CN114912858A

CN114912858A - Method, apparatus and storage medium for inventory management system

Info

Publication number: CN114912858A
Application number: CN202110183747.5A
Authority: CN
Inventors: 刘汝杰
Original assignee: Fujitsu Ltd
Current assignee: Fujitsu Ltd
Priority date: 2021-02-10
Filing date: 2021-02-10
Publication date: 2022-08-16

Abstract

The present disclosure relates to a method and apparatus for an inventory management system and a storage medium. According to one embodiment of the disclosure, the method comprises: determining representative ex-warehouse volume fluctuation associated with the actual ex-warehouse volume and the fitted ex-warehouse volume of each order cycle in the plurality of order cycles for the target class commodities based on the historical data; determining representative single-day in-out warehouse accumulated difference upper limits for target commodities in a plurality of ordering periods based on historical data; determining safety stock aiming at the target class of commodities based on the representative ex-warehouse quantity fluctuation and the representative single-day in-warehouse accumulated difference upper limit; and providing order recommendation information related to the order for the next order cycle to the warehouse manager for the target item based on the safety stock. The beneficial effects of the method, apparatus and storage medium of the present disclosure include at least one of: the inventory holding cost and the stock shortage cost are balanced, and the utilization efficiency of the warehouse is improved.

Description

Method, apparatus and storage medium for inventory management system

Technical Field

The present disclosure relates generally to logistics management, and more particularly, to a method, apparatus, and storage medium for a storage management system.

Background

Inventory management is an important aspect of logistics management. Warehouse managers of an enterprise typically use an inventory management system (inventory management system) to monitor the amount of warehousing, ex-warehousing, etc. for target types of goods. These data may be stored in a database of the inventory management system.

For a target class of goods, the warehouse manager of the enterprise orders the suppliers of the target class of goods periodically (e.g., monthly, weekly, or daily, corresponding to an order period); after receiving the order, the supplier sends the order to the warehouse in batches or in a centralized way to generate warehouse entry data; the user (customer or distributor) purchases the target type of goods from the warehouse manager periodically or non-periodically, and the warehouse manager provides the target type of goods to the user to generate the warehouse volume data.

Due to some uncertainty factors in both market demand and supplier supply, the order quantity is difficult to be completely matched with the actual future demand, so that the target type of goods may be out of stock or overstocked. The warehouse manager wishes to maintain the appropriate inventory for the target class of goods. High inventory levels can accommodate large fluctuations in sales (ex-warehouse) and improve customer experience, but can drive up inventory holding costs for the target class of goods. Low safe inventory may reduce inventory holding costs, but may also occur for out of stock when demand is present, resulting in high out of stock costs. Therefore, it is desirable to determine an appropriate inventory amount to improve the efficiency of warehouse utilization by the enterprise.

Disclosure of Invention

A brief summary of the disclosure is provided below in order to provide a basic understanding of some aspects of the disclosure. It should be understood that this summary is not an exhaustive overview of the disclosure. It is not intended to identify key or critical elements of the disclosure or to delineate the scope of the disclosure. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is discussed later.

According to one aspect of the present disclosure, a computer-implemented method for an inventory management system is provided. The method comprises the following steps: determining a representative ex-warehouse quantity fluctuation associated with an actual ex-warehouse quantity and a fitted ex-warehouse quantity for each order cycle in a plurality of order cycles for a target class of goods based on historical data related to warehouses in a database of an inventory management system; determining representative single-day in-out warehouse accumulated difference upper limits for target commodities for a plurality of order cycles based on historical data in a database of an inventory management system; determining safety stock aiming at the target class of commodities based on the representative ex-warehouse quantity fluctuation and the representative single-day in-warehouse accumulated difference upper limit; and providing order recommendation information related to an order of a next order cycle for the target goods to the warehouse manager based on the safety stock; wherein the representative outbound volume fluctuation is associated with a difference between an actual outbound volume and a fit outbound volume for each of the plurality of order cycles; the fitting ex-warehouse quantity is determined by a fitting function obtained by fitting actual ex-warehouse quantities of a plurality of order periods; and the representative single-day warehouse-in and warehouse-out accumulation upper limit is at least associated with the single-day warehouse-out accumulation and the single-day warehouse-in accumulation counted by taking the order cycle as a unit in one order cycle in the plurality of order cycles.

According to one aspect of the present disclosure, an apparatus for inventory management is provided. The device includes: a memory having instructions stored thereon; and one or more processors in communication with the memory to execute the instructions retrieved from the memory, and the instructions cause the one or more processors to: a memory having instructions stored thereon; and one or more processors in communication with the memory to execute the instructions retrieved from the memory, and the instructions cause the one or more processors to: determining a representative ex-warehouse quantity fluctuation associated with an actual ex-warehouse quantity and a fitted ex-warehouse quantity for each order cycle in a plurality of order cycles for a target class of goods based on historical data related to warehouses in a database of an inventory management system; determining representative single-day in-out warehouse accumulated difference upper limits for target commodities for a plurality of order cycles based on historical data in a database of an inventory management system; determining a safety stock for the target commodity based on the representative warehouse-out quantity fluctuation and the representative single-day warehouse-in and warehouse-out accumulated difference upper limit; and providing order recommendation information regarding an order for a next order cycle for the target item to the warehouse manager based on the safety stock; wherein the representative outbound volume fluctuation is associated with a difference between an actual outbound volume and a fit outbound volume for each of the plurality of order cycles; the fitting ex-warehouse quantity is determined by a fitting function obtained by fitting actual ex-warehouse quantities of a plurality of order periods; and the representative single-day warehouse-in and warehouse-out accumulation upper limit is at least related to the single-day warehouse-out accumulation and the single-day warehouse-in accumulation of one order cycle in the plurality of order cycles, which are counted by taking the order cycle as a unit.

