CN120911877A

CN120911877A - Goods dispatching method, device, equipment and medium based on warehouse processing system

Info

Publication number: CN120911877A
Application number: CN202511070507.9A
Authority: CN
Inventors: 曾国重; 彭德瑶
Original assignee: Duodian Life Wuhan Technology Co ltd
Current assignee: Duodian Life Wuhan Technology Co ltd
Priority date: 2025-07-31
Filing date: 2025-07-31
Publication date: 2025-11-07

Abstract

This disclosure discloses a method, apparatus, equipment, and medium for goods scheduling based on a warehouse processing system. One specific implementation of the method includes: for each picker, performing a first determination step: acquiring picking report data and corresponding performance evaluation configurations; determining picking efficiency information; determining the picking level corresponding to the picking efficiency information; generating an estimated picking quantity sequence; controlling the warehouse processing system to adaptively adjust the picking flow rate of items corresponding to each picking point and the business arrangements corresponding to each picker, thereby obtaining goods scheduling information; displaying the goods scheduling information on the corresponding warehouse visualization operation page of the warehouse processing system; and executing the scheduling content corresponding to the adjusted goods scheduling information on the warehouse visualization operation page. This implementation, by determining the picking efficiency of each picker and the estimated picking quantity corresponding to each picking point, can accurately and efficiently achieve goods scheduling.

Description

Goods dispatching method, device, equipment and medium based on warehouse processing system

Technical Field

The embodiment of the disclosure relates to the technical field of computers, in particular to a cargo scheduling method, a cargo scheduling device, cargo scheduling equipment and cargo scheduling media based on a warehouse processing system.

Background

At present, picking is an indispensable part of the warehouse, logistics, retail and manufacturing industries. With the continued advancement of technology and the continued change in consumer demand, the picking process is also continually optimized and innovated to meet more efficient, accurate, and economical logistics demands. The adjustment of the sorting number of each sorting person can greatly improve the cargo dispatching efficiency based on the warehouse processing system. For the goods dispatching method, the method generally adopts a mode of realizing the adaptive adjustment of each goods picking port or each goods picking person by a manual adjustment mode so as to realize the dispatching of the goods.

However, when the task is updated in the above manner, there are often the following technical problems:

The mode of manually adjusting and carrying out cargo scheduling is inefficient, so that the execution of the cargo picking task is not efficient enough, and more machine resources and human resources are wasted.

The above information disclosed in this background section is only for enhancement of understanding of the background of the inventive concept and, therefore, may contain information that does not form the prior art that is already known to those of ordinary skill in the art in this country.

Disclosure of Invention

The disclosure is in part intended to introduce concepts in a simplified form that are further described below in the detailed description. The disclosure is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

Some embodiments of the present disclosure propose a cargo scheduling method, apparatus, device and medium based on a warehouse processing system to solve one or more of the technical problems mentioned in the background section above.

In a first aspect, some embodiments of the present disclosure provide a cargo scheduling method based on a warehouse processing system, where the method includes performing a first determining step of acquiring, for each picker corresponding to a target picker, pick report data and corresponding assessment configuration of the picker in a target assessment time period, determining pick efficiency information corresponding to the picker according to the pick report information and the assessment configuration, determining a pick level corresponding to the pick efficiency information, generating a predicted pick number sequence corresponding to each pick port in the target picker in a target future time period, controlling the warehouse processing system according to the acquired pick level set and each predicted pick number sequence, adaptively adjusting a cargo flow rate of each pick port and a service arrangement corresponding to each picker to obtain cargo scheduling information, displaying the cargo scheduling information on a visual operation page corresponding to the warehouse processing system, wherein the visual operation page supports a button for displaying the cargo scheduling information, and a drag button for deleting the cargo scheduling information, and a drag button for performing a drag operation on a node, and a drag operation for a drag operation, and a drag operation for adjusting the cargo scheduling node.

In a second aspect, some embodiments of the present disclosure provide a cargo dispatching device based on a warehouse processing system, where the cargo dispatching device includes a first execution unit configured to perform a first determination step of acquiring cargo picking report data and corresponding check configuration of the cargo picker in a target check time period for each cargo picker corresponding to a target cargo picker, determining cargo picking efficiency information corresponding to the cargo picker according to the cargo picking report information and the check configuration, determining a cargo picking level corresponding to the cargo picking efficiency information, a generation unit configured to generate a predicted cargo picking number sequence corresponding to each cargo picking port in the target cargo picker in a target future time period, a control unit configured to control the warehouse processing system to adaptively adjust a cargo picking flow rate and a service arrangement corresponding to each cargo picker according to the obtained cargo picking level sequence, obtain cargo dispatching information, a display unit configured to display the cargo dispatching information on a page of the warehouse processing system, and a display unit configured to display a page of the cargo dispatching information, wherein the display unit is configured to display a page of the cargo dispatching information on a warehouse node, and a second display node is configured to display a page, and a cargo dispatching node is configured to display the cargo dispatching information.

In a third aspect, some embodiments of the present disclosure provide an electronic device comprising one or more processors, and storage means having one or more programs stored thereon, which when executed by the one or more processors, cause the one or more processors to implement the method described in any of the implementations of the first aspect.

In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.

