CN112001679B - Method and system for improving warehousing cargo allocation efficiency - Google Patents

Method and system for improving warehousing cargo allocation efficiency Download PDF

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CN112001679B
CN112001679B CN202010871937.1A CN202010871937A CN112001679B CN 112001679 B CN112001679 B CN 112001679B CN 202010871937 A CN202010871937 A CN 202010871937A CN 112001679 B CN112001679 B CN 112001679B
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章耀宇
马卫清
赵坚密
骆海东
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Jiaxing Jushuitan Intelligent Technology Co.,Ltd.
Luo Haidong
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Abstract

The invention discloses a method and a system for improving warehousing and goods distribution efficiency, which greatly reduce scanning times, improve goods picking efficiency and give generated goods distribution mode batches. The technical scheme is as follows: step 1: acquiring data of all current non-delivery orders; step 2: all the obtained current non-shipped order data and the minimum amount of orders of each batch are substituted into the integer planning model to generate order batches, so that more orders can be covered as far as possible on the premise that the minimum amount of orders of each batch is met; and step 3: in the picking stage, picking is carried out according to the order batch generated in the step 2, and the picking mode is that the commodities with the same item are respectively placed in different grids of the picking truck according to the commodities, and the commodities with different items are all placed in the same grid; and 4, step 4: in the distribution stage, a different item of commodity is obtained, an order directly related to the commodity is scanned, and then one of the other commodities of the same item under the order is taken to complete packaging and delivery.

Description

Method and system for improving warehousing cargo allocation efficiency
Technical Field
The invention relates to the technical field of e-commerce warehousing and distribution, in particular to a method and a system for improving warehousing and distribution efficiency.
Background
In the traditional e-commerce warehousing distribution, a mode of 'picking first and then sowing' is often adopted, that is, a certain batch of orders are loaded into a picking truck from a shelf first, and then sowing is carried out in a sowing cabinet. The seeding cabinet comprises a plurality of grids, each grid is used for placing all goods of a certain order, a distributor scans and picks the goods in the truck, the system prompts the corresponding grids to be placed, and the grids can be packed and delivered after all the grids are scanned and placed.
The method requires an operation of scanning all the commodities in the picking truck and putting them in the sowing cabinet during sowing, resulting in low efficiency. Therefore, how to greatly reduce the number of scanning times to improve the picking efficiency is an urgent problem to be solved in the current industry in the face of this application scenario.
Disclosure of Invention
The following presents a simplified summary of one or more aspects in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements of all aspects nor delineate the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that is presented later.
The present invention is directed to solving the above problems, and provides a method and system for improving the warehousing and distribution efficiency, which can greatly reduce the number of scanning times to improve the picking efficiency, and at the same time, generate the batch of distribution patterns.
The technical scheme of the invention is as follows: the invention discloses a method for improving the warehousing and cargo allocation efficiency, which comprises the following steps:
step 1: acquiring data of all current non-delivery orders;
step 2: all the obtained current non-shipped order data and the minimum amount of orders of each batch are substituted into the integer planning model to generate order batches, so that more orders can be covered as far as possible on the premise that the minimum amount of orders of each batch is met;
and step 3: in the picking stage, picking is carried out according to the order batch generated in the step 2, and the picking mode is that the commodities with the same item are respectively placed in different grids of the picking truck according to the commodities, and the commodities with different items are all placed in the same grid;
and 4, step 4: in the distribution stage, a different item of commodity is obtained, an order directly related to the commodity is scanned, and then one of the other commodities of the same item under the order is taken to complete packaging and delivery.
According to an embodiment of the method for improving warehousing and distribution efficiency, in step 1, all currently non-shipped order data is acquired from an e-commerce ERP system.
According to an embodiment of the method for improving warehousing and distribution efficiency of the present invention, in step 2, the manner of generating the order batch by the integer programming model is as follows:
let the order pool be W, the order pool contains the total number of orders n, the minimum number of orders per batch b, the number of all possible combinations of the set A is W, and the variable x is 0-1ijWhether order j is generated as AiAn order of type;
an objective function:
Figure BDA0002651399730000021
constraint conditions are as follows:
Figure BDA0002651399730000022
Figure BDA0002651399730000023
xij∈{0，1}
and solving according to the objective function and the constraint condition to obtain the order batch which accords with the integer programming model.