According to one aspect of the present disclosure, an apparatus for inventory management is provided. The device comprises: a first determination unit configured to determine, for a target class of commodities, a representative shipment fluctuation associated with an actual shipment and a fitted shipment for each of a plurality of order cycles based on historical data relating to warehouses in a database of an inventory management system; a second determination unit configured to determine a representative single-day in-out warehouse accumulated difference upper limit for the target class of commodities for a plurality of order cycles based on historical data in a database of the inventory management system; a third determination unit configured to determine a safe stock for the target class of commodities based on the representative ex-warehouse volume fluctuation and the representative single-day in-warehouse accumulated difference upper limit; a recommending unit configured to provide order recommendation information regarding an order of a next order cycle for a target commodity to a warehouse manager based on the safety stock; wherein the representative outbound volume fluctuation is associated with a difference between an actual outbound volume and a fit outbound volume for each of the plurality of order cycles; the fitting ex-warehouse quantity is determined by a fitting function obtained by fitting actual ex-warehouse quantities of a plurality of order periods; and the representative single-day warehouse-in and warehouse-out accumulation upper limit is at least associated with the single-day warehouse-out accumulation and the single-day warehouse-in accumulation counted by taking the order cycle as a unit in one order cycle in the plurality of order cycles.

According to an aspect of the present disclosure, there is provided a computer-readable recording medium storing a program. The program causes a computer running the program to: determining a representative shipment fluctuation associated with an actual shipment and a fit shipment for each of a plurality of order cycles for a target class of merchandise based on historical data relating to the warehouse in a database of the inventory management system; determining representative single-day warehouse-in and warehouse-out accumulated difference upper limits for target commodities for a plurality of ordering periods based on historical data in a database of an inventory management system; determining safety stock aiming at the target class of commodities based on the representative ex-warehouse quantity fluctuation and the representative single-day in-warehouse accumulated difference upper limit; and providing order recommendation information regarding an order for a next order cycle for the target item to the warehouse manager based on the safety stock; wherein the representative outbound volume fluctuation is associated with a difference between an actual outbound volume and a fit outbound volume for each of the plurality of order cycles; the fitting ex-warehouse quantity is determined by a fitting function obtained by fitting actual ex-warehouse quantities of a plurality of order periods; and the representative single-day warehouse-in and warehouse-out accumulation upper limit is at least related to the single-day warehouse-out accumulation and the single-day warehouse-in accumulation of one order cycle in the plurality of order cycles, which are counted by taking the order cycle as a unit.

The beneficial effects of the method, apparatus and storage medium of the present disclosure include at least one of: the inventory holding cost and the stock shortage cost are balanced, and the utilization efficiency of the warehouse is improved.

Drawings

The above and other objects, features and advantages of the present disclosure will be more readily understood from the following description of embodiments thereof with reference to the accompanying drawings. The drawings are only for the purpose of illustrating the principles of the disclosure. The dimensions and relative positioning of the elements in the figures are not necessarily drawn to scale. Like reference numerals may denote like features. In the drawings:

FIG. 1 illustrates an exemplary flow diagram of a method for an inventory management system according to one embodiment of the disclosure;

FIG. 2 illustrates an exemplary actual yield and fitted yield curve according to one embodiment of the present disclosure;

FIG. 3 illustrates an example normalized cumulative line graph according to one embodiment of this disclosure;

FIG. 4 illustrates an exemplary block diagram of an apparatus for an inventory management system according to one embodiment of the disclosure;

FIG. 5 illustrates an exemplary block diagram of an apparatus for an inventory management system according to one embodiment of the present disclosure; and

fig. 6 shows an exemplary block diagram of an information processing apparatus according to one embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure will be described hereinafter with reference to the accompanying drawings. In the interest of clarity and conciseness, not all features of an actual embodiment are described in the specification. It will of course be appreciated that in the development of any such actual embodiment, numerous implementation-specific decisions may be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which will vary from one implementation to another.

Here, it should be further noted that, in order to avoid obscuring the present disclosure with unnecessary details, only the device structure closely related to the scheme according to the present disclosure is shown in the drawings, and other details not so related to the present disclosure are omitted.

It is to be understood that the disclosure is not limited to the described embodiments, as described below with reference to the drawings. In this context, embodiments may be combined with each other, features may be replaced or borrowed between different embodiments, one or more features may be omitted in one embodiment, where feasible.