The goods scheduling method based on the warehouse processing system has the advantages that goods scheduling can be accurately and efficiently achieved through the goods scheduling method based on the warehouse processing system, and through the fact that the goods selecting efficiency corresponding to the goods selecting person determines the estimated goods selecting number corresponding to each goods selecting port. Specifically, the inefficiency of the cargo scheduling is caused by the inefficiency of the manual adjustment of the cargo scheduling mode, resulting in inefficient execution of the picking task and waste of more machine resources and human resources. Based on the above, the goods scheduling method based on the warehouse processing system according to some embodiments of the present disclosure firstly, for each picker corresponding to a target picking station, a first determining step is performed, where the first step obtains picking report data and corresponding checking configuration of the picker in a target checking period, so as to obtain checking configuration of the picker in checking the picking data and the picking level in the picking process. And secondly, accurately determining the picking efficiency information corresponding to the pickers according to the picking report information and the checking configuration. Here, by determining the pick efficiency information, the pick speed and pick quality corresponding to the pickers may be efficiently determined, facilitating subsequent determinations of pick levels. And thirdly, accurately determining the picking level corresponding to the picking efficiency information so as to determine the picking proficiency corresponding to the picker. Then, a predicted picking number sequence corresponding to each picking port in the target picking station in the target future time period is generated so as to facilitate the subsequent adaptive adjustment of the article picking flow rate corresponding to each picking port. Furthermore, according to the obtained goods picking level set and each estimated goods picking number sequence, the storage processing system is controlled, so that the goods picking flow rate corresponding to each goods picking port and the business arrangement corresponding to each goods picking person can be accurately and efficiently adjusted, and the goods scheduling information is obtained. And displaying the goods scheduling information on a storage visual operation page corresponding to the storage processing system, wherein the storage visual operation page supports drag adjustment, key deletion and key addition on a goods picking person node, a goods picking port node and a goods transportation route, so that drag adjustment on relevant contents in the aspect of goods scheduling is facilitated in a visual mode. And finally, executing the scheduling content corresponding to the adjusted goods scheduling information on the visual operation page of the warehouse so as to realize the efficient execution of picking goods. In summary, by determining the order picking level corresponding to the order picker and the estimated order picking number sequence corresponding to each order picking port, accurate generation of the goods scheduling information can be achieved based on the data. On the basis, through carrying out various page operations on the visual operation page of the warehouse, more accurate adjustment of cargo scheduling information can be realized, and then high-efficiency execution under the cargo picking task is realized.

Drawings

The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. The same or similar reference numbers will be used throughout the drawings to refer to the same or like elements. It should be understood that the figures are schematic and that elements and components are not necessarily drawn to scale.

FIG. 1 is a flow chart of some embodiments of a warehouse processing system based cargo scheduling method according to the present disclosure;

FIG. 2 is a schematic diagram of some embodiments of a warehouse processing system based cargo scheduling device according to the present disclosure;

Fig. 3 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.

It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings. Embodiments of the present disclosure and features of embodiments may be combined with each other without conflict.

It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units.

It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.

The names of messages or information interacted between the various devices in the embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

Referring to fig. 1, a flow 100 of some embodiments of a warehouse processing system based cargo scheduling method according to the present disclosure is shown. The goods scheduling method based on the warehouse processing system comprises the following steps:

step 101, for each picker corresponding to the target picking station, performing the following first determining step:

step 1011, acquiring the pick report data and the corresponding assessment configuration of the pick personnel in the target assessment time period.

In some embodiments, an execution subject (e.g., a computing device) of the method for dispatching goods based on the warehouse processing system may obtain pick report data and corresponding assessment configuration of the pick person during a target assessment period. The target picking station may be a picking station to be subjected to goods scheduling, picking person scheduling and picking port scheduling. The picker may be a person performing a picking job at the target pick station. The target assessment time period may be a time period during which the pickers assess the corresponding pick efficiencies. In practice, pick efficiency may be demonstrated by pick level. The higher the corresponding pick level, the more efficient the characterization of the corresponding pickers for picking. For example, the pick level may be one of a first level, a second level, and a third level. The first level corresponds to a higher pick efficiency than the second level corresponds to a pick efficiency. The second level corresponds to a higher pick efficiency than the third level corresponds to a pick efficiency. The pick report data may be a data report of the pickers picking during the target review period. The order picking report data can be used for providing various data indexes for order picking by the order picking personnel in the target examination time period. For example, the pick report data may include, but is not limited to, at least one of a total pick number, a pick rate, pick port information, a pick route. The assessment configuration may be a configuration item of how the pickers are assessed for the corresponding pick efficiency. In practice, the assessment configuration may be a configuration item preset for the target assessment period. For example, the qualification configuration may include, but is not limited to, at least one of a configuration for efficiency qualification based on the pick number and the pick duration, and a configuration for efficiency qualification based on the pick number, the pick duration, and the pick quality. The warehouse processing system may be a system that supports various processing operations on warehouses. In practice, the warehouse processing system corresponds to a warehouse processing platform. The various processing operations may include, but are not limited to, at least one of pick port item flow rate processing, personnel scheduling, shelf processing, machine deployment processing, route adjustment. The warehousing processing system can further comprise a goods picking person behavior function module, a person grade assessment module, a behavior excitation module and a goods picking assessment report generation module. The picker behavior function may be a function responsible for providing technical support for the pick job of the picker's performance. In practice, the pickers behavioral functional module may perform order rationalization allocation, pickers task generation, pickers task packaging entry. The personnel rating module may be a functional module that performs rating of the pickers. The behavioral incentive module may be a functional module that determines incentive information for the pickers. The pick assessment report generation module may be a functional module that generates a pick assessment report.

