CN116308026A - Automatic warehouse inventory allocation method and device - Google Patents
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Abstract
The application relates to the technical field of warehousing and discloses an automatic allocation method and device of warehouse inventory, wherein the method comprises the steps of combining the quantity of delivery, sales scenes, sales quantity and inventory allowance design plan order quantity based on historical transaction record data; based on the planned order quantity, carrying out autonomous periodic replenishment for a preset warehouse arranged in a hierarchy; based on the receiving address, in combination with delivery time limit and transportation cost, the hierarchically arranged warehouses are matched with the target warehouse for shipment from the lower hierarchy to the higher hierarchy. The method and the device have the effects of reducing the condition of material diapause and expiration and smoothing the order delivery period deviation of suppliers.
Description
Technical Field
The application relates to the technical field of warehouse, in particular to an automatic warehouse inventory allocation method and device.
Background
And when the normal storage stock of the required materials is not satisfied, triggering a replenishment mechanism of the warehouse. The existing warehouse goods supplementing mechanism adopts a re-ordering point to supplement goods, namely when the consumption and use of materials reach the re-ordering point, the next material purchase order is carried out, and the materials required for production or delivery are supplemented along with the arrival of the purchase order, so that the continuous production or delivery can be ensured, and the condition of material shortage or material cutoff does not occur. Wherein, the average daily consumption is multiplied by the number of days of the supply period to be used as the trigger number of the re-ordering points.
However, the actual sales and the expected sales of the materials often have the incongruity, and the water level of warehouse stock is higher at the moment, so that the problem of overdue materials due to stagnation occurs. Moreover, since daily consumption is unknown, the order point replenishment method does not form a relatively fixed replenishment frequency, which easily results in a shortage of production cycle of suppliers, and a problem of large deviation of order delivery time of suppliers, which affects delivery time.
Aiming at the related technology, the inventor finds that the existing warehouse replenishing mode has the problems of material diapause and expiration and large material delivery deadline deviation.
Disclosure of Invention
In order to reduce the condition of material diapause and expiration, order delivery period deviation of suppliers is smoothed, the application provides an automatic warehouse inventory allocation method and device.
In a first aspect, the present application provides a method for automatically allocating warehouse inventory.
The application is realized by the following technical scheme:
an automatic allocation method of warehouse stock comprises the following steps,
based on the historical transaction record data, combining the quantity of delivery, sales scenes, sales quantity and quantity of inventory balance design plan order quantity;
based on the planned order quantity, performing autonomous periodic replenishment for a preset hierarchically arranged warehouse;
based on the receiving address, in combination with delivery time limit and transportation cost, the hierarchically arranged warehouses are matched with the target warehouse for shipment from the lower hierarchy to the higher hierarchy.
The present application may be further configured in a preferred example to: the step of planning the order quantity based on the historical transaction record data in combination with the delivery volume, sales scenario, sales quantity and inventory balance includes,
acquiring the required order quantity and MOQ (metal oxide semiconductor) filling quantity;
predicting a planned order amount based on the demand order amount and the MOQ replenishment amount, wherein the planned order amount is calculated as follows,
planned order number= (demand order number+moq replenishment amount);
demand number = average sales number x sales scenario change factor x sales number change factor x (lead period x lead period factor + lead frequency) +safe inventory-current inventory-on-the-go order-unacknowledged return;
when the required order quantity < minimum order quantity, minimum order replenishment quantity = minimum order quantity-required order quantity; when the required order quantity is greater than the minimum order quantity, the minimum order replenishment quantity is 0;
secure stock quantity = average sales quantity x (delivery period/2-1);
wherein the average sales number is the average daily sales number in the statistical period, the sales scene change coefficient is constant, the adjustment range of the sales scene change coefficient is [0.1,1.9], the sales number change coefficient is sales volume trend in the statistical period, the delivery period is delivery time of the supplier, the delivery period coefficient is used for coping with delivery period variation of the supplier, the delivery period coefficient is constant, the safety stock quantity is used for coping with demand variation of the customer, the current stock quantity is available stock of the current warehouse, the in-transit order quantity is the quantity of the ordered goods which are not yet arrived before, and the unacknowledged return quantity is estimated customer return quantity.
The present application may be further configured in a preferred example to: the method also comprises the following steps of,
when the goods sales units are inconsistent with the corresponding goods ordering units, acquiring the minimum packaging quantity, wherein the minimum packaging quantity is the minimum unit quantity of the goods delivered by the suppliers;
predicting a planned order amount based on the minimum packaging amount, wherein the planned order amount is calculated as follows,
planned order number= (demand order number/minimum package amount+moq replenishment amount) ×minimum package amount.
