CN110648099A - Storage resource allocation method and device, electronic equipment and storage medium - Google Patents

Storage resource allocation method and device, electronic equipment and storage medium Download PDF

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CN110648099A
CN110648099A CN201910892462.1A CN201910892462A CN110648099A CN 110648099 A CN110648099 A CN 110648099A CN 201910892462 A CN201910892462 A CN 201910892462A CN 110648099 A CN110648099 A CN 110648099A
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华雨臻
温华剑
张好
李纪东
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Beijing Sankuai Online Technology Co Ltd
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Abstract

The application discloses a method, a device, equipment and a storage medium for allocating storage resources, wherein the method comprises the following steps: obtaining one or more prospective orders based on historical orders, each prospective order containing one or more items; acquiring the quantity and commodity parameters of each commodity in each expected order; determining an expected order meeting the constraint condition according to the quantity of each commodity in the expected target order, the commodity parameters and the volume of a target shelf of the target warehousing goods area, wherein the expected order meeting the constraint condition comprises the target commodities with reference types, the sum of the quantity of the target commodities in all expected orders meeting the constraint condition is not more than the expected sales volume of the target commodities in the shelf life, and the total volume of the target commodities in all expected orders meeting the constraint condition is not more than the volume of the target shelf of the target warehousing goods area; target shelf resources of the target warehousing goods area are allocated for goods in the prospective order meeting the constraint conditions. And unified planning of warehousing resources is realized.

Description

Storage resource allocation method and device, electronic equipment and storage medium
Technical Field
The embodiment of the application relates to the technical field of warehousing management, in particular to a method and a device for allocating warehousing resources, electronic equipment and a storage medium.
Background
With the development of the super-retail industry, the super-retail model is enriched day by day, such as the increasingly popular online sales model. In the online sales mode, warehousing resources need to be allocated in advance to store commodities in advance. For example, for goods sold on the line, the warehousing resources are allocated according to the kinds of the goods, and the goods are stored on the shelves of different warehousing goods areas under the line in advance.
However, the method of allocating the warehousing resources according to the types of the commodities has certain limitations, the allocation method is not reasonable enough, and the allocated warehousing resources are not balanced enough, so a method of uniformly planning the warehousing resources and making the allocation result of the warehousing resources more reasonable is urgently needed to be provided.
Disclosure of Invention
The embodiment of the application provides a storage resource allocation method, a storage resource allocation device, electronic equipment and a storage medium, so that the storage resources are planned in a unified manner, and the allocation result of the storage resources is more reasonable. The technical scheme is as follows:
in one aspect, an embodiment of the present application provides a method for allocating storage resources, where the method includes: obtaining prospective orders based on historical orders, the prospective orders comprising one or more, each prospective order containing one or more commodities; acquiring the quantity of each commodity in each expected order and commodity parameters, wherein the commodity parameters comprise the quality guarantee period of the commodity and the volume of the commodity; determining an expected order meeting the constraint condition according to the quantity of each commodity in the expected target order, the commodity parameters and the volume of a target shelf of a target storage goods area, wherein the expected order meeting the constraint condition comprises a reference type quantity of target commodities, the sum of the quantity of the target commodities in all expected orders meeting the constraint condition is not more than the expected sales volume of the target commodities in the shelf life, and the total volume of the target commodities in all expected orders meeting the constraint condition is not more than the volume of the target shelf of the target storage goods area; and allocating target shelf resources of a target storage goods area for the commodities in the expected orders meeting the constraint conditions.
In a possible embodiment of the present application, the merchandise parameter further includes a replenishment period of the merchandise; determining an expected order meeting the constraint condition according to the quantity of each commodity in the expected target order, the commodity parameters and the volume of a target shelf of a target storage goods area, wherein the expected order meeting the constraint condition comprises a reference type quantity of target commodities, the sum of the quantity of the target commodities in all expected orders meeting the constraint condition is not more than the expected sales volume of the target commodities in the shelf life, and the total volume of the target commodities in all expected orders meeting the constraint condition is not more than the volume of the target shelf of the target storage goods area, and the method comprises the following steps: determining expected orders meeting the constraint condition according to the quantity of each commodity in the expected target orders, the quality guarantee period of the commodity, the replenishment period of the commodity, the volume of the commodity and the volume of the target shelf of the target storage goods area, wherein the expected orders meeting the constraint condition comprise the target commodities of the quantity of the reference type, the sum of the quantity of the target commodities in all the expected orders meeting the constraint condition is not larger than the expected sales volume of the target commodities in the quality guarantee period, the total volume of the target commodities in all the expected orders meeting the constraint condition is not larger than the volume of the target shelf of the target storage goods area, and the sum of the quantity of the target commodities in all the expected orders meeting the constraint condition is not smaller than the expected sales volume of the target commodities in the replenishment period.
In a possible embodiment of the present application, the goods parameter further includes a storage temperature of the goods, and the target shelf of the target warehousing goods area includes a plurality of storage spaces with different storage temperatures; determining an expected order meeting the constraint condition according to the quantity of each commodity in the expected target order, the commodity parameters and the volume of a target shelf of a target storage goods area, wherein the expected order meeting the constraint condition comprises a reference type quantity of target commodities, the sum of the quantity of the target commodities in all expected orders meeting the constraint condition is not more than the expected sales volume of the target commodities in the shelf life, and the total volume of the target commodities in all expected orders meeting the constraint condition is not more than the volume of the target shelf of the target storage goods area, and the method comprises the following steps: determining an expected order meeting the constraint condition according to the quantity of each commodity in the expected target order, the quality guarantee period of the commodity, the volume of a target shelf of a target storage goods area and the volume of each storage space, wherein the expected order meeting the constraint condition comprises the target commodities of the reference type quantity, the sum of the quantity of the target commodities in all the expected orders meeting the constraint condition is not more than the expected sales volume of the target commodity in the quality guarantee period, the total volume of the target commodities in all the expected orders meeting the constraint condition is not more than the volume of the target shelf of the target storage goods area, and the total volume of the target commodities at the same storage temperature in all the expected orders meeting the constraint condition is not more than the volume of the corresponding storage space.
In a possible embodiment of the present application, before allocating the target shelf resources of the target storage area for the goods in the prospective order meeting the constraint condition, the method further includes: determining whether a shelf of a target warehousing goods area contains a reference commodity, wherein the reference commodity represents a necessary article of the shelf; and when the goods shelf of the target warehousing goods area contains the reference goods, taking the rest goods shelf after the reference goods are placed as the target goods shelf of the target warehousing goods area.
In a possible embodiment of the present application, the allocating target shelf resources of a target storage goods area for the goods in the prospective order meeting the constraint condition includes: when the expected orders meeting the constraint conditions contain the reference commodities, acquiring a first standard quantity of the reference commodities; allocating target shelf resources of a target warehousing goods area to the reference goods contained in the expected order meeting the constraint condition, so that the target shelf resources of the target warehousing goods area contain a second standard quantity of the reference goods, and the sum of the first standard quantity and the second standard quantity is smaller than a target standard quantity.