In some alternative implementations of some embodiments, prior to step 101, the method further comprises:

First, orders are picked in accordance with a zoned order picking or order picking order mode to generate order picking orders. The order picking can be regional picking according to an order storage region corresponding to the order. Picking by order may be picking by individual items in the order. The pick task may be a task of picking items corresponding to an order.

And secondly, distributing the picking task to a picker according to a target distribution algorithm. The target assignment algorithm may be an algorithm that assigns a pick task to a corresponding appropriate pick person. For example, the target allocation algorithm may be a quantitative allocation algorithm or an allocation algorithm based on the area in which the picker is located.

And thirdly, instructing the picker to enter the distributed picking task information in a packing way at the handheld terminal. The order picking task information may be task information corresponding to an order picking task. For example, the pick job information may include pick items, pick times, pick sites.

Step 1012, determining the picking efficiency information corresponding to the picker according to the picking report information and the checking configuration.

In some embodiments, the executing entity may determine pick efficiency information corresponding to the picker according to the pick report information and the assessment configuration. Wherein the pick efficiency information may characterize the efficiency of the pickers in picking. In practice, the pick efficiency information may be in the form of scores. The higher the corresponding score, the higher the corresponding pick efficiency.

As an example, the execution subject may extract basic data required in the assessment configuration from the pick report information. And substituting the basic data into an assessment rule corresponding to the assessment configuration to obtain the order picking efficiency information.

In some optional implementations of some embodiments, the above-described assessment configuration information may be generated by:

First, the executing body may obtain initial assessment configuration information of the target pick site configuration. Wherein the target picking station may be a distribution center where the target picker works. The initial assessment configuration information may be an unverified rule for assessing the target pickers. The verification may be checking and verifying the data or information.

And secondly, the execution main body can check whether the configuration information of the order picking index rule in the initial checking configuration information meets a preset first configuration requirement. Wherein, the first configuration requirement may be to set different value intervals for consecutive scores (for example, the value interval set for 1 score may be 0-50, and the value interval set for 2 scores may be 51-99). The order picking index rule configuration information may be order picking index rules configured by the target order picking station. The pick indicator rule may be a scoring rule for at least one pick indicator. The scoring rules may be rules that assess the pick indicator score. The pick indicator score may be a score of a pick indicator corresponding to the target picker. For example, the pick indicators may include total inventory, after-market labor, quick take-off duty, and daily number of items. The total order amount may be a sum of the number of pick complete orders by the target pickers during the target task qualification period. The pick complete order may be an order in which the target picker completes the package. The packaging may be performed by packaging the commodity according to a predetermined requirement (for example, sealing with an adhesive tape). The after-sales work order number may be the number of after-sales work orders. The after-sales work order may be the pick complete order for a refund due to the target picker during the target task qualification period. The quick discharging ratio may be a ratio of the quick discharging amount of orders to the total amount of orders. The quick-shipment order quantity may be the quantity of quick-shipment orders. The quick pick order may be the pick complete order with a pick duration less than a preset duration (e.g., the preset duration may be 12 minutes). The shipment duration may be a duration during which the target picker completes the pick complete order. The daily average item number may be a ratio of the total number of items to natural days in the target task assessment period. The total number of items may be. The total number of items may be the sum of the number of items. The item number may be the number of commodity types. In practice, the commodity type may be a category number corresponding to the order (for example, a category number 10082303 corresponding to mineral water). The pick completion order may be generated by:

In response to the target picker confirming receipt of the order, the executing body may record a pick start time of the target picker, substep 1. Wherein the order may be an electronic file that records the target customer's consumption (e.g., the electronic file may include the commodity name and the commodity quantity). The customer may be a person purchasing the merchandise. The commodity may be a product in the order (e.g. the product may be mineral water, peanut oil, laundry detergent). The pick start time may be a time at which the target picker starts a pick job.

In response to acquiring the pick start time and the target picker confirming that the item is not out of stock, the executing body may record a pick complete time. Wherein the absence may indicate that the target picker cannot acquire the item in the order. The picking completion time may be a time when the target picker ends the picking operation.

In response to acquiring the pick completion time and the target picker confirming that the packing of the goods is completed, the executing body may record the packing completion time to generate the pick completion order. The packing completion time may be a time when the target picker completes a packing job.

The above-described fast off-bin duty cycle may be generated by:

In sub-step 1, the picking system may obtain the picking start time and the packing completion time of the order to obtain the out-of-warehouse time. The picking system may be a system for collecting picking job data of a target picker. For example, the picking job data may be the picking start time, the picking completion time, and the packing completion time. The shipment time may be the packing completion time subtracted from the pick start time.

And 2, responding that the ex-warehouse time is smaller than the preset time, and determining the order as a quick ex-warehouse order by the execution body. The preset time period may be 12 minutes.

And 3, dividing the rapid delivery order quantity in the target task assessment time period by the total single quantity by the execution main body to obtain the rapid delivery duty ratio.