Computer program code for carrying out operations for aspects of embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages.

The method of the present disclosure may be implemented by a circuit having a corresponding functional configuration. The circuitry includes circuitry for a processor.

When ordering goods, a warehouse manager or operator typically sets the order quantity as the sum of the expected sales volume and the safety stock for a target class of goods, wherein the expected sales volume and the safety stock are both for one order period. Safety stock can be considered as an additional order volume that can cope with fluctuations in sales volume. Considering the influence factors of safety stock on the target class of commodities, the inventor generally conceals the scheme that: safety stock is determined based on representative relative fluctuations in demand and a representative single-day warehouse access accumulation difference ceiling. The representative relative fluctuation of demand is conceived as a representative shipment fluctuation, which is a fluctuation of actual shipment relative to predicted shipment, wherein the predicted shipment may be determined using a shipment fitting function. The single-day warehousing-out accumulation difference is defined as the difference between single-day sales accumulation (ex-warehouse accumulation) and single-day warehousing accumulation (arrival accumulation) counted by taking the order period as a unit, and if one order period comprises N natural days, the corresponding single-day sales accumulation and single-day warehousing accumulation counted by taking the order period as a unit are respectively arranged on each natural day in the N natural days. Therefore, for each natural day of an order cycle, there is a corresponding single-day warehousing-ex-warehousing accumulated difference of the natural day. There are N single-day warehouse-in and warehouse-out accumulated differences in one ordering period. The maximum value of the N single-day accumulated difference in warehouse entry is referred to as the upper limit of the single-day accumulated difference in warehouse entry for the order cycle. The multiple ordering periods correspond to the multiple single daily-out and warehousing accumulated difference upper limits. One representative value (e.g., their average or other value having an average property) may be determined as a representative single-day warehousing cumulative difference upper limit based on a plurality of single-day warehousing cumulative difference upper limits for calculating the safety stock. Proper safe inventory is beneficial to balancing inventory holding cost and stock shortage cost, and the utilization efficiency of the inventory is improved. It is desirable to determine the appropriate safety stock.

One aspect of the present disclosure provides a computer-implemented method for an inventory management system. The method is described below with reference to fig. 1.

FIG. 1 illustrates an exemplary flow diagram of a method 100 for an inventory management system according to one embodiment of this disclosure.

In step S101, a representative shipment amount fluctuation Dro is determined. Specifically, an actual shipment amount (denoted by Co [ i ]. OutA or may be abbreviated as OutA) and a representative shipment amount fluctuation Dro associated with a fitted shipment amount (denoted by Co [ i ]. OutF or may be abbreviated as OutF) for each order cycle (denoted by Co [ i ]) in a plurality of order cycles for a target class commodity are determined based on the historical data about the warehouse in the database DB of the inventory management system. The order period has a predetermined time, e.g., one week, one month, one quarter, etc. The ex warehouse volume may correspond to the sales volume of the target class of goods for the warehouse. Actual ex-warehouse quantity Co [ i ] of the order period Co [ i ], OutA corresponds to the accumulated sales quantity in the target order period. The representative delivery fluctuation Dro is associated with a difference Co [ i ]. Df (which may also be abbreviated as Df) between an actual delivery Co [ i ]. OutA and a fitted delivery Co [ i ]. OutF for each of a plurality of order cycles, wherein,

Co[i].Df＝Co[i].OutA-Co[i].OutF。

the fitted ex-warehouse quantity OutF is determined by a fitting function obtained by fitting the actual ex-warehouse quantities for a plurality of order cycles. The fit may be a linear fit or a polynomial fit such as a quadratic function, preferably a linear fit. The linear fit function is expressed, for example, as:

Co[i].OutF＝K*Co[i].OutA+Const。

where K is the slope and Const is the intercept. Both K and Const are given by the fitting results.

FIG. 2 illustrates an exemplary actual ex warehouse volume and fitted ex warehouse volume curve, where Out represents the ex warehouse volume, i represents the order cycle number, and the data for each point is shown in Table one, according to one embodiment of the present disclosure.

Table actual delivery volume of 6 order cycles

i	1	2	3	4	5	6
							OutA	54	26	21	38	53	72
OutF	30.57	35.94	41.31	46.69	52.06	57.43
							Df	23.43	-9.94	-20.31	-8.69	0.94	14.57

In one example, the representative shipment amount fluctuation Dro is associated with an Average [ abs (df) ] of absolute values of differences between actual shipment amounts and fitted shipment amounts for each of a plurality of order cycles. For example, take Dro equal Average [ abs (Df) ]. Average [ abs (Df) ] can be calculated according to equation (1).

Where Abs () is an absolute value function and i _ max is the maximum value of i. When the reasonable value of the inventory of the commodity is an integer, optionally, the Average [ abs (df) ] is rounded and then is assigned to Dro, and the rounding can be upper rounding or lower rounding, preferably upper rounding.

In one example, the representative shipment volume fluctuation Dro is associated with a standard deviation σ of a difference between an actual shipment volume and a fitted shipment volume for each of the plurality of order cycles, e.g., take Dro equal to the standard deviation σ. The standard deviation σ is calculated as equation (2).

