CN117408780A - Order processing method, order processing device, electronic equipment and machine-readable storage medium - Google Patents

Order processing method, order processing device, electronic equipment and machine-readable storage medium Download PDF

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CN117408780A
CN117408780A CN202311406759.5A CN202311406759A CN117408780A CN 117408780 A CN117408780 A CN 117408780A CN 202311406759 A CN202311406759 A CN 202311406759A CN 117408780 A CN117408780 A CN 117408780A
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sub
orders
goods
wave
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宋金胆
唐恒博
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Hangzhou Hikrobot Co Ltd
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Hangzhou Hikrobot Co Ltd
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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
    • G06Q30/00—Commerce
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    • G06Q30/0601—Electronic shopping [e-shopping]
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    • G06Q30/0635—Processing of requisition or of purchase orders
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    • 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
    • G06Q10/0875—Itemisation or classification of parts, supplies or services, e.g. bill of materials

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Abstract

The application provides an order processing method, an order processing device, electronic equipment and a machine-readable storage medium, wherein the method comprises the following steps: acquiring original order information; carrying out correlation analysis on goods included in each order in the original order, and determining correlation among the goods; splitting all orders in the original order according to the correlation among the goods to obtain split sub orders; wherein, in the same order, the higher the correlation between goods, the higher the possibility of being split into the same sub-order; performing wave number combination on the sub orders according to the similarity of goods among the sub orders, and distributing the orders to a workstation for execution according to the wave number; wherein, the higher the goods similarity of the sub-orders, the higher the probability of combining into the same wave number. The method can effectively improve the order processing efficiency.

Description

Order processing method, order processing device, electronic equipment and machine-readable storage medium
Technical Field
The present disclosure relates to the field of logistics distribution technologies, and in particular, to an order processing method, an order processing device, an electronic device, and a machine-readable storage medium.
Background
Aiming at the orders with large partial traffic and clear delivery timeliness requirements in the logistics distribution service, if the orders are processed according to the traditional order-based operation mode, the timeliness requirements cannot be met due to overlong execution time. Thus, it is necessary to execute the order after splitting and reorganizing to improve timeliness.
The traditional order splitting mode aims at a manual operation warehouse and cannot be suitable for robot goods arrival scenes.
For a robot goods arrival scene, how to reasonably realize order splitting becomes a technical problem to be solved.
Disclosure of Invention
In view of the foregoing, the present application provides an order processing method, an order processing device, an electronic device, and a machine-readable storage medium.
According to a first aspect of an embodiment of the present application, there is provided an order processing method, including:
acquiring original order information;
carrying out correlation analysis on goods included in each order in the original order, and determining correlation among the goods;
splitting all orders in the original order according to the correlation among the goods to obtain split sub orders; wherein, in the same order, the higher the correlation between goods, the higher the possibility of being split into the same sub-order;
performing wave number combination on the sub orders according to the similarity of goods among the sub orders, and distributing the orders to a workstation for execution according to the wave number; wherein, the higher the goods similarity of the sub-orders, the higher the probability of combining into the same wave number.
According to a second aspect of embodiments of the present application, there is provided an order processing apparatus, including:
the acquisition unit is used for acquiring original order information;
the determining unit is used for carrying out correlation analysis on the goods included in each order in the original order and determining the correlation among the goods;
the splitting unit is used for splitting the sub-orders of each order in the original order according to the correlation among the goods to obtain split sub-orders; wherein, in the same order, the higher the correlation between goods, the higher the possibility of being split into the same sub-order;
the combining unit is used for carrying out wave combination on the sub orders according to the similarity of goods among the sub orders; wherein, the higher the similarity of goods of the sub-order, the higher the possibility of combining into the same wave number;
and the allocation unit is used for allocating orders to the workstations for execution according to the wave number.
According to a third aspect of embodiments of the present application, there is provided an electronic device comprising a processor and a machine-readable storage medium storing machine-executable instructions executable by the processor for executing the machine-executable instructions to implement the method provided in the first aspect.
According to a fourth aspect of embodiments of the present application, there is provided a machine-readable storage medium having stored therein machine-executable instructions which, when executed by a processor, implement the method provided in the first aspect.
