CN112070330A - Warehouse-out method and device - Google Patents
Warehouse-out method and device Download PDFInfo
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- CN112070330A CN112070330A CN201910500150.1A CN201910500150A CN112070330A CN 112070330 A CN112070330 A CN 112070330A CN 201910500150 A CN201910500150 A CN 201910500150A CN 112070330 A CN112070330 A CN 112070330A
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- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
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Abstract
The invention discloses a warehouse-out method and device, and relates to the technical field of computers. One embodiment of the method comprises: judging whether the difference value between the picking end time and the current time is smaller than a preset time threshold value or not; if so, screening out the order tasks to be delivered from the warehouse between the current time and the picking end time, and establishing a plurality of task lists according to the order tasks to be delivered and the predicted capacity of each picking person; wherein each task order comprises a plurality of goods to be picked; and configuring the picking priority of the plurality of task lists as the highest priority, and sending the plurality of task lists to a task pool so as to be preferentially picked by picking personnel. The implementation mode can solve the technical problem that the risk of hanging the order is easily caused when the picking end time is close.
Description
Technical Field
The invention relates to the technical field of warehousing, in particular to a warehouse-out method and device.
Background
At present, with the rapid development of logistics, the order quantity is generally large, and the number of the single order is usually small. Therefore, during warehouse production, the production is carried out according to the mode of the collection sheet. When the collection list is established, the warehouse configures the parameters of the collection list according to the warehouse capacity, the storage area rule and the like; after the configuration is completed, the downloaded orders are constructed according to the parameters of the collection sheet, and then a plurality of task sheets are distributed according to the collection sheet.
In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art:
when the picking personnel automatically receives the picking task order, the order which is not close to the picking end time can be distributed to the picking personnel together according to the principle of optimal picking path, so that the picking personnel can not pick the order which is close to the picking end time by automatically receiving the picking task order. Therefore, the risk of hanging orders is easily caused near the end time of picking.
Disclosure of Invention
In view of the above, embodiments of the present invention provide a method and an apparatus for delivering a delivery order, so as to solve the technical problem of a risk of hanging orders when the time of picking orders is close.
To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a method for ex-warehouse, including:
judging whether the difference value between the picking end time and the current time is smaller than a preset time threshold value or not;
if so, screening out the order tasks to be delivered from the warehouse between the current time and the picking end time, and establishing a plurality of task lists according to the order tasks to be delivered and the predicted capacity of each picking person; wherein each task order comprises a plurality of goods to be picked;
and configuring the picking priority of the plurality of task lists as the highest priority, and sending the plurality of task lists to a task pool so as to be preferentially picked by picking personnel.
Optionally, before the step of building a plurality of task orders according to the tasks of the orders to be delivered from the warehouse and the forecasted capacity of each order picker, the method further comprises the following steps:
respectively calculating the historical capacity of each goods picking person according to the historical work total amount and the work duration of each goods picking person;
and respectively calculating the predicted capacity of each goods picking person according to the historical capacity of each goods picking person, the difference value between the goods picking ending time and the current time and the number of the current remaining goods picking numbers.
Optionally, a plurality of task orders are established according to the tasks of the orders to be delivered and the predicted capacity of each order picker, wherein the task orders comprise:
calculating the total number of the goods to be picked according to the order task to be delivered;
calculating the average estimated capacity of the picking personnel according to the estimated capacity of each picking personnel;
and calculating the number of the task orders based on the total number of the goods to be picked and the average predicted capacity, thereby constructing a plurality of task orders.
Optionally, the method further comprises:
after the picking personnel finish the picking task, the rechecking priority of the plurality of task sheets is configured to be the highest, and the plurality of task sheets are pushed to the rechecking personnel, so that the order task to be delivered is delivered out preferentially.
In addition, according to another aspect of the embodiments of the present invention, there is provided a warehouse exit apparatus including:
the building module is used for judging whether the difference value between the picking end time and the current time is smaller than a preset time threshold value or not; if so, screening out the order tasks to be delivered from the warehouse between the current time and the picking end time, and establishing a plurality of task lists according to the order tasks to be delivered and the predicted capacity of each picking person; wherein each task order comprises a plurality of goods to be picked;
and the task module is used for configuring the picking priority of the plurality of task lists to be the highest and sending the plurality of task lists to the task pool so as to be preferentially picked by picking personnel.