The daily average item number can be generated by the following steps:

In the substep 1, the executing body may acquire an order set of the target picker in the target task assessment period. The order set may be a set of order completed for the target pickers in the target task assessment time period.

And 2, determining the number of items corresponding to the orders by the execution main body according to the commodity types of each order in the order set so as to obtain the total number of items.

And 3, dividing the total number of items by the natural days in the task examination time by the execution main body to obtain the daily average item number.

And thirdly, responding to the order picking index rule configuration information to meet the first configuration requirement, wherein the execution body can check whether the order picking efficiency information rule configuration information in the initial checking configuration information meets a preset second configuration requirement. Wherein the second configuration requirement may be to set different score segments for the pick efficiency information (e.g., a score segment for a one-star pickers may be 0-99, and a score segment for a two-star pickers may be 99-149). The pick efficiency information may be a one-star pick, a two-star pick, a three-star pick, a four-star pick, and a five-star pick. The order picking efficiency information rule configuration information may be order picking efficiency information rules configured by the target order picking station. The order picking efficiency information rule may be a rule for generating the order picking efficiency information corresponding to the target order picker.

And step four, responding to the order picking efficiency information rule configuration information to meet the second configuration requirement, and the execution body can check whether the rewarding rule configuration information in the initial checking configuration information meets a preset third configuration requirement. Wherein, the third configuration requirement may be to allocate different rewards to the target pickers according to the number of attendance days and the total number of items of the target pickers (for example, the two-star pickers may be 100 yuan for attendance 5 days, and the two-star pickers may be 80 yuan for item total number of items of the two-star pickers greater than 1000). The attendance days may be natural days of the target picker's job during the target task assessment period. The reward rule configuration information may be a reward rule configured by the target picking site, and the reward rule may be target reward information corresponding to the target picker generated according to the picking efficiency information.

And fifthly, responding to the reward rule configuration information to meet the third configuration requirement, and the execution body can store the initial assessment configuration information to the target storage end to obtain assessment configuration information.

In some optional implementations of some embodiments, the pick report data is stored periodically in a warehouse database corresponding to the warehouse processing system. And the order picking report data is generated by the following steps:

First, in response to determining that the pick data acquisition time is reached, acquiring an order set of the pick person within the target assessment time period.

Second, for each order in the order set, the following second determination is performed:

And 1, acquiring the time length from the picking start time to the packing completion time of the order to obtain the delivery time length.

And 2, in response to determining that the ex-warehouse duration is less than the preset duration, determining the order as a quick ex-warehouse order.

And 3, determining the number of items corresponding to the order according to the types of the items in the order.

And thirdly, acquiring the after-sales work orders of the pickers in the target assessment time period.

And step four, generating total quantity of orders, quick delivery duty ratio, after-sales work orders and daily number of items corresponding to the order set according to the order set, the quick delivery order set and the number of items.

And fifthly, summarizing the total quantity of orders, the rapid delivery duty ratio, the daily average item number and the after-sales work number to generate the goods picking report data.

In some optional implementations of some embodiments, the executing entity may determine pick efficiency information corresponding to the picker according to the pick report information and the assessment configuration, including the following steps:

And a first step of determining at least one sort index score corresponding to the sort index set according to the sort report data and the assessment configuration. The goods picking index set comprises total quantity of orders, rapid delivery duty ratio, after-sales work orders and daily average item numbers. Wherein, the order picking index in the order picking index set has a one-to-one correspondence with the order picking index score in the at least one order picking index score. The pickface score may characterize the performance of pickers under pickface. That is, the higher the pick indicator score, the better the performance of the corresponding pickers under the pick indicator is characterized.

And secondly, carrying out weighted summation on at least one sort index score corresponding to the sort index set so as to generate the sort efficiency score.

And thirdly, generating the order picking efficiency information according to the order picking efficiency score.

As an example, the executing entity may directly determine the pick efficiency score as pick efficiency information.

In some optional implementations of some embodiments, the determining, according to the assessment configuration information and the picking efficiency information, the picking efficiency information corresponding to the target picker includes:

In response to determining that the pick efficiency information is within a first fractional interval, the executing entity may configure the pick level corresponding to the target pick person as a first level. The first score interval may be a numerical interval (for example, the numerical interval is 0-99). The first level may indicate that the pick efficiency information corresponding to the target picker is one level.

In response to determining that the pick efficiency information is in a second score interval, the executing body may configure the pick level corresponding to the target pick person to a second level. The second score interval may be a numerical interval (for example, the numerical interval is 99-149). The second level may indicate that the pick efficiency information corresponding to the target picker is second level.

Third, in response to determining that the pick efficiency information is in a third fractional interval, the executing entity may configure the pick level corresponding to the target picker to be a third level. The third fractional interval may be a numerical interval (e.g., a numerical interval of 150-399). The third level may indicate that the pick efficiency information corresponding to the target picker is three levels.

Fourth, in response to determining that the pick efficiency information is in a fourth fractional interval, the executing entity may configure the pick level corresponding to the target picker to be a fourth level. The fourth fractional interval may be a numerical interval (e.g., 400-549). The fourth level may indicate that the pick efficiency information corresponding to the target picker is four levels.