In a possible embodiment of the present application, before allocating the target shelf resources of the target storage area for the goods in the prospective order meeting the constraint condition, the method further includes: determining whether the time of obtaining the expected order meeting the constraint condition meets standard time; and when the time for obtaining the prospective order meeting the constraint condition meets the standard time, taking the result obtained in the standard time as the prospective order meeting the constraint condition.
In one aspect, an embodiment of the present application provides an apparatus for allocating storage resources, where the apparatus includes: the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring prospective orders based on historical orders, the prospective orders comprise one or more commodities, and each prospective order comprises one or more commodities; the second acquisition module is used for acquiring the quantity of each commodity in each expected order and commodity parameters, wherein the commodity parameters comprise the quality guarantee period of the commodity and the volume of the commodity; a determining module, configured to determine an expected order meeting a constraint condition according to the quantity of each commodity in the expected target order, the commodity parameters, and the volume of a target shelf of a target warehousing goods area, where the expected order meeting the constraint condition includes a reference kind of quantity of target commodities, the sum of the quantities of the target commodities in all expected orders meeting the constraint condition is not greater than the expected sales volume of the target commodities in the shelf life, and the total volume of the target commodities in all expected orders meeting the constraint condition is not greater than the volume of the target shelf of the target warehousing goods area; and the third acquisition module is used for allocating target shelf resources of the target storage goods area for the goods in the expected order meeting the constraint condition.
In a possible embodiment of the present application, the merchandise parameter further includes a replenishment period of the merchandise; the determining module is used for determining the expected orders meeting the constraint conditions according to the quantity of each commodity in the expected target orders, the quality guarantee period of the commodity, the replenishment period of the commodity, the volume of the commodity and the volume of the target shelf of the target warehousing goods area, wherein the expected orders meeting the constraint conditions comprise the target commodities of the reference type quantity, the sum of the quantity of the target commodities in all the expected orders meeting the constraint conditions is not larger than the expected sales volume of the target commodities in the quality guarantee period, the total volume of the target commodities in all the expected orders meeting the constraint conditions is not larger than the volume of the target shelf of the target warehousing goods area, and the sum of the quantity of the target commodities in all the expected orders meeting the constraint conditions is not smaller than the expected sales volume of the target commodities in the replenishment period.
In a possible embodiment of the present application, the goods parameter further includes a storage temperature of the goods, and the target shelf of the target warehousing goods area includes a plurality of storage spaces with different storage temperatures; the determining module is used for determining the expected orders meeting the constraint conditions according to the quantity of each commodity in the expected target orders, the quality guarantee period of the commodity, the volume of the target shelf of the target warehousing goods area and the volume of each storage space, wherein the expected orders meeting the constraint conditions comprise the target commodities of the reference type quantity, the sum of the quantity of the target commodities in all the expected orders meeting the constraint conditions is not larger than the expected sales volume of the target commodities in the quality guarantee period, the total volume of the target commodities in all the expected orders meeting the constraint conditions is not larger than the volume of the target shelf of the target warehousing goods area, and the total volume of the target commodities at the same storage temperature in all the expected orders meeting the constraint conditions is not larger than the volume of the corresponding storage space.
In a possible embodiment of the present application, the third obtaining module is further configured to determine whether a shelf of the target warehousing goods area contains a reference good, where the reference good represents a necessary item of the shelf; and when the goods shelf of the target warehousing goods area contains the reference goods, taking the rest goods shelf after the reference goods are placed as the target goods shelf of the target warehousing goods area.
In a possible embodiment of the present application, the third obtaining module is further configured to obtain a first standard quantity of the reference product when the expected order meeting the constraint condition includes the reference product; allocating target shelf resources of a target warehousing goods area to the reference goods contained in the expected order meeting the constraint condition, so that the target shelf resources of the target warehousing goods area contain a second standard quantity of the reference goods, and the sum of the first standard quantity and the second standard quantity is smaller than a target standard quantity.
In a possible embodiment of the application, the third obtaining module is further configured to determine whether a time of obtaining the prospective order meeting the constraint condition meets a standard time; and when the time for obtaining the prospective order meeting the constraint condition meets the standard time, taking the result obtained in the standard time as the prospective order meeting the constraint condition.
In one aspect, an embodiment of the present application provides an electronic device, where the electronic device includes: the storage is stored with at least one instruction, and the at least one instruction is loaded and executed by the processor to realize the warehousing resource allocation method.
In one aspect, an embodiment of the present application provides a computer-readable storage medium, where at least one instruction is stored in the storage medium, and the instruction is loaded and executed by a processor to implement the method for allocating warehousing resources as described in any one of the above.
In one aspect, an embodiment of the present application provides a computer program (product), which includes: computer program code which, when run by a computer, causes the computer to perform the method of the above aspects.
The technical scheme provided by the embodiment of the application at least has the following beneficial effects:
the method comprises the steps that expected orders and commodities in the expected orders are obtained based on historical orders, target commodities with reference types and quantity in the expected orders meeting constraint conditions are determined according to the quantity of each commodity in each expected order, the quality guarantee period of the commodity and the volume of the commodity, and because the quantity of the target commodities in the expected orders is not more than the expected sales volume of the corresponding target commodity in the quality guarantee period and the total volume of all the expected orders meeting the constraint conditions is not more than the volume of a target shelf in a target storage goods area, the commodities meeting the constraint conditions in the obtained expected orders are all placed in the target storage goods area, unified planning of storage resources is achieved, distribution results of the storage resources are more reasonable, and excessive and untimely sales of the commodities stored in advance can be avoided; or the goods stored in advance are too much, and the stored goods are extruded due to the limited shelf capacity of the storage goods area, so that the selling of the goods is influenced, and the storage cost is increased.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a flowchart of a method for allocating storage resources according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of an allocation apparatus for storage resources according to an embodiment of the present disclosure;
fig. 3 is a block diagram of an electronic device provided in an embodiment of the present application;
fig. 4 is a schematic diagram of a terminal according to an embodiment of the present application.
Detailed Description
To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
With the development of the super-retail industry, the super-retail model is enriched day by day, such as the increasingly popular online sales model. However, since the goods are sold on the line, the goods are stored in advance on shelves of different storage areas on the line according to the kinds of the goods. When the received orders contain a plurality of types of commodities which are not in a goods area, the orders are split and are respectively sorted in the goods area storing the commodities of the type.
For example, when the received order contains life goods and sports goods, the goods can be sorted in the goods area for storing the life goods and the goods area for storing the sports goods, so that the sorting efficiency is reduced, and the off-line sorting cost is increased. And when the pre-stored commodities are too many, the stored commodities cannot be sold in time or the pre-stored commodities are too many, and the stored commodities are extruded due to the limited shelf capacity of the storage goods area, so that the commodity selling is influenced, and the offline storage cost is increased. Therefore, it is desired to provide a distribution method of warehousing resources that can reduce the sorting cost and the storage cost and improve the sorting efficiency. In order to avoid the above problems, the embodiments of the present application provide a method for allocating warehousing resources, which is described in detail in the following embodiments.
