warehoused goods divided by the cost is used as a score (rank) for the shelf, so that the condition that more goods are picked from one shelf as much as possible is guaranteed, and meanwhile, shelves with lower cost are selected for warehouse-out.
FIG. 4 schematically illustrates a flow diagram of a heuristic commodity ex-warehouse method according to an embodiment of the present disclosure. The method steps of the embodiment of the present disclosure may be executed by the terminal device, the server, or the terminal device and the server interactively, for example, the server 105 in fig. 1 described above, but the present disclosure is not limited thereto.
In step S410, order data is obtained, wherein the order data includes the type and quantity of the goods.
In this step, the terminal device or the server may acquire order data, where the order data includes the type and the number of the goods. The order data may be an order for a customer to purchase goods at a shopping site. The terminal device or the server may obtain order data in real time or at a specific time, or obtain a specific number of orders each time, which is not limited in this application.
In one embodiment, the method further comprises statistically classifying the order data to obtain the types of goods and the quantity of each type of goods included in the order data.
In the embodiments of the present disclosure, the terminal device may be implemented in various forms. For example, the terminal described in the present disclosure may include a mobile terminal such as a mobile phone, a tablet computer, a notebook computer, a palmtop computer, a Personal Digital Assistant (PDA), a Portable Media Player (PMP), a delivery device of goods, a wearable device, a smart band, a pedometer, a robot, an unmanned vehicle, and the like, and a fixed terminal such as a digital TV (television), a desktop computer, and the like.
In step S420, shelf information is acquired, wherein the shelf information includes the kind and number of the stored goods for each shelf in the warehouse.
In this step, the terminal device or the server may acquire shelf information including the kind and number of the stored goods for each shelf in the warehouse. The rack information may also include the distance of each rack in the warehouse from the item picking platform and may also include the distance of the automated guided vehicle from each rack.
In step S430, a minimum ex-warehouse shelf set of each type of product in the order data is obtained according to the order data and the shelf information, where the minimum ex-warehouse shelf set of each type of product is a shelf set that uses the minimum number of shelves when the type of product is ex-warehouse.
In this step, the terminal device or the server obtains the minimum storage rack set of each type of goods in the order data according to the order data and the shelf information, wherein the minimum storage rack set of each type of goods is the rack set which meets the requirement of using the minimum number of shelves when the type of goods is stored. For example, in one embodiment, the order data includes three categories ABC of items, wherein 100 items A, 50 items B, and 20 items C; in one embodiment, the minimum ex-warehouse shelf set of the A commodities is a shelf set which can ex-warehouse 100 items and needs the minimum number; for example, in a warehouse, if the number of the a commodities on one or a plurality of shelves is greater than or equal to 100, the one or the plurality of shelves is the least ex-warehouse shelf set of the a commodities; for another example, when the number of single shelves in the warehouse is less than 100, it needs to be considered whether the sum of the numbers of a commodities of two or more shelves among all the shelves including the a commodity is greater than or equal to 100; if shelf X, shelf Y, and shelf Z of A item are included in the warehouse with A items 60, and 50, respectively, then the minimum set of shelves for A item out of the warehouse are set 1 (shelf X, shelf Y), set 2 (shelf X, shelf Z), and set 3 (shelf Y, shelf Z) in this embodiment. And the BC commodities are analogized in the same way.
In step S440, when the least warehouse-out shelf set of a certain type of goods in the order data is one, the least warehouse-out shelf set of the certain type of goods is made to be the warehouse-out shelf set of the certain type of goods.
In this step, when the minimum set of shelves for warehousing a certain type of goods in the order data is one, the terminal device or the server makes the minimum set of shelves for warehousing the certain type of goods be the set of shelves for warehousing the certain type of goods. For example, if the number of a items in the order data is 100, if the number of a items on only one shelf is greater than or equal to 100, the one shelf is made to be the ex-warehouse shelf set of the a items; or when the number of the single shelves in the warehouse is less than 100, the sum of the numbers of the A commodities contained in the two shelves containing the A commodity is more than or equal to 100, and the two shelves are the ex-warehouse shelf set of the A commodity.
