CN111768144A - Product selection method and device for man-machine mixed warehouse - Google Patents
Product selection method and device for man-machine mixed warehouse Download PDFInfo
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Abstract
The embodiment of the invention discloses a method and a device for selecting products for a man-machine mixed warehouse, and relates to the technical field of warehouse logistics. The method comprises the following steps: determining a first class set of a warehouse according to classes of commodities stored in the warehouse; filtering out explosive products and lost products in the first class set, and determining a second class set of the warehouse; calculating the selection coefficient of the commodities in the current second category set according to the daily average sales of the commodities in the current second category set, the planned inventory occupation volume proportion in the automation area and the order splitting index; and selecting the commodities in the current second category set to be stored in the automatic area according to the selection coefficient, the volume and the planned inventory of the automatic area of the commodities in the current second category set. The commodity selection method reduces the commodity order dismantling rate of the manual area and the automatic area of the man-machine mixed warehouse, saves cost, and improves commodity delivery efficiency of the man-machine mixed warehouse.
Description
Technical Field
The invention relates to the technical field of warehouse logistics, in particular to a method and a device for selecting products in a man-machine mixed warehouse.
Background
Currently, a warehouse management mode of man-machine mixing is adopted for part of warehouse management, namely, a manual area and an automatic area exist in one warehouse. In the manual area, workers perform operations such as sorting, carrying, packing, delivery and the like on commodities. In the automation area, a goods-to-person or goods-to-mechanical arm mode based on an Automatic Guided Vehicle (AGV) or a multi-deck shuttle may be adopted, goods are stored in corresponding storage media (shelves or bins), and the storage media are transported to a workstation through the AGV or the multi-deck shuttle and a transport line for manual or mechanical picking of the goods.
In the related art, the problem of commodity selection in a man-machine hybrid warehouse management mode is solved, namely, commodities to be warehoused in a man-machine hybrid warehouse are selected to be stored in an automatic area, and commodities are stored in a manual area. The warehouse can adopt a manual commodity selection mode, and the workers select commodities stored in the automatic area according to a certain strategy, for example, all commodities under a certain brand are selected to be placed in the automatic area, or commodities with daily average sales in a certain range are selected to be placed in the automatic area. Due to subjective deviation and limitation of manual selection, the error rate of the mode of manual selection is high, and the commodity bill dismantling rate of a manual area and an automatic area in a warehouse is high. The warehouse can also adopt a system automatic selection mode, namely the system automatically selects commodities to be placed in an automatic area by taking the lowest order splitting rate as a target. Because the automatic selection of the system does not aim at the different characteristics of the manual area and the automatic area, the commodity list dismantling rate of the manual area and the automatic area in the warehouse is high.
Disclosure of Invention
In order to solve the problem of high order removal rate of commodities in a manual area and an automatic area in a warehouse in the related art, the embodiment of the invention provides a method and a device for selecting commodities in a man-machine mixed warehouse, which reduce the order removal rate of the commodities in the manual area and the automatic area of the man-machine mixed warehouse, save the cost and improve the commodity delivery efficiency of the man-machine mixed warehouse.
According to an aspect of the present invention, there is provided an item selection method for an automated-human hybrid warehouse, the warehouse including a manual area and an automation area, the item selection method including:
determining a first class set of the warehouse according to the classes of the commodities stored in the warehouse;
filtering out explosive products and lost products in the first product set, and determining a second product set of the warehouse;
calculating the selection coefficient of the commodities in the current second category set according to the daily average sales volume of the commodities in the current second category set, the planned inventory occupation volume proportion in the automation area and the order splitting index; and
and selecting the commodities in the current second category set to be stored in the automatic area according to the selection coefficient and the volume of the commodities in the current second category set and the planned inventory amount of the automatic area.
Preferably, before the filtering out the explosives and the stalked products in the first class set and determining the second class set of the warehouse, the product selection method further includes: determining explosive products in the first product set, then
The determining explosives in the first class set comprises:
dividing a first time period into a plurality of second time periods according to historical order information of commodities in the first class set in the first time period, and counting the ex-warehouse quantity of each commodity in each second time period;
calculating a first number of each commodity in the second time period corresponding to the condition that the warehouse-out quantity of each commodity in the second time period is greater than or equal to the product of the standard code disc quantity of each commodity and a first configuration parameter;
calculating a second number of each commodity in the second time period corresponding to the condition that the ex-warehouse quantity of each commodity in the second time period is greater than zero;
and if the ratio of the first number to the second number is greater than or equal to a second configuration parameter, the corresponding commodity is an explosive product.
Preferably, before the filtering out the explosives and the stalked products in the first class set and determining the second class set of the warehouse, the product selection method further includes: determining the lost article in the first article set, then
The determining a merchantable item in the first set of items comprises:
calculating the average daily sales volume of each commodity according to historical order information of commodities in the first class set in a third time period;
and if the daily average sales of the commodities in the first commodity set is less than or equal to a third configuration parameter, the corresponding commodity is a lost commodity.
Preferably, after the explosive and the lost sales in the first class set are filtered and the second class set of the warehouse is determined, the product selection method further includes: calculating the planned inventory occupancy volume proportion of each commodity in the second commodity set in the automation area
Said calculating said projected inventory occupancy volume proportion for each item in said second set of items in said automation zone comprises:
calculating the projected inventory amount of the automation zone for each item in the second set of items;
calculating the planned inventory volume fraction based on the planned inventory amount, the volume, and the available storage space of the automation zone for each item in the second set of items.