Fifth, in response to determining that the pick efficiency information is in a fifth score interval, the execution body may configure the pick level corresponding to the target picker as a fifth level. The fifth score interval may be a numerical interval (for example, the numerical interval is greater than 549). The fifth level may indicate that the pick efficiency information corresponding to the target picker is five levels. Wherein the first fractional section, the second fractional section, the third fractional section, the fourth fractional section, and the fifth fractional section are each consecutive fractional sections in sequence.

Optionally, after determining the pick efficiency information corresponding to the picker according to the pick report information and the assessment configuration, the method further includes:

First, generating attendance rewards and punishment information according to the order picking processing level, the attendance days of the target order picker in the target task assessment time period and the assessment configuration information. Wherein, the attendance reward and punishment information can be the value of the rewards of the staff attendance. For example, the attendance reward and punishment information may be attendance payouts.

As an example, first, the executing body may screen out reward and punish rules from the assessment configuration information according to the order of the picking process. And screening out the attendance reward and punishment information on the attendance days from the reward and punishment rules.

And secondly, generating item rewarding and punishing information according to the order picking processing level, the total number of items of the target order picker in the target task assessment time period and the assessment configuration information. The item rewarding and punishing information can be a value of rewarding and punishing the number of items of the items which are picked by staff. The greater the number of items processed, the higher the corresponding line rewards and punishments.

As an example, first, the execution subject may screen out the item rewards and punishments rule from the assessment configuration information according to the order of the picking process. And screening out the attendance reward and punishment information under the total number of the paid items from the reward and punishment rules.

Thirdly, generating target reward and punishment information according to the reward and punishment information and the item reward and punishment information.

As an example, the executing body may add the attendance reward and punishment information and the item reward and punishment information, and may obtain target reward and punishment information.

And step four, the target reward and punish information is sent to a corresponding use terminal of the picker through a target communication encryption mode, so that the picker can determine the target reward and punish information on a goods scheduling page based on a warehouse processing system in the use terminal.

In step 1013, a pick level corresponding to the pick efficiency information is determined.

In some embodiments, the executing entity may determine a pick level corresponding to the pick efficiency information. Wherein the pick level may characterize the efficiency of the pickers in picking. For example, the pick level may be one of a first level, a second level, a third level, a fourth level, and a fifth level. The first level corresponds to a higher pick efficiency than the second level corresponds to a pick efficiency. The second level corresponds to a higher pick efficiency than the third level corresponds to a pick efficiency. The third level corresponds to a higher pick efficiency than the fourth level corresponds to a pick efficiency. The fourth level corresponds to a higher pick efficiency than the fifth level corresponds to a pick efficiency.

Step 102, generating a predicted picking number sequence corresponding to each picking port in the target picking station in the target future time period.

In some embodiments, the executing entity may generate a sequence of estimated pick numbers corresponding to respective pick ports in the target pick station over a target future time period. Wherein the target future time period may be a future time period for which the pick number to be performed is estimated. For example, the target future time period may be within one week after the current time. The pick port may be a pick port. In practice, there may be a corresponding type of pick item per pick port. That is, the pick port will only output the corresponding type of pick item. There is a one-to-one correspondence of the estimated pick number in the sequence of estimated pick numbers to the future time in the sequence of target future times. The estimated pick number may be the number of items that the pick port is to pick at some future time. Each pick port has a corresponding sequence of estimated pick numbers.

In some optional implementations of some embodiments, the executing entity may generate a sequence of estimated pick numbers corresponding to respective pick ports in the target pick station over a target future time period, including the steps of:

The first step, for each of the above-mentioned individual pickopenings, performs the following generating steps:

And 1, acquiring the type of the goods picking object corresponding to the goods picking port. The sort item type may be an item category corresponding to the sort item.

And 2, acquiring a first historical picking number sequence corresponding to the picking item type from a target database. Wherein the target database may store historical pick conditions for pick item types under each type. The first historical pick number sequence may be a sequence of numbers at each historical point in time that pick items of the pick item type corresponding item were picked.

And 3, acquiring a second historical picking number sequence corresponding to the picking port. Wherein the second historical pick number sequence may be a pick number case for the pick port at the historical time period. The second sequence of historical pick numbers may be the pick numbers of the pick ports at each historical time.

And a sub-step 4 of correcting each target historical picking number in the second historical picking number sequence according to the first historical picking number sequence to obtain a corrected historical picking number sequence. Wherein each historical pick number in the corrected sequence of historical pick numbers does not have an outlier (i.e., the corresponding historical pick number corresponds to a very high value for the number of nearby picks).

As an example, the executing entity may adjust the outlier in the second historical pick number sequence to the corresponding first historical pick number in the first historical pick number sequence at the same time to reduce the impact of the pick number of items not under the pick gate.

And a substep 5 of generating a future pick number sequence of the target pick station under the pick item type in the target future time period according to the first historical pick number sequence. Wherein the sequence of future pick numbers may be a sequence of numbers of picks likely to be performed at various future times within the future time period.

As an example, the executing entity may generate a future pick number sequence for the target pick station under the pick item type for the target future time period using a time-sequential neural network model (e.g., LSTM model) based on the first historical pick number sequence.

And step 6, acquiring a picking duty ratio sequence of the picking port in a target historical time period which has a contemporaneous relation with the target future time period.