Wherein the content of the first and second substances,

that is, average (Df) is Co [1]].Df、Co[1].Df、Co[2].Df、……、Co[i_max]Average of Df. When the reasonable value of the inventory of the commodity is an integer, the round of sigma or Std (Df) is optionally given to Dro, and the round can be an upper round or a lower round, preferably the upper round.

In one example, a representative shipment volume fluctuation Dro is associated with the sum of the Average [ abs (df) ] and the standard deviation σ. For example, Dro equals their sum, Dro ═ Averge [ abs (df) ] + std (df). The calculation method can obtain larger Dro, and can relatively reduce the stock out cost.

In one example, the representative shipment amount fluctuation Dro is associated with a maximum value of differences between actual shipment amounts and fitted shipment amounts for each of the plurality of order cycles. For example, Dro equals the maximum value Max (Df) of the difference between the actual ex-warehouse volume and the fitted out-warehouse volume for each order cycle Max (Df) Max (Co 1. Df, Co 2. Df, … …, Co i Max. Df).

Where Max () is a maximum extraction function. For example, in 10 order cycles, of the 10 differences between the actual out-of-stock amount counted and the fitted out-of-stock amount, the maximum value is 72, and Dro is set to 72.

It should be noted that, when the reasonable value of the inventory amount of the commodity should be an integer, the calculated Dro may not be taken as an integer, because the calculated intermediate result of the safety inventory may be taken as the safety inventory after being rounded when the safety inventory is calculated.

Returning to fig. 1, in step S103, a representative single-day warehouse-in/warehouse-out accumulated difference upper limit Inr is determined. The representative single-day warehousing/ex-warehousing cumulative difference upper limit Inr may be an average value of a plurality of single-day warehousing/ex-warehousing cumulative difference upper limits corresponding to a plurality of order cycles or a value similar to the average value in meaning, that is, a value having an average property. Specifically, the representative single-day warehouse-in/warehouse-out accumulated difference upper limit Inr for the target class of products for a plurality of order cycles is determined based on the history data in the database DB of the inventory management system. The representative one-day warehouse-in/warehouse-out accumulated difference upper limit Inr is at least associated with one-day warehouse-out accumulated Co [ i ']. OutS [ j ] (can be abbreviated as OutS) and one-day warehouse-in accumulated Co [ i' ]. IntS [ j ] (can be abbreviated as IntS) of one ordering period in a plurality of ordering periods, which are counted by the ordering period as a unit. For example, Inr is associated with at least the difference Co [ i '], Ds [ j ] ═ Co [ i' ], OutS [ j ] - [ Co [ i '], IntS [ j ], between the single-day out-warehouse accumulation Co [ i' ], IntS [ j ], of one of the plurality of order cycles, counted in units of the order cycle. Note that the plurality of order cycles considered in step S103 correspond to a cycle that is the same length as the plurality of order cycles in step S101, but the corresponding time periods may not be exactly the same (e.g., the former corresponding to weeks 34-44 of the year and the latter corresponding to weeks 33-43), so different terminology is used to indicate that they may be different, not exactly the same, or the same. Ds is for a single day of an order cycle of a plurality of order cycles. For example, for wednesday in order cycle i' of the 3 rd week cycle, statistics show that 111 target commodities are sold (i.e. ex-warehouse) cumulatively from monday to the single day, and 99 target commodities are sold cumulatively, and the results are recorded as:

Co[i’].Ds[3]＝Co[3].OutS[3]-Co[3].IntS[3]＝111-99＝12。

the statistical method of the single-day ex-warehouse accumulation and the single-day in-warehouse accumulation, which is counted by taking one ordering period in the plurality of ordering periods as a unit, can refer to a table II. Table two shows an example of the single-day ex-warehouse accumulation and the single-day in-warehouse accumulation in an order cycle, wherein the length of the order cycle is one week.

Statistics of second-day warehouse-out accumulation and single-day warehouse-in accumulation of table

That is to say that

Wherein, Co [ i ' ]. Out _ D represents the sales volume of the natural day j ' included in the order cycle i '; int _ D represents the arrival amount of a natural day j 'included in an order cycle i'.

In one example, a representative single-day in-out cumulative difference upper limit Inr is associated with an average of single-day in-out cumulative sample differences for each of a plurality of order cycles. The single-day warehouse-in and warehouse-out accumulated sampling difference of each order period in a plurality of order periods is selected from a plurality of single-day warehouse-in and warehouse-out accumulated differences of the order period, and the single-day warehouse-in and warehouse-out accumulated difference is the difference between the single-day warehouse-out accumulation and the single-day warehouse-in accumulation counted by taking the order period as a unit. For example, the single-day warehouse-in/warehouse-out sampling difference for each order cycle is the maximum value MaxDs [ i '] Max (Co [ i' ]. Ds [1], … …, Co [ i ']. Ds [ j _ Max ]) among the differences between the single-day warehouse-out accumulation and the single-day warehouse-in accumulation counted in units of the order cycle, and Inr is equal to the average value of the plurality of MaxDs [1], … … MaxDs [ i' _ Max ] for a plurality of order cycles, and is written as:

Inr＝Average[MaxDs]。

for example, for 5 ordering cycles, the maximum value of Ds MaxDs is 103, 109, 105, 107, 101, respectively, and Inr is 105.