According to the order processing method, correlation analysis is carried out on the goods included in each order in the original order, correlation among the goods is determined, sub-order splitting is carried out on each order in the original order according to the correlation among the goods, split sub-orders are obtained, further, wave order combination is carried out on the sub-orders according to the similarity of the goods among the sub-orders, the orders are distributed to a workstation for execution according to the wave order, when the sub-orders are split, the goods with high correlation are split to the same sub-order preferentially, and when the wave order combination is carried out, the sub-orders with high similarity of the goods are combined to the same wave order preferentially, so that the carrying efficiency of the same goods in different orders can be improved, and further, the order processing efficiency is effectively improved.
Drawings
Fig. 1 is a schematic flow chart of an order processing method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of an order splitting process provided in an embodiment of the present application;
FIG. 3 is a schematic flow chart of order processing according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an order processing device according to an embodiment of the present application;
fig. 5 is a schematic hardware structure of an electronic device according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application as detailed in the accompanying claims.
The terminology used in the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
In order to enable those skilled in the art to better understand the technical solutions provided in the embodiments of the present application, some terms related to the embodiments of the present application will be briefly described below.
1. Goods to people: in the warehouse logistics operation process, an operator is at a fixed position, and the robot equipment conveys goods to a designated position for the operator to operate;
2. original order: the original order issued by the upstream system is referred to;
3. sub-orders: after splitting the original order, generating a new order;
4. SKU (Stock Keeping Unit ): in the warehouse, only distinguishable goods are indicated, and one SKU uniquely identifies one type of goods;
5. order lines: an order line refers to each item in an order. An order typically contains a plurality of order lines, one for each item and its associated information, such as SKU, product description, quantity, lot, etc.
In order to make the above objects, features and advantages of the embodiments of the present application more comprehensible, the following describes the technical solutions of the embodiments of the present application in detail with reference to the accompanying drawings.
It should be noted that, the sequence number of each step in the embodiment of the present application does not mean that the execution sequence of each process should be determined by the function and the internal logic of each process, and should not limit the implementation process of the embodiment of the present application in any way.
Referring to fig. 1, a flow chart of an order processing method provided in an embodiment of the present application is shown in fig. 1, where the order processing method may include the following steps:
step S100, original order information is acquired.
And step S110, carrying out correlation analysis on the goods included in each order in the original order, and determining the correlation among the goods.
Step S120, splitting all orders in the original order according to the correlation among the goods to obtain split sub orders; wherein the higher the correlation between items in the same order, the higher the likelihood of being split into the same sub-order.
In this embodiment of the present application, for any order, in the case of splitting an order, the correlation between the items in the order may be considered, so as to split the order according to the principle of splitting the items with high correlation to the same sub-order.
Accordingly, under the condition that the original order information is acquired, correlation analysis can be carried out on the goods included in each order in the original order, and correlation among the goods can be determined.
Wherein the higher the correlation between different items, the higher the probability that the different items will appear in the same order.
Sub-order splitting can be performed on the original orders according to the correlation among the goods, and split sub-orders are obtained.
Illustratively, the higher the correlation between items, the higher the likelihood of being split to the same sub-order, i.e., in the case of splitting orders, the higher the correlation of items are preferentially split to the same sub-order.
Step S130, carrying out wave number combination on the sub orders according to the similarity of goods among the sub orders, and distributing the wave numbers to a workstation for execution; wherein, the higher the goods similarity of the sub-orders, the higher the probability of combining into the same wave number.
In order to improve the order processing efficiency, in the case that the order splitting is completed in the above manner, the sub orders may be combined according to the similarity of the goods between the sub orders, that is, the sub orders with high similarity, which are obtained by splitting different orders, are combined into the same wave.
For example, the item similarity between sub-orders may be determined based on the duty cycle of the same items included in the sub-orders.
For example, assuming that sub-order 1 includes items 1-2 and sub-order 2 also includes items 1-2, the similarity of sub-order 1 and sub-order 2 may be 100%.
Assuming that sub-order 1 includes items 1-3 and sub-order 2 includes items 1-2, 4, the similarity of sub-order 1 and sub-order 2 may be 67%.
Illustratively, the higher the item similarity of the sub-orders, the higher the priority of combining into the same wave-times.
In the embodiment of the present application, when the combination of the wave numbers is performed in the above manner, the order may be allocated according to the wave numbers, and the order may be allocated to the workstation for execution.
It can be seen that, in the method flow shown in fig. 1, by performing correlation analysis on the items included in the original orders, determining the correlation between the items, and splitting each sub-order in the original order according to the correlation between the items, so as to obtain split sub-orders, further, according to the similarity of the items between the sub-orders, performing wave-order combination on the sub-orders, and distributing the orders to the workstation for execution according to the wave-order.