Preferably, the calculating the selection coefficient of the commodities in the current second category set according to the average daily sales of the commodities in the current second category set, the planned inventory occupation volume proportion in the automation area and the order splitting index comprises:
calculating the order splitting index of each commodity in the current second class set, then
Said calculating said singleton index for each commodity in said current second set of grades comprises:
selecting a historical order including the commodities in the current second class set in a fourth time period, and taking the historical order as an order set;
taking the class of the commodity contained in each historical order in the order set as a third class set of each historical order;
calculating the order splitting index of each commodity in the current second class set according to the order set and the third class set of each historical order.
Preferably, if the initial value of the accumulated volume of the selected commodities in the automation area is zero and the initial value of the fourth category set consisting of the categories of the commodities selected to be stored in the automation area is null, the accumulated volume of the selected commodities in the automation area is zero
The selecting the commodities in the current second category set to be stored in the automation area according to the selection coefficient and the volume of the commodities in the current second category set and the planned inventory amount of the automation area comprises:
selecting the commodity with the highest selection coefficient corresponding to the commodities which are not stored in the automation area in the current second category set as a first commodity to be stored currently;
adding the current accumulated volume and the total volume of the first commodity of the planned inventory amount;
comparing the volume of the addition operation with the size of the available storage space of the automation region.
Preferably, the selecting the commodities in the current second category set to be stored in the automation area according to the selection coefficient, the volume and the planned inventory amount of the automation area of the commodities in the current second category set further comprises:
if the volume sum is larger than the available storage space, deleting the first commodity from the current second category set, and judging whether the updated second category set is empty or not;
if the updated second category set is empty, the commodities in the current fourth category set are used as the selected commodities needing to be stored in the automatic area;
if the updated second category set is not empty, recalculating the order splitting index and the selection coefficient of the commodities in the updated second category set, and reselecting the commodities in the updated second category set to be stored in the automation area.
Preferably, the selecting the commodities in the current second category set to be stored in the automation area according to the selection coefficient, the volume and the planned inventory amount of the automation area of the commodities in the current second category set further comprises:
if the volume sum is less than or equal to the available storage space, adding the first commodity into a current fourth category set;
searching a historical order containing the first commodity in the order set, and deleting the first commodity from the third class set corresponding to the historical order;
deleting the historical order from the order set that the third category set is empty.
Preferably, the selecting the commodities in the current second category set to be stored in the automation area according to the selection coefficient, the volume and the planned inventory amount of the automation area of the commodities in the current second category set further comprises:
deleting the first commodity from the current second category set, and judging whether the updated second category set is empty or not;
if the updated second category set is empty, taking the commodities in the current fourth category set as the selected commodities needing to be stored in the automation area;
if the updated second category set is not empty, recalculating the order splitting index and the selection coefficient of the commodities in the updated second category set, and reselecting the commodities in the updated second category set to be stored in the automation area.
According to another aspect of the present invention, there is provided an option device for an automated hybrid warehouse, the warehouse including a manual area and an automation area, the option device comprising:
a first determination unit configured to determine a first category set of the warehouse according to categories of commodities stored in the warehouse;
a second determining unit configured to perform filtering out explosives and sluggish products in the first class set, and determine a second class set of the warehouse;
a first calculating unit, configured to calculate a selection coefficient of the commodities in the current second category set according to the daily average sales volume of the commodities in the current second category set, the planned inventory occupation volume proportion in the automation area and a dissembling index; and
a selection unit configured to perform selecting the commodities in the current second category set to be deposited into the automation area according to the selection coefficient, the volume and the planned inventory amount of the automation area of the commodities in the current second category set.
According to still another aspect of the present invention, there is provided a selection control apparatus for a human-machine mixing warehouse, including: a processor; a memory for storing the processor-executable instructions; wherein the processor is configured to execute the above-described selection method for the human-machine mixing warehouse.
According to yet another aspect of the present invention, there is provided a computer-readable storage medium, characterized in that the computer-readable storage medium stores computer instructions which, when executed, implement the method for selecting items for an ergonomic hybrid warehouse as described above.
According to a further aspect of the present invention, there is provided a computer program product comprising a computer program product, the computer program comprising program instructions which, when executed by a mobile terminal, cause the mobile terminal to perform the steps of the above-described method for selection of a man-machine hybrid warehouse.
One embodiment of the present invention has the following advantages or benefits:
and filtering out explosive products and lost products in the first class set, and determining a second class set of the warehouse. And calculating the selection coefficient of the commodities in the current second class set according to the daily average sales volume of the commodities in the current second class set, the planned inventory occupation volume ratio in the automation area and the order splitting index. And selecting the commodities in the current second category set to be stored in the automatic area according to the selection coefficient, the volume and the planned inventory of the automatic area of the commodities in the current second category set. The daily average sales volume and volume of the commodities, the order removing indexes in the automatic area and the manual area, the planned inventory in the automatic area and the planned inventory occupation volume proportion in the automatic area are used as the basis of selecting commodities, the selection coefficient of the commodities in the current second class set is calculated in real time, the selection strategy is adjusted, and the order removing rate of the commodities in the manual area and the automatic area in the warehouse is reduced. Meanwhile, manual selection is not needed, and subjective deviation and limitation of workers are avoided.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent from the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:
fig. 1 shows a flow chart of a product selection method for an automated mixed warehouse according to an embodiment of the present invention.