The invention also discloses a system for improving the warehousing and cargo allocation efficiency, which comprises:
the order data acquisition module is used for acquiring all current non-delivery order data;
the order batch generation module is used for substituting the acquired current all non-shipped order data and the minimum order number of each batch into the integer planning model to generate order batches so as to cover more orders as far as possible on the premise of meeting the minimum order number of each batch;
the picking module picks the goods according to the order batch generated in the order batch generating module in a picking stage, wherein the picking mode is that the goods with the same item are respectively placed in different lattices of the picking vehicle according to the goods, and the goods with different items are all placed in the same lattice;
and the goods distribution module is used for acquiring different items of goods in the goods distribution stage, directly associating the different items of goods with the order of the goods through scanning, and then taking one of the other same items of goods in the order to complete packaging and delivery.
According to an embodiment of the system for improving warehousing and distribution efficiency, the order data acquisition module acquires all current non-delivery order data from an e-commerce ERP system.
According to an embodiment of the system for improving warehousing and distribution efficiency of the present invention, the order batch generation module generates the order batch based on the integer programming model in the following manner:
let the order pool be W, the order pool contains the total number of orders n, the minimum number of orders per batch b, the number of all possible combinations of the set A is W, and the variable x is 0-1ijWhether order j is generated as AiAn order of type;
an objective function:
Figure BDA0002651399730000031
constraint conditions are as follows:
Figure BDA0002651399730000032
Figure BDA0002651399730000033
xij∈{0，1}
and solving according to the objective function and the constraint condition to obtain the order batch which accords with the integer programming model.
The invention also discloses a system for improving the warehousing and cargo allocation efficiency, which comprises:
a processor; and
a memory configured to store a series of computer-executable instructions and computer-accessible data associated with the series of computer-executable instructions,
wherein the series of computer executable instructions, when executed by the processor, cause the processor to perform the method as described above.
Also disclosed is a non-transitory computer readable storage medium having stored thereon a series of computer executable instructions which, when executed by a computing device, cause the computing device to perform the method as described above.
Compared with the prior art, the invention has the following beneficial effects: in the scene of e-commerce warehousing and distribution, the order batch is generated through the integer programming model, and then the goods are picked according to the generated order batch, so that the technical effects of greatly reducing the number of times of material scanning and further improving the goods picking efficiency are achieved.
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The above features and advantages of the present disclosure will be better understood upon reading the detailed description of embodiments of the disclosure in conjunction with the following drawings. In the drawings, components are not necessarily drawn to scale, and components having similar relative characteristics or features may have the same or similar reference numerals.
Fig. 1 shows a flowchart of an embodiment of a method for improving warehousing cargo allocation efficiency according to the present invention.
FIG. 2 illustrates a schematic diagram of one embodiment of a system for improving warehouse distribution efficiency of the present invention.
Fig. 3 illustrates a schematic diagram of another embodiment of the system for improving warehouse distribution efficiency of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. It is noted that the aspects described below in connection with the figures and the specific embodiments are only exemplary and should not be construed as imposing any limitation on the scope of the present invention.
Fig. 1 shows a flow of an embodiment of the method for improving warehousing cargo allocation efficiency according to the present invention. Referring to fig. 1, the steps of the method of the present embodiment are detailed as follows.
Step 1: and acquiring all current non-delivery order data.
In this embodiment, all of the current non-shipping order data is typically obtained from the e-commerce ERP system.
Step 2: and substituting the acquired current all-consigned order data and the minimum orders per batch set by the user into an integer planning model to generate order batches so as to cover more orders as much as possible on the premise of meeting the minimum orders per batch.