Optionally, the building module is further configured to: before a plurality of task lists are established according to the tasks of the orders to be delivered and the predicted capacity of each order picker,
respectively calculating the historical capacity of each goods picking person according to the historical work total amount and the work duration of each goods picking person;
and respectively calculating the predicted capacity of each goods picking person according to the historical capacity of each goods picking person, the difference value between the goods picking ending time and the current time and the number of the current remaining goods picking numbers.
Optionally, a plurality of task orders are established according to the tasks of the orders to be delivered and the predicted capacity of each order picker, wherein the task orders comprise:
calculating the total number of the goods to be picked according to the order task to be delivered;
calculating the average estimated capacity of the picking personnel according to the estimated capacity of each picking personnel;
and calculating the number of the task orders based on the total number of the goods to be picked and the average predicted capacity, thereby constructing a plurality of task orders.
Optionally, the method further comprises:
and the rechecking module is used for configuring the rechecking priority of the plurality of task sheets to be the highest after the picking personnel finishes the picking task and pushing the plurality of task sheets to the rechecking personnel so as to carry out the order task to be delivered out of the warehouse preferentially.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any of the embodiments described above.
According to another aspect of the embodiments of the present invention, there is also provided a computer readable medium, on which a computer program is stored, which when executed by a processor implements the method of any of the above embodiments.
One embodiment of the above invention has the following advantages or benefits: because the technical means that if the difference value between the picking end time and the current time is smaller than the preset time threshold value, a plurality of task lists are established according to the order tasks to be delivered and the predicted production capacity, and the priority of the task lists is configured to be the highest is adopted, the technical problem that the risk of hanging the lists is easily caused when the picking end time is close to in the prior art is solved. When the picking ending time is close, the embodiment of the invention flexibly constructs a plurality of task lists according to the order tasks to be delivered and the expected capacity, and the priority of the task lists is configured to be the highest, so that the order tasks to be delivered close to the picking ending time are guaranteed to be preferentially taken, and only the goods to be picked of the order tasks to be delivered close to the picking ending time are in the task lists, thereby increasing the efficiency of the picking personnel for processing the order tasks to be delivered close to the picking ending time, maximizing the picking efficiency and avoiding the risk of hanging the lists.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a schematic diagram of a main flow of a ex-warehouse method according to an embodiment of the invention;
FIG. 2 is a prior art pick path;
FIG. 3 is a pick path according to an embodiment of the present invention;
FIG. 4 is a schematic view of a main flow of a ex-warehouse method according to a referential embodiment of the present invention;
FIG. 5 is a prior art review sequence;
FIG. 6 is a review sequence according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of the main modules of a ex-warehouse device according to an embodiment of the invention;
FIG. 8 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 9 is a schematic structural diagram of a computer system suitable for implementing a terminal device or a server according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In the prior art, when the picking time is close to the picking end time, due to the fact that the number of the collection sheets is too large, the picking personnel cannot pick the orders close to the picking end time by automatically picking the picking task order, and therefore the collection sheets cannot be guaranteed to be completely produced, and the risk of hanging the order is caused.
For example, as shown in the following table, the order picking end time of the collection sheet A is 11:00, and the collection sheet A may be at risk of hanging orders due to the current time being 10: 50.
Time of wave | End time of picking | Current time | Capacity of production | Whether or not to hang the bill | |
Collection sheet A | 10:10 | 11:00 | 10:50 | 10/min | Is that |
Collection sheet B | 11:10 | 12:00 | 10:50 | 10/min | Whether or not |
No personnel configuration is considered in the prior art group of single rules: when the personnel are insufficient, the built goods picking task cannot be reduced according to the productivity; when the personnel are sufficient, the built picking task cannot be increased according to the productivity. If the completion condition of the current picking task of the staff is not considered during order forming, the order forming is completed only according to the number of the staff, and the order forming is completed, and enough staff does not pick the goods, so that the system hangs the order. Moreover, because there is no emergency review process, after the picking of the goods is completed, the order is not known to be an emergency order, and the order cannot be reviewed preferentially, so that the system hangs the order.