Fig. 2 shows a flow chart of a product selection method for the man-machine mixing warehouse according to an embodiment of the invention.
Fig. 3 shows a flow chart of a product selection method for the man-machine mixing warehouse according to an embodiment of the invention.
Fig. 4 is a schematic structural diagram of an option device for an in-person mixing warehouse according to an embodiment of the present invention.
Fig. 5 is a schematic structural diagram of an option device for an in-person mixing warehouse according to an embodiment of the invention.
Fig. 6 is a schematic structural diagram of an option device for an in-person mixing warehouse according to an embodiment of the present invention.
Fig. 7 is a schematic structural diagram of an option device for an in-person mixing warehouse according to an embodiment of the present invention.
Fig. 8 is a schematic structural diagram of an option device for an in-person mixing warehouse according to an embodiment of the present invention.
Fig. 9 is a schematic structural diagram of an option control device for an automated mechanical mixing warehouse according to an embodiment of the present invention.
Detailed Description
The present invention will be described below based on examples, but the present invention is not limited to only these examples. In the following detailed description of the present invention, certain specific details are set forth. It will be apparent to one skilled in the art that the present invention may be practiced without these specific details. Well-known methods, procedures, and procedures have not been described in detail so as not to obscure the present invention. The figures are not necessarily drawn to scale.
Aiming at the commodity selection problem in the man-machine mixed warehouse management mode, the manual area and the automatic area of the man-machine mixed warehouse have different working characteristics. In the manual area, the workers select the commodities stored in the automatic area according to a certain strategy, so that the flexibility is high, and the cost is high in the long run. The automated area adopts a mode of goods-to-people or goods-to-mechanical arm based on an Automatic Guided Vehicle (AGV) or a multi-layer shuttle, so that the overall operation cost is low in the long term, but the flexibility and the flexibility are poor.
Particularly, for some explosive products or general large commodities which are delivered from the warehouse, the manual area can be used for delivering the commodities in a whole supporting mode, and the efficiency is high. For some lost commodities, if the lost commodities are placed in an automation area, the carrying cost of one storage medium out of the warehouse is high (the storage medium is more likely to be stored in a remote position because of the lost commodities), the quantity of commodities which can be picked is small, and the efficiency is low. Since the automation area has a low operation cost in the long term, the commodities should be stored in the automation area as much as possible. Aiming at different characteristics of a manual area and an automatic area, the invention provides a product selecting method for a man-machine mixed warehouse to reduce the rate of order splitting, namely the rate of orders which cannot be completely selected in the same area (the manual area or the automatic area), thereby improving the commodity delivery efficiency of the man-machine mixed warehouse.
Fig. 1 is a schematic flow chart of a product selection method for an automated mechanical mixing warehouse according to an embodiment of the invention. The man-machine hybrid warehouse comprises a manual area and an automatic area, and specifically comprises the following steps:
in step S110, a first category set of the warehouse is determined according to categories of the commodities stored in the warehouse.
At present, when an e-commerce plans storage of warehouse commodities, the common method is as follows: the commodities of the same category are put in the same warehouse as much as possible. The categories can be classified into multiple levels (e.g., primary category, secondary category, tertiary category, etc.) according to different services. And e, as primary products: a household appliance; secondary categories under household appliances may include: televisions, air conditioners, washing machines, refrigerators, kitchen and bathroom major power supplies, kitchen minor power supplies, household appliances, personal health care, home video and audio and imported appliances; the tv down tertiary categories may include: joint venture brand, domestic brand, internet brand; the three-level category under the air conditioner can comprise a wall-mounted air conditioner, a cabinet air conditioner, a central air conditioner and air conditioner accessories; the three-level product under the washing machine can comprise drum washing machine, washing and drying integrated machine, impeller washing machine, mini washing machine and washing machine accessories.
In this step, a first category set of the warehouse is determined according to categories of the commodities stored in the warehouse, where the categories may be a second category and a third category. For example, a warehouse is used for storing household appliances, and determining a first class set of the warehouse according to the classes of goods stored in the warehouse includes: television, air conditioner, washing machine, refrigerator, kitchen large electric appliance, kitchen small electric appliance, life electric appliance, personal health care, household video and audio and imported electric appliance.
In step S120, explosive and lost goods in the first category set are filtered out, and a second category set of the warehouse is determined.
In this step, explosive and obsolete products in the first class set are filtered out, and a second class set of the warehouse is determined. For example, if the tv and the air conditioner are explosive money and the living electrical appliances are lost goods in the first category set of the warehouse, the second category set of the warehouse includes: washing machine, refrigerator, kitchen large electric appliance, kitchen small electric appliance, personal health care, household video and audio, and imported electric appliance.
In step S130, a selection coefficient of the commodities in the current second category set is calculated according to the average daily sales of the commodities in the current second category set, the planned inventory occupation volume ratio in the automation area, and the order splitting index.