In some embodiments, the performing a correlation analysis on the items included in each order in the original order to determine the correlation between the items may include:
determining the correlation between the goods according to the correlation parameters of the goods;
wherein the relevancy parameters of the item include one or more of the following:
name, category, frequency of occurrence of different items in the same order.
For example, the correlation between items may be determined based on one or more of the item name, type, and frequency of occurrence of different items in the same order.
For example, "toothbrush" and "toothpaste" are similar in name and are commonly used articles of daily use, and their correlation may be relatively high.
For another example, assuming a total of 100 orders in which item 1 and item 2 occur simultaneously in 90 orders, the correlation of item 1 and item 2 may be relatively high.
In one example, a relevance score between items may be determined from how frequently different items appear in the same order; wherein the higher the relevance score, the higher the relevance between the items.
For example, assume a total of 100 orders, where item 1 and item 2 occur simultaneously in 90 orders, the relevance score may be 0.9.
In some embodiments, the splitting the sub-order for each order in the original order according to the correlation between the items may include:
sub-order splitting is carried out on the original order according to the correlation among goods and the order splitting limiting condition;
the order splitting limiting conditions comprise an upper limit of the volume of the single sub order and/or an upper limit of the quantity of the single sub order.
In one example, to avoid over-sizing of a single sub-order volume (i.e., the volume of items included in the sub-order), the volume of the sub-order may also be considered in making the order split.
Accordingly, the original order can be split according to the correlation among goods and the volume upper limit of the single sub order, so that the volume of the sub order is prevented from exceeding the preset volume upper limit of the single sub order.
In another example, to avoid an excessive number of sub-orders resulting from a single order split, the number of sub-orders may also be considered when making the order split.
Accordingly, the sub-order splitting can be performed on the original order according to the correlation between goods and the upper limit of the sub-order number of the single order splitting, so that the number of the sub-orders split by the single order is prevented from exceeding the preset upper limit of the sub-order number of the single order splitting.
In yet another example, sub-order splitting may be performed on the original order based on the correlation between items, the upper limit of the volume of the individual sub-orders, and the upper limit of the number of individual sub-orders to split.
In some embodiments, the performing the wave order combination on the sub-orders according to the item similarity between the sub-orders may include:
and carrying out wave number combination on the sub orders according to the similarity of the goods among the sub orders according to the order priority order from high to low.
For example, in order to ensure that orders with high priority can be processed preferentially, when order combination is performed on sub-orders, the order combination can be performed on the sub-orders according to the order from high priority to low priority and the similarity of goods between the sub-orders, that is, the order combination is performed on the sub-orders obtained by splitting the order with high priority preferentially. Further, orders with high priority may be preferentially assigned to workstation execution.
For example, assuming that the order 1 includes items 1-4, the order 2 includes items 1-2 and 5-6, the order 3 includes items 3-4 and 7-8, the order 1 is split into a sub-order 11 (including items 1-2) and a sub-order 12 (including items 3-4), the order 2 is split into a sub-order 21 (including items 1-2) and a sub-order 22 (including items 5-6), the order 3 is split into a sub-order 31 (including items 3-4) and a sub-order 12 (including items 7-8), the similarity of the sub-order 11 and the sub-order 21 is 100%, the similarity of the sub-order 12 and the sub-order 31 is 100%, and the sub-order 11 and the sub-order 21 may be combined (the order 1 and the order 2 may be combined), or the sub-order 12 and the sub-order 31 may be combined (the order 1 and the order 3 may be combined) under the same priority of the orders 1-3; in the case where the priority of order 1 and order 2 is higher than that of order 3, the manner in which sub-order 11 and sub-order 21 are grouped may be adopted, and accordingly, sub-order 12 and sub-order 22 are grouped.
In some embodiments, the performing the wave order combination on the sub-orders according to the similarity of the goods between the sub-orders includes:
carrying out wave combination on the sub orders according to the similarity of goods among the sub orders and the quantity of order lines of the sub orders; wherein, the difference value between the order line numbers of different wave passes is smaller than a preset threshold value.
In the process of carrying out the wave number combination on the sub-orders, in order to avoid the situation that the number of the order lines in different wave numbers is too large, so that the unbalanced distribution of resources is caused, some working areas are busy, other areas are idle, and in the process of carrying out the wave number combination on the sub-orders according to the similarity of goods among the sub-orders, the order line number balance among the wave numbers needs to be ensured as much as possible.