Fig. 1 is a schematic diagram of a main flow of a ex-warehouse method according to an embodiment of the present invention. As an embodiment of the present invention, as shown in fig. 1, the ex-warehouse method may include:
step 101, judging whether the difference value between the picking end time and the current time is smaller than a preset time threshold value or not; if yes, go to step 102.
A time threshold, which is a constant and is set in units of minutes, may be set in the system in advance. The time threshold may be set according to actual needs, for example, 30 minutes, 45 minutes, 60 minutes, and the like, which is not limited in this embodiment of the present invention.
Alternatively, different time thresholds may be set for different periods of time (e.g., off-season, high-season, active period, inactive period, etc.), and an appropriate time threshold may be automatically selected for comparison with the difference between the pick end time and the current time.
When the picking end time is close, the number of the collection sheets is too large, and the collection sheets cannot be guaranteed to be completely produced.
And 102, screening out the order tasks to be delivered between the current time and the picking end time, and establishing a plurality of task lists according to the order tasks to be delivered and the predicted capacity of each picking person.
If the difference between the picking end time and the current time is less than the preset time threshold, it indicates that the current time is close to the picking end time, there is a risk of hanging orders, and therefore, the orders with the risk of hanging orders need to be processed preferentially.
Specifically, the order task to be delivered is screened out, wherein the order task needs to be picked between the current time and the picking end time, and then a plurality of task lists are established according to the order details (mainly comprising an item SKU and the number of items) of the order task to be delivered and the capacity of each picking person. Wherein each order includes a plurality of items to be picked.
Assuming that the total number of the goods to be picked is 100 according to the task statistics of the order to be delivered, the prior art only constructs 1 task order, although 10 picking personnel can pick the goods, the number of the task order is only 1, and only 1 person can be allocated to pick the goods, so that the maximum picking efficiency can not be achieved, and the order hanging can be caused. The embodiment of the invention can be constructed into a plurality of task lists, such as 5 task lists, each task list comprises 20 goods to be picked, so that a plurality of goods picking personnel can pick the goods simultaneously, the goods picking efficiency is maximized, and the risk of hanging the order is avoided.
Therefore, the embodiment of the invention constructs a plurality of task lists according to the order tasks to be delivered and the expected capacity of the picking personnel, so that a plurality of people can pick the goods at the same time, thereby achieving the centralized maximum quantity of picking the goods and avoiding that the single task list is too large and is centralized to a certain person, and other people do not have picking tasks.
The embodiment of the invention further considers personnel configuration, namely the task list is constructed by combining the capacity of the goods picking personnel. Specifically, the projected capacity of each picker is calculated using the following method: respectively calculating the historical capacity of each goods picking person according to the historical work total amount and the work duration of each goods picking person; and respectively calculating the predicted capacity of each goods picking person according to the historical capacity of each goods picking person, the difference value between the goods picking ending time and the current time and the number of the current remaining goods picking numbers.
For example, the projected capacity for each picker may be calculated by:
historical capacity (piece/hour) ═ total work amount in previous day/[ work duration ]
Predicted capacity (piece) ([ end time of picking ] - [ current time ]) historical capacity-number of picking pieces left in current task of picking person
After obtaining the projected capacity of each picker, step 102 may specifically include: calculating the total number of the goods to be picked according to the order task to be delivered; calculating the average estimated capacity of the picking personnel according to the estimated capacity of each picking personnel; and calculating the number of the task orders based on the total number of the goods to be picked and the average predicted capacity, thereby constructing a plurality of task orders. In an embodiment of the present invention, the total number of items to be picked may be divided by the average projected capacity of the picker, and the quotient of the two divisions may be used as the number of order sheets, such as 10 order sheets, 20 order sheets, etc.
For example, the embodiment of the invention constructs 10 task orders according to the total number of the goods to be picked and the predicted capacity of the picking personnel, each task order comprises 10 goods to be picked, and then 10 picking personnel can pick at the same time, thereby maximizing the total picking amount in a period of time, completing the picking task and avoiding the hanging of the order.