Referring to fig. 1, an embodiment of the present application provides a method for allocating storage resources, where the method is applicable to an electronic device, and the electronic device may be a terminal or a server. In the embodiment of the present application, taking a terminal as an example, as shown in fig. 1, the method includes:
in step 101, prospective orders are obtained based on historical orders, the prospective orders comprising one or more, each prospective order containing one or more items.
For example, the prospective order is obtained based on the historical order, the prospective order can be predicted by counting the historical order of the target time, or the prospective time can be input into the machine learning model, and the prospective order within the prospective time can be given through the machine learning model. The expected time corresponding to the expected order may be determined according to actual storage needs, for example, the expected time may be one worship, one month, and the like. The expected time is not limited in the embodiments of the present application. The expected order may be one or more. While the type of goods contained in each prospective order may also be one or more. The number of prospective orders and the number of types of goods included in each prospective order are not limited in the embodiments of the present application.
In step 102, the quantity of each commodity in each expected order and commodity parameters including the shelf life of the commodity and the volume of the commodity are obtained.
For example, after the prospective orders are obtained, the quantity of each commodity in each prospective order can be obtained through a statistical manner. And meanwhile, the commodity parameters of each commodity can be obtained. The commodity parameter may be obtained by searching in the network by the commodity name. In the embodiment of the application, the commodity parameters comprise the quality guarantee period of the commodity and the volume of the commodity, and the quantity of the commodity stored in advance is limited through the quality guarantee period of the commodity, so that the stored commodity can be sold in the quality guarantee period of the commodity, the volume of the stored commodity is ensured to meet the volume of a target storage area, the commodity is prevented from being extruded to influence the sale of the commodity, and the off-line storage cost is reduced.
In step 103, according to the quantity of each commodity in the target prospective order, the commodity parameters and the volume of the target shelf of the target storage goods area, the prospective order meeting the constraint condition is determined, the prospective order meeting the constraint condition comprises the target commodities with the reference type quantity, the sum of the quantity of the target commodities in all the prospective orders meeting the constraint condition is not larger than the expected sales volume of the target commodities in the shelf life, and the total volume of the target commodities in all the prospective orders meeting the constraint condition is not larger than the volume of the target shelf of the target storage goods area.
Illustratively, the sum of the number of the target product in all the expected orders satisfying the constraint condition is not larger than the expected sales volume of the target product in the shelf life, as shown in the following formula (1):
Figure BDA0002209179130000071
wherein: n is the expected order quantity; skujIs a jth kind of commodity; x is the number ofiIs the ith prospective order; q (x)i,skuj) The quantity in the ith prospective order for the jth type of item; djShelf life for the jth category of goods;
Figure BDA0002209179130000072
the daily sales are expected for the jth category of goods.
Assume that the expected order in the expected time includes four, respectively order x1Order x2Order x3And order x4Wherein the order x1The commodity included is (A, B, C), order x2The commodity included is (B, C, D), order x3The commodity included is (A, C, D), order x4The commercial product included is (A, B, C). The expression of A, B, C, D for the number of four types of goods in four orders can be obtained by the above formula (1):
A：q(x1,skuA)+q(x3,skuA)+q(x4,skuA) (2)
B：q(x1,skuB)+q(x2,skuB)+q(x4,skuB) (3)
C：q(x1,skuC)+q(x2,skuC)+q(x3,skuC)+q(x4,skuC) (4)
D：q(x2,skuD)+q(x3,skuD) (5)
the target commodity in the corresponding order can be obtained in the four expressions through the operational research principle, so that the sum of the number of the target commodity in all expected orders meeting the constraint condition is not larger than the expected sales volume of the target commodity in the quality guarantee period. The reference number may be the number of all the kinds of the goods included in the order or the number of more than half of the kinds included in the order, and the reference number is not limited in the embodiment of the present application as long as the reference number is greater than 1. For example for order x1If all kinds of commodities contained in the order meet the constraint condition, all kinds of commodities in the order are placed in the target storage goods area, then the storage cost and the sorting cost of the order are reduced, even the corresponding storage cost and sorting cost are not available, and meanwhile, the sorting efficiency of the corresponding order is improved. Therefore, the evaluation criterion based on the operational research principle can make the commodities meeting the constraint condition belong to the same order to the maximum extent. For example for order x1When the A-type commodities in the commodities contained in the commodity package satisfy the constraint condition (6), the B-type commodities satisfy the constraint condition (7). For order x1Including class C goods when order x1Order x2Order x3Number of C-class goods and order x contained in2Order x3Order x4The total number of the C-type commodities is less than
Figure BDA0002209179130000081
Preference includes order x1Is shown in formula (8), such that order x1All the commodities contained in the product satisfy the constraint condition.
Figure BDA0002209179130000082
Figure BDA0002209179130000084
The expected daily sales of the above commodities are predicted by a machine learning model, and are specifically represented by the following formula:
Figure BDA0002209179130000085
wherein: y issku,tThe expected daily sales;an expected daily sales volume for the machine learning model; t is expected time, the unit of the expected time can be days or months, and the person skilled in the art can determine the expected time according to actual use needs, and the examples of the application take days as an example for explanation; epsilonsku,tRandom error of predicted result for t days in future of machine learning model, which can obey positive distribution
Figure BDA0002209179130000087
Expected sales volume predicted by machine learning model in expected future t days
Figure BDA0002209179130000088
Has a confidence of p, where zpIs a confidence value of the positive-too distribution.
The manner of determining the expected order meeting the shelf life requirement of the commodity and the volume requirement of the stored commodity is consistent with the principle of determining the expected order meeting the shelf life requirement of the commodity, and the embodiment of the application is not described herein again. The specific constraint conditions satisfy the following formulas (1) and (9) at the same time:
Figure BDA0002209179130000089
wherein: n is the expected order quantity; skujIs a jth kind of commodity; x is the number ofiIs the ith prospective order; q (x)i,skuj) The quantity in the ith prospective order for the jth type of item; djShelf life for the jth category of goods;
Figure BDA0002209179130000092
the daily sales are expected for the jth category of goods.
Figure BDA0002209179130000091
Wherein: n is the expected order quantity; i is the number of commodity types; skujIs a jth kind of commodity; x is the number ofiIs the ith prospective order; q (x)i,skuj) The quantity in the ith prospective order for the jth type of item; v. ofjIs the jth type of commodity volume; v is the volume of the target goods shelf of the target storage goods area.
By acquiring the expected orders meeting the constraint conditions at the same time, the commodities in the corresponding expected orders are placed on the target shelf of the target storage goods area, so that the quantity of the prestored commodities is ensured to meet the quality guarantee period requirement and the volume requirement of the target shelf of the target storage goods area, and the situation of commodity extrusion in the target storage goods area is avoided.
In step 104, target shelf resources of the target warehousing goods area are allocated for the goods in the prospective order that satisfy the constraint.