Accordingly, in the process of carrying out wave number combination on the sub-orders according to the goods similarity of each sub-order, for any optional wave number combination scheme, the difference of the number of order lines among the wave numbers in the scheme can be determined, and under the condition that the difference of the number of order lines of different wave numbers is greater than or equal to a preset threshold value, the wave number combination scheme can be eliminated, and then the wave number combination scheme that the difference of the number of order lines of different wave numbers is smaller than the preset threshold value is selected.
Taking the above example as an example, assuming that the similarity between the sub-order 11 and the sub-order 21 is 100%, and the similarity between the sub-order 12 and the sub-order 31 is also 100%, in the case where the priorities of the orders 1 to 3 are the same, it is possible to determine the difference between the number of order lines of different wave times in the case where the sub-order 11 and the sub-order 21 are combined (the order 1 and the order 2 are combined), and the difference between the number of order lines of different wave times in the case where the sub-order 12 and the sub-order 31 are combined (the order 1 and the order 3 are combined), respectively; if the difference value between the order line numbers of different wave numbers is larger than or equal to a preset threshold value, and the difference value between the order line numbers of different wave numbers is smaller than or equal to the preset threshold value, the latter wave combination scheme can be selected.
In some embodiments, the allocating orders to workstations for execution on a wave-by-wave basis may include:
for different wave times, determining the allocation sequence of each wave time according to the priority of the order in the wave time and/or the creation time of the order in the wave time;
for any wave number to be distributed, determining the distance from each article to different work stations according to the stock of each article and work station distribution in the wave number, and distributing orders according to the nearby principle according to the distance from each article to different work stations.
For example, in order to ensure that orders with high priority can be processed as preferentially as possible, and/or orders with early creation time can be processed as preferentially as possible, in the process of allocating orders to workstations for execution according to the wave number, for different wave numbers, the allocation sequence of each wave number can be determined according to the priority of orders in the wave number and/or the creation time of orders in the wave number.
Illustratively, the order priority within a wave-time refers to the priority of sub-orders within a wave-time, and the priority of sub-orders may be determined according to the priority of the order.
In one example, the priority of the highest priority child order within a wave-order may be determined as the priority of the wave-order.
In another example, the priority of each sub-order within a wave may be weighted averaged to determine the priority of the wave.
Taking the priority of the sub-order with the highest priority in the wave number as the priority of the wave number as an example, for different wave numbers, the priority of the wave number can be determined according to the priority of the sub-order with the highest priority in the wave number, and the orders can be distributed to the work stations for execution according to the wave number from high to low according to the priority.
Illustratively, the order creation time is implemented similarly to priority.
For example, taking the case where the creation time of the sub order with the earliest creation time in the wave number is determined as the creation time of the wave number, for different wave numbers, the creation time of the wave number may be determined according to the creation time of the sub order with the earliest creation time in the wave number, and the orders may be allocated to the workstations for execution according to the wave number in the order from the early to the late of the creation time.
In the case where the allocation order of the respective orders is determined, the orders may be allocated to the workstation for execution in order by order.
For any wave number, according to the stock of each goods and the distribution of the work stations in the wave number, the distance between each goods and different work stations is determined, and according to the distance between each goods and different work stations, order distribution is carried out according to the nearby principle.
In one example, the distance (such as average distance or total distance) between each item and different work stations may be determined according to the stock of each item in the same wave, and work stations with smaller distances are selected for order allocation, so as to improve the order processing efficiency.
For example, assuming that the sub-order 11 and the sub-order 21 are combined into the same order, the sub-order 11 and the sub-order 21 each include the item 1 and the item 2, and the workstation includes the workstation 1 and the workstation 2, the distances from the inventory position of the item 1 to the workstation 1 (assumed to be D11) and from the inventory position of the item 1 to the workstation 2 (assumed to be D12), and the distances from the inventory position of the item 2 to the workstation 1 (assumed to be D21) and from the inventory position of the item 2 to the workstation 2 (assumed to be D22), respectively, then:
in case d11+d21 > d12+d22, the sub-order 11 and the sub-order 21 may be assigned to workstation 2;
in case d11+d21 < d12+d22, the sub-order 11 and the sub-order 21 may be assigned to workstation 1;
in the case of d11+d21=d12+d22, the allocation of the sub-order 11 and the sub-order 21 to the workstation 1 or the workstation 2 may be determined in accordance with other strategies. For example, a workstation with a smaller workload is selected for allocation depending on the current workload of the workstation 1 and the workstation 2.