In this step, the current second category set includes: taking the commodity 1, the commodity 2 and the commodity 3 as examples, the selection coefficients of the commodity 1, the commodity 2 and the commodity 3 are respectively calculated according to the daily average sales volume of the commodity 1, the planned inventory occupation volume proportion and the order splitting index in the automation area, the daily average sales volume of the commodity 2, the planned inventory occupation volume proportion and the order splitting index in the automation area, and the daily average sales volume of the commodity 3, the planned inventory occupation volume proportion and the order splitting index in the automation area.
In step S140, the commodities in the current second category set are selected to be stored in the automation area according to the selection coefficient and volume of the commodities in the current second category set and the planned inventory amount of the automation area.
In this step, the current second category set includes: the commodities 1, 2, and 3 are exemplified, and the commodities among the commodities 1, 2, and 3 are selected to be stored in the automation area according to the selection coefficient, volume, and planned inventory of the automation area of the commodity 1, the selection coefficient, volume, and planned inventory of the automation area of the commodity 2, the selection coefficient, volume, and planned inventory of the automation area of the commodity 3, and the selection coefficient, volume, and planned inventory of the automation area of the commodity 3.
According to the embodiment of the invention, explosive products and lost sales products in the first class set are filtered, and the second class set of the warehouse is determined. And calculating the selection coefficient of the commodities in the current second class set according to the daily average sales of the commodities in the current second class set, the planned inventory occupation volume proportion in the automation area and the order splitting index. And selecting the commodities in the current second category set to be stored in the automatic area according to the selection coefficient and the volume of the commodities in the current second category set and the planned inventory of the automatic area. The daily average sales volume and the volume of the commodities, the order removing indexes in the automatic area and the manual area, the planned inventory in the automatic area and the planned inventory occupation volume ratio in the automatic area are used as the basis of selecting commodities, the selection coefficient of the commodities in the current second class set is calculated in real time, the selection strategy is adjusted, and the order removing rate of the commodities in the manual area and the automatic area in the warehouse is reduced. Meanwhile, manual selection is not needed, and subjective deviation and limitation of workers are avoided.
Fig. 2 is a schematic flow chart of a product selection method for the man-machine hybrid warehouse according to an embodiment of the present invention. The method specifically comprises the following steps:
in step S2010, a first category set of the warehouse is determined according to categories of the commodities stored in the warehouse.
Step 2010 corresponds to step S110 in fig. 1, and will not be described again here.
In step S2020, explosive and obsolete products in the first set of products are filtered out, and a second set of products in the warehouse is determined.
In this step, explosive items in the first set of items are determined.
Specifically, according to the historical order information of the commodities in the first class set in the first time period (for example, 1 week in the past), the first time period is divided into a plurality of second time periods (for example, the 1 week in the past is divided into 24 × 7 × 2 second time periods, and each second time period is 30 minutes), and the ex-warehouse quantity of each commodity s in each second time period is counted
Where m represents a certain second time period.
Calculating the delivery amount of each commodity s in the second time period
The standard code disc quantity (namely the number of the commodities S stored on the 1 tray at most) S of each commodity S is more than or equal tosWith a first configuration parameter thetasOf (i.e. the product of (c))
θs∈[0,1]) What is needed isCorresponding to the first number of second time segments for each type of article s, N1. First configuration parameter thetasIt can be set by the staff as desired, for example 0.5. Calculating the delivery amount of each commodity s in the second time period
Greater than zero (i.e. case)
) A second number N2 of a second time period for each corresponding commodity s, wherein if the ratio of the first number N1 to the second number N2 is greater than or equal to a second configuration parameter pi, the corresponding commodity s is an explosive product, wherein the second configuration parameter pi, pi ∈ [0,1]And can be set in advance by a worker according to needs, for example, 0.75.
A stalemate in the first set of items is determined.
Specifically, the average daily sales of each commodity is calculated according to the historical order information of the commodities in the first class set in the third time period (such as the past T days) by considering the sales situation of the third time period. The formula for calculating the average daily sales for each commodity is:
wherein the content of the first and second substances,
the average daily sales of the goods s, T the number of days in the third time period,
sales of the commercial product s on the t-th day are shown.
Where t is taken as
May be weighted, in some embodiments, such that
Is set to other values, e.g. 1, i.e. equation (1) can be transformed into:
wherein the content of the first and second substances,
the average daily sales of the goods s, T the number of days in the third time period,
sales of the commercial product s on the t-th day are shown.
If the average daily sales of the items s in the first set of items
Less than or equal to the third configuration parameter ξ (i.e., the
) The corresponding product s is a lost product, wherein ξ>0, for example, ξ ═ 1.
And filtering out explosive products and lost products in the first class set, and determining a second class set S of the warehouse.
In step S2030, the planned inventory occupancy volume proportion of each item in the second category set in the automation zone is calculated.
In this step, the planned inventory quantity Q of each of the commodities S in the second category set S in the automation area is calculateds. Calculating the planned inventory quantity QsThe formula of (1) is:
wherein the content of the first and second substances,
is the daily average sales of the commodity s, θTThe number of days the goods s are kept in safety in the automation area,
the total amount of the commodities s to be warehoused is obtained. ThetaTCan be set by the staff in advance as required, for example, 7 days.
According to the planned inventory quantity Q of each commodity S in the second class set SsVolume VsAnd available storage space V of automation areamaxCalculating the planned inventory occupancy volume ratio Rs. Calculating the planned inventory occupancy volume ratio RsThe formula of (1) is:
wherein R issFor the planned inventory occupancy volume proportion, Q, of the goods S in the second set of items SsFor the planned stock of goods s in the automation zone, VsVolume of the commodity s, VmaxIs the available storage space of the automation area.