The present application may be further configured in a preferred example to: the sales quantity variation coefficient is predicted by a linear regression algorithm, including,
substituting the required order quantity and delivery period into a linear regression equation, and calculating the slope of the sales trend line in the statistical period to be used as a sales quantity change coefficient.
The present application may be further configured in a preferred example to: the warehouse with the preset hierarchical arrangement comprises a first-level warehouse, a second-level warehouse and a third-level warehouse, wherein the first-level warehouse is used for specially providing appointed clients, the second-level warehouse is positioned at an appointed point of a provincial area, and the third-level warehouse is positioned in a specific region.
The present application may be further configured in a preferred example to: the primary bin, the secondary bin and the tertiary bin are all provided with standby bins, and the standby bins are used for supplementing deficient materials for the warehouses at the same level.
The present application may be further configured in a preferred example to: the step of matching the target warehouse for shipping based on the receiving address, combining delivery time limit and transportation cost, and arranging the warehouses in a hierarchy from low hierarchy to high hierarchy, further comprises,
acquiring an order data packet;
judging whether the goods source priority exists or not according to the order data packet;
if the source priority exists, the designated warehouse is taken as a target warehouse for shipment according to the source priority order;
and if the priority of the goods does not exist, matching the target warehouse for delivery based on the receiving address and combining the delivery time limit and the transportation cost.
The present application may be further configured in a preferred example to: after the matching target warehouse performs shipment, the method further comprises the following steps,
judging whether the matched available inventory of the target warehouse is met;
and if the available inventory of the matched target warehouse is met, directly delivering the matched target warehouse.
The present application may be further configured in a preferred example to: the method also comprises the following steps of,
if the available inventory of the matched target warehouse is not satisfied, judging whether the available inventory of other warehouses has redundant inventory according to the sequence from the low level to the high level of the warehouses arranged in the hierarchy;
if the available stock of the other warehouse has redundant stock, judging whether the redundant stock of the other warehouse meets the order requirement or not;
if the redundant stock of other warehouses meets the order demands, generating an allocation and shifting list according to the order demands, and allocating the goods from the other warehouses for delivery.
The present application may be further configured in a preferred example to: after the step of determining whether the available inventory of the other warehouse has excess inventory, the method further comprises,
if the available inventory of other warehouses does not have redundant inventory, judging whether other warehouses have corresponding goods sources of the target warehouse or not;
and if other bins are stored in the corresponding goods sources of the target warehouse, generating a purchase order according to the order demand and the number of the corresponding goods sources of the corresponding other warehouses, and distributing the purchase order to the suppliers corresponding to the matched target warehouse until the goods of the target warehouse are purchased, and then, carrying out shipment by the target warehouse and the corresponding other warehouses.
The present application may be further configured in a preferred example to: after the step of determining whether the other warehouse has the corresponding source of the target warehouse, the method further comprises,
if other warehouses do not have the corresponding goods sources of the target warehouse, continuing to judge whether the available inventory of the other warehouses has redundant inventory according to the sequence from the low level to the high level of the warehouses arranged in the hierarchy, and simultaneously, judging whether the other warehouses without redundant inventory have the corresponding goods sources of the target warehouse until the other warehouses with the corresponding goods sources of the target warehouse are searched;
and generating a purchase order according to the order demand and the number of corresponding goods sources of the corresponding other warehouses, and distributing the purchase order to the supplier corresponding to the matched target warehouse until the goods of the target warehouse are purchased, and then, carrying out shipment by the target warehouse and the corresponding other warehouses.
The present application may be further configured in a preferred example to: after the step of determining whether the excess inventory of the other warehouse meets the order requirement, the method further comprises,
if the redundant stock of the other warehouse does not meet the order requirement, judging whether the other warehouse has a corresponding goods source of the target warehouse or not;
and if other bins are stored in the corresponding goods sources of the target warehouse, generating a purchase order according to the order demand and the number of the corresponding goods sources of the corresponding other warehouses, and distributing the purchase order to the suppliers corresponding to the matched target warehouse until the goods of the target warehouse are purchased, and then, carrying out shipment by the target warehouse and the corresponding other warehouses.
In a second aspect, the present application provides an automated warehouse inventory allocation device.
The application is realized by the following technical scheme:
an automatic warehouse inventory allocation device comprises,
the autonomous periodic replenishment prediction module is used for combining the delivery quantity, the sales scene, the sales quantity and the inventory balance design plan ordering quantity based on the historical transaction record data;
the hierarchy storage module is used for carrying out autonomous periodic replenishment on a preset hierarchy-arranged warehouse based on the planned ordering quantity;
and the warehouse inventory allocation module is used for matching the target warehouse to carry out shipment according to the order of the warehouses arranged in the layers from the low layer to the high layer by combining the delivery time limit and the transportation cost based on the receiving address.