And 7, correspondingly multiplying the picking ratio in the picking ratio sequence and the future picking number in the future picking number sequence to obtain an estimated picking number sequence corresponding to the picking port. The estimated pick number may be an estimated pick number at a future time. The estimated pick number in the estimated pick number sequence has a temporal correspondence with the future pick number in the future pick number sequence.

And 103, controlling a warehouse processing system according to the obtained order picking level set and each estimated order picking number sequence, and carrying out adaptive adjustment on the order picking flow rate of the articles corresponding to each order picking port and the business arrangement corresponding to each order picking person to obtain the order dispatching information.

In some embodiments, the executing body may control the warehouse processing system according to the obtained pick level set and each estimated pick number sequence, and adaptively adjust the pick flow rate of the articles corresponding to each pick port and the business arrangement corresponding to each pick person, so as to obtain the cargo scheduling information. The item pick flow rate may be a flow rate at which the pick port corresponds to transporting the item. The item pick flow rate may also characterize the rate at which the pickers pick items at the pick port. The corresponding business arrangement of the pickers may be to arrange new pickers for the pickers. The goods schedule information may include personnel schedule corresponding to the pickers and adjustment information of the article pick flow rate.

In some optional implementations of some embodiments, the executing body may control the warehouse processing system according to the obtained pick level set and each estimated pick number sequence, and adaptively adjust a pick flow rate of the article corresponding to each pick port and a business arrangement corresponding to each pick person to obtain the cargo scheduling information, where the method includes the following steps:

and firstly, dividing the target future time period by a preset granularity time length to obtain a future sub-time period sequence. The predetermined granularity time division may be a preset time granularity division.

Second, for each future sub-time period in the sequence of future sub-time periods, performing the generating step of:

And a substep 1, for each estimated picking number sequence in the estimated picking number sequences, querying an estimated picking number subsequence corresponding to the future sub-time period from the estimated picking number sequences.

And 2, acquiring the maximum pickers condition of the pickers, the synchronous pickers finishing condition of the pickers and the pickers level in proportion to the pickers. The pick port maximum pickers condition may be a person number limit condition where the pick port performs the maximum pick process. The order picking port synchronous order picking completion condition may be a condition that each order picking port synchronously completes the order picking process. The condition that the pick level is proportional to the pick number may be a condition that the pick level is proportional to the pick number.

And 3, generating an adjustment prompt word for adaptively adjusting the article picking flow rate corresponding to each picking port and the business arrangement corresponding to each picking person according to the picking level set, the estimated picking number sequence, the maximum picking person condition of the picking port, the synchronous picking completion condition of the picking port and the condition that the picking level is in direct proportion to the picking number.

And step 4, generating cargo scheduling information by using a large language model for cargo scheduling, which is correspondingly deployed by the warehouse processing system, according to the adjustment prompt words.

And 104, displaying the goods scheduling information on a visual operation page of the warehouse corresponding to the warehouse processing system.

In some embodiments, the execution body may display the cargo scheduling information on a storage visualization operation page corresponding to the storage processing system. The warehouse visualization operation page may be a page that performs a visualization operation on support related to cargo scheduling in a warehouse. The visual operation page supports drag adjustment, key deletion and key addition on the picker node, the picker node and the article transportation route.

And 105, executing the scheduling content corresponding to the adjusted cargo scheduling information on the warehouse visual operation page.

In some embodiments, the executing body may execute the scheduling content corresponding to the adjusted cargo scheduling information on the warehouse visualization operation page.

In some alternative implementations of some embodiments, the method further comprises:

And a first step of generating an aging class label, a quality class label and the comprehensive class label according to the order picking report data, the order picking efficiency score, the order picking processing level and the target rewarding information. The time-effect type label can represent the label of the time-effect completion condition of the target pickers in the picking process. For example, the aging type label may be one of a 1-grade aging label, a 2-grade aging label, and a 3-grade aging label. The quality class label may be a label of the task completion quality of the target pickers in the picking process. For example, the quality class tag may be one of a class 1 quality tag, a class 2 quality tag, a class 3 quality tag. The integrated class label may be a label of the integrated completion under various aspects of the picking process by the target picker.

As an example, the executing entity may use a predetermined aging class label association table, a quality class label, and a comprehensive class label, and may determine the aging class label, the quality class label, and the comprehensive class label according to the pick report data, the pick efficiency score, the pick process level, and the target rewards information.

And secondly, sending the time-effect type label, the quality type label and the comprehensive type label to a handheld terminal corresponding to the target pickers so as to display the pickapplication pages corresponding to the handheld terminal.

With further reference to fig. 2, as an implementation of the method shown in the foregoing figures, the present disclosure provides some embodiments of a cargo scheduling apparatus based on a warehouse processing system, where the embodiments of the apparatus correspond to those of the method shown in fig. 1, and the cargo scheduling method based on a warehouse processing system may be specifically applied to various electronic devices.