In step S2040, the singulation index for each item in the current second category set is calculated.
In this step, the historical orders including the current items in the second category set S in the fourth time period (for example, the past 1 month) are selected, and the related historical orders are used as the order set O. Using the product class of each historical order in the order set O as a third class set S of each historical ordero. For example, an item to be purchased for a historical order includes: 1 joint-venture brand television, 1 wall-hanging air conditioner, 1 air conditioner accessory, 1 roller washing machine and 1 washing machine accessory, then the third category set S of the historical orderoThe method comprises the following steps: televisions, air conditioners, and washing machines.
According to the order set O and a third item set S of each historical orderoCalculating the order splitting index c of each commodity S in the current second class set Ss. Calculating the order splitting index c of each commodity S in the current second class set SsThe formula of (1) is:
wherein, csIs the index of splitting the order of the commodity S in the second category set S, | O | is the number of the historical orders in the order set O, | SoiI is the third item set S of the ith historical order in the order set OoiNumber of types of commodities contained, | Soi\ S | is a third set S of categories for the ith historical order in the order set OoiThe number of the product types included in the product S removed is S ∈ SoiThen | Soi\s|＝|Soi1 if
Then
The | O | in the formula (5) is the number of historical orders in the current order set O, | SoiI is a third item set S of the ith historical order in the current order set OoiNumber of items of the included commodities. If the order set O in step S2080, the third category set S of the historical orders in the order set OoIf the order is updated, the updated order set O and a third class set S of historical orders in the order set O are usedoSubstituting into equation (5). c. CsIf the second category set S is updated in step S2090, the updated second category set S is the order splitting index of the goods S obtained by the formula (5).
In step S2050, a selection coefficient of each product in the current second category set is calculated according to the daily average sales volume of each product in the current second category set, the planned inventory occupancy volume proportion in the automation area, and the order splitting index.
In this step, the daily average sales of each commodity S in the current second category set S is calculated
Planned inventory occupancy volume ratio R in an automation zonesAnd tear single index csCalculating the selection coefficient k of each commodity S in the current second class set Ss. Calculating the selection coefficient k of each commodity S in the current second class set SsThe formula of (1) is:
wherein k issSelection coefficients for the products S of the current second set S, csIs the order splitting index of the commodity s,
is the daily average sales of the commodity s, RsThe planned inventory occupancy volume fraction for the item s.
If the second category set S is updated in step S2090, the selection coefficient of the goods in the updated second category set S is calculated by equation (6).
In step S2060, the commodity with the highest selection coefficient corresponding to the commodities which are not stored in the automation area in the current second category set is selected as the first commodity to be currently stored; and adding the current accumulated volume and the total volume of the first commodity of the planned inventory amount.
The initial value of the fourth category set omega consisting of the initial value of the accumulated volume V of the selected commodities in the automatic area of the warehouse is zero and the categories of the commodities selected to be stored in the automatic area of the warehouse is
In this step, the product with the highest selection coefficient among the products not stored in the automation area in the current second category group S is selected as the first product S1 to be currently stored. Comparing the current accumulated volume V to the planned inventory Qs1Of the first article s1Addition of products, i.e.
V’＝V+Vs1×Qs1(7)。
Wherein V' is the current accumulated volume V and the planned inventory Qs1The sum of the volumes, V, of the total volume of the first commercial product s1s1Volume of the first commodity s1 currently to be stored, Qs1Is the planned inventory amount of the first commodity s1 to be currently stored.
In step S2070, the volume of the addition and the size of the available storage space of the automation zone are compared. If the volume sum is less than or equal to the available storage space, then step S2080 is performed. If the volume sum is greater than the available memory space, then step S2090 is performed.
In this step, the sum V' of the volumes of the addition is compared with the available storage space V of the automation zonemaxThe size of (2). If V' is ≦ VmaxThen step S2080 is performed. If V'>VmaxThen, step S2090 is performed.
In step S2080, adding the first commodity into the current fourth category set; searching a historical order containing the first commodity in the order set, and deleting the first commodity from the third class set corresponding to the historical order; deleting the historical order from the order set that the third category set is empty.
In this step, the first commodity s1 to be currently stored is added to the current fourth category set Ω. Searching a historical order containing the first commodity S1 in the order set O, and selecting the first commodity S1 from a third class set S corresponding to the historical orderoIs deleted. Collecting the third class SoIs composed of
The history order is deleted from the order set O. After step S2080 is executed, step S2090 is executed.
In step S2090, the first item is deleted from the current second category set, and it is determined whether the updated second category set is empty. If the updated second set of categories is empty, step S2100 is executed. If the updated second category set is not empty, go to step S2040.
In this step, the first commodity S1 is deleted from the current second commodity set S, and it is determined whether or not the updated second commodity set S is
If the updated second class set S is
Step S2100 is performed. If the updated second class set S is not
Step S2040 is executed.
In step S2100, the items in the current fourth category set are selected as items to be stored in the automation area.
In this step, the items in the current fourth category set Ω are deposited as selected items to the automation area.