103, configuring the picking priority of the plurality of task lists to be the highest, and sending the plurality of task lists to a task pool to be picked by picking personnel preferentially.
In the embodiment of the invention, the picking priority of the task order built in the step 102 is configured to be the highest, and when picking the task order, the picking personnel preferentially distribute the task order built by the invention to the picking personnel, so that the task of the order to be delivered from the warehouse adjacent to the picking ending time can be preferentially picked, and only the items to be picked of the order to be delivered task adjacent to the picking ending time are in the task order, thereby increasing the efficiency of the picking personnel for processing the order to be delivered task adjacent to the picking ending time.
In the prior art, since the priority of the order tasks to be delivered from the warehouse near the picking end time is configured to be the highest, when the picking personnel automatically receives the picking task order, the order not near the picking end time can be distributed to the picking personnel according to the principle of optimal picking path, so that the picking personnel cannot pick the order near the picking end time by automatically receiving the picking task order, and the risk of hanging the order is easily caused. As shown in fig. 2, according to the conventional picking strategy, the picking personnel needs to walk 500 meters, and needs to pick 10 storage locations, wherein the 10 storage locations are both the order (emergency order) near the picking end time and the order (non-emergency order) not near the picking end time, so that the picking efficiency cannot be maximized in the prior art, and the risk of picking orders is easily caused.
However, in the embodiment of the invention, the task order of the component is preferentially distributed to the order picking personnel, and only the goods to be picked of the order task to be delivered from the warehouse near the end time of the order picking are in the task order. As shown in fig. 3, the picking personnel only need to walk 200 meters, and only need to pick 4 storage positions, and the 4 storage positions are all orders (emergency orders) near the end time of picking, so that the picking efficiency can be maximized, and the risk of hanging orders is avoided.
According to the various embodiments described above, it can be seen that the present invention solves the problem of the prior art that the risk of hanging orders is easily caused when the picking end time is close by, by constructing a plurality of task orders according to the to-be-delivered order tasks and the expected capacity and configuring the priority of the task orders as the highest technical means if the difference between the picking end time and the current time is less than the preset time threshold. When the picking ending time is close, the embodiment of the invention flexibly constructs a plurality of task lists according to the order tasks to be delivered and the expected capacity, and the priority of the task lists is configured to be the highest, so that the order tasks to be delivered close to the picking ending time are guaranteed to be preferentially taken, and only the goods to be picked of the order tasks to be delivered close to the picking ending time are in the task lists, thereby increasing the efficiency of the picking personnel for processing the order tasks to be delivered close to the picking ending time, maximizing the picking efficiency and avoiding the risk of hanging the lists.
Fig. 4 is a schematic diagram of a main flow of a ex-warehouse method according to a referential embodiment of the present invention, where the ex-warehouse method may specifically include:
at step 401, the projected capacity of each picker is calculated.
Specifically, the projected capacity of each picker is calculated using the following method: respectively calculating the historical capacity of each goods picking person according to the historical work total amount and the work duration of each goods picking person; and respectively calculating the predicted capacity of each goods picking person according to the historical capacity of each goods picking person, the difference value between the goods picking ending time and the current time and the number of the current remaining goods picking numbers.
Step 402, judging whether the difference value between the picking end time and the current time is less than a preset time threshold value; if yes, go to step 403; if not, the process is ended.
And 403, screening out the order tasks to be delivered between the current time and the picking end time.
If the difference value between the picking end time and the current time is smaller than the preset time threshold value, the current time is close to the adjacent picking end time, and the risk of hanging the order exists, so that the order task to be delivered, which needs to complete the picking between the current time and the picking end time, needs to be screened out preferentially.
Step 404, a plurality of task orders are established according to the order tasks to be delivered and the predicted capacity of each order picker.
The method can specifically comprise the following steps: calculating the total number of the goods to be picked according to the order task to be delivered; calculating the average estimated capacity of the picking personnel according to the estimated capacity of each picking personnel; and calculating the number of the task orders based on the total number of the goods to be picked and the average predicted capacity, thereby constructing a plurality of task orders.