For example, in the embodiment of the application, for orders in any of the wave times allocated to the workstation in the above manner, in the process of performing wave-time picking, the picking order of each order may be determined according to the priority of the order in the wave time and/or the creation time of the order in the wave time.
For example, the creation time of a child order may be determined based on the creation time of the order to which it belongs.
For example, within the same wave, a child order with a high priority may be preferentially picked; sub orders of the same priority are created early in time and can be picked preferentially.
For another example, within the same wave, child orders with early creation times may be preferentially picked; sub orders with the same time are created, and the sub orders with high priority can be picked preferentially.
It should be noted that, in the implementation of the present application, considering that, in a case where other orders are being processed in the workstation, there may be a case where an idle task carrier (such as a bin) cannot meet the requirement of the order that is currently ready to be processed, in order to improve the order processing efficiency, the idle task carrier may be preferentially processed to be able to meet the requirement of the order.
For example, for two sub-orders (assuming sub-order 11 and sub-order 21) within the same wave-time, the picking order determined in the above manner is sub-order 11 in front and sub-order 21 in back, but since there are other orders being processed, the currently free task vehicle cannot meet the requirements of sub-order 11, in which case sub-order 21 may be processed first if the currently free task vehicle can meet the requirements of sub-order 21.
In order to pick an order, the order with a small number of times of conveyance and a short conveyance distance may be preferentially processed in consideration of the number of times of conveyance, the conveyance distance, and the like of the task vehicle.
Furthermore, considering that there may be a certain overlap of the routes in different order processing procedures, in the case that there is a narrow area such as a tunnel on the route, congestion may occur, and thus, abnormality occurs in order processing, in the case of order picking, it is necessary to avoid such a situation as far as possible, for example, for any order to be picked, the processing route of the order overlaps with the processing route of a certain order currently being processed, and there is a narrow area such as a tunnel on the route, so that when the processing of the order currently being processed is completed, the order to be picked may be processed.
In order to enable those skilled in the art to better understand the technical solutions provided by the embodiments of the present application, the technical solutions provided by the embodiments of the present application are described below with reference to specific examples.
The embodiment provides a long order splitting method suitable for a robot in a goods-to-person scene, realizes recombination after splitting a plurality of long orders, and realizes optimization processing of original long orders by considering the superposition degree of sub orders (namely the similarity of goods among the sub orders), the boxing volume (namely the volume of the sub orders), the stock distribution and the task balance.
For ease of understanding, a specific example is set forth below and described in connection with that specific example.
Assuming now 4 original orders (as in fig. 2), each of which needs to be processed for a long time (2 orders processed by a single site 2 h), these orders are submitted to 2 persons for processing. According to the conventional goods-to-person mode, each person is responsible for one picking station, and it is assumed that each station can process 2 orders simultaneously, and 2 persons need 2h to complete the batch of long orders, namely, orders O1-O4 all need 2h to complete.
Because each order has execution time limitation, for example, 2 orders (O1, O2) need to be processed and completed in 1h, after the orders are split and recombined, 2 persons need to process O1 and O2 in 1h first, so that the orders can be sent out on time.
In order to ensure that O1 and O2 can be processed in time with priority, a higher priority (such as a highest priority supported by a system) may be set for O1 and O2, and further, a priority of a wave obtained by performing order splitting and wave combining on O1 and O2 may be highest, and when performing wave allocation and picking, a child order in O1 and O2 may be processed with priority.
The original order is split, various splitting results exist, and if the splitting is not controlled, the number of robot carrying times is increased in the actual operation process after the splitting. The splitting method provided by the embodiment of the application can optimize the splitting process, so that the total carrying times are minimum after the split sub-orders are recombined. For example, in fig. 2, the common split is compared with the optimized split, and the robot is carried more times.
As shown in fig. 2, in the case of no order splitting, the orders O1 and O2 include a, b, d, e, f and g together, 6 different kinds of goods are distributed to the workstation w1 for processing, and the order O1 and O2 need to be carried 6 times; similarly, orders O3 and O4 also need to be handled 6 times.