Repeating the steps S2040 to S2100, and when the order set O and a third item set S corresponding to the historical orders in the order set O are adoptedoAnd when the second category set S is updated, calculating the order splitting index and the selection coefficient of each commodity in the current second category set S through formulas (5) and (6) by utilizing the updated data in real time, and realizing that the commodities are selected from the current second category set S and stored in the automatic area of the warehouse.
According to the embodiment of the invention, when the order set and the third class set and the second class set corresponding to the historical orders in the order set are updated, the updated data are used in real time to calculate the order splitting index and the selection coefficient of each commodity in the current second class set, so that the commodity is selected from the current second class set to be stored in the automatic area of the warehouse, the information such as the daily average sales volume, the volume and the planned stock quantity of the commodity and the information such as the planned stock occupation volume ratio and the available storage space of the automatic area of the warehouse for a certain commodity are used as the basis for selecting the commodity, the order splitting rate and the cost of the commodity in the manual area and the automatic area of the warehouse are reduced, and the warehouse-out efficiency of the commodity in the warehouse is improved.
In addition, explosive products and lost products in the first product set are filtered, the second product set of the warehouse is determined, and products are selected by the second product set, so that the workload of the product selection method in the embodiment of the application is reduced.
Fig. 3 is a flow chart of an item selection method for the man-machine mixing warehouse according to an embodiment of the invention. The method specifically comprises the following steps:
in step S3010, a first category set of the warehouse is determined based on categories of the commodities stored in the warehouse.
Step S3010 is identical to step S110 in fig. 1, and will not be described here.
In step S3020, explosives and slugs in the first set of classes are determined.
In step S3030, the planned inventory occupancy volume proportion of each item in the first set of items in the automation zone is calculated.
In step S3040, the dissembling index of each product in the current first set of products is calculated.
In step S3050, a selection coefficient of each commodity in the current first class set is calculated according to a daily average sales volume of each commodity in the current first class set, a planned inventory occupancy volume proportion in the automation region, and a dissembling index. For the selection coefficients of the explosive and the obsolete products in the current first class set, the corresponding selection coefficients can be multiplied by a certain sales weight between 0 and 1 (i.e. the selection coefficients are discounted). For example, the weight of sales for explosives is 1 and the weight of sales for sluggish is 0.
In step S3060, selecting a product with the highest selection coefficient from the products that are not stored in the automation area in the current first product set as a first product to be stored; and adding the current accumulated volume and the total volume of the first commodity of the planned inventory amount.
In step S3070, the volume of the addition and the size of the available memory space of the automation area are compared. If the volume sum is less than or equal to the available storage space, then step S2080 is performed. If the volume sum is greater than the available memory space, then step S2090 is performed.
In step S3080, adding the first commodity into a current fourth category set; searching a historical order containing the first commodity in the order set, and deleting the first commodity from the third class set corresponding to the historical order; deleting the historical order from the order set that the third category set is empty. After the execution of step S3080, step S2090 is executed.
In step S3090, the first product is deleted from the current first product group, and it is determined whether the updated first product group is empty. If the updated first set of categories is empty, step S2100 is performed. If the updated first class set is not empty, step S2040 is executed.
In step S3100, the items in the current fourth category group are deposited as selected items to be placed in the automation area.
Fig. 4 is a schematic structural diagram of an option device for an automated mechanical mixing warehouse according to an embodiment of the present invention. The warehouse includes a manual area and an automation area. As shown in fig. 4, the selecting apparatus for the man-machine mixing warehouse includes: a first determining unit 410, a second determining unit 420, a first calculating unit 430 and a selecting unit 440.
A first determining unit 410 configured to perform determining a first category set of the warehouse according to categories of the goods stored in the warehouse.
A second determining unit 420 configured to perform filtering out explosives and stalactites in the first class set, and determine a second class set of the warehouse.
A first calculating unit 430, configured to calculate a selection coefficient of the goods in the current second category set according to the daily average sales volume of the goods in the current second category set, the planned inventory occupation volume proportion in the automation area and the inventory splitting index.
A selecting unit 440 configured to perform selecting the goods in the current second category set to be deposited into the automation area according to the selection coefficient, the volume and the planned inventory amount of the automation area of the goods in the current second category set.
Fig. 5 is a schematic structural diagram of an option device for an in-person mixing warehouse according to an embodiment of the present invention. As shown in fig. 5, the selecting apparatus for the human-machine mixing warehouse includes: a first determining unit 510, a third determining unit 520, a fourth determining unit 530, a second determining unit 540, a fifth calculating unit 550, a first calculating unit 560, and a selecting unit 570.
A first determining unit 510 configured to determine a first category set of the warehouse according to categories of the goods stored in the warehouse.
A third determining unit 520 configured to perform determining explosives in the first set of classes.
A fourth determining unit 530 configured to perform determining a late item in the first set of items.
A second determining unit 540 configured to perform filtering out explosives and stalactites in the first class set, and determine a second class set of the warehouse.
A fifth calculating unit 550 configured to perform calculating the planned inventory occupancy volume proportion of each item in the second category set in the automation zone.
A first calculating unit 560 configured to calculate a selection coefficient of the goods in the current second category set according to the daily average sales volume of the goods in the current second category set, the planned inventory occupation volume proportion in the automation area and the inventory splitting index.
A selecting unit 570 configured to perform selecting the goods in the current second category set to be deposited into the automation area according to the selection coefficient, the volume and the planned inventory amount of the automation area of the goods in the current second category set.