As shown in fig. 2, a cargo scheduling device 200 based on a warehouse processing system includes a first execution unit 201, a generation unit 202, a control unit 203, a display unit 204, and a second execution unit 205. The first execution unit 201 is configured to execute a first determination step of acquiring, for each pick-up person corresponding to a target pick-up station, pick-up report data and corresponding check configuration of the pick-up person in a target check time period, determining pick-up efficiency information corresponding to the pick-up person according to the pick-up report information and the check configuration, determining a pick-up level corresponding to the pick-up efficiency information, generating a predicted pick-up number sequence corresponding to each pick-up port in the target pick-up station in a target future time period, controlling a warehouse processing system to adaptively adjust a pick-up flow rate of an item corresponding to each pick-up port and a service arrangement corresponding to each pick-up person according to the obtained pick-up report information and the check configuration, displaying the pick-up efficiency information corresponding to the warehouse processing system, generating a predicted pick-up number sequence corresponding to each pick-up port in the target pick-up station in the target future time period, controlling the warehouse processing system 203 to adaptively adjust a pick-up flow rate of the item corresponding to each pick-up port and a service arrangement corresponding to each pick-up person to obtain a warehouse scheduling information, displaying unit 204 is configured to display the goods scheduling information on a warehouse visualized operation page corresponding to the warehouse operation, wherein the warehouse visualized page 205 is configured to delete a button on a warehouse supporting page, a node and a map node and a route for the user is configured to adjust the item.

It will be appreciated that the elements described in this warehouse-based handling system cargo scheduler 200 correspond to the various steps in the method described with reference to fig. 1. Thus, the operations, features and advantages described above with respect to the method are equally applicable to a warehouse-based cargo scheduling device 200 and the units contained therein, and are not described herein.

Referring now to fig. 3, a schematic diagram of an electronic device (e.g., electronic device) 300 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device shown in fig. 3 is merely an example and should not impose any limitations on the functionality and scope of use of embodiments of the present disclosure.

As shown in fig. 3, the electronic device 300 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 301 that may perform various suitable actions and processes in accordance with a program stored in a Read Only Memory (ROM) 302 or a program loaded from a storage means 308 into a Random Access Memory (RAM) 303. In the RAM303, various programs and data required for the operation of the electronic apparatus 300 are also stored. The processing device 301, the ROM 302, and the RAM303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.

In general, devices may be connected to I/O interface 305 including input devices 306 such as a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc., output devices 307 including a Liquid Crystal Display (LCD), speaker, vibrator, etc., storage devices 308 including, for example, magnetic tape, hard disk, etc., and communication devices 309. The communication means 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. While fig. 3 shows an electronic device 300 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead. Each block shown in fig. 3 may represent one device or a plurality of devices as needed.

In particular, according to some embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, some 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 shown in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via communications device 309, or from storage device 308, or from ROM 302. The above-described functions defined in the methods of some embodiments of the present disclosure are performed when the computer program is executed by the processing means 301.

It should be noted that, in some embodiments of the present disclosure, the computer readable medium may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of a 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 some embodiments of the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, the computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. 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 electrical wiring, fiber optic cable, RF (radio frequency), and the like, or any suitable combination of the foregoing.

In some embodiments, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.

The computer readable medium may be included in the electronic device or may exist alone without being incorporated into the electronic device. The computer readable medium carries one or more programs, when the one or more programs are executed by the electronic equipment, the electronic equipment is caused to execute the first determining step of acquiring goods picking report data and corresponding checking configuration of the goods picker in a target checking time period, determining goods picking efficiency information corresponding to the goods picker according to the goods picking report information and the checking configuration, determining goods picking level corresponding to the goods picking efficiency information, generating estimated goods picking number sequences corresponding to all goods picking ports in the target goods picking station in a target future time period, controlling a storage processing system to adaptively adjust goods picking flow rates corresponding to all goods picking ports and service arrangements corresponding to all goods picking personnel according to the obtained goods picking level sets and all estimated goods picking number sequences, obtaining goods dispatching information, displaying the goods dispatching information on storage visual operation pages corresponding to the storage processing system, wherein the storage visual operation pages support the storage visual operation pages, the storage nodes perform button adjustment on the storage visual operation pages, and the storage nodes, and delete the goods dispatching nodes, and perform adjustment on the storage nodes.

Computer program code for carrying out operations for some embodiments of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

The flowcharts 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 disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/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 units described in some embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. The described units may also be provided in a processor, which may be described as a processor comprising a first execution unit, a generation unit, a control unit, a presentation unit and a second execution unit, for example. Wherein the names of the units do not constitute a limitation of the unit itself in some cases, for example, the generation unit may also be described as "generating a sequence of estimated pick numbers corresponding to individual pick ports in the above-described target pick station over a target future time period".

The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic that may be used include Field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems-on-a-chip (SOCs), complex Programmable Logic Devices (CPLDs), and the like.

The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above technical features, but encompasses other technical features formed by any combination of the above technical features or their equivalents without departing from the spirit of the invention. Such as the above-described features, are mutually substituted with (but not limited to) the features having similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A cargo scheduling method based on a warehouse processing system comprises the following steps:

for each picker corresponding to the target pickers, the following first determining step is performed:

acquiring the order picking report data and the corresponding checking configuration of the order picker in the target checking time period;

According to the order picking report information and the assessment configuration, order picking efficiency information corresponding to the order picker is determined;

Determining a picking level corresponding to the picking efficiency information;

Generating a sequence of estimated pick numbers corresponding to each pick port in the target pick station over a target future time period;

Controlling a storage processing system according to the obtained goods picking level set and each estimated goods picking number sequence, and carrying out adaptive adjustment on the goods picking flow rate corresponding to each goods picking port and the business arrangement corresponding to each goods picking person to obtain goods scheduling information;

Displaying the goods scheduling information on a storage visual operation page corresponding to the storage processing system, wherein the storage visual operation page supports drag adjustment, key deletion and key addition of a goods picking person node, a goods picking port node and a goods transportation route;

and executing the scheduling content corresponding to the goods scheduling information after adjustment on the warehouse visual operation page.