In the common splitting scheme, the similarity of goods is not considered when the order is split and the waves are combined, the wave times (assumed to be wave time 1) obtained by the waves of the sub-orders o11 and o21 are composed of 3 different goods in total, and the wave times (assumed to be wave time 2) obtained by the waves of the o12 and o22 are composed of 3 different goods in total; the wave times (assumed to be wave time 3) obtained by the o31 wave and the o41 wave groups comprise 3 different cargoes of a, b and c; the wave times obtained by the o32 and o42 wave groups (the wave time is assumed to be 4), the wave times 1 and 3 are distributed to the station w1 for processing, the station w1 needs to carry 3 times when processing the wave time 1, and the station w1 needs to carry 3 times when processing the wave time 3, and the total is 6 times; the processing is allocated to the station 2 in the case of the frequency 2 and the frequency 4, the station 2 needs to carry 3 times when processing the frequency 2, and the station needs to carry 7 times when processing the frequency 4, that is, 13 times in total, the carrying frequency increases.
In the optimization splitting scheme, the similarity of goods is considered when the order splitting and wave combining are carried out, for O1 and O2, a and f are split into the same sub-orders (O11 and O21), the rest is the other sub-orders (O12 and O22), the wave combining is carried out on the O11 and O21 (wave time 1), and the wave combining is carried out on the O12 and O22 (wave time 2); similarly, for O3 and O3, splitting b and c into the same sub-orders (O32 and O42), and the rest is another sub-order (O31 and O41), and performing wave combination to obtain wave number 3 and wave number 4; in order to ensure that O1 and O2 can be completed within 1 hour, respectively distributing the wave times 1 and 2 to sites w1 and w2 for processing, and carrying 6 times for the processes of processing the wave times 1 and 2 by w1 and w 2; the processing of the wave 3 and the wave 4 is allocated to the sites w1 and w2 respectively, and the processing of the wave 3 and the wave 4 for the sites w1 and w2 requires the carrying 6 times, namely 12 times in total.
Compared with the common splitting scheme, the carrying times are reduced from 13 times to 12 times; in addition, in the scheme without splitting, O1 and O2 are processed by a site w1 single line, and the process is completed in 2 hours; in the optimized splitting scheme, sub-order splitting and wave number combination are carried out on O1 and O2, wave numbers corresponding to O1 and O2 are respectively distributed to sites w1 and w2 for double-line processing, and processing can be completed within 1 hour.
As shown in fig. 2, with the order splitting scheme provided in the embodiment of the present application, the total handling times of the orders O1 and O2 can be increased as little as possible (compared with before splitting) when the total handling times are increased as much as possible, that is, when the O1 and O2 are guaranteed to be processed in time, the total handling times are increased as little as possible.
In actual order splitting, the original order is more in single order, the original order pool is larger in standard, the corresponding warehouse area is larger, and the number of work stations is also more. Thus, specific order splitting and post-split sub-order allocation need to be considered and are not limited to the following factors:
1. a sub-order volume limit and/or a sub-order count limit;
2. sub-order inventory distribution;
3. original order task priority.
In this embodiment, the specific flow of order processing may be as shown in fig. 3, including the following steps:
s1, obtaining n original orders through an original order issued by the upstream, wherein the single order is expressed as: oi (i=1, 2,3, …, n).
S2, according to the limit requirement of the volume Vm of the sub-orders and/or the maximum detachable sub-order quantity S of a single order, the detachable order quantity of each original order can be obtained.
S3, carrying out correlation analysis on all the SKUs (one SKU identifies one type of goods) involved in the acquired original order to obtain a correlation index of the SKU.
S4, according to the SKU correlation index, preferentially classifying the SKU with high correlation in the original order into one sub order, splitting each original order according to the principle, wherein the splitting process considers a plurality of limiting conditions (including but not limited to the following conditions):
s5, wave combination (wave order combination) is carried out on the sub orders according to the similarity among the sub orders, and the wave combination is carried out according to the principle that the sub orders with similar order contents are combined into one wave order in priority.
Wherein, the sub-order with high priority (sub-order obtained by splitting the order with high priority) is preferentially grouped into waves.
S6, distributing the sub orders to the workstations for execution according to the wave number.
Illustratively, for different wavenumbers, the allocation order of the wavenumbers is determined according to the order priority within the wavenumbers and/or the order creation time within the wavenumbers.
For any to-be-allocated wave number, the order allocation considers the spatial relation between SKU inventory and workstation distribution in the wave number order, and the order allocation is performed nearby preferentially, namely, the order allocation is performed according to nearby principles according to the distances between each goods and different workstations.