In this embodiment, the mathematical definition of the picking mode of the present invention (i.e., the conditions that should be satisfied by the orders describing the picking lot) is as follows:
if a batch of orders exist, wherein all orders contain the same quantity of commodities and only one commodity is different, the batch of orders has higher picking efficiency due to fewer commodity types, in the packing and scanning stage, the orders can be associated by only scanning different commodities, and then the packing and delivery can be completed by taking one of the other same commodities. It is strictly defined as follows:
given a set of orders S, a total number of orders card (S) ═ m, order Oi∈S i＝1，2，...m，OiThe commodity set is CiThen there is a set of items a and a constant Q,
so that
card(Ci)＝Q i＝1，2，...m
card(A)＝Q-1
Figure BDA0002651399730000054
In this embodiment, the integer programming model generates the order batch as follows.
Setting the order pool as W, the order pool comprises the total number of orders as n, the minimum order number of each batch as b, the set A, the possible combination number of all order commodities as W, the combination isAiWherein i ═ 1, 2.. w,0-1 variable xijWhether order j is generated as AiThe type of order.
The objective function is as follows:
Figure BDA0002651399730000051
constraint conditions are as follows:
Figure BDA0002651399730000052
Figure BDA0002651399730000053
xij∈{0，1}
and solving according to the objective function and the constraint condition to obtain the order batch which accords with the integer programming model.
And step 3: and in the picking stage, picking is carried out according to the order batch generated in the step 2, wherein the picking mode is that the commodities with the same item are respectively placed in different grids of the picking truck according to the commodities, and the commodities with different items are all placed in the same grid.
And 4, step 4: in the distribution stage, a different item of commodity is obtained, an order directly related to the commodity is scanned, and then one of the other commodities of the same item under the order is taken to complete packaging and delivery.
Figure 2 illustrates the principles of one embodiment of the system for improving warehouse distribution efficiency of the present invention. Referring to fig. 2, the system of the present embodiment includes: the order data acquisition module, the order batch generation module, the picking module and the distribution module.
The order data acquisition module is used for acquiring all current non-delivery order data. In this embodiment, all the current non-shipping order data is obtained from the e-commerce ERP system.
The order batch generation module is used for substituting the acquired current all-un-shipped order data and the minimum amount of orders per batch into the integer planning model to generate order batches so as to cover more orders as much as possible on the premise of meeting the minimum amount of orders per batch.
In this embodiment, the mathematical definition of the picking mode of the present invention (i.e., the conditions that should be satisfied by the orders describing the picking lot) is as follows:
if a batch of orders exist, wherein all orders contain the same quantity of commodities and only one commodity is different, the batch of orders has higher picking efficiency due to fewer commodity types, in the packing and scanning stage, the orders can be associated by only scanning different commodities, and then the packing and delivery can be completed by taking one of the other same commodities. It is strictly defined as follows:
given a set of orders S, a total number of orders card (S) ═ m, order Oi∈Si＝1,2,…m,OiThe commodity set is CiThen there is a set of items a and a constant Q,
so that
card(Ci)＝Q i＝1，2，...m
card(A)＝Q-1
Figure BDA0002651399730000071
In this embodiment, the manner in which the order batch generation module generates the order batch based on the integer programming model is as follows:
setting the order pool as W, the order pool includes n total orders, b minimum orders in each batch, W possible combination number of all orders in the set A, and A combinationiWherein i ═ 1, 2.. w,0-1 variable xijWhether order j is generated as AiAn order of type;
an objective function:
Figure BDA0002651399730000072
constraint conditions are as follows:
Figure BDA0002651399730000073
Figure BDA0002651399730000074
xij∈{0，1}
and solving according to the objective function and the constraint condition to obtain the order batch which accords with the integer programming model.
The order picking module is used for picking the orders according to the order batch generated in the order batch generating module in the order picking stage, and the order picking mode is that the commodities with the same item are respectively placed in different lattices of the order picking vehicle according to the commodities, and the commodities with different items are all placed in the same lattice.
The goods distribution module is used for acquiring different items of goods in the goods distribution stage, directly associating the different items of goods with the order of the goods through scanning, and then taking one of the other same items of goods in the order to complete packaging and delivery.
Referring to fig. 3, the system shown in fig. 3 includes a processor and a memory. The memory is configured to store a series of computer-executable instructions and computer-accessible data associated with the series of computer-executable instructions that, when executed by the processor, cause the processor to perform the method as shown in the embodiment of fig. 1.
Furthermore, a non-transitory computer-readable storage medium is disclosed, on which a series of computer-executable instructions are stored, which, when executed by a computing device, cause the computing device to perform the method as shown in the embodiment of fig. 1.