In a third aspect, the present application provides a computer device.
The application is realized by the following technical scheme:
a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of any of the warehouse inventory automatic allocation methods described above when the computer program is executed.
In a fourth aspect, the present application provides a computer-readable storage medium.
The application is realized by the following technical scheme:
a computer readable storage medium storing a computer program which when executed by a processor performs the steps of any of the above automatic warehouse inventory allocation methods.
To sum up, compared with the prior art, the beneficial effects brought by the technical scheme provided by the application at least include:
based on historical transaction record data, the delivery quantity, sales scene, sales quantity and inventory allowance design plan order quantity are combined, so that the plan order quantity can dynamically adapt to the actual sales quantity and inventory allowance, the requirement of a complex transaction scene is met, the condition of material diapause and expiration is reduced, meanwhile, a periodic and quantitative replenishment mode is adopted, the time dimension is increased by the replenishment mode, the order exchange period deviation of a supplier is smoothed, a stable cooperation rhythm is conveniently established with the supplier, the supplier can prepare goods in advance, the problem of shortage of production period of the supplier is thoroughly solved, and autonomous periodic replenishment is realized; the warehouse is arranged in a hierarchical mode, so that the transportation cost and the material delivery deadline are considered, and the warehouse stock can meet the order demands to the greatest extent; based on the receiving addresses, the order from low level to high level of the warehouses which are distributed according to the level and adopt the autonomous periodic replenishment is matched with the target warehouse for delivery, so that the condition of material diapause and expiration is reduced, and meanwhile, the order delivery period deviation of suppliers is smoothed, and the material delivery on schedule is facilitated.
Drawings
Fig. 1 is an overall flow diagram of a method for automatically distributing warehouse inventory according to an exemplary embodiment of the present application.
Fig. 2 is a statistical diagram of historical transaction records of an automatic warehouse inventory allocation method according to another exemplary embodiment of the present application.
Fig. 3 is a graph of deviation of actual and theoretical lead times of suppliers in an automatic warehouse inventory allocation method according to another exemplary embodiment of the present application.
FIG. 4 is a schematic diagram of the effect of calculating trend lines based on a linear regression algorithm and adopting an average algorithm in an automatic allocation method of warehouse inventory according to an exemplary embodiment of the present application.
Fig. 5 is a schematic diagram of a single template configuration of an automatic warehouse inventory allocation method according to an exemplary embodiment of the present application.
Fig. 6 is a schematic diagram of a plurality of template configurations of a method for automatically distributing warehouse inventory according to an exemplary embodiment of the present application.
Fig. 7 is a material base configuration information visual display diagram of an automatic warehouse inventory allocation method according to an exemplary embodiment of the present application.
Fig. 8 is a schematic diagram of a simulation algorithm model of an automatic warehouse inventory allocation method according to an exemplary embodiment of the present application and visually showing calculation results and simulation results.
Fig. 9 is an overall flow chart of a method for automatically distributing warehouse inventory according to an exemplary embodiment of the present application.
Fig. 10 is a flowchart of determining priority of a source of a warehouse according to an exemplary embodiment of the present application.
Fig. 11 is a schematic distribution flow chart of an automatic warehouse inventory distribution method according to an exemplary embodiment of the present application.
Fig. 12 is a block diagram of an automatic warehouse inventory allocation device according to an exemplary embodiment of the present application.
Detailed Description
The present embodiment is merely illustrative of the present application and is not intended to be limiting, and those skilled in the art, after having read the present specification, may make modifications to the present embodiment without creative contribution as required, but is protected by patent laws within the scope of the claims of the present application.
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
In addition, the term "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In this context, unless otherwise specified, the term "/" generally indicates that the associated object is an "or" relationship.
Embodiments of the present application are described in further detail below with reference to the drawings attached hereto.
Referring to fig. 1, an embodiment of the present application provides an automatic warehouse inventory allocation method, and main steps of the method are described as follows.
S1, based on historical transaction record data, combining the quantity of delivery, sales scenes, sales quantity and quantity of inventory balance design plan orders;
s2, based on the planned order quantity, carrying out autonomous periodic replenishment on a preset warehouse arranged in a hierarchy;
and S3, matching the target warehouse for shipping according to the order of the warehouses arranged in the layers from the low layer to the high layer based on the receiving address and combining the delivery time limit and the transportation cost.