Illustratively, order x when analyzed as described above1If all kinds of commodities satisfy the constraint condition, the order x can be selected1And allocating target shelf resources of the target warehousing goods area for the medium-sized goods. If order x passes the above analysis1Only the A-type commodities and the B-type commodities meet the constraint condition, and can be orders x1The A-type commodities and the B-type commodities in the system are allocated with target shelf resources of a target warehousing goods area, and orders x can also be allocated with the target shelf resources1All sorts of goods in (1) allocate target shelf resources of the target warehousing goods area. Through analysis, whether all kinds of commodities in the order or partial kinds of commodities are placed on the target goods shelf of the same target storage goods area, the storage cost and the sorting cost can be correspondingly reduced, and the sorting efficiency is improved.
The warehousing resource allocation method provided by the embodiment of the application acquires the expected orders and the commodities in the expected orders based on the historical orders, according to the quantity of each commodity in each expected order, the quality guarantee period of the commodity and the volume of the commodity, determining that the expected orders meeting the constraint conditions contain the target commodities with reference kinds, because the quantity of the target commodities in the expected order is not more than the expected sales volume in the quality guarantee period of the corresponding target commodity and the total volume of the target goods in all the expected orders meeting the constraint condition is not more than the volume of the target goods shelf in the target warehousing goods area, the commodities meeting the constraint condition in the obtained expected order are all placed in one target warehousing goods area, the unified planning of warehousing resources is realized, the distribution result of the warehousing resources is more reasonable, and the condition that the commodities stored in advance are too many and are not sold in time can be avoided; or the goods stored in advance are too much, and the stored goods are extruded due to the limited shelf capacity of the storage goods area, so that the selling of the goods is influenced, and the storage cost is increased.
In a possible embodiment of the present application, the merchandise parameter further includes a replenishment period of the merchandise;
in step 103, the method comprises the following steps: and determining the expected orders meeting the constraint condition according to the quantity of each commodity in the target expected orders, the quality guarantee period of the commodity and the replenishment period of the commodity, wherein the expected orders meeting the constraint condition comprise the target commodities with the reference type quantity, the sum of the quantity of the target commodities in all the expected orders meeting the constraint condition is not greater than the expected sales quantity of the target commodities in the quality guarantee period, and the sum of the quantity of the target commodities in all the expected orders meeting the constraint condition is not less than the expected sales quantity of the target commodities in the replenishment period.
For example, the specific manner of determining the expected orders meeting the shelf life requirement and the replenishment cycle requirement of the commodity is consistent with the above principle of determining the expected orders meeting the shelf life requirement of the commodity, and the embodiments of the present application are not described herein again. The specific constraint conditions satisfy the following formulas (1) and (10) at the same time:
Figure BDA0002209179130000101
wherein: n is the expected order quantity; skujIs a jth kind of commodity; x is the number ofiIs the ith prospective order; q (x)i,skuj) The quantity in the ith prospective order for the jth type of item; djShelf life for the jth category of goods;
Figure BDA0002209179130000103
the daily sales are expected for the jth category of goods.
Figure BDA0002209179130000102
Wherein: n is the expected order quantity; skujIs a jth kind of commodity; x is the number ofiIs the ith prospective order; q (x)i,skuj) The quantity in the ith prospective order for the jth type of item; t is tjA replenishment period for a jth type of commodity;
Figure BDA0002209179130000104
the daily sales are expected for the jth category of goods.
By acquiring the expected orders meeting the constraint conditions at the same time, the commodities in the corresponding expected orders are placed on the target shelf of the target storage goods area, so that the condition of goods failure is avoided while the quantity of the prestored commodities meets the requirement of the quality guarantee period.
In a possible embodiment of the present application, the goods parameter further includes a storage temperature of the goods, and the target shelf of the target warehousing goods area includes a plurality of storage spaces with different storage temperatures;
in step 103, the method comprises the following steps: and determining the expected orders meeting the constraint condition according to the quantity of each commodity in the expected target orders, the shelf life of the commodity, the volume of the commodity and the volume of each storage space, wherein the expected orders meeting the constraint condition comprise the target commodities of the reference type quantity, the sum of the quantity of the target commodities in all the expected orders meeting the constraint condition is not more than the expected sales volume of the target commodity in the shelf life, and the total volume of the target commodities at the same storage temperature in all the expected orders meeting the constraint condition is not more than the volume of the corresponding storage space.
For example, the specific manner of determining the prospective order meeting the shelf life requirement of the commodity and the volume requirement of the stored commodity is consistent with the above principle of determining the prospective order meeting the shelf life requirement of the commodity, and the embodiments of the present application are not described herein again. The specific constraint conditions satisfy the following formulas (1) and (11) at the same time:
Figure BDA0002209179130000111
wherein: n is the expected order quantity; skujIs a jth kind of commodity; x is the number ofiIs the ith prospective order; q (x)i,skuj) The quantity in the ith prospective order for the jth type of item; djShelf life for the jth category of goods;
Figure BDA0002209179130000113
the daily sales are expected for the jth category of goods.
Figure BDA0002209179130000112
Wherein: n is the expected order quantity; i is the number of commodity types; skujIs of the j th speciesA commodity-like product; x is the number ofiIs the ith prospective order; q (x)i,skuj) The quantity in the ith prospective order for the jth type of item; v. ofjIs the jth type of commodity volume; vkThe volume of the kth storage space of the target shelf of the target warehousing goods area.
By acquiring the expected orders meeting the constraint conditions at the same time, the commodities in the corresponding expected orders are placed on the target shelf of the target storage goods area, so that the quantity of the prestored commodities is ensured to meet the quality guarantee period requirement, and the volume requirements of storage spaces of the target shelf of the target storage goods area at different storage temperatures are met, the stored commodities can be stored in the storage spaces with the corresponding storage temperature requirements, and the quality of the stored commodities is ensured.
In a possible embodiment of the present application, before step 104, the method further comprises: and determining whether the goods shelf of the target storage goods area contains reference goods, wherein the reference goods represent necessary goods of the goods shelf. And when the goods shelves of the target warehousing goods area contain the reference goods, taking the rest goods shelves after the reference goods are placed as the target goods shelves of the target warehousing goods area.
For example, for a target storage cargo area, some necessary articles, such as mineral water, may be placed on the shelves of the target storage cargo area in advance, or for a relatively heavy article, the relatively heavy article may be placed on the shelves of the storage cargo area for easy handling in order to facilitate storage and transportation. Therefore, if necessary goods are placed on the shelves of the target warehousing goods area, the remaining shelves after the reference goods are placed are used as the target shelves of the target warehousing goods area.
In a possible embodiment of the present application, step 104 includes: when the expected order meeting the constraint condition contains the reference commodity, acquiring a first standard quantity of the reference commodity. And allocating the target shelf resources of the target warehousing goods area for the reference goods contained in the expected order meeting the constraint condition, so that the target shelf resources of the target warehousing goods area contain the reference goods with the second standard quantity, and the sum of the first standard quantity and the second standard quantity is smaller than the target standard quantity.