In step S450, when there are a plurality of the least ex-warehouse shelf sets of a certain type of goods in the order data, the shelves of the plurality of the least ex-warehouse shelf sets of the type of goods are sorted according to the type of goods stored in each shelf in the least ex-warehouse shelf set of the type of goods and the ex-warehouse cost of each shelf, and the ex-warehouse shelf set of the type of goods is determined according to the sorting.
In this step, when the minimum ex-warehouse shelf set of a certain type of goods in the order data is multiple, the terminal device or the server sorts the shelves of the multiple minimum ex-warehouse shelf sets of the type of goods according to the type of goods stored in each shelf in the minimum ex-warehouse shelf set of the type of goods and the ex-warehouse cost of each shelf, and determines the ex-warehouse shelf set of the type of goods according to the sorting.
In one embodiment, the number of the types of commodities stored in each shelf is used as a numerator, the ex-warehouse cost of each shelf is used as a denominator, and the shelves of the least ex-warehouse shelf set of the commodities are sorted according to the numerical value of each shelf from large to small. In one embodiment, the sorting order numbers of the shelves included in each of the plurality of minimum ex-warehouse shelf sets of the commodity are summed, and the minimum ex-warehouse shelf set with the smallest summed value is the ex-warehouse shelf set of the commodity. In one embodiment, the distance of each shelf from the item picking platform is used as one of the criteria for the cost of ex-warehouse for that shelf. In one embodiment, the distance of the automated guided vehicle from each shelf is used as one of the set standards of the warehouse-out cost of the shelf.
For example, in one embodiment, the order data includes ABC categories of items, 100 items A, 50 items B, 20 items C; in one embodiment, the minimum ex-warehouse shelf set of the A commodities is a shelf set which can ex-warehouse 100 items and needs the minimum number; for example, in a warehouse, if the number of a products on 10 shelves is equal to or greater than 100, then the 10 shelves are the minimum ex-warehouse shelf set of the a products, and then the 10 shelves are sorted from large to small according to the value with the category of the three types of ABC products included as numerator and the ex-warehouse cost as denominator, and the shelf with the first rank is the ex-warehouse shelf set of the a products.
For another example, when the number of a items on a single shelf in the warehouse is less than 100, if the shelf X, the shelf Y, and the shelf Z of the a item in the warehouse have a items 60, and 50, respectively, then in this embodiment, the minimum ex-warehouse shelf sets of the a item are set 1 (shelf X, shelf Y), set 2 (shelf X, shelf Z), and set 3 (shelf Y, shelf Z); firstly, sorting the 3 shelves according to numerical values from large to small by using the types of the three ABC commodities of the shelf X, the shelf Y and the shelf Z as numerators and the ex-warehouse cost as denominators; if the ordering result is: 1-shelf Z, 2-shelf Y and 3-shelf X, the sum of the sorting sequence numbers of the set 1 is 5, the sum of the sorting sequence numbers of the set 2 is 4, the sum of the sorting sequence numbers of the set 3 is 3, and the sum of the sorting sequence numbers of the set 3 is minimum, so that the set 3 is taken as the ex-warehouse shelf set of the commodity A. In an embodiment, the ratio of the category of the commodity of each shelf in the shelf set as the numerator and the ex-warehouse cost as the denominator may also be summed, and at this time, the set with the largest value of the summed sets needs to be taken as the ex-warehouse shelf set of the commodity, which is not described herein again.
In step S460, the warehouse-out shelf set of the order data is obtained according to the warehouse-out shelf set of each type of goods in the order data.
In this step, the terminal device or the server obtains the warehouse-out shelf set of the order data according to the warehouse-out shelf set of each type of goods in the order data.
In step S470, the product is delivered according to the delivery shelf set of the order data.
In this step, the terminal device or the server takes out the commodity according to the delivery shelf set of the order data.
The commodity warehouse-out method optimizes the shelf cost and the picking cost simultaneously, designs an efficient heuristic method for solving, and optimizes the picking efficiency and cost.