In step 405, the picking priority of the plurality of task orders is configured to be the highest.
And 406, issuing the plurality of task lists to a task pool so as to be preferentially picked by the picking personnel.
When picking up the task order, the order picking personnel preferentially distribute the task order constructed by the invention to the order picking personnel, so that the order task to be delivered from the warehouse adjacent to the order picking ending time can be preferentially picked, and only the items to be picked of the order task to be delivered from the warehouse adjacent to the order picking ending time are in the task order, thereby increasing the efficiency of the order picking personnel for processing the order task to be delivered from the warehouse adjacent to the order picking ending time.
And step 407, after the order picking personnel completes the order picking task, configuring the rechecking priority of the plurality of task orders to be the highest.
After the pick is completed, the review priority of the order sheets may be automatically configured to be highest.
And step 408, pushing the plurality of task lists to recheckers, so as to carry out the priority delivery of the order tasks to be delivered.
After the picking is finished, the task orders are preferentially recommended to the rechecking personnel, and the rechecking personnel can preferentially recheck the task orders, namely preferentially recheck the order tasks to be delivered from the warehouse, which are close to the picking end time.
In the rechecking process, the system prompts that tasks needing to be taken out of the warehouse preferentially, such as words of 'please review preferentially', and forces the rechecking personnel to review the tasks of the orders to be taken out of the warehouse close to the picking end time preferentially so as to ensure that the tasks of the orders to be taken out of the warehouse close to the picking end time preferentially take out of the warehouse.
As shown in fig. 5, in the prior art, sequential rechecking is performed according to the sequence of arriving at the compound station, and the order task to be delivered from the warehouse adjacent to the picking end time cannot be rechecked preferentially, resulting in the risk of hanging orders. As shown in fig. 6, in the embodiment of the present invention, since the highest priority is configured, the order tasks to be delivered from the warehouse near the picking end time can be checked preferentially to ensure that the order tasks to be delivered from the warehouse are delivered preferentially, so as to avoid the risk of hanging orders.
In addition, in one embodiment of the present invention, the detailed implementation of the ex-warehouse method is described in detail above, and therefore, the repeated content will not be described herein.
Fig. 7 is a schematic diagram of main modules of the ex-warehouse device according to the embodiment of the invention. As shown in fig. 7, the library output device 700 includes a building module 701 and a task module 702. The building module 701 is configured to determine whether a difference between the picking end time and the current time is smaller than a preset time threshold; if so, screening out the order tasks to be delivered from the warehouse between the current time and the picking end time, and establishing a plurality of task lists according to the order tasks to be delivered and the predicted capacity of each picking person; wherein each task order comprises a plurality of goods to be picked; the task module 702 is configured to configure the picking priority of the task sheets to be the highest, and issue the task sheets to the task pool to be preferentially picked by the picking staff.
Optionally, the building module 701 is further configured to: before a plurality of task lists are established according to the tasks of the orders to be delivered and the predicted capacity of each order picker,
respectively calculating the historical capacity of each goods picking person according to the historical work total amount and the work duration of each goods picking person;
and respectively calculating the predicted capacity of each goods picking person according to the historical capacity of each goods picking person, the difference value between the goods picking ending time and the current time and the number of the current remaining goods picking numbers.
Optionally, a plurality of task orders are established according to the tasks of the orders to be delivered and the predicted capacity of each order picker, wherein the task orders comprise:
calculating the total number of the goods to be picked according to the order task to be delivered;
calculating the average estimated capacity of the picking personnel according to the estimated capacity of each picking personnel;
and calculating the number of the task orders based on the total number of the goods to be picked and the average predicted capacity, thereby constructing a plurality of task orders.
Optionally, the method further comprises:
the rechecking module 703 is configured to configure the rechecking priority of the plurality of task sheets to be the highest after the picking staff completes the picking task, and push the plurality of task sheets to the rechecking staff, so as to preferentially deliver the to-be-delivered order task.