Illustratively, reference goods are placed on the shelves of the target warehousing goods area, and when the expected orders meeting the constraint condition contain the same reference goods, a first standard quantity of the reference goods placed on the shelves of the target warehousing goods area is obtained. The target shelf resources of the target warehousing goods area contain the reference goods of the second standard quantity through the limitation of the target standard quantity, so that the sum of the first standard quantity and the second standard quantity is smaller than the target standard quantity. The target standard quantity may be any value within an expected sales volume of the corresponding reference commodity over the shelf life. The person skilled in the art can determine the number of the reference goods in the target warehousing goods area according to the actual use scenario.
In a possible embodiment of the present application, before step 104, the method further comprises: it is determined whether the time to get the prospective order meeting the constraint satisfies a criterion time. And when the time of obtaining the prospective order meeting the constraint condition meets the standard time, taking the result obtained in the standard time as the prospective order meeting the constraint condition.
For example, in the process of determining prospective orders satisfying the constraints described above, as the constraints increase, as well as the number of prospective orders increases and the types of goods included in the prospective orders increase, the time to determine prospective orders satisfying the constraints will increase. In order to meet the actual use requirement, obtain the expected order meeting the constraint condition as soon as possible, and allocate the warehousing resources to the commodities in the expected order meeting the constraint condition in time, a heuristic algorithm can be adopted to obtain an optimization result within an acceptable standard time as the expected order meeting the constraint condition, and the commodities contained in the expected order are stored on the target shelf of the target warehousing goods area. And the target goods shelf of the target warehousing goods area is subjected to commodity storage in time, so that the utilization rate and the commodity turnover rate of the target goods shelf of the target warehousing goods area are improved, and the storage space of the target warehousing goods area is fully utilized.
Based on the same conception, the embodiment of the present application provides an allocation apparatus for storage resources, referring to fig. 2, the apparatus includes:
a first obtaining module 201, configured to obtain prospective orders based on historical orders, where the prospective orders include one or more items, and each prospective order includes one or more items;
a second obtaining module 202, configured to obtain the quantity of each commodity in each expected order and commodity parameters, where the commodity parameters include a shelf life of the commodity and a volume of the commodity;
a determining module 203, configured to determine a prospective order meeting the constraint condition according to the quantity of each commodity in the prospective target order, the commodity parameters, and the volume of a target shelf in a target warehousing goods area, where the prospective order meeting the constraint condition includes a reference type quantity of target commodities, a sum of the quantities of the target commodities in all prospective orders meeting the constraint condition is not greater than an expected sales volume of the target commodities in a shelf life, and a total volume of the target commodities in all prospective orders meeting the constraint condition is not greater than the volume of the target shelf in the target warehousing goods area;
and a third obtaining module 204, configured to allocate target shelf resources of the target warehousing goods area for the goods in the expected order meeting the constraint condition.
The warehousing resource allocation device provided by the embodiment of the application acquires the expected orders and the commodities in the expected orders based on the historical orders, according to the quantity of each commodity in each expected order, the quality guarantee period of the commodity and the volume of the commodity, determining that the expected orders meeting the constraint conditions contain the target commodities with reference kinds, because the quantity of the target commodities in the expected order is not more than the expected sales volume in the quality guarantee period of the corresponding target commodity and the total volume of the target goods in all the expected orders meeting the constraint condition is not more than the volume of the target goods shelf in the target warehousing goods area, the commodities meeting the constraint condition in the obtained expected order are all placed in one target warehousing goods area, the unified planning of warehousing resources is realized, the distribution result of the warehousing resources is more reasonable, and the condition that the commodities stored in advance are too many and are not sold in time can be avoided; or the goods stored in advance are too much, and the stored goods are extruded due to the limited shelf capacity of the storage goods area, so that the selling of the goods is influenced, and the storage cost is increased.
In a possible embodiment of the present application, the commodity parameter further comprises a replenishment period of the commodity;
the determining module 203 is used for determining the expected orders meeting the constraint conditions according to the quantity of each commodity in the expected target orders, the shelf life of the commodity, the replenishment period of the commodity, the volume of the commodity and the volume of the target shelf of the target storage goods area, wherein the expected orders meeting the constraint conditions contain the target commodities of the reference type quantity, the sum of the quantity of the target commodities in all the expected orders meeting the constraint conditions is not greater than the expected sales volume of the target commodity in the shelf life, the total volume of the target commodities in all the expected orders meeting the constraint conditions is not greater than the volume of the target shelf of the target storage goods area, and the sum of the quantity of the target commodities in all the expected orders meeting the constraint conditions is not less than the expected sales volume of the target commodity in the replenishment period.
In a possible embodiment of the present application, the goods parameter further includes a storage temperature of the goods, and the target shelf of the target warehousing goods area includes a plurality of storage spaces with different storage temperatures;
the determining module 203 is configured to determine the expected orders meeting the constraint condition according to the number of each commodity in the expected target orders, the shelf life of the commodity, the volume of the target shelf in the target storage goods area, and the volume of each storage space, where the expected orders meeting the constraint condition include the target commodities of the reference type, the sum of the numbers of the target commodities in all the expected orders meeting the constraint condition is not greater than the expected sales volume of the target commodity in the shelf life, the total volume of the target commodities in all the expected orders meeting the constraint condition is not greater than the volume of the target shelf in the target storage goods area, and the total volume of the target commodities at the same storage temperature in all the expected orders meeting the constraint condition is not greater than the volume of the corresponding storage space.
In a possible embodiment of the present application, the third obtaining module 204 is further configured to determine whether a shelf of the target warehousing goods area contains a reference good, where the reference good represents a necessary item of the shelf; and when the goods shelves of the target warehousing goods area contain the reference goods, taking the rest goods shelves after the reference goods are placed as the target goods shelves of the target warehousing goods area.
In a possible embodiment of the present application, the third obtaining module 204 is further configured to obtain a first standard quantity of the reference product when the expected order meeting the constraint condition includes the reference product; and allocating target shelf resources of the target warehousing goods area for the reference goods contained in the expected order meeting the constraint condition, so that the target shelf resources of the target warehousing goods area contain a second standard quantity of the reference goods, and the sum of the first standard quantity and the second standard quantity is smaller than the target standard quantity.
In a possible embodiment of the present application, the third obtaining module 204 is further configured to determine whether a time of obtaining the prospective order meeting the constraint condition meets a standard time; and when the time of obtaining the prospective order meeting the constraint condition meets the standard time, taking the result obtained in the standard time as the prospective order meeting the constraint condition.
It should be noted that, when the apparatus provided in the foregoing embodiment implements the functions thereof, only the division of the functional modules is illustrated, and in practical applications, the functions may be distributed by different functional modules according to needs, that is, the internal structure of the apparatus may be divided into different functional modules to implement all or part of the functions described above. In addition, the apparatus and method embodiments provided by the above embodiments belong to the same concept, and specific implementation processes thereof are described in the method embodiments for details, which are not described herein again.