Referring to fig. 2, in particular, historical transaction record data is analyzed, for example, inventory amounts of class a materials, class B materials, and class C materials are counted, and plan order amounts are designed in combination with amounts of delivery, sales scenarios such as seasons, major activities, etc., sales amounts, and inventory margins.
Referring to fig. 3, deviation comparison of actual delivery period and theoretical delivery period of suppliers of a class material, a class B material and a class C material is performed, and a periodic replenishment algorithm is designed in consideration of delivery period, order frequency and the like, so as to achieve the purpose of autonomous periodic replenishment according to sales volume conditions and inventory margins.
In one embodiment, the step of S1, based on the historical transaction record data, combining the quantity out of stock, the sales scenario, the quantity sold, and the quantity ordered by the inventory balance design plan includes,
acquiring the required order quantity and MOQ (metal oxide semiconductor) filling quantity;
predicting a planned order amount based on the demand order amount and the MOQ replenishment amount, wherein the planned order amount is calculated as follows,
planned order number= (demand order number+moq replenishment amount);
demand number = average sales number x sales scenario change factor x sales number change factor k x (lead period x lead period factor + lead frequency) +safe inventory-current inventory-on-the-way order-unacknowledged return;
when the required order quantity < minimum order quantity, minimum order replenishment quantity = minimum order quantity-required order quantity; when the required order quantity is greater than the minimum order quantity, the minimum order replenishment quantity is 0;
secure stock quantity = average sales quantity x (delivery period/2-1);
wherein the average sales number is the average daily sales number in the statistical period, the sales scene change coefficient is constant, the adjustment range of the sales scene change coefficient is [0.1,1.9], the sales number change coefficient k is sales volume trend in the statistical period, the delivery period is delivery time of the supplier, the delivery period coefficient is used for coping with delivery period variation of the supplier, the delivery period coefficient is constant, the safety stock quantity is used for coping with demand variation of the customer, the current stock quantity is available stock of the current warehouse, the in-transit order quantity is the quantity of the prior order not yet arrived, and the unacknowledged return quantity is estimated customer return quantity.
In this embodiment, the average sales number is recorded through manual statistics, and the value can be adjusted according to the authority. The value range of the sales scene change coefficient is designed between [0.1,1.9], for example, the sales scene change coefficient is 1.6 in the case of large promotion. The sales scene change coefficient can be adjusted according to actual conditions. The lead time coefficient is taken to be 1.1 for coping with lead time variation of the supplier. The delivery period coefficient can be adjusted according to actual conditions. The safety stock quantity designs a plurality of constants for selection, such as the larger the safety stock quantity design under the condition of large activity promoting factors; and the smaller the design of the safe stock quantity for the out-of-season commodity. There are a number of modes of secure inventory for selection.
In one embodiment, the method further comprises the following steps,
when the goods sales units are inconsistent with the corresponding goods ordering units, acquiring the minimum packaging quantity, wherein the minimum packaging quantity is the minimum unit quantity of the goods delivered by the suppliers;
predicting a planned order amount based on the minimum packaging amount, wherein the planned order amount is calculated as follows,
planned order number= (demand order number/minimum package amount+moq replenishment amount) ×minimum package amount.
In one embodiment, the sales volume change factor is predicted using a linear regression algorithm, including,
substituting the required order quantity and delivery period into a linear regression equation, and calculating the slope of the sales trend line in the statistical period to be used as a sales quantity change coefficient.
Referring to fig. 4, the actual customer order quantity and the lead time factor for each time are imported into the existing linear regression algorithm to obtain a predicted expected value. As more and more actual data is available, the higher the machine learning accuracy, the closer the expected value is to the next actual ordering situation. Through machine learning, a trend line is calculated based on a linear regression algorithm, sales in the next stage are predicted, and the real situation can be fitted more than the simple average value.
Referring to fig. 5 to 6, the planned order quantity is designed by performing template arrangement. Each type of product can be configured with a plurality of templates according to actual conditions, an example is newly built, the planned order quantity is calculated in an operation mode, and the minimum packaging quantity and the MOQ filling quantity are converted.
Referring to fig. 7, by visually displaying the underlying configuration information of the materials, more material transaction data is obtained, also facilitating verification and tracking.
Referring to fig. 8, the calculation result and the simulation result are visualized through a simulation algorithm model, for example, the satisfaction rate of the planned order quantity of the a-class material design reaches 87.3%, the satisfaction rate of the planned order quantity of the B-class material design reaches 63.6%, the satisfaction rate of the planned order quantity of the C-class material design reaches 27.4%, and the stock water level reaches 25.57 ten thousand yuan based on the order requirement of 23.21 ten thousand yuan and the current configuration, so that the actual order requirement can be satisfied.