In one embodiment, when determining the ex-warehouse shelf set of a certain type of goods in the order data, if one or more shelves in a least ex-warehouse shelf set of the type of goods are shelves in ex-warehouse shelf sets of other types of goods, the least ex-warehouse shelf set of the type of goods is made to be the ex-warehouse shelf set of the type of goods. In this embodiment, when determining the ex-warehouse shelf set of a certain type of goods in the order data, the terminal device or the server makes one minimum ex-warehouse shelf set of the type of goods be the ex-warehouse shelf set of the type of goods if one or more shelves in the minimum ex-warehouse shelf set of the type of goods are shelves in the ex-warehouse shelf sets of other types of goods. In one embodiment, when a plurality of least warehouse-out shelf sets exist, and one or more shelves are shelves in warehouse-out shelf sets of other kinds of commodities, the shelves of the plurality of least warehouse-out shelf sets are sorted, and the warehouse-out shelf set of the commodity is determined according to the sorting.
For example, in one embodiment, the order data includes ABC categories of items, 100 items A, 50 items B, 20 items C; if the ex-warehouse shelf set of the commodity A is determined, when the commodity B is determined, if the least ex-warehouse shelf set of the commodity B is multiple, if one or more shelves in one of the least ex-warehouse shelf sets are overlapped with the shelves in the ex-warehouse shelf set of the commodity A (the same shelf), the least ex-warehouse shelf set is used as the ex-warehouse shelf set of the commodity B. If more than one least ex-warehouse shelf set in the plurality of least ex-warehouse shelf sets of the B commodities has shelves overlapped with shelves in the ex-warehouse shelf set of the A commodities (the same shelves), sorting the shelves of the more than one least ex-warehouse shelf sets, and determining the ex-warehouse shelf sets of the commodities according to the sorting, wherein the sorting can refer to the sorting description of the step S450, and the description is omitted here.
In one embodiment, the items that are often purchased simultaneously by the customer are placed on the same shelf based on the customer's order statistics.
The shelf sorting algorithm of the present application is as follows:
ginseng introduction: commodity demand vector D ═ Di)|I|The shelf storage single quantity matrix S ═ (S)ri)|R|×|I|，
Ginseng production: shelf set R for leaving warehouse0And the on-shelf pick matrix P ═ P (P)ri)|R|×|I|
Description of the Algorithm
In the step 20, the step of the method,
the row r ' in the matrix P ', the shipment vector of all the items in the shelf r ',
represents the sum of all shipment quantities of r'. The same applies to step 35.
In step 27, if several shelves score the same, then r' is expressed from { r | Tr＝＝max{T}，r∈R″0Randomly choose oneAnd (7) a shelf.
The algorithm can be accelerated by using a sparse storage mode, for example, when the types of commodities P and P' are many, a large number of 0 s appear, and the storage space and the query times can be reduced by using the sparse storage.
Details of algorithm implementation
Reference is made to the description: d ═ D (D)i)|I|The demand D of the commodity i is obtained by summarizing the collection list constructed by the grouping algorithm according to the upstream real-time orderi. Due to the fact that the variety of commodities is possibly very large and the size of the collection list is limited, D is possibly a very large sparse vector, sparse storage can be used when the algorithm is implemented, and only the commodities with the required quantity are reserved. S can also be stored as a sparse matrix in the same way.
See the description: warehouse-out shelf set R0Representing a set of ex-warehouse shelves, pick matrix P ═ P (P)ri)|R|×|I|The number of the commodities which are delivered from each shelf is represented, and sparse storage can be used in implementation.
Step 2 shows that the jump-out circulation condition of the algorithm is that all commodities in the collection list are met. The visibility algorithm assumes that the goods stored in the shelf must satisfy the current aggregated sheet. When programming is implemented, a vector of commodity surplus in a goods shelf can be maintained in a program, so that before an algorithm is called, whether the commodity requirement in the collection list can be met or not is judged according to the vector, and commodities with insufficient surplus can be deleted in the collection list or only the maximum quantity which can be met by warehouse-out is considered.
Steps 4 to 10 show that for each commodity, the highest quantity of single-shelf ex-warehouse is taken as a reference unit quantity (step 7), and only the shelves capable of meeting the reference unit are considered (step 8). This step is compatible with minimizing individual picking costs in the objective function. And when the shelf r can meet the reference unit of the commodity i, the commodity i is taken out of the warehouse in the temporary shelf in a gathering way, and as can be seen from the step 26 to the step 27, the step is equivalent to adding a score to the current shelf.