When the reasonable value of the stock of the commodity is an integer, optionally, the integer of Average [ MaxDs ] is rounded and then assigned to Inr, and the rounding can be upper rounding or lower rounding, preferably upper rounding.

For example, a representative single-day in-out cumulative difference upper bound with average properties may be constructed using the difference coefficient and average sales. In one example, the representative single-day warehouse-in/warehouse-Out accumulated difference upper limit Inr is associated with a product of a difference coefficient Cd and the Average warehouse-Out amount Average (Out _ OC) of a single order period of a plurality of order periods, wherein the difference coefficient Cd is the maximum value of the differences Cds [1] to Cds [ j _ max ] between the normalized single-day warehouse-Out accumulation and the normalized single-day warehouse-in accumulation of one order period of the plurality of order periods, which are counted by taking the order period as a unit, and is abbreviated as: cd ═ max (cds). For example, selecting order cycle Co [ i ' ] in i ' _ max order cycles to determine difference coefficient Cd, normalizing each single-day ex-warehouse accumulation Co [ i ' ]. OutS [ j ] in the order cycle by maximum single-day ex-warehouse accumulation in multiple single-day ex-warehouse accumulations counted by the order cycle as unit to obtain normalized single-day ex-warehouse accumulation Co [ i ' ]. OutSn [ j ], normalizing each single-day ex-warehouse accumulation Co [ i ' ]. IntS [ j ] in the order cycle Co [ i ' ]. with maximum single-day warehouse accumulation in multiple single-day warehouse accumulations counted by the order cycle as unit to obtain normalized single-day warehouse accumulation Co [ i ' ]. IntS [ j ], calculating j, taking Co [ i ' ]. Int ] as export difference of Cds [ i ' ]. CdSn [ j ], the maximum value among the plurality of Cds (i.e., Cds [1] to Cds [ j _ max ]) is taken as the difference coefficient Cd. Out _ OC is the sales volume for each of i' _ max order cycles (i.e., the shipment volume within one order cycle, corresponding to the actual shipment volume OutA described earlier), and Average (Out _ OC) represents the Average of these shipment volumes. For example, Inr — Cd × Average (Out _ OC). When the reasonable value of the stock of the commodity is an integer, optionally, Cd × Average (Out _ OC) is rounded and then given to Inr, and the rounding can be upper rounding or lower rounding, preferably upper rounding. Examples of obtaining normalized single-day ex-warehouse accumulation OutSn and normalized single-day in-warehouse accumulation IntSn by using the data shown in table two are shown in table three, wherein "80" is used to normalize "single-day in-warehouse accumulation" to obtain IntSn, "80" is used to normalize "single-day ex-warehouse accumulation" to obtain OutSn, and Cd obtained by using the data in the table is 0.2625.

Tabular three normalized single-day ex-warehouse accumulation and normalized single-day in-warehouse accumulation statistics

Using the normalized cumulative data Sn (including OutSn and IntSn) in table three, the line graph of the example normalized cumulative shown in fig. 3 can be obtained.

In step S105, the safety stock As for the target type of merchandise is determined based on the representative shipment amount fluctuation Dro and the representative single-day shipment/sale accumulated difference upper limit Inr. In one example, the safety stock As is a weighted sum of the representative shipment volume fluctuation Dro and the representative single-day warehouse-in/warehouse-out cumulative difference upper limit Inr, which is recorded As:

As＝w1*Dro+w2*Inr。

wherein w1 and w2 are weights. In general, w1 and w2 are real numbers close to 1. For example: w 1-w 2-1. In one example, w1, w2 may be determined based on historical inventory data for a target class of merchandise. If the sales amount of the target category goods is related to the season, different weights may be provided according to the season. Alternatively, the weighted sum may be rounded As.

In step S107, order recommendation information on an order of the next order cycle for the target product is provided to the warehouse manager based on the safety stock As. One example of providing recommendation information is: the recommendation information is displayed on a display of the information processing apparatus. Further, order recommendation information related to an order of a next order cycle for the target commodity may be provided to the warehouse manager based on the safety stock As, the current stock and the demand estimation of the current order cycle for the target commodity; further, demand estimates for the next order cycle may also be considered. The order recommendation information includes: the order quantity of the target commodities. The warehouse manager here places an order to a supplier (producer) of the target commodity and also places an order to a user (customer or distributor).

Method 100 may be varied with reasonable variations. For example, the method 100 may further include: when the stock quantity of the target class of commodities changes (for example, warehousing or ex-warehousing occurs), whether the current stock quantity is smaller than a stock quantity threshold value related to the safe stock quantity is determined, and when the determination result is yes, an operation of sending a prompt message related to the stock quantity to the mobile terminal is triggered in response to the determination result. In one example, the method 100 may further include: as time progresses, the safety stock is updated with recent order cycles, historical data of order cycles.