Referring to fig. 9, after template configuration and new creation, the calculation of the planned order quantity is performed, and the minimum packing quantity and the MOQ replenishment quantity are converted, basic configuration information, calculation results and simulation results of the materials are visually displayed, and the planned order quantity of the materials is generated when the requirements are met, as shown by the numerical value of the replenishment quantity in the last column.
In this embodiment, the relevant parameters are stored by customizing the corresponding database table structure, and the number of database tables is designed according to the supply demand, so as to meet the actual supply demand.
And based on the planned order quantity, carrying out autonomous periodic replenishment for a preset warehouse arranged in a hierarchy.
In one embodiment, the preset hierarchically arranged warehouse comprises a first-level warehouse for specially providing specified clients, a second-level warehouse located at a specified point of a provincial area and a third-level warehouse located in a specific region.
The primary bin is also called a front bin and is used for being specially used for appointed clients, so that materials can be rapidly and accurately delivered out of a warehouse, and large clients can be better served.
The second bin is located at a designated point of the province and city, such as baoding, martial arts, guangzhou, etc. The method is generally used for traffic junction sections, and the delivery speed is high-efficiency and convenient.
The three-level bin is positioned in a specific region and can be named in a self-defining way, such as a Shendong bin, a Huabei bin and the like, and can be used as a temporary stock warehouse for a certain material to play a role in temporarily supplementing stock.
Further, the primary bin, the secondary bin and the tertiary bin are all configured with spare bins. The standby bin is used as a parallel bin of the warehouses arranged at each level and is used for supplementing deficient materials for the warehouses at the same level, plays a role in timely supplementing deficient material inventory under the conditions of great promotion activity or special scenes, and can flexibly cope with complex sales scenes.
Based on the receiving address, in combination with delivery time limit and transportation cost, the hierarchically arranged warehouses are matched with the target warehouse for shipment from the lower hierarchy to the higher hierarchy.
In this embodiment, the ordering of the layer levels is: primary bin < secondary bin < tertiary bin. For example, based on the order data package, the receiving address is obtained, the order of the warehouse arranged in the hierarchy is combined with the delivery time limit and the transportation cost, the order of the warehouse arranged in the hierarchy is from low hierarchy to high hierarchy, the target warehouse meeting the delivery time limit and having the minimum transportation cost is matched, the customer number is bound to the warehouse and the business logic binding of the order data package with the primary warehouse, the secondary warehouse and the tertiary warehouse is realized through the marking processing of the order data package and the interaction with the CRM of the customer management system.
Referring to fig. 10, in one embodiment, the step S3 of matching the destination warehouse to carry out shipment based on the shipping address in combination with the delivery time limit and the transportation cost, before the step of hierarchically arranging the warehouses from the lower hierarchy to the higher hierarchy,
s31, acquiring an order data packet;
s32, judging whether the source priority exists according to the order data packet;
s331, if the source priority exists, taking the appointed warehouse as a target warehouse to carry out shipment according to the source priority sequence;
and S332, if the priority of the goods source is not available, matching the target warehouse for delivery based on the receiving address and combining the delivery time limit and the transportation cost.
In this embodiment, the preset source priority may be: customer-specified source shipment > target warehouse inventory shipment > all warehouse inventory shipment > other regional source shipment > warehouse inventory source shipment. Wherein once the shipment of the source in the other region is set, the source selection logic does not go to the warehouse to inventory the shipment of the source, indicating that the source covers all other regions of the country. If the warehouse source does not have a warehouse meeting the condition, the requirements are transferred and met by other warehouses.
When the customer designates the goods source for delivery, whether the inventory is satisfied or not, the goods source is directly sent from the customer; if no customer specifies a source shipment, inventory is preferentially consumed.
Referring to fig. 11, in one embodiment, after the matching target warehouse performs shipment, further comprising the steps of,
judging whether the matched available inventory of the target warehouse is met;
and if the available inventory of the matched target warehouse is met, directly delivering the matched target warehouse.
In an embodiment, if the available inventory of the matched target warehouse is not satisfied, determining whether the available inventory of other warehouses has redundant inventory according to the order from the low level to the high level of the warehouses arranged in the hierarchy;
if the available stock of the other warehouse has redundant stock, judging whether the redundant stock of the other warehouse meets the order requirement or not;
if the redundant stock of other warehouses meets the order demands, generating an allocation and shifting list according to the order demands, and allocating the goods from the other warehouses for delivery.