Steps 12 to 21 show that the algorithm selects the remaining commodities preferentially from the shelves already out of the warehouse, and selects the commodities from the shelves already out of the warehouse, so that the use amount of the shelves can be reduced, and the shelf cost is reduced in accordance with the objective function. It should be noted that after a certain item (the reference unit amount) is picked from the shelf, the current item needs to be removed from other candidate shelves (steps 18 to 21) to avoid repeated picking. Steps 20 through 21 represent removing from the candidate set if the candidate shelf can no longer pick items, reducing the amount of computation in subsequent cycles of the algorithm.
In steps 23 to 36, the shelves are screened from the remaining shelves where no picking occurs, and the shelves are taken out of the warehouse. Wherein in step 23, the loop-out condition is that each shelf in the remaining candidate shelves is empty. This skipping condition must eventually be satisfied because each time an item in the algorithm design is picked, the item is removed from the other shelves accordingly (steps 33 to 26, as in steps 18 to 21 above). Steps 24 through 26 represent scoring each current candidate shelf, and as can be seen from step 26, the present application scores the current shelf satisfaction item category divided by the shelf cost, and the present application wishes to select a candidate shelf that satisfies more items (lower picking cost) and lower shelf cost (step 27).
Description of model optimization
The algorithm provided by the application has strong expansibility. For example, in step 7, the present application calculates the shipment volume of item i as the minimum value of the current demand and the maximum shelf capacity. The purpose of this is to try to ensure that a shelf is shipped sufficiently out, as more shipped is less costly to pick. In practice, when the shipment reaches a certain level, the individual item picking cost will remain unchanged, assuming that the threshold is CutOff for item iiTherefore, Q can be expressed hereiSet to a variable value, e.g. Qi≥{Di，max({Sri|r∈R})，CutOffiThus, the number of products shipped from a shelf has more choices.
The goods are taken out of the warehouse and often have great relation with the goods layout of the goods shelf and effective group lists, and the good goods layout can increase the picking efficiency. For example, placing items that are often purchased by customers simultaneously on the same shelf can increase picking efficiency. Therefore, a more effective commodity layout scheme and a reasonable order combining algorithm can be designed, and a more reasonable sorting strategy is provided by combining the warehouse-out algorithm.
Fig. 5 schematically shows a block diagram of an ex-warehouse device of goods according to an embodiment of the present disclosure. The commodity delivery device 500 provided in the embodiment of the present disclosure may be provided in a terminal device, a server, or a part of the terminal device and a part of the server, for example, the server 105 in fig. 1, but the present disclosure is not limited thereto.
The device 500 for delivering goods provided by the embodiment of the present disclosure may include an obtaining module 510, a least delivery shelf set determining module, a selecting module 530, a delivery shelf set determining module 540, and a delivery module 550.
The obtaining module 510 is configured to obtain order data and shelf information, where the order data includes the type and number of the goods, and the shelf information includes the type and number of the goods stored in each shelf; the least ex-warehouse shelf set determining module 520 is configured to obtain, according to the order data and the shelf information, a least ex-warehouse shelf set of each type of goods in the order data, where the least ex-warehouse shelf set of each type of goods is a shelf set that satisfies that the least number of shelves are used when the type of goods is ex-warehouse; the selecting module 530 is configured to make the least ex-warehouse shelf set of a certain type of goods in the order data be the ex-warehouse shelf set of the certain type of goods when the least ex-warehouse shelf set of the certain type of goods in the order data is one; when the least ex-warehouse shelf set of a certain type of commodity in the order data is multiple, sorting the shelves of the multiple least ex-warehouse shelf sets of the commodity according to the commodity type stored by each shelf in the least ex-warehouse shelf set of the commodity and the ex-warehouse cost of each shelf, and determining the ex-warehouse shelf set of the commodity according to the sorting; the ex-warehouse shelf set determining module 540 is configured to obtain an ex-warehouse shelf set of the order data according to the ex-warehouse shelf set of each type of goods in the order data; and the ex-warehouse module 550 is configured to ex-warehouse the goods according to the ex-warehouse shelf set of the order data.
According to the embodiment of the present disclosure, the device 500 for delivering commodities can be used to implement the method for delivering commodities described in the embodiment of fig. 4.