The present disclosure also provides an apparatus for an inventory management system. An exemplary description is provided below with reference to fig. 4. FIG. 4 illustrates an exemplary block diagram of an apparatus 400 for an inventory management system according to one embodiment of the present disclosure. The apparatus 400 comprises: first determining section 401, second determining section 403, third determining section 405, and recommending section 407. The first determination unit 401 is configured to: determining, for a target class of merchandise, a representative shipment fluctuation associated with an actual shipment and a fit shipment for each of a plurality of order cycles based on historical data relating to the warehouse in a database of the inventory management system, wherein the representative shipment fluctuation is associated with a difference between the actual shipment and the fit shipment for each of the plurality of order cycles; and the fitted ex-warehouse quantity is determined by a fitting function obtained by fitting actual ex-warehouse quantities for a plurality of order cycles. The second determination unit 403 is configured to: and determining a representative single-day warehouse-in and warehouse-out accumulation upper limit of the target commodities for a plurality of order cycles based on historical data in a database of the inventory management system, wherein the representative single-day warehouse-in and warehouse-out accumulation upper limit is at least associated with the single-day warehouse-out accumulation and the single-day warehouse-in accumulation counted by taking the order cycle as a unit in one order cycle in the plurality of order cycles. The third determining unit 405 is configured to: and determining safety stock aiming at the target class of commodities based on the representative warehouse-out quantity fluctuation and the representative single-day warehouse-in and warehouse-out accumulated difference upper limit. The recommendation unit 407 is configured to: order recommendation information regarding an order for a next order cycle for the target item is provided to the warehouse manager based on the safety stock. The apparatus 400 and the method 100 have a corresponding relationship. Further configuration aspects of the apparatus 400 may be found in the description of the method 100 of the present disclosure.

The present disclosure also provides an apparatus for an inventory management system. An exemplary description is provided below with reference to fig. 5. Fig. 5 illustrates an exemplary block diagram of an apparatus 500 for an inventory management system according to one embodiment of the disclosure. The apparatus 500 comprises: a memory 501 having instructions stored thereon; and one or more processors 503, the one or more processors 503 capable of communicating with the memory to execute the instructions retrieved from the memory, and the instructions cause the one or more processors to: determining a representative ex-warehouse quantity fluctuation associated with an actual ex-warehouse quantity and a fitted ex-warehouse quantity for each order cycle in a plurality of order cycles for a target class of goods based on historical data related to warehouses in a database of an inventory management system; determining representative single-day in-out warehouse accumulated difference upper limits for target commodities for a plurality of order cycles based on historical data in a database of an inventory management system; determining a safety stock for the target commodity based on the representative warehouse-out quantity fluctuation and the representative single-day warehouse-in and warehouse-out accumulated difference upper limit; and providing order recommendation information regarding an order for a next order cycle for the target item to the warehouse manager based on the safety stock; wherein the representative shipment volume fluctuation is associated with a difference between an actual shipment volume and a fitted shipment volume for each of the plurality of order cycles; the fitting ex-warehouse quantity is determined by a fitting function obtained by fitting actual ex-warehouse quantities of a plurality of order periods; and the representative single-day warehouse-in and warehouse-out accumulation upper limit is at least associated with the single-day warehouse-out accumulation and the single-day warehouse-in accumulation counted by taking the order cycle as a unit in one order cycle in the plurality of order cycles. The functionality of the instructions corresponds to the method 100, and thus reference is made to the description of the method 100 for further details.

One aspect of the present disclosure provides a computer-readable storage medium having stored thereon a program whose functions correspond to those of the following method: determining a representative shipment fluctuation associated with an actual shipment and a fit shipment for each of a plurality of order cycles for a target class of merchandise based on historical data relating to the warehouse in a database of the inventory management system; determining representative single-day in-out warehouse accumulated difference upper limits for target commodities for a plurality of order cycles based on historical data in a database of an inventory management system; determining a safety stock for the target commodity based on the representative warehouse-out quantity fluctuation and the representative single-day warehouse-in and warehouse-out accumulated difference upper limit; and providing order recommendation information related to an order of a next order cycle for the target goods to the warehouse manager based on the safety stock; wherein the representative shipment volume fluctuation is associated with a difference between an actual shipment volume and a fitted shipment volume for each of the plurality of order cycles; the fitting ex-warehouse quantity is determined by a fitting function obtained by fitting actual ex-warehouse quantities of a plurality of order periods; and the representative single-day warehouse-in and warehouse-out accumulation upper limit is at least related to the single-day warehouse-out accumulation and the single-day warehouse-in accumulation of one order cycle in the plurality of order cycles, which are counted by taking the order cycle as a unit. Further configuration details of the process may be found in the description of the method 100 of the present disclosure.

Fig. 6 is an exemplary block diagram of an information processing apparatus 600 according to one embodiment of the present disclosure. In fig. 6, a Central Processing Unit (CPU)601 performs various processes in accordance with a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 to a Random Access Memory (RAM) 603. The RAM 603 also stores data and the like necessary when the CPU 601 executes various processes, as necessary.