In one embodiment, after the step of determining whether the available inventory of the other warehouse has excess inventory, the method further comprises,
if the available inventory of other warehouses does not have redundant inventory, judging whether other warehouses have corresponding goods sources of the target warehouse or not;
and if other bins are stored in the corresponding goods sources of the target warehouse, generating a purchase order according to the order demand and the number of the corresponding goods sources of the corresponding other warehouses, and distributing the purchase order to the suppliers corresponding to the matched target warehouse until the goods of the target warehouse are purchased, and then, carrying out shipment by the target warehouse and the corresponding other warehouses.
In one embodiment, after the step of determining whether the other warehouse has a corresponding source of the target warehouse, the method further comprises,
if other warehouses do not have the corresponding goods sources of the target warehouse, continuing to judge whether the available inventory of the other warehouses has redundant inventory according to the sequence from the low level to the high level of the warehouses arranged in the hierarchy, and simultaneously, judging whether the other warehouses without redundant inventory have the corresponding goods sources of the target warehouse until the other warehouses with the corresponding goods sources of the target warehouse are searched;
and generating a purchase order according to the order demand and the number of corresponding goods sources of the corresponding other warehouses, and distributing the purchase order to the supplier corresponding to the matched target warehouse until the goods of the target warehouse are purchased, and then, carrying out shipment by the target warehouse and the corresponding other warehouses.
In one embodiment, after the step of determining whether the excess inventory of the other warehouse meets the order requirement, the method further comprises,
if the redundant stock of the other warehouse does not meet the order requirement, judging whether the other warehouse has a corresponding goods source of the target warehouse or not;
and if other bins are stored in the corresponding goods sources of the target warehouse, generating a purchase order according to the order demand and the number of the corresponding goods sources of the corresponding other warehouses, and distributing the purchase order to the suppliers corresponding to the matched target warehouse until the goods of the target warehouse are purchased, and then, carrying out shipment by the target warehouse and the corresponding other warehouses.
Through the scheme, the parts which are not met by the warehouse are transferred and met by the redundant warehouses of other warehouses. And the part which is still not satisfied is preferentially purchased from the warehouse goods source. If the warehouse has no goods source, purchasing and allocating from other warehouses.
In summary, the automatic warehouse inventory allocation method is based on historical transaction record data, and combines the inventory quantity, sales scenes, sales quantity and inventory allowance design plan order quantity, so that the plan order quantity can dynamically adapt to the actual sales quantity and inventory allowance, meet the requirements of complex transaction scenes, reduce the condition of material diapause and expiration, meanwhile, adopt a periodic and quantitative replenishment mode, the replenishment mode increases the time dimension, smoothes the order exchange period deviation of suppliers, is convenient for establishing a stable cooperation rhythm with the suppliers, facilitates the suppliers to prepare goods in advance, thoroughly solves the problem of shortage of the production period of the suppliers, and realizes autonomous periodic replenishment; the warehouse is arranged in a hierarchical mode, so that the transportation cost and the material delivery deadline are considered, and the warehouse stock can meet the order demands to the greatest extent; based on the receiving addresses, the order from low level to high level of the warehouses which are distributed according to the level and adopt the autonomous periodic replenishment is matched with the target warehouse for delivery, so that the condition of material diapause and expiration is reduced, and meanwhile, the order delivery period deviation of suppliers is smoothed, and the material delivery on schedule is facilitated.
Through the warehouse of hierarchical arrangement, guarantee that the material is high-efficient convenient delivery, simultaneously, according to the goods source priority of predetermineeing to select the storehouse to send/directly send etc. goods source delivery mode, the delivery mode is more nimble, can adapt to the individualized order demand of complicated changeable sales scene, and data are clear, be convenient for calculate the sale cost.
It should be understood that the sequence number of each step in the foregoing embodiment 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. 12, an embodiment of the present application further provides an automatic warehouse inventory allocation device, where the automatic warehouse inventory allocation device corresponds to the automatic warehouse inventory allocation method in the foregoing embodiment one by one. The automatic warehouse inventory allocation device comprises,
the autonomous periodic replenishment prediction module is used for combining the delivery quantity, the sales scene, the sales quantity and the inventory balance design plan ordering quantity based on the historical transaction record data;
the hierarchy storage module is used for carrying out autonomous periodic replenishment on a preset hierarchy-arranged warehouse based on the planned ordering quantity;
and the warehouse inventory allocation module is used for matching the target warehouse to carry out shipment according to the order of the warehouses arranged in the layers from the low layer to the high layer by combining the delivery time limit and the transportation cost based on the receiving address.
For a specific definition of an automatic allocation device for warehouse inventory, reference may be made to the definition of an automatic allocation method for warehouse inventory hereinabove, and the description thereof will not be repeated here. The above-mentioned modules in an automatic warehouse inventory allocation device may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by the processor, implements any of the warehouse inventory automatic allocation methods described above.