According to the various embodiments described above, it can be seen that the present invention solves the problem of the prior art that the risk of hanging orders is easily caused when the picking end time is close by, by constructing a plurality of task orders according to the to-be-delivered order tasks and the expected capacity and configuring the priority of the task orders as the highest technical means if the difference between the picking end time and the current time is less than the preset time threshold. When the picking ending time is close, the embodiment of the invention flexibly constructs a plurality of task lists according to the order tasks to be delivered and the expected capacity, and the priority of the task lists is configured to be the highest, so that the order tasks to be delivered close to the picking ending time are guaranteed to be preferentially taken, and only the goods to be picked of the order tasks to be delivered close to the picking ending time are in the task lists, thereby increasing the efficiency of the picking personnel for processing the order tasks to be delivered close to the picking ending time, maximizing the picking efficiency and avoiding the risk of hanging the lists.
It should be noted that, in the embodiments of the present invention, the details of the library output device are already described in detail in the above library output method, and therefore, the repeated details are not described herein.
Fig. 8 illustrates an exemplary system architecture 800 to which the ex-warehouse method or the ex-warehouse apparatus of an embodiment of the present invention may be applied.
As shown in fig. 8, the system architecture 800 may include terminal devices 801, 802, 803, a network 804, and a server 805. The network 804 serves to provide a medium for communication links between the terminal devices 801, 802, 803 and the server 805. Network 804 may include various types of connections, such as wire, wireless communication links, or fiber optic cables, to name a few.
A user may use the terminal devices 801, 802, 803 to interact with a server 804 over a network 804 to receive or send messages or the like. The terminal devices 801, 802, 803 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 801, 802, 803 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 805 may be a server that provides various services, such as a back-office management server (for example only) that supports shopping-like websites browsed by users using the terminal devices 801, 802, 803. The background management server may analyze and process the received data such as the product information query request, and feed back a processing result (for example, target push information and product information — only an example) to the terminal device.
It should be noted that the ex-warehouse method provided by the embodiment of the present invention is generally executed on the terminal devices 801, 802, and 803 in the public place, and may also be executed by the server 805, and accordingly, the ex-warehouse device is generally installed on the terminal devices 801, 802, and 803 in the public place, and may also be installed in the server 805.
It should be understood that the number of terminal devices, networks, and servers in fig. 8 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 9, shown is a block diagram of a computer system 900 suitable for use with a terminal device implementing an embodiment of the present invention. The terminal device shown in fig. 9 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 9, the computer system 900 includes a Central Processing Unit (CPU)901 that can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)902 or a program loaded from a storage section 908 into a Random Access Memory (RAM) 903. In the RAM903, various programs and data necessary for the operation of the system 900 are also stored. The CPU 901, ROM 902, and RAM903 are connected to each other via a bus 904. An input/output (I/O) interface 905 is also connected to bus 904.
The following components are connected to the I/O interface 905: an input portion 906 including a keyboard, a mouse, and the like; an output section 907 including components such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 908 including a hard disk and the like; and a communication section 909 including a network interface card such as a LAN card, a modem, or the like. The communication section 909 performs communication processing via a network such as the internet. The drive 910 is also connected to the I/O interface 905 as necessary. A removable medium 911 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 910 as necessary, so that a computer program read out therefrom is mounted into the storage section 908 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 909, and/or installed from the removable medium 911. The above-described functions defined in the system of the present invention are executed when the computer program is executed by a Central Processing Unit (CPU) 901.
It should be noted that the computer readable medium shown in the present invention can 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 invention, 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 the present invention, however, 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 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 medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, 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 systems, methods and computer program products according to various embodiments of the present invention. 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 described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes a build module, a task module, and a review module, where the names of the modules do not in some cases constitute a limitation on the modules themselves.
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise: judging whether the difference value between the picking end time and the current time is smaller than a preset time threshold value or not; if so, screening out the order tasks to be delivered from the warehouse between the current time and the picking end time, and establishing a plurality of task lists according to the order tasks to be delivered and the predicted capacity of each picking person; wherein each task order comprises a plurality of goods to be picked; and configuring the picking priority of the plurality of task lists as the highest priority, and sending the plurality of task lists to a task pool so as to be preferentially picked by picking personnel.