The CPU 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input/output interface 605 is also connected to the bus 604.

The following components are connected to the input/output interface 605: an input portion 606 including a soft keyboard and the like; an output portion 607 including a display such as a Liquid Crystal Display (LCD) and a speaker; a storage section 608 such as a hard disk; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet, a local area network, a mobile network, or a combination thereof.

A driver 610 is also connected to the input/output interface 605 as necessary. A removable medium 611 such as a semiconductor memory or the like is mounted on the drive 610 as needed, so that the program read therefrom is mounted to the storage section 608 as needed.

The CPU 601 may run a program corresponding to a method applied to the inventory management system.

Aspects of the present disclosure include determining a safety stock for a target class of goods using a representative shipment fluctuation determined by a particular rule and a representative single-day in-out cumulative difference upper bound. The safety stock is determined in a manner different from the conventional method of simply adopting fluctuation, and more factors are considered to determine the safety stock. The beneficial effects of the method, apparatus and storage medium of the present disclosure include at least one of: the inventory holding cost and the stock shortage cost are balanced, and the utilization efficiency of the warehouse is improved.

As described above, according to the present disclosure, a principle of determining a safe stock for a target class of commodities using a representative shipment volume fluctuation and a representative single-day shipment/sale accumulation difference upper limit is provided. It is to be noted that the effects of the scheme of the present disclosure are not necessarily limited to the above-described effects, and any of the effects shown in the present specification or other effects that can be understood from the present specification may be achieved in addition to or instead of the effects described in the preceding paragraphs.

While the invention has been described in terms of specific embodiments thereof, it will be appreciated that those skilled in the art will be able to devise various modifications (including combinations and substitutions of features between the embodiments, where appropriate), improvements and equivalents of the invention within the spirit and scope of the appended claims. Such modifications, improvements and equivalents are also intended to be included within the scope of the present invention.

It should be emphasized that the term "comprises/comprising" when used herein, is taken to specify the presence of stated features, elements, steps or components, but does not preclude the presence or addition of one or more other features, elements, steps or components.

Furthermore, the methods of the embodiments of the present invention are not limited to being performed in the time sequence described in the specification or shown in the drawings, and may be performed in other time sequences, in parallel, or independently. Therefore, the order of execution of the methods described in this specification does not limit the technical scope of the present invention.

Attached notes

The present disclosure includes, but is not limited to, the following schemes.

1. A computer-implemented method for an inventory management system, comprising:

determining, for a target class of merchandise, a representative shipment fluctuation associated with an actual shipment and a fit shipment for each of a plurality of order cycles based on historical data relating to a warehouse in a database of the inventory management system;

determining a representative single-day in-out cumulative difference upper limit for the target class of goods for a plurality of order cycles based on the historical data in the inventory management system's database;

determining a safe stock for the target class of commodities based on the representative ex-warehouse volume fluctuation and the representative single-day ex-warehouse accumulated difference upper limit; and

providing order recommendation information regarding an order for a next order cycle for the target item to a warehouse manager based on the safety stock;

wherein the representative shipment volume fluctuation is associated with a difference between an actual shipment volume and a fit shipment volume for each of the plurality of order cycles;

the fitted ex-warehouse quantity is determined by a fitting function obtained by fitting actual ex-warehouse quantities of the plurality of order periods; and is

The representative single-day warehouse-in and warehouse-out accumulation upper limit is at least related to single-day warehouse-out accumulation and single-day warehouse-in accumulation of one ordering period in the plurality of ordering periods, wherein the single-day warehouse-out accumulation and the single-day warehouse-in accumulation are counted by taking the ordering period as a unit.

2. The method according to supplementary note 1, wherein the fitting is a linear fitting.

3. The method according to supplementary note 1, wherein the fitting is a polynomial fitting.

4. The method according to supplementary note 1, wherein the fitting is a binomial fitting.

5. The method according to supplementary note 1, wherein the representative shipment fluctuation is associated with an average value of absolute values of differences between the actual shipment and the fitted shipment for each of the plurality of order cycles.

6. The method according to supplementary note 1, wherein the representative shipment fluctuation is associated with a standard deviation of a difference between an actual shipment and a fitted shipment for each of the plurality of order cycles.

7. The method according to supplementary note 1, wherein the representative shipment volume fluctuation is associated with a sum of a mean value and a standard deviation;

the average value is an average value of absolute values of differences between actual ex-warehouse quantities and fitted ex-warehouse quantities of each order period in the plurality of order periods; and is provided with

The standard deviation is a standard deviation of a difference between an actual ex-warehouse quantity and a fitted ex-warehouse quantity for each of the plurality of order cycles.

8. The method according to supplementary note 1, wherein the representative shipment fluctuation is associated with a maximum value among differences between the actual shipment and the fitted shipment for each of the plurality of order cycles.

9. The method according to supplementary note 1, wherein each of the plurality of order periods is one week.

10. The method according to supplementary note 1, wherein the representative single-day warehouse entry cumulative difference upper limit is associated with an average value of single-day warehouse entry cumulative sampling differences for each of the plurality of order cycles.