Fig. 6 schematically shows a block diagram of an apparatus 600 for delivering goods according to another embodiment of the present invention.
As shown in fig. 6, the apparatus 600 for delivering goods further includes a display module 610 in addition to the acquisition module 510, the least warehouse-out shelf set determination module, the selection module 530, the warehouse-out shelf set determination module 540 and the warehouse-out module 550 described in the embodiment of fig. 5.
Specifically, the display module 610 displays the ex-warehouse shelf set on the terminal after the ex-warehouse shelf set determining module 540 obtains the ex-warehouse shelf set of the order data according to the ex-warehouse shelf set of each type of goods in the order data.
In the delivery device 600 for the product, the display module 610 can visually display the delivery shelf set.
Fig. 7 schematically shows a block diagram of an apparatus 700 for ex-warehouse of goods according to another embodiment of the present invention.
As shown in fig. 7, the apparatus 700 for warehousing goods includes a storage module 710 in addition to the acquisition module 510, the least warehouse-out shelf set determination module, the selection module 530, the warehouse-out shelf set determination module 540, and the warehouse-out module 550 described in the embodiment of fig. 5.
Specifically, the storage module 710 is used for storing the ex-warehouse shelf set for facilitating subsequent calling and reference.
It is understood that the obtaining module 510, the least ex warehouse shelf set determining module, the selecting module 530, the ex warehouse shelf set determining module 540, the ex warehouse module 550, the displaying module 610 and the storing module 710 may be combined into one module to be implemented, or any one of them may be split into a plurality of modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module. According to an embodiment of the present invention, at least one of the obtaining module 510, the minimum ex-warehouse shelf set determining module, the selecting module 530, the ex-warehouse shelf set determining module 540, the ex-warehouse module 550, the displaying module 610, and the storing module 710 may be at least partially implemented as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or implemented in a suitable combination of three implementations of software, hardware, and firmware. Alternatively, at least one of the acquisition module 510, the minimum ex-warehouse shelf set determination module, the selection module 530, the ex-warehouse shelf set determination module 540, the ex-warehouse module 550, the display module 610, and the storage module 710 may be at least partially implemented as a computer program module that, when executed by a computer, may perform the functions of the respective module.
For details that are not disclosed in the embodiment of the apparatus of the present invention, reference is made to the above-mentioned embodiment of the method for delivering commodities, because each module of the device for delivering commodities of the example embodiment of the present invention can be used to implement the steps of the above-mentioned example embodiment of the method for delivering commodities described in fig. 4.
The specific implementation of each module, unit and subunit in the device for delivering commodities provided by the embodiment of the present disclosure may refer to the content in the method for delivering commodities, and will not be described herein again.
It should be noted that although several modules, units and sub-units of the apparatus for action execution are mentioned in the above detailed description, such division is not mandatory. Indeed, the features and functionality of two or more modules, units and sub-units described above may be embodied in one module, unit and sub-unit, in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module, unit and sub-unit described above may be further divided into embodiments by a plurality of modules, units and sub-units.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. A method for delivering commodities, comprising:
acquiring order data, wherein the order data comprises the types and the quantity of commodities;
the method comprises the steps of obtaining shelf information, wherein the shelf information comprises the types and the quantity of commodities stored in each shelf in a warehouse;
acquiring the least ex-warehouse shelf set of each type of commodity in the order data according to the order data and the shelf information, wherein the least ex-warehouse shelf set of each type of commodity is the shelf set which meets the requirement that the least number of shelves are used when the commodity is ex-warehouse;
when the least ex-warehouse shelf set of a certain type of commodity in the order data is one, enabling the least ex-warehouse shelf set of the certain type of commodity to be the ex-warehouse shelf set of the certain type of commodity;
when the least ex-warehouse shelf set of a certain type of commodity in the order data is multiple, sorting the shelves of the multiple least ex-warehouse shelf sets of the commodity according to the commodity type stored by each shelf in the least ex-warehouse shelf set of the commodity and the ex-warehouse cost of each shelf, and determining the ex-warehouse shelf set of the commodity according to the sorting;
acquiring the ex-warehouse shelf set of the order data according to the ex-warehouse shelf set of each type of commodity in the order data;
and delivering the commodities according to the delivery shelf set of the order data.