The embodiment of the application also provides the electronic equipment, and the electronic equipment can be a server. As shown in fig. 3, the apparatus includes: a memory 302 and a processor 301, wherein the memory 302 stores at least one instruction, and the at least one instruction is loaded and executed by the processor 301 to implement the method for allocating warehousing resources according to the above embodiments. The processor 301 and the memory 302 are connected by a communication bus 303.
It should be understood that the processor may be a Central Processing Unit (CPU), other general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or any conventional processor or the like. It is noted that the processor may be an advanced reduced instruction set machine (ARM) architecture supported processor.
Further, in an alternative embodiment, the memory may include both read-only memory and random access memory, and provide instructions and data to the processor. The memory may also include non-volatile random access memory. For example, the memory may also store device type information.
The memory may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The non-volatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an electrically Erasable EPROM (EEPROM), or a flash memory. Volatile memory can be Random Access Memory (RAM), which acts as external cache memory. By way of example, and not limitation, many forms of RAM are available. For example, Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), Enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct memory bus RAM (DR RAM).
Referring to fig. 4, a schematic structural diagram of a terminal 500 provided in an embodiment of the present application is shown. The terminal 500 may be a portable mobile terminal such as: a smartphone, a tablet laptop or a desktop computer. Terminal 500 may also be referred to by other names such as user equipment, portable terminal, laptop terminal, desktop terminal, and the like.
In general, the terminal 500 includes: a processor 501 and a memory 502.
The processor 501 may include one or more processing cores, such as a 4-core processor, a 5-core processor, and so on. The processor 501 may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 501 may also include a main processor and a coprocessor, where the main processor is a processor for Processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 501 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content required to be displayed on the display screen. In some embodiments, processor 501 may also include an AI (Artificial Intelligence) processor for processing computational operations related to machine learning.
Memory 502 may include one or more computer-readable storage media, which may be non-transitory. Memory 502 may also include high-speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments, a non-transitory computer readable storage medium in memory 502 is used to store at least one instruction for execution by processor 501 to implement the allocation method of warehousing resources provided by the method embodiments herein.
In some embodiments, the terminal 500 may further optionally include: a peripheral interface 503 and at least one peripheral. The processor 501, memory 502 and peripheral interface 503 may be connected by a bus or signal lines. Each peripheral may be connected to the peripheral interface 503 by a bus, signal line, or circuit board. Specifically, the peripheral device includes: at least one of radio frequency circuitry 504, touch screen display 505, camera 506, audio circuitry 507, positioning components 508, and power supply 509.
The peripheral interface 503 may be used to connect at least one peripheral related to I/O (Input/Output) to the processor 501 and the memory 502. In some embodiments, the processor 501, memory 502, and peripheral interface 503 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 501, the memory 502, and the peripheral interface 503 may be implemented on a separate chip or circuit board, which is not limited in this embodiment.
The Radio Frequency circuit 504 is used for receiving and transmitting RF (Radio Frequency) signals, also called electromagnetic signals. The radio frequency circuitry 504 communicates with communication networks and other communication devices via electromagnetic signals. The rf circuit 504 converts an electrical signal into an electromagnetic signal to transmit, or converts a received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 504 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and so forth. The radio frequency circuitry 504 may communicate with other terminals via at least one wireless communication protocol. The wireless communication protocols include, but are not limited to: metropolitan area networks, various generation mobile communication networks (2G, 3G, 4G, and 5G), Wireless local area networks, and/or WiFi (Wireless Fidelity) networks. In some embodiments, the rf circuit 504 may further include NFC (Near Field Communication) related circuits, which are not limited in this application.
The display screen 505 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display screen 505 is a touch display screen, the display screen 505 also has the ability to capture touch signals on or over the surface of the display screen 505. The touch signal may be input to the processor 501 as a control signal for processing. At this point, the display screen 505 may also be used to provide virtual buttons and/or a virtual keyboard, also referred to as soft buttons and/or a soft keyboard. In some embodiments, the display screen 505 may be one, providing the front panel of the terminal 500; in other embodiments, the display screens 505 may be at least two, respectively disposed on different surfaces of the terminal 500 or in a folded design; in still other embodiments, the display 505 may be a flexible display disposed on a curved surface or on a folded surface of the terminal 500. Even more, the display screen 505 can be arranged in a non-rectangular irregular figure, i.e. a shaped screen. The Display screen 505 may be made of LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), and other materials.
The camera assembly 506 is used to capture images or video. Optionally, camera assembly 506 includes a front camera and a rear camera. Generally, a front camera is disposed at a front panel of the terminal, and a rear camera is disposed at a rear surface of the terminal. In some embodiments, the number of the rear cameras is at least two, and each rear camera is any one of a main camera, a depth-of-field camera, a wide-angle camera and a telephoto camera, so that the main camera and the depth-of-field camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize panoramic shooting and VR (Virtual Reality) shooting functions or other fusion shooting functions. In some embodiments, camera assembly 506 may also include a flash. The flash lamp can be a monochrome temperature flash lamp or a bicolor temperature flash lamp. The double-color-temperature flash lamp is a combination of a warm-light flash lamp and a cold-light flash lamp, and can be used for light compensation at different color temperatures.
Audio circuitry 507 may include a microphone and a speaker. The microphone is used for collecting sound waves of a user and the environment, converting the sound waves into electric signals, and inputting the electric signals to the processor 501 for processing, or inputting the electric signals to the radio frequency circuit 504 to realize voice communication. For the purpose of stereo sound collection or noise reduction, a plurality of microphones may be provided at different portions of the terminal 500. The microphone may also be an array microphone or an omni-directional pick-up microphone. The speaker is used to convert electrical signals from the processor 501 or the radio frequency circuit 504 into sound waves. The loudspeaker can be a traditional film loudspeaker or a piezoelectric ceramic loudspeaker. When the speaker is a piezoelectric ceramic speaker, the speaker can be used for purposes such as converting an electric signal into a sound wave audible to a human being, or converting an electric signal into a sound wave inaudible to a human being to measure a distance. In some embodiments, audio circuitry 507 may also include a headphone jack.
The positioning component 508 is used for positioning the current geographic Location of the terminal 500 for navigation or LBS (Location Based Service). The positioning component 508 may be a positioning component based on the GPS (global positioning System) in the united states, the beidou System in china, the graves System in russia, or the galileo System in the european union.
Power supply 509 is used to power the various components in terminal 500. The power source 509 may be alternating current, direct current, disposable or rechargeable. When power supply 509 includes a rechargeable battery, the rechargeable battery may support wired or wireless charging. The rechargeable battery may also be used to support fast charge technology.
In some embodiments, terminal 500 also includes one or more sensors 510. The one or more sensors 510 include, but are not limited to: acceleration sensor 511, gyro sensor 512, pressure sensor 513, fingerprint sensor 514, optical sensor 515, and proximity sensor 516.