11. The method according to supplementary note 11, wherein the single-day warehousing-in/out accumulation sampling difference for each order period is the maximum value of the difference between the single-day warehousing-in accumulation and the single-day warehousing accumulation counted in units of the order period.

12. The method according to supplementary note 1, wherein,

the representative single-day warehouse-in and warehouse-out accumulated difference upper limit is related to the product of the difference coefficient and the average warehouse-out amount of the single order period of the plurality of order periods; and is provided with

The difference coefficient is the maximum value of the difference between the normalized single-day ex-warehouse accumulation and the normalized single-day in-warehouse accumulation of the order period in the plurality of order periods.

13. The method according to supplementary note 1, wherein the safe stock is a weighted sum of the representative fluctuation in the warehouse-out amount and the representative single-day warehouse-in/out cumulative difference upper limit amount.

14. The method of supplementary note 1, wherein the weight for the weighted sum is determined based on historical inventory data for the target class of merchandise.

15. The method according to supplementary note 1, wherein for the target class of goods, order recommendation information about an order of a next order cycle is provided to the warehouse manager based on the safety stock, the current stock and the demand estimation of the current order cycle.

16. The method according to supplementary note 15, wherein the order recommendation information includes an order amount for a target class of goods.

17. An apparatus for an inventory management system, comprising:

a memory having instructions stored thereon; and

one or more processors in communication with the memory to execute the instructions retrieved from the memory, and the instructions cause the one or more processors to:

determining a representative single-day in-out cumulative difference upper bound for the target class of goods for a plurality of order cycles based on the historical data in the inventory management system's database;

wherein the representative shipment fluctuation is associated with a difference between an actual shipment and a fit shipment for each of the plurality of order cycles;

the fitted ex-warehouse quantity is determined by a fitting function obtained by fitting actual ex-warehouse quantities of the plurality of order periods; and is provided with

The representative single-day warehouse-in and warehouse-out accumulated difference upper limit is at least related to the single-day warehouse-out accumulation and the single-day warehouse-in accumulation of one order period in the plurality of order periods, which are counted by taking the order period as a unit.

18. The apparatus according to supplementary note 17, wherein the representative shipment fluctuation is associated with an average value of absolute values of differences between the actual shipment and the fitted shipment for each of the plurality of order cycles.

19. The apparatus of supplementary note 17, wherein the representative upper limit of the single-day accumulated difference in warehouse entry is associated with an average of the single-day accumulated sampling differences in warehouse entry for each of the plurality of order cycles.

20. A computer-readable recording medium storing a program, the program causing a computer running the program to:

determining a representative shipment fluctuation associated with an actual shipment and a fit shipment for each of a plurality of order cycles for a target class of merchandise based on historical data relating to the warehouse in a database of the inventory management system;

providing order recommendation information related to an order for a next order cycle for the target item to a warehouse manager based on the safe inventory;

the fitting ex-warehouse quantity is determined by a fitting function obtained by fitting actual ex-warehouse quantities of the plurality of order cycles; and is

Claims

2. The method of claim 1, wherein the fitting is a linear fitting.

3. The method of claim 1, wherein the representative shipment fluctuation is associated with an average of absolute values of differences between the actual shipment and the fitted shipment for each of the plurality of order cycles.

4. The method of claim 1, wherein the representative shipment fluctuation is associated with a maximum value in a difference between an actual shipment and a fitted shipment for each of the plurality of order cycles.

5. The method of claim 1, wherein the representative single-day in-out cumulative difference upper bound is associated with an average of single-day in-out cumulative sample differences for each of the plurality of order cycles.

6. The method of claim 5, wherein the single-day ex-warehouse cumulative sampling difference for each order cycle is the maximum value of the difference between the single-day ex-warehouse cumulative and the single-day in-warehouse cumulative counted in units of the order cycle.

7. The method of claim 1 wherein said representative single-day in-out cumulative difference upper bound is associated with a product of a difference coefficient and a single-order-cycle average out-of-stock quantity for said plurality of order cycles; and is

The difference coefficient is the maximum value of the difference between the normalized single-day ex-warehouse accumulation and the normalized single-day in-warehouse accumulation which are counted by taking the ordering period as a unit in one ordering period of the plurality of ordering periods.

8. The method of claim 1, wherein the safety stock is a weighted sum of the representative outbound volume fluctuation and the representative single-day inbound and outbound cumulative difference ceiling.

9. An apparatus for an inventory management system, comprising:

a memory having instructions stored thereon; and

determining, for a target class of goods, a representative shipment fluctuation associated with an actual shipment and a fit shipment for each of a plurality of order cycles based on historical warehouse-related data in a database of the inventory management system;

determining safe stock for the target class of commodities based on the representative ex-warehouse quantity fluctuation and the representative single-day ex-warehouse accumulated difference upper limit; and

10. A computer-readable recording medium storing a program, the program causing a computer running the program to:

determining a representative ex-warehouse quantity fluctuation associated with an actual ex-warehouse quantity and a fitted ex-warehouse quantity for each order cycle in a plurality of order cycles for a target class of goods based on historical data related to warehouses in a database of an inventory management system;