Fig. 6 is a schematic structural diagram of an option device for an in-person mixing warehouse according to an embodiment of the present invention. As shown in fig. 6, the third determining unit 520 includes: a counting unit 521, a second calculating unit 522, a third calculating unit 523, and a first judging unit 524.
The counting unit 521 is configured to perform dividing a first time period into a plurality of second time periods according to historical order information of the commodities in the first class set in the first time period, and counting the ex-warehouse quantity of each commodity in each second time period.
A second calculating unit 522 configured to perform calculation of a first number of the second time period of each commodity corresponding to a case where the warehouse-out amount of each commodity in the second time period is greater than or equal to a product of a standard code disc amount of each commodity and a first configuration parameter.
The third calculating unit 523 is configured to calculate a second number of the second time period of each commodity corresponding to a case where the delivery amount of each commodity in the second time period is greater than zero.
The first judging unit 524 is configured to execute that if the ratio of the first number to the second number is greater than or equal to a second configuration parameter, the corresponding commodity is an explosive product.
Fig. 7 is a schematic structural diagram of an option device for an in-person mixing warehouse according to an embodiment of the present invention. As shown in fig. 7, the fourth determining unit 530 includes: fourth calculating section 531 and second judging section 532.
A fourth calculating unit 531 configured to calculate the average daily sales amount of each commodity according to historical order information of commodities in the first category set in a third time period.
A second determination unit 532 configured to perform that if the daily average sales amount of the commodities in the first commodity set is less than or equal to a third configuration parameter, the corresponding commodity is a lost commodity.
Fig. 8 is a schematic structural diagram of an option device for an in-person mixing warehouse according to an embodiment of the present invention. As shown in fig. 8, the fifth calculation unit 550 includes: a sixth calculation unit 551 and a seventh calculation unit 552.
A sixth calculating unit 551 configured to perform calculating the planned inventory amount of the automation area of each commodity in the second set of grades.
A seventh calculating unit 552 configured to perform calculating the planned inventory volume proportion according to the planned inventory amount, the volume and the available storage space of the automation zone for each item in the second set of categories.
Fig. 9 is a configuration diagram of an option control apparatus for an in-person mixing warehouse according to an embodiment of the present invention. The apparatus shown in fig. 9 is only an example and should not be used to limit the scope of the invention.
Referring to fig. 9, the apparatus includes a processor 910, a memory 920, and an input-output device 930 connected by a bus. Memory 920 includes Read Only Memory (ROM) and Random Access Memory (RAM), and various computer instructions and data required to perform system functions are stored in memory 920 and read by processor 910 from memory 920 to perform various appropriate actions and processes. An input/output device including an input portion of a keyboard, a mouse, and the like; an output section including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section including a hard disk and the like; and a communication section including a network interface card such as a LAN card, a modem, or the like. The memory 920 also stores computer instructions to perform the operations specified by the selection method for the human-machine hybrid warehouse according to the embodiment of the present invention.
Accordingly, embodiments of the present invention provide a computer readable storage medium storing computer instructions that, when executed, implement the operations specified in the above-described method for selecting items for a human-computer hybrid warehouse.
Correspondingly, the embodiment of the invention also provides a computer program product, which comprises a computer program, wherein the computer program comprises program instructions, and when the program instructions are executed by the mobile terminal, the mobile terminal is enabled to execute the steps of the product selecting method for the man-machine mixed warehouse.
The flowcharts and block diagrams in the figures and block diagrams illustrate the possible architectures, functions, and operations of the systems, methods, and apparatuses according to the embodiments of the present invention, and may represent a module, a program segment, or merely a code segment, which is an executable instruction for implementing a specified logical function. It should also be noted that the executable instructions that implement the specified logical functions can be recombined to create new modules and program segments. Accordingly, the blocks of the drawings, and the order of the blocks, are provided to better illustrate the processes and steps of the embodiments and should not be taken as limiting the invention itself.
The above description is only a few embodiments of the present invention, and is not intended to limit the present invention, and various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (13)
1. A method of selecting items for a human-machine hybrid warehouse, the warehouse comprising a manual area and an automated area, the method of selecting items comprising:
determining a first class set of the warehouse according to the classes of the commodities stored in the warehouse;
filtering out explosive products and lost products in the first class set, and determining a second class set of the warehouse;
calculating the selection coefficient of the commodities in the current second category set according to the daily average sales of the commodities in the current second category set, the planned inventory occupation volume proportion in the automation area and the order splitting index; and
and selecting the commodities in the current second category set to be stored in the automatic area according to the selection coefficient and the volume of the commodities in the current second category set and the planned inventory amount of the automatic area.
2. The method of selecting as claimed in claim 1 wherein said filtering out explosives and losers in said first set of categories and prior to determining said second set of categories for said warehouse, said method further comprises: determining explosive articles in the first article set, then
The determining explosives in the first class set comprises:
dividing a first time period into a plurality of second time periods according to historical order information of commodities in the first class set in the first time period, and counting the ex-warehouse quantity of each commodity in each second time period;
calculating a first number of each commodity in the second time period corresponding to the condition that the warehouse-out quantity of each commodity in the second time period is greater than or equal to the product of the standard code disc quantity of each commodity and a first configuration parameter;
calculating a second number of each commodity in the second time period corresponding to the condition that the ex-warehouse quantity of each commodity in the second time period is greater than zero;
and if the ratio of the first number to the second number is greater than or equal to a second configuration parameter, the corresponding commodity is an explosive product.