In one embodiment, a computer readable storage medium is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of when executing the computer program:
s1, based on historical transaction record data, combining the quantity of delivery, sales scenes, sales quantity and quantity of inventory balance design plan orders;
s2, based on the planned order quantity, carrying out autonomous periodic replenishment on a preset warehouse arranged in a hierarchy;
and S3, matching the target warehouse for shipping according to the order of the warehouses arranged in the layers from the low layer to the high layer based on the receiving address and combining the delivery time limit and the transportation cost.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the system is divided into different functional units or modules to perform all or part of the above-described functions.
Claims (15)
1. An automatic warehouse inventory allocation method is characterized by comprising the following steps,
based on the historical transaction record data, combining the quantity of delivery, sales scenes, sales quantity and quantity of inventory balance design plan order quantity;
based on the planned order quantity, performing autonomous periodic replenishment for a preset hierarchically arranged warehouse;
based on the receiving address, in combination with delivery time limit and transportation cost, the hierarchically arranged warehouses are matched with the target warehouse for shipment from the lower hierarchy to the higher hierarchy.
2. The method for automatically allocating warehouse inventory according to claim 1, wherein the step of combining the inventory, sales scenario, sales quantity and inventory balance design plan order quantity based on the historical transaction record data comprises,
acquiring the required order quantity and MOQ (metal oxide semiconductor) filling quantity;
predicting a planned order amount based on the demand order amount and the MOQ replenishment amount, wherein the planned order amount is calculated as follows,
planned order number= (demand order number+moq replenishment amount);
demand number = average sales number x sales scenario change factor x sales number change factor x (lead period x lead period factor + lead frequency) +safe inventory-current inventory-on-the-go order-unacknowledged return;
when the required order quantity < minimum order quantity, minimum order replenishment quantity = minimum order quantity-required order quantity; when the required order quantity is greater than the minimum order quantity, the minimum order replenishment quantity is 0;
secure stock quantity = average sales quantity x (delivery period/2-1);
wherein the average sales number is the average daily sales number in the statistical period, the sales scene change coefficient is constant, the adjustment range of the sales scene change coefficient is [0.1,1.9], the sales number change coefficient is sales volume trend in the statistical period, the delivery period is delivery time of the supplier, the delivery period coefficient is used for coping with delivery period variation of the supplier, the delivery period coefficient is constant, the safety stock quantity is used for coping with demand variation of the customer, the current stock quantity is available stock of the current warehouse, the in-transit order quantity is the quantity of the ordered goods which are not yet arrived before, and the unacknowledged return quantity is estimated customer return quantity.
3. The automated warehouse inventory allocation method according to claim 2, further comprising the steps of,
when the goods sales units are inconsistent with the corresponding goods ordering units, acquiring the minimum packaging quantity, wherein the minimum packaging quantity is the minimum unit quantity of the goods delivered by the suppliers;
predicting a planned order amount based on the minimum packaging amount, wherein the planned order amount is calculated as follows,
planned order number= (demand order number/minimum package amount+moq replenishment amount) ×minimum package amount.
4. The automated warehouse inventory allocation method according to claim 2, wherein the sales quantity variation coefficient is predicted using a linear regression algorithm, comprising,
substituting the required order quantity and delivery period into a linear regression equation, and calculating the slope of the sales trend line in the statistical period to be used as a sales quantity change coefficient.
5. The automatic warehouse inventory allocation method according to claim 1, wherein the preset hierarchically arranged warehouse includes a primary warehouse dedicated to a specific customer, a secondary warehouse located at a specific point of a provincial district, and a tertiary warehouse located in a specific region.
6. The automated warehouse inventory allocation method according to claim 5, wherein the primary bin, the secondary bin and the tertiary bin are each configured with a spare bin for supplementing the same level warehouse with scarce material.
7. The method for automatic allocation of warehouse inventory according to any one of claims 1 to 6, characterized in that the step of matching the target warehouse for shipment based on the order of the warehouses arranged in the hierarchy from the lower hierarchy to the higher hierarchy in combination of the delivery time limit and the transportation cost, further comprises,
acquiring an order data packet;
judging whether the goods source priority exists or not according to the order data packet;
if the source priority exists, the designated warehouse is taken as a target warehouse for shipment according to the source priority order;
and if the priority of the goods does not exist, matching the target warehouse for delivery based on the receiving address and combining the delivery time limit and the transportation cost.
8. The automated warehouse inventory allocation method according to claim 7, further comprising the step of, after shipment of the matching target warehouse,
judging whether the matched available inventory of the target warehouse is met;
and if the available inventory of the matched target warehouse is met, directly delivering the matched target warehouse.