The methods provided herein are described above. The apparatus provided in this application is described below:
referring to fig. 4, a schematic structural diagram of an order processing device provided in an embodiment of the present application, as shown in fig. 4, the order processing device may include:
an acquisition unit 410 for acquiring original order information;
a determining unit 420, configured to perform correlation analysis on items included in each order of the original order, and determine correlation between items;
the splitting unit 430 is configured to split the sub-orders of each order in the original order according to the correlation between the goods, so as to obtain split sub-orders; wherein, in the same order, the higher the correlation between goods, the higher the possibility of being split into the same sub-order;
a combining unit 440 for performing wave number combination on the sub orders according to the similarity of the goods between the sub orders; wherein, the higher the similarity of goods of the sub-order, the higher the possibility of combining into the same wave number;
an allocation unit 450 for allocating orders to workstation execution by wave number.
In some embodiments, the determining unit 420 performs a correlation analysis on items included in each order in the original order, and determines a correlation between items, including:
determining the correlation between the goods according to the correlation parameters of the goods;
wherein the relevancy parameters of the item include one or more of the following:
name, category, frequency of occurrence of different items in the same order.
In some embodiments, the splitting unit 430 performs sub-order splitting on each order in the original order according to the correlation between the items, including:
sub-order splitting is carried out on the original order according to the correlation among goods and the order splitting limiting condition;
the order splitting limiting conditions comprise an upper limit of the volume of the single sub order, and/or an upper limit of the quantity of the single sub order splitting orders.
In some embodiments, the combining unit 440 performs a wave order combination on the sub-orders according to the item similarity between the sub-orders, including:
and carrying out wave number combination on the sub orders according to the similarity of the goods among the sub orders according to the order priority order from high to low.
In some embodiments, the combining unit 440 performs a wave order combination on the sub-orders according to the item similarity between the sub-orders, including:
carrying out wave combination on the sub orders according to the similarity of goods among the sub orders and the quantity of order lines of the sub orders; wherein, the difference value between the order line numbers of different wave passes is smaller than a preset threshold value.
In some embodiments, the allocation unit 450 allocates orders to workstation execution by wave number, including:
for different wave times, determining the allocation sequence of each wave time according to the priority of the order in the wave time and/or the creation time of the order in the wave time;
for any wave number to be distributed, determining the distance from each article to different work stations according to the stock of each article and work station distribution in the wave number, and distributing orders according to the nearby principle according to the distance from each article to different work stations.
An embodiment of the present application provides an electronic device, including a processor and a memory, where the memory stores machine executable instructions capable of being executed by the processor, and the processor is configured to execute the machine executable instructions to implement the order processing method described above.
Fig. 5 is a schematic hardware structure of an electronic device according to an embodiment of the present application. The electronic device may include a processor 501, a memory 502 storing machine-executable instructions. The processor 501 and the memory 502 may communicate via a system bus 503. Also, the processor 501 may perform the order processing method described above by reading and executing machine executable instructions in the memory 502 corresponding to the order processing logic.
The memory 502 referred to herein may be any electronic, magnetic, optical, or other physical storage device that may contain or store information, such as executable instructions, data, or the like. For example, a machine-readable storage medium may be: RAM (Radom Access Memory, random access memory), volatile memory, non-volatile memory, flash memory, a storage drive (e.g., hard drive), a solid state drive, any type of storage disk (e.g., optical disk, dvd, etc.), or a similar storage medium, or a combination thereof.
In some embodiments, a machine-readable storage medium, such as memory 502 in FIG. 5, is also provided, having stored thereon machine-executable instructions that when executed by a processor implement the order-processing method described above. For example, the storage medium may be ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.
It is noted that relational terms such as target and object, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing description of the preferred embodiments of the present invention is not intended to limit the invention to the precise form disclosed, and any modifications, equivalents, improvements and alternatives falling within the spirit and principles of the present invention are intended to be included within the scope of the present invention.

Claims (10)

1. An order processing method, comprising:
acquiring original order information;
carrying out correlation analysis on goods included in each order in the original order, and determining correlation among the goods;
splitting all orders in the original order according to the correlation among the goods to obtain split sub orders; wherein, in the same order, the higher the correlation between goods, the higher the possibility of being split into the same sub-order;
performing wave number combination on the sub orders according to the similarity of goods among the sub orders, and distributing the orders to a workstation for execution according to the wave number; wherein, the higher the goods similarity of the sub-orders, the higher the probability of combining into the same wave number.