3. The method of selecting as claimed in claim 2 wherein said filtering out explosives and losers in said first set of categories and prior to determining said second set of categories for said warehouse, said method further comprises: determining a lost article in the first set of articles, then
The determining a merchantable item in the first set of items comprises:
calculating the average daily sales volume of each commodity according to historical order information of commodities in the first class set in a third time period;
and if the daily average sales volume of the commodities in the first commodity set is less than or equal to a third configuration parameter, the corresponding commodities are lost commodities.
4. A method of selecting a commodity according to claim 3, wherein said filtering out explosives and stalactites from said first set of commodities, and after determining said second set of commodities for said warehouse, said method of selecting a commodity further comprises: calculating the planned inventory occupancy volume proportion of each commodity in the second category set in the automation area
Said calculating said planned inventory occupancy volume proportion for each item in said second set of items in said automation zone comprises:
calculating the projected inventory amount of the automation zone for each item in the second set of items;
calculating the planned inventory volume proportion according to the planned inventory amount, the volume and the available storage space of the automation area of each commodity in the second category set.
5. The method of selecting as claimed in claim 1, wherein said calculating selection factors for the items in the current second set of categories based on the average daily sales of the items in the current second set of categories, the projected inventory occupancy volume fraction in the automation zone, and the order splitting index comprises:
calculating the order splitting index of each commodity in the current second class set, then
Said calculating said singleton index for each commodity in said current second set of categories comprises:
selecting a historical order including the commodities in the current second class set in a fourth time period, and taking the historical order as an order set;
taking the class of the commodity contained in each historical order in the order set as a third class set of each historical order;
and calculating the order splitting index of each commodity in the current second class set according to the order set and the third class set of each historical order.
6. A method of selecting items according to claim 5, wherein the initial value of the cumulative volume of selected items in the automation area is zero and the initial value of the fourth set of items selected to be the set of items stored in the automation area is null, then
The selecting the commodities in the current second category set to be stored in the automation area according to the selection coefficient and the volume of the commodities in the current second category set and the planned inventory amount of the automation area comprises:
selecting the commodity with the highest selection coefficient corresponding to the commodities which are not stored in the automation area in the current second category set as a first commodity to be stored currently;
adding the current accumulated volume and the total volume of the first commodity of the planned inventory amount;
comparing the volume of the addition operation with the size of the available storage space of the automation region.
7. The method of selecting items according to claim 6, wherein said selecting items from said current second set of items for deposit in said automation zone based on said selection factor, volume and planned inventory level of said automation zone further comprises:
if the volume sum is larger than the available storage space, deleting the first commodity from the current second category set, and judging whether the updated second category set is empty or not;
if the updated second category set is empty, the commodities in the current fourth category set are used as the selected commodities needing to be stored in the automatic area;
if the updated second category set is not empty, recalculating the order splitting index and the selection coefficient of the commodities in the updated second category set, and reselecting the commodities in the updated second category set to be stored in the automation area.
8. The method of selecting items according to claim 6, wherein said selecting items from said current second set of items for deposit in said automation zone based on said selection factor, volume and planned inventory level of said automation zone further comprises:
if the volume sum is less than or equal to the available storage space, adding the first commodity into a current fourth category set;
searching a historical order containing the first commodity in the order set, and deleting the first commodity from the third class set corresponding to the historical order;
deleting the historical order from the order set that the third category set is empty.
9. The method of selecting items according to claim 8, wherein said selecting items from said current second set of items for deposit in said automation zone based on said selection factor, volume and planned inventory level of said automation zone further comprises:
deleting the first commodity from the current second category set, and judging whether the updated second category set is empty or not;
if the updated second category set is empty, the commodities in the current fourth category set are used as the selected commodities needing to be stored in the automatic area;
if the updated second category set is not empty, recalculating the order splitting index and the selection coefficient of the commodities in the updated second category set, and reselecting the commodities in the updated second category set to be stored in the automation area.
10. A selection device for a human-machine hybrid warehouse, characterized in that the warehouse comprises a manual area and an automation area, the selection device comprising:
a first determination unit configured to determine a first category set of the warehouse according to categories of commodities stored in the warehouse;
a second determining unit configured to perform filtering out explosives and stalactites in the first class set, and determine a second class set of the warehouse;
a first calculating unit, configured to calculate a selection coefficient of the commodities in the current second category set according to the daily average sales volume of the commodities in the current second category set, the planned inventory occupation volume proportion in the automation area and the inventory splitting index; and
a selection unit configured to perform selecting the goods in the current second category set to be deposited into the automation area according to the selection coefficient, the volume and the planned inventory amount of the automation area of the goods in the current second category set.
11. A selection control device for a human-machine mixing warehouse, comprising:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to perform the method of selecting items for a human-machine mixing warehouse of any one of the preceding claims 1 to 9.
12. A computer-readable storage medium storing computer instructions which, when executed, implement the method of selecting items for a human-machine hybrid warehouse according to any one of claims 1 to 9.
13. A computer program product comprising a computer program comprising program instructions which, when executed by a mobile terminal, cause the mobile terminal to carry out the steps of the method of choice for a human-machine hybrid warehouse according to any one of claims 1 to 9.
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