The acceleration sensor 510 may detect the magnitude of acceleration on three coordinate axes of a coordinate system established with the terminal 500. For example, the acceleration sensor 511 may be used to detect components of the gravitational acceleration in three coordinate axes. The processor 501 may control the touch screen 505 to display the user interface in a landscape view or a portrait view according to the gravitational acceleration signal collected by the acceleration sensor 511. The acceleration sensor 511 may also be used for acquisition of motion data of a game or a user.
The gyro sensor 512 may detect a body direction and a rotation angle of the terminal 500, and the gyro sensor 512 may cooperate with the acceleration sensor 511 to acquire a 3D motion of the user on the terminal 500. The processor 501 may implement the following functions according to the data collected by the gyro sensor 512: motion sensing (such as changing the UI according to a user's tilting operation), image stabilization at the time of photographing, game control, and inertial navigation.
The pressure sensor 513 may be disposed on a side bezel of the terminal 500 and/or an underlying layer of the touch display screen 505. When the pressure sensor 513 is disposed on the side frame of the terminal 500, a user's holding signal of the terminal 500 may be detected, and the processor 501 performs left-right hand recognition or shortcut operation according to the holding signal collected by the pressure sensor 513. When the pressure sensor 513 is disposed at the lower layer of the touch display screen 505, the processor 501 controls the operability control on the UI interface according to the pressure operation of the user on the touch display screen 505. The operability control comprises at least one of a button control, a scroll bar control, an icon control and a menu control.
The fingerprint sensor 514 is used for collecting a fingerprint of the user, and the processor 501 identifies the identity of the user according to the fingerprint collected by the fingerprint sensor 514, or the fingerprint sensor 514 identifies the identity of the user according to the collected fingerprint. Upon recognizing that the user's identity is a trusted identity, the processor 501 authorizes the user to perform relevant sensitive operations including unlocking the screen, viewing encrypted information, downloading software, paying, and changing settings, etc. The fingerprint sensor 514 may be provided on the front, back, or side of the terminal 500. When a physical button or a vendor Logo is provided on the terminal 500, the fingerprint sensor 514 may be integrated with the physical button or the vendor Logo.
The optical sensor 515 is used to collect the ambient light intensity. In one embodiment, the processor 501 may control the display brightness of the touch display screen 505 based on the ambient light intensity collected by the optical sensor 515. Specifically, when the ambient light intensity is high, the display brightness of the touch display screen 505 is increased; when the ambient light intensity is low, the display brightness of the touch display screen 505 is turned down. In another embodiment, processor 501 may also dynamically adjust the shooting parameters of camera head assembly 506 based on the ambient light intensity collected by optical sensor 515.
A proximity sensor 516, also referred to as a distance sensor, is typically disposed on the front panel of the terminal 500. The proximity sensor 516 is used to collect the distance between the user and the front surface of the terminal 500. In one embodiment, when the proximity sensor 516 detects that the distance between the user and the front surface of the terminal 500 gradually decreases, the processor 501 controls the touch display screen 505 to switch from the bright screen state to the dark screen state; when the proximity sensor 516 detects that the distance between the user and the front surface of the terminal 500 becomes gradually larger, the processor 501 controls the touch display screen 505 to switch from the screen-rest state to the screen-on state.
Those skilled in the art will appreciate that the configuration shown in fig. 4 is not intended to be limiting of terminal 500 and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components may be used.
The present application provides a computer program, which when executed by a computer, may cause the processor or the computer to perform the respective steps and/or procedures corresponding to the above-described method embodiments.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the procedures or functions described in accordance with the present application are generated, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (e.g., coaxial cable, fiber optic, digital subscriber line) or wirelessly (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid state disk), among others.
All the above optional technical solutions may be combined arbitrarily to form optional embodiments of the present application, and are not described herein again.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above description is only exemplary of the present application and should not be taken as limiting the present application, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims (10)

1. A method for allocating storage resources, the method comprising:
obtaining prospective orders based on historical orders, the prospective orders comprising one or more, each prospective order containing one or more commodities;
acquiring the quantity of each commodity in each expected order and commodity parameters, wherein the commodity parameters comprise the quality guarantee period of the commodity and the volume of the commodity;
determining an expected order meeting the constraint condition according to the quantity of each commodity in the expected target order, the commodity parameters and the volume of a target shelf of a target storage goods area, wherein the expected order meeting the constraint condition comprises a reference type quantity of target commodities, the sum of the quantity of the target commodities in all expected orders meeting the constraint condition is not more than the expected sales volume of the target commodities in the shelf life, and the total volume of the target commodities in all expected orders meeting the constraint condition is not more than the volume of the target shelf of the target storage goods area;
and allocating target shelf resources of a target storage goods area for the commodities in the expected orders meeting the constraint conditions.
2. The method of claim 1, wherein the commodity parameters further include a replenishment period for the commodity;
determining an expected order meeting the constraint condition according to the quantity of each commodity in the expected target order, the commodity parameters and the volume of a target shelf of a target storage goods area, wherein the expected order meeting the constraint condition comprises a reference type quantity of target commodities, the sum of the quantity of the target commodities in all expected orders meeting the constraint condition is not more than the expected sales volume of the target commodities in the shelf life, and the total volume of the target commodities in all expected orders meeting the constraint condition is not more than the volume of the target shelf of the target storage goods area, and the method comprises the following steps:
determining expected orders meeting the constraint condition according to the quantity of each commodity in the expected target orders, the quality guarantee period of the commodity, the replenishment period of the commodity, the volume of the commodity and the volume of the target shelf of the target storage goods area, wherein the expected orders meeting the constraint condition comprise the target commodities of the quantity of the reference type, the sum of the quantity of the target commodities in all the expected orders meeting the constraint condition is not larger than the expected sales volume of the target commodities in the quality guarantee period, the total volume of the target commodities in all the expected orders meeting the constraint condition is not larger than the volume of the target shelf of the target storage goods area, and the sum of the quantity of the target commodities in all the expected orders meeting the constraint condition is not smaller than the expected sales volume of the target commodities in the replenishment period.
3. The method of claim 1, wherein the goods parameters further comprise a storage temperature of the goods, and the target shelf of the target warehousing goods area comprises a plurality of storage spaces with different storage temperatures;
determining an expected order meeting the constraint condition according to the quantity of each commodity in the expected target order, the commodity parameters and the volume of a target shelf of a target storage goods area, wherein the expected order meeting the constraint condition comprises a reference type quantity of target commodities, the sum of the quantity of the target commodities in all expected orders meeting the constraint condition is not more than the expected sales volume of the target commodities in the shelf life, and the total volume of the target commodities in all expected orders meeting the constraint condition is not more than the volume of the target shelf of the target storage goods area, and the method comprises the following steps:
determining an expected order meeting the constraint condition according to the quantity of each commodity in the expected target order, the quality guarantee period of the commodity, the volume of a target shelf of a target storage goods area and the volume of each storage space, wherein the expected order meeting the constraint condition comprises the target commodities of the reference type quantity, the sum of the quantity of the target commodities in all the expected orders meeting the constraint condition is not more than the expected sales volume of the target commodity in the quality guarantee period, the total volume of the target commodities in all the expected orders meeting the constraint condition is not more than the volume of the target shelf of the target storage goods area, and the total volume of the target commodities at the same storage temperature in all the expected orders meeting the constraint condition is not more than the volume of the corresponding storage space.