While, for purposes of simplicity of explanation, the methodologies are shown and described as a series of acts, it is to be understood and appreciated that the methodologies are not limited by the order of acts, as some acts may, in accordance with one or more embodiments, occur in different orders and/or concurrently with other acts from that shown and described herein or not shown and described herein, as would be understood by one skilled in the art.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. 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 invention.
The various illustrative logical blocks, modules, and circuits described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.
In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a web site, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk (disk) and disc (disc), as used herein, includes Compact Disc (CD), laser disc, optical disc, Digital Versatile Disc (DVD), floppy disk and blu-ray disc where disks (disks) usually reproduce data magnetically, while discs (discs) reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
The previous description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (6)

1. A method for improving warehousing distribution efficiency, the method comprising:
step 1: acquiring data of all current non-delivery orders;
step 2: all the obtained current non-shipped order data and the minimum amount of orders of each batch are substituted into the integer planning model to generate order batches, so that more orders can be covered as far as possible on the premise that the minimum amount of orders of each batch is met;
and step 3: in the picking stage, picking is carried out according to the order batch generated in the step 2, and the picking mode is that the commodities with the same item are respectively placed in different grids of the picking truck according to the commodities, and the commodities with different items are all placed in the same grid;
and 4, step 4: in the distribution stage, firstly, different commodities are obtained, orders directly related to the commodities are scanned, then one commodity is taken from the other commodities of the same item under the orders, and packaging and delivery are completed;
in step 2, the mode of generating order batches by the integer programming model is as follows:
let the order pool be W, the order pool contains the total number of orders n, the minimum number of orders per batch b, the number of all possible combinations of the set A is W, and the variable x is 0-1ijWhether order j is generated as AiAn order of type;
an objective function:
Figure FDA0003250688600000011
constraint conditions are as follows:
Figure FDA0003250688600000012
Figure FDA0003250688600000013
xij∈{0,1}
and solving according to the objective function and the constraint condition to obtain the order batch which accords with the integer programming model.
2. The method for improving warehousing shipment efficiency as claimed in claim 1, wherein in step 1, all the current non-shipment order data is obtained from an e-commerce ERP system.
3. A system for improving warehousing distribution efficiency, the system comprising:
the order data acquisition module is used for acquiring all current non-delivery order data;
the order batch generation module is used for substituting the acquired current all non-shipped order data and the minimum order number of each batch into the integer planning model to generate order batches so as to cover more orders as far as possible on the premise of meeting the minimum order number of each batch;
the picking module picks the goods according to the order batch generated in the order batch generating module in a picking stage, wherein the picking mode is that the goods with the same item are respectively placed in different lattices of the picking vehicle according to the goods, and the goods with different items are all placed in the same lattice;
the goods distribution module is used for acquiring different commodities in a goods distribution stage, directly associating orders of the commodities by scanning, and then taking one of the other commodities in the same item under the orders to finish packaging and delivery;
the order batch generation module generates the order batch based on the integer programming model in the following mode:
let the order pool be W, the order pool contains the total number of orders n, the minimum number of orders per batch b, the number of all possible combinations of the set A is W, and the variable x is 0-1ijWhether order j is generated as AiAn order of type;
an objective function:
Figure FDA0003250688600000021
constraint conditions are as follows:
Figure FDA0003250688600000022
Figure FDA0003250688600000023
xij∈{0,1}
and solving according to the objective function and the constraint condition to obtain the order batch which accords with the integer programming model.
4. The system for improving warehousing distribution efficiency according to claim 3, wherein the order data acquisition module acquires all currently non-shipped order data from an e-commerce ERP system.
5. A system for improving warehousing distribution efficiency, the system comprising:
a processor; and
a memory configured to store a series of computer-executable instructions and computer-accessible data associated with the series of computer-executable instructions,
wherein the series of computer executable instructions, when executed by the processor, cause the processor to perform the method of any of claims 1 to 2.
6. A non-transitory computer readable storage medium having stored thereon a series of computer executable instructions that, when executed by a computing device, cause the computing device to perform the method of any of claims 1-2.
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