2. The method of claim 1, wherein the determining pick efficiency information corresponding to the picker based on the pick report information and the qualification configuration comprises:

Determining at least one picking index score corresponding to a picking index set according to the picking report data and the checking configuration, wherein the picking index set comprises total single quantity, quick delivery duty ratio, after-sales work number and daily average item number;

weighting and summing at least one picking index score corresponding to the picking index set to generate a picking efficiency score;

and generating the order picking efficiency information according to the order picking efficiency score.

3. The method of claim 2, wherein after the determining of the pick efficiency information corresponding to the pick person from the pick report information and the qualification configuration, the method further comprises:

Generating attendance reward and punishment information according to the order picking processing level, the attendance days of the target order picker in the target task assessment time period and the assessment configuration information;

generating item rewards and punishments information according to the order picking processing level, the total number of items of the target order picker in the target task assessment time period and the assessment configuration information;

generating target reward and punishment information according to the reward and punishment information and the item reward and punishment information;

And sending the target reward and punish information to a corresponding use terminal of the picker in a target communication encryption mode so as to ensure that the picker can determine the target reward and punish information on a cargo scheduling page based on a warehouse processing system in the use terminal.

4. The method of claim 1, wherein the pick report data is periodically stored in a warehouse database corresponding to the warehouse processing system, and wherein the pick report data is generated by:

in response to determining that the pick data acquisition time is reached, acquiring an order set of the pick person within the target assessment time period;

for each order in the set of orders, performing the following second determining step:

acquiring the time length from the picking start time to the packing completion time of the order to obtain the delivery time length;

Responsive to determining that the out-of-bin duration is less than a preset duration, determining the order as a quick out-of-bin order;

The number of items corresponding to the order is determined according to the types of the items in the order, and the after-sales work orders of the pickers in the target examination time period are obtained;

Generating total quantity of orders, quick delivery duty ratio, after-sales work number and daily average item number corresponding to the order set according to the order set, the quick delivery order set and the item number set;

And summarizing the total quantity of orders, the rapid delivery duty ratio, the daily average item number and the after-sales work orders to generate the order picking report data.

5. The method of claim 1, wherein the determining a pick level for which the pick efficiency information corresponds comprises:

in response to determining that the pick efficiency information is in a first fractional interval, configuring a pick level corresponding to the pick person as a first level;

in response to determining that the pick-up processing level is in a second score interval, configuring a pick level corresponding to the pick person as a second level;

in response to determining that the pick efficiency information is in a third fractional interval, configuring a pick level corresponding to the pick person to a third level;

In response to determining that the pick efficiency information is in a fourth fractional interval, configuring a pick level corresponding to the pick person to be a fourth level;

In response to determining that the pick efficiency information is in a fifth fractional interval, configuring a pick level corresponding to the pick person as a fifth level, wherein the first, second, third, fourth, and fifth fractional intervals are respective fractional intervals that are consecutive in sequence.

6. The method of claim 1, wherein prior to said performing the following first determining step for each picker corresponding to a target pick station, the method further comprises:

Generating order picking tasks according to the order picking task modes of sorting according to the partitions or sorting according to the orders;

distributing the order picking task to an order picker according to a target distribution algorithm;

the order picker is instructed to package and enter the assigned order picking task information at the handheld terminal.

7. A method according to claim 3, wherein the method further comprises:

Generating an aging class label, a quality class label and the comprehensive class label according to the order picking report data, the order picking efficiency score, the order picking processing level and the target reward and punishment information;

and sending the time-effect type label, the quality type label and the comprehensive type label to a handheld terminal corresponding to a picking person so as to display a picking application page corresponding to the handheld terminal.

8. A warehouse processing system based cargo scheduling device, comprising:

the first execution unit is configured to execute the following first determination steps of acquiring the order picking report data and the corresponding checking configuration of the order picker in a target checking time period for each order picker corresponding to a target order picking station;

a generation unit configured to generate a sequence of estimated pick numbers corresponding to individual pick ports in the target pick station over a target future time period;

The control unit is configured to control the storage processing system according to the obtained goods picking level set and each estimated goods picking number sequence, and adaptively adjust the goods picking flow rate corresponding to each goods picking port and the business arrangement corresponding to each goods picking person to obtain goods scheduling information;

The display unit is configured to display the goods scheduling information on a storage visual operation page corresponding to the storage processing system, wherein the storage visual operation page supports drag adjustment, key deletion and key addition of a picker node, a picker node and an article transportation route;

the second execution unit is configured to execute the scheduling content corresponding to the adjusted cargo scheduling information on the warehouse visual operation page.

9. An electronic device, comprising:

one or more processors;

a storage device having one or more programs stored thereon,

When executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-7.

10. A computer readable medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the method of any of claims 1-7.