According to the technical scheme of the embodiment of the invention, as the technical means that if the difference value between the picking end time and the current time is less than the preset time threshold value, a plurality of task lists are established according to the order tasks to be delivered and the predicted capacity, and the priority of the task list is configured to be the highest is adopted, the technical problem that the risk of hanging the list is easily caused when the picking end time is close to the prior art is solved. When the picking ending time is close, the embodiment of the invention flexibly constructs a plurality of task lists according to the order tasks to be delivered and the expected capacity, and the priority of the task lists is configured to be the highest, so that the order tasks to be delivered close to the picking ending time are guaranteed to be preferentially taken, and only the goods to be picked of the order tasks to be delivered close to the picking ending time are in the task lists, thereby increasing the efficiency of the picking personnel for processing the order tasks to be delivered close to the picking ending time, maximizing the picking efficiency and avoiding the risk of hanging the lists.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method of ex-warehouse, comprising:
judging whether the difference value between the picking end time and the current time is smaller than a preset time threshold value or not;
if so, screening out the order tasks to be delivered from the warehouse between the current time and the picking end time, and establishing a plurality of task lists according to the order tasks to be delivered and the predicted capacity of each picking person; wherein each task order comprises a plurality of goods to be picked;
and configuring the picking priority of the plurality of task lists as the highest priority, and sending the plurality of task lists to a task pool so as to be preferentially picked by picking personnel.
2. The method of claim 1, wherein prior to assembling a plurality of job orders based on the tasks for the orders to be picked and the forecasted capacity of each picker, further comprising:
respectively calculating the historical capacity of each goods picking person according to the historical work total amount and the work duration of each goods picking person;
and respectively calculating the predicted capacity of each goods picking person according to the historical capacity of each goods picking person, the difference value between the goods picking ending time and the current time and the number of the current remaining goods picking numbers.
3. The method of claim 1, wherein the step of forming a plurality of job orders based on the job of the order to be picked and the projected capacity of each picker comprises:
calculating the total number of the goods to be picked according to the order task to be delivered;
calculating the average estimated capacity of the picking personnel according to the estimated capacity of each picking personnel;
and calculating the number of the task orders based on the total number of the goods to be picked and the average predicted capacity, thereby constructing a plurality of task orders.
4. The method of claim 1, further comprising:
after the picking personnel finish the picking task, the rechecking priority of the plurality of task sheets is configured to be the highest, and the plurality of task sheets are pushed to the rechecking personnel, so that the order task to be delivered is delivered out preferentially.
5. An ex-warehouse device, comprising:
the building module is used for judging whether the difference value between the picking end time and the current time is smaller than a preset time threshold value or not; if so, screening out the order tasks to be delivered from the warehouse between the current time and the picking end time, and establishing a plurality of task lists according to the order tasks to be delivered and the predicted capacity of each picking person; wherein each task order comprises a plurality of goods to be picked;
and the task module is used for configuring the picking priority of the plurality of task lists to be the highest and sending the plurality of task lists to the task pool so as to be preferentially picked by picking personnel.
6. The apparatus of claim 5, wherein the composition module is further configured to: before a plurality of task lists are established according to the tasks of the orders to be delivered and the predicted capacity of each order picker,
respectively calculating the historical capacity of each goods picking person according to the historical work total amount and the work duration of each goods picking person;
and respectively calculating the predicted capacity of each goods picking person according to the historical capacity of each goods picking person, the difference value between the goods picking ending time and the current time and the number of the current remaining goods picking numbers.
7. The apparatus of claim 5, wherein the building of the plurality of job orders based on the job of the order to be picked and the projected capacity of each picker comprises:
calculating the total number of the goods to be picked according to the order task to be delivered;
calculating the average estimated capacity of the picking personnel according to the estimated capacity of each picking personnel;
and calculating the number of the task orders based on the total number of the goods to be picked and the average predicted capacity, thereby constructing a plurality of task orders.
8. The apparatus of claim 6, further comprising:
and the rechecking module is used for configuring the rechecking priority of the plurality of task sheets to be the highest after the picking personnel finishes the picking task and pushing the plurality of task sheets to the rechecking personnel so as to carry out the order task to be delivered out of the warehouse preferentially.
9. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-4.
10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-4.
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