2. The method of claim 1, wherein sorting the shelves of the minimum set of shelves for the item according to the category of items stored on each shelf and the cost of each shelf in the minimum set of shelves for the item comprises:
and sorting the shelves of the least warehouse-out shelf set of the commodities according to the numerical value of each shelf from large to small by taking the number of the commodity types stored by each shelf as a numerator and the warehouse-out cost of each shelf as a denominator.
3. The method of claim 1, wherein determining the set of ex-warehouse shelves for the type of item according to the ranking comprises:
and summing the sequencing serial numbers of the shelves included in each of the plurality of least ex-warehouse shelf sets of the commodity, and taking the least ex-warehouse shelf set with the smallest summed value as the ex-warehouse shelf set of the commodity.
4. The method of claim 1, wherein when determining the ex-warehouse shelf set of a certain type of goods in the order data, if one or more shelves in a least ex-warehouse shelf set of the type of goods are shelves in ex-warehouse shelf sets of other types of goods, making the least ex-warehouse shelf set of the type of goods as the ex-warehouse shelf set of the type of goods comprises:
when a plurality of least warehouse-out shelf sets exist and one or more shelves are shelves in the warehouse-out shelf sets of other kinds of commodities, the shelves of the least warehouse-out shelf sets are sequenced, and the warehouse-out shelf sets of the commodities are determined according to the sequencing.
5. The method of claim 1, further comprising:
when determining the ex-warehouse shelf set of a certain type of goods in the order data, if one or more shelves in the least ex-warehouse shelf set of the type of goods are shelves in the ex-warehouse shelf sets of other types of goods, enabling the least ex-warehouse shelf set of the type of goods to be the ex-warehouse shelf set of the type of goods.
6. The method of claim 1, further comprising:
according to the order statistics of the customers, the commodities which are frequently purchased by the customers at the same time are placed on the same shelf.
7. The method of claim 1, further comprising:
the distance between each shelf and the goods picking platform is used as one of the established standards of the delivery cost of the shelf, and the distance between the unmanned carrier and each shelf is used as one of the established standards of the delivery cost of the shelf.
8. An apparatus for delivering a commodity, comprising:
the system comprises an acquisition module, a storage module and a display module, wherein the acquisition module is configured to acquire order data and shelf information, the order data comprises the types and the quantity of commodities, and the shelf information comprises the types and the quantity of the commodities stored in each shelf;
the least ex-warehouse shelf set determining module is configured to obtain a least ex-warehouse shelf set of each type of commodity in the order data according to the order data and the shelf information, wherein the least ex-warehouse shelf set of each type of commodity is a shelf set which meets the requirement that the commodity uses the least number of shelves when being ex-warehouse;
the selection module is configured to enable the least ex-warehouse shelf set of a certain type of commodity to be the ex-warehouse shelf set of the certain type of commodity when the least ex-warehouse shelf set of the certain type of commodity in the order data is one; when the least ex-warehouse shelf set of a certain type of commodity in the order data is multiple, sorting the shelves of the multiple least ex-warehouse shelf sets of the commodity according to the commodity type stored by each shelf in the least ex-warehouse shelf set of the commodity and the ex-warehouse cost of each shelf, and determining the ex-warehouse shelf set of the commodity according to the sorting;
the ex-warehouse shelf set determining module is configured to acquire an ex-warehouse shelf set of the order data according to the ex-warehouse shelf set of each type of commodity in the order data; and
and the ex-warehouse module is configured to ex-warehouse the commodities according to the ex-warehouse shelf set of the order data.
9. An electronic device, comprising:
one or more processors;
a storage device configured to store one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-7.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 7.
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| CN110852668A (en) * | 2019-09-23 | 2020-02-28 | 北京旷视机器人技术有限公司 | Goods warehousing processing method and device, warehousing system and computer equipment |
| CN111382974A (en) * | 2020-03-09 | 2020-07-07 | 北京旷视机器人技术有限公司 | Method and device for determining shelf position, warehousing system and computer equipment |
| CN111754176A (en) * | 2020-06-28 | 2020-10-09 | 北京理工大学 | Two-stage intelligent order sorting method for multiple mobile shelves |
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