4. The method of claim 1, wherein before allocating target shelf resources of a target warehousing goods area for goods in the prospective order meeting the constraint, the method further comprises:
determining whether a shelf of a target warehousing goods area contains a reference commodity, wherein the reference commodity represents a necessary article of the shelf;
and when the goods shelf of the target warehousing goods area contains the reference goods, taking the rest goods shelf after the reference goods are placed as the target goods shelf of the target warehousing goods area.
5. The method of claim 4, wherein the allocating target shelf resources of a target warehousing goods area for the goods in the prospective order meeting the constraint condition comprises:
when the expected orders meeting the target conditions contain the reference commodities, acquiring a first standard quantity of the reference commodities;
allocating target shelf resources of a target warehousing goods area to the reference goods contained in the expected order meeting the constraint condition, so that the target shelf resources of the target warehousing goods area contain a second standard quantity of the reference goods, and the sum of the first standard quantity and the second standard quantity is smaller than a target standard quantity.
6. The method according to any one of claims 1-5, wherein before allocating target shelf resources of a target warehousing goods area for goods in the prospective order meeting the constraint, the method further comprises:
determining whether the time of obtaining the expected order meeting the constraint condition meets standard time;
and when the time for obtaining the prospective order meeting the constraint condition meets the standard time, taking the result obtained in the standard time as the prospective order meeting the constraint condition.
7. An apparatus for allocating storage resources, the apparatus comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring prospective orders based on historical orders, the prospective orders comprise one or more commodities, and each prospective order comprises one or more commodities;
the second acquisition module is used for acquiring the quantity of each commodity in each expected order and commodity parameters, wherein the commodity parameters comprise the quality guarantee period of the commodity and the volume of the commodity;
a determining module, configured to determine an expected order meeting a constraint condition according to the quantity of each commodity in the expected target order, the commodity parameters, and the volume of a target shelf of a target warehousing goods area, where the expected order meeting the constraint condition includes a reference kind of quantity of target commodities, the sum of the quantities of the target commodities in all expected orders meeting the constraint condition is not greater than the expected sales volume of the target commodities in the shelf life, and the total volume of the target commodities in all expected orders meeting the constraint condition is not greater than the volume of the target shelf of the target warehousing goods area;
and the third acquisition module is used for allocating target shelf resources of the target storage goods area for the goods in the expected order meeting the constraint condition.
8. The apparatus of claim 7, wherein the merchandise parameters further include a replenishment period for the merchandise; the determining module is used for determining the expected orders meeting the constraint conditions according to the quantity of each commodity in the expected target orders, the quality guarantee period of the commodity, the replenishment period of the commodity, the volume of the commodity and the volume of the target shelf of the target warehousing goods area, wherein the expected orders meeting the constraint conditions comprise the target commodities of the reference type quantity, the sum of the quantity of the target commodities in all the expected orders meeting the constraint conditions is not larger than the expected sales volume of the target commodities in the quality guarantee period, the total volume of the target commodities in all the expected orders meeting the constraint conditions is not larger than the volume of the target shelf of the target warehousing goods area, and the sum of the quantity of the target commodities in all the expected orders meeting the constraint conditions is not smaller than the expected sales volume of the target commodities in the replenishment period.
9. An electronic device, comprising: the apparatus comprises:
a memory and a processor, the memory storing at least one instruction, the at least one instruction being loaded and executed by the processor to implement the method of allocating warehousing resources of any of claims 1-6.
10. A storage medium, comprising: the storage medium has at least one instruction stored therein, and the instruction is loaded and executed by a processor to implement the warehousing resource allocation method of any of claims 1-6.
CN201910892462.1A 2019-09-20 2019-09-20 Storage resource allocation method and device, electronic equipment and storage medium Pending CN110648099A (en)

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Cited By (8)

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CN112184100A (en) * 2020-09-09 2021-01-05 北京每日优鲜电子商务有限公司 Article inventory monitoring method and device, electronic equipment and computer readable medium
CN112200390A (en) * 2020-11-13 2021-01-08 同济大学 Distribution estimation algorithm-based unmanned shipment warehouse goods carrying shelf space planning method
CN113139761A (en) * 2020-01-16 2021-07-20 北京京东乾石科技有限公司 Method, apparatus and computer readable storage medium for storing goods in warehouse
CN113256192A (en) * 2020-02-07 2021-08-13 北京京东振世信息技术有限公司 Warehouse article planning method and device
CN113298451A (en) * 2020-04-30 2021-08-24 阿里巴巴集团控股有限公司 Distribution method, distribution device, distribution equipment and storage medium
CN113919764A (en) * 2020-07-07 2022-01-11 上海顺如丰来技术有限公司 Method and device for determining in-bin replenishment quantity, computer equipment and storage medium
CN114186903A (en) * 2020-09-14 2022-03-15 上海顺如丰来技术有限公司 Warehouse product selection method and device, computer equipment and storage medium
CN115330299A (en) * 2022-07-22 2022-11-11 上海聚水潭网络科技有限公司 Hot area planning method and system based on integer planning and electronic equipment

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Publication number Priority date Publication date Assignee Title
CN113139761A (en) * 2020-01-16 2021-07-20 北京京东乾石科技有限公司 Method, apparatus and computer readable storage medium for storing goods in warehouse
CN113256192A (en) * 2020-02-07 2021-08-13 北京京东振世信息技术有限公司 Warehouse article planning method and device
CN113298451A (en) * 2020-04-30 2021-08-24 阿里巴巴集团控股有限公司 Distribution method, distribution device, distribution equipment and storage medium
CN113919764A (en) * 2020-07-07 2022-01-11 上海顺如丰来技术有限公司 Method and device for determining in-bin replenishment quantity, computer equipment and storage medium
CN112184100A (en) * 2020-09-09 2021-01-05 北京每日优鲜电子商务有限公司 Article inventory monitoring method and device, electronic equipment and computer readable medium
CN114186903A (en) * 2020-09-14 2022-03-15 上海顺如丰来技术有限公司 Warehouse product selection method and device, computer equipment and storage medium
CN112200390A (en) * 2020-11-13 2021-01-08 同济大学 Distribution estimation algorithm-based unmanned shipment warehouse goods carrying shelf space planning method
CN112200390B (en) * 2020-11-13 2022-08-19 同济大学 Distribution estimation algorithm-based unmanned shipment warehouse goods carrying shelf space planning method
CN115330299A (en) * 2022-07-22 2022-11-11 上海聚水潭网络科技有限公司 Hot area planning method and system based on integer planning and electronic equipment
CN115330299B (en) * 2022-07-22 2023-09-01 上海聚水潭网络科技有限公司 Hot zone planning method and system based on integer programming and electronic equipment

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