9. The automated warehouse inventory allocation method according to claim 7, further comprising the steps of,
if the available inventory of the matched target warehouse is not satisfied, judging whether the available inventory of other warehouses has redundant inventory according to the sequence from the low level to the high level of the warehouses arranged in the hierarchy;
if the available stock of the other warehouse has redundant stock, judging whether the redundant stock of the other warehouse meets the order requirement or not;
if the redundant stock of other warehouses meets the order demands, generating an allocation and shifting list according to the order demands, and allocating the goods from the other warehouses for delivery.
10. The method for automatically allocating warehouse inventory according to claim 9, wherein after the step of determining whether the surplus inventory exists in the available inventory of the other warehouse, further comprising,
if the available inventory of other warehouses does not have redundant inventory, judging whether other warehouses have corresponding goods sources of the target warehouse or not;
and if other bins are stored in the corresponding goods sources of the target warehouse, generating a purchase order according to the order demand and the number of the corresponding goods sources of the corresponding other warehouses, and distributing the purchase order to the suppliers corresponding to the matched target warehouse until the goods of the target warehouse are purchased, and then, carrying out shipment by the target warehouse and the corresponding other warehouses.
11. The automated warehouse inventory allocation method according to claim 10, wherein after the step of determining whether the other warehouse has a corresponding source of the target warehouse, further comprising,
if other warehouses do not have the corresponding goods sources of the target warehouse, continuing to judge whether the available inventory of the other warehouses has redundant inventory according to the sequence from the low level to the high level of the warehouses arranged in the hierarchy, and simultaneously, judging whether the other warehouses without redundant inventory have the corresponding goods sources of the target warehouse until the other warehouses with the corresponding goods sources of the target warehouse are searched;
and generating a purchase order according to the order demand and the number of corresponding goods sources of the corresponding other warehouses, and distributing the purchase order to the supplier corresponding to the matched target warehouse until the goods of the target warehouse are purchased, and then, carrying out shipment by the target warehouse and the corresponding other warehouses.
12. The method for automatically allocating warehouse inventory according to claim 9, wherein after the step of determining whether the excess inventory of the other warehouse meets the order requirement, further comprising,
if the redundant stock of the other warehouse does not meet the order requirement, judging whether the other warehouse has a corresponding goods source of the target warehouse or not;
and if other bins are stored in the corresponding goods sources of the target warehouse, generating a purchase order according to the order demand and the number of the corresponding goods sources of the corresponding other warehouses, and distributing the purchase order to the suppliers corresponding to the matched target warehouse until the goods of the target warehouse are purchased, and then, carrying out shipment by the target warehouse and the corresponding other warehouses.
13. An automatic warehouse inventory allocation device, characterized by comprising,
the autonomous periodic replenishment prediction module is used for combining the delivery quantity, the sales scene, the sales quantity and the inventory balance design plan ordering quantity based on the historical transaction record data;
the hierarchy storage module is used for carrying out autonomous periodic replenishment on a preset hierarchy-arranged warehouse based on the planned ordering quantity;
and the warehouse inventory allocation module is used for matching the target warehouse to carry out shipment according to the order of the warehouses arranged in the layers from the low layer to the high layer by combining the delivery time limit and the transportation cost based on the receiving address.
14. A computer device comprising a memory, a processor and a computer program stored on the memory, the processor executing the computer program to perform the steps of the method of any one of claims 1 to 12.
15. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the steps of the method of any one of claims 1 to 12.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116882905A (en) * | 2023-09-08 | 2023-10-13 | 深圳市元美供应链管理有限公司 | Big data-based supply chain intelligent inventory management system and method |
| CN116882903A (en) * | 2023-09-07 | 2023-10-13 | 北京中亦信科技有限公司 | Method for managing order application and computer readable storage medium |
| CN117787712A (en) * | 2023-12-28 | 2024-03-29 | 广州美亿互联信息技术有限公司 | Intelligent wind control system and method for cross-border e-commerce digitization |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116882903A (en) * | 2023-09-07 | 2023-10-13 | 北京中亦信科技有限公司 | Method for managing order application and computer readable storage medium |
| CN116882905A (en) * | 2023-09-08 | 2023-10-13 | 深圳市元美供应链管理有限公司 | Big data-based supply chain intelligent inventory management system and method |
| CN116882905B (en) * | 2023-09-08 | 2023-12-22 | 深圳市元美供应链管理有限公司 | Big data-based supply chain intelligent inventory management system and method |
| CN117787712A (en) * | 2023-12-28 | 2024-03-29 | 广州美亿互联信息技术有限公司 | Intelligent wind control system and method for cross-border e-commerce digitization |
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