2. The method of claim 1, wherein the performing a correlation analysis on items included in each of the original orders to determine a correlation between the items comprises:
determining the correlation between the goods according to the correlation parameters of the goods;
wherein the relevancy parameters of the item include one or more of the following:
name, category, frequency of occurrence of different items in the same order.
3. The method of claim 1, wherein the sub-order splitting of each order in the original order according to the correlation between items comprises:
sub-order splitting is carried out on the original order according to the correlation among goods and the order splitting limiting condition;
the order splitting limiting conditions comprise an upper limit of the volume of the single sub order, and/or an upper limit of the quantity of the single sub order splitting orders.
4. The method of claim 1, wherein the performing a wave order combination on the sub-orders based on the item similarity between the sub-orders comprises:
and carrying out wave number combination on the sub orders according to the similarity of the goods among the sub orders according to the order priority order from high to low.
5. The method of claim 1 or 4, wherein the performing a wave order combination on the sub-orders based on the item similarity between the sub-orders comprises:
carrying out wave combination on the sub orders according to the similarity of goods among the sub orders and the quantity of order lines of the sub orders; wherein, the difference value between the order line numbers of different wave passes is smaller than a preset threshold value.
6. The method of claim 1, wherein assigning orders to workstations for execution on a wave-by-wave basis comprises:
for different wave times, determining the allocation sequence of each wave time according to the priority of the order in the wave time and/or the creation time of the order in the wave time;
for any wave number to be distributed, determining the distance from each article to different work stations according to the stock of each article and work station distribution in the wave number, and distributing orders according to the nearby principle according to the distance from each article to different work stations.
7. An order processing apparatus, comprising:
the acquisition unit is used for acquiring original order information;
the determining unit is used for carrying out correlation analysis on the goods included in each order in the original order and determining the correlation among the goods;
the splitting unit is used for splitting the sub-orders of each order in the original order according to the correlation among the goods to obtain split sub-orders; wherein, in the same order, the higher the correlation between goods, the higher the possibility of being split into the same sub-order;
the combining unit is used for carrying out wave combination on the sub orders according to the similarity of goods among the sub orders; wherein, the higher the similarity of goods of the sub-order, the higher the possibility of combining into the same wave number;
and the allocation unit is used for allocating orders to the workstations for execution according to the wave number.
8. The apparatus according to claim 7, wherein the determining unit performs a correlation analysis on items included in each of the original orders, determines a correlation between the items, comprising:
determining the correlation between the goods according to the correlation parameters of the goods;
wherein the relevancy parameters of the item include one or more of the following:
name, category, frequency of occurrence of different items in the same order;
and/or the splitting unit splits each order in the original order according to the correlation between the goods, including:
sub-order splitting is carried out on the original order according to the correlation among goods and the order splitting limiting condition;
the order splitting limiting conditions comprise an upper limit of the volume of a single sub order and/or an upper limit of the quantity of single sub orders;
and/or the number of the groups of groups,
the combination unit performs wave number combination on the sub orders according to the similarity of goods among the sub orders, and the wave number combination comprises the following steps:
performing wave number combination on the sub orders according to the goods similarity among the sub orders according to the order priority from high to low;
and/or the number of the groups of groups,
the combination unit performs wave number combination on the sub orders according to the similarity of goods among the sub orders, and the wave number combination comprises the following steps:
carrying out wave combination on the sub orders according to the similarity of goods among the sub orders and the quantity of order lines of the sub orders; wherein, the difference value between the order line numbers of different wave passes is smaller than a preset threshold value;
and/or the number of the groups of groups,
the allocation unit allocates orders to the workstations for execution according to the wave number, and the allocation unit comprises:
for different wave times, determining the allocation sequence of each wave time according to the priority of the order in the wave time and/or the creation time of the order in the wave time;
for any wave number to be distributed, determining the distance from each article to different work stations according to the stock of each article and work station distribution in the wave number, and distributing orders according to the nearby principle according to the distance from each article to different work stations.
9. An electronic device comprising a processor and a memory, the memory storing machine executable instructions executable by the processor for executing the machine executable instructions to implement the method of any of claims 1-6.
10. A machine-readable storage medium having stored thereon machine-executable instructions which, when executed by a processor, implement the method of any of claims 1-6.
CN202311406759.5A 2023-10-25 2023-10-25 Order processing method, order processing device, electronic equipment and machine-readable storage medium Pending CN117408780A (en)

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