CN112085441A - Information generation method and device, electronic equipment and computer readable medium - Google Patents
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Abstract
The embodiment of the disclosure discloses a method and a device for generating information, electronic equipment and a computer readable medium. One embodiment of the method comprises: acquiring an article estimated acquisition quantity set and an article quality guarantee attribute value set of an article in a preset future time period; acquiring article related information of an article; acquiring an item order quantity set, an item ex-warehouse quantity set and an item satisfaction quantity set of an item in a preset historical time period; generating an item availability ratio and an item satisfaction ratio based on the item order quantity set, the item ex-warehouse quantity set and the item satisfaction quantity set; and generating the estimated goods ordering amount of the goods in the preset future time period based on the existing inventory of the micro-warehouse, the existing inventory of the total warehouse, the goods supplement amount, the goods acquisition amount in unit time, the goods availability ratio, the goods satisfaction rate, the estimated goods acquisition amount set and the quality guarantee attribute value set of the goods. This embodiment improves the turnover rate of the article.
Description
Technical Field
Embodiments of the present disclosure relate to the field of computer technologies, and in particular, to an information generation method, an information generation device, an electronic device, and a computer-readable medium.
Background
With the development of internet technology and the arrival of the e-commerce era, more and more online shopping platforms appear. The user may select items by browsing the web pages of the online shopping platform. At present, the online shopping platform usually makes orders according to the historical ordering amount of the goods.
However, ordering the order according to the historical order quantity of the articles has the following technical problems:
firstly, ordering according to historical related data of the articles, so that the accuracy of ordering data of the articles is not high;
second, placing orders based on historical orders for articles can result in inefficient turnover of articles.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Some embodiments of the present disclosure propose information generation methods, apparatuses, electronic devices, and computer readable media to solve one or more of the technical problems mentioned in the background section above.
In a first aspect, some embodiments of the present disclosure provide an information generating method, including: acquiring an article estimated acquisition quantity set and an article quality guarantee attribute value set of an article in a preset future time period; acquiring article-related information of the article, wherein the article-related information includes: a micro-warehouse existing stock quantity corresponding to the article, a total warehouse existing stock quantity corresponding to the article, an article replenishment quantity corresponding to the article, and an article acquisition quantity per unit time corresponding to the article; acquiring an item order quantity set, an item ex-warehouse quantity set and an item satisfaction quantity set of the items in a preset historical time period, wherein the duration of the preset historical time period is equal to the duration of the preset future time period; generating an item availability ratio and an item satisfaction ratio based on the item order quantity set, the item ex-warehouse quantity set and the item satisfaction quantity set; and generating the estimated ordered goods quantity of the goods in the preset future time period based on the existing micro-warehouse inventory quantity, the total warehouse inventory quantity, the goods replenishment quantity, the goods acquisition quantity in the unit time, the goods availability ratio, the goods satisfaction ratio, the estimated goods acquisition quantity set and the quality guarantee attribute value set.
In a second aspect, some embodiments of the present disclosure provide an information generating apparatus, the apparatus comprising: a first obtaining unit configured to obtain a set of article pre-estimation obtaining amounts and a set of article quality guarantee attribute values of an article in a preset future time period; a second obtaining unit configured to obtain item-related information of the item, wherein the item-related information includes: a micro-warehouse existing stock quantity corresponding to the article, a total warehouse existing stock quantity corresponding to the article, an article replenishment quantity corresponding to the article, and an article acquisition quantity per unit time corresponding to the article; a third obtaining unit configured to obtain an item order quantity set, an item ex-warehouse quantity set, and an item satisfaction quantity set of the item within a preset historical time period, wherein a duration of the preset historical time period is equal to a duration of the preset future time period; a first generation unit configured to generate an item availability rate and an item satisfaction rate based on the item order quantity set, the item ex-warehouse quantity set, and the item satisfaction quantity set; a second generation unit configured to generate an estimated ordered quantity of the article in the preset future time period based on the micro-warehouse existing inventory quantity, the total warehouse existing inventory quantity, the article replenishment quantity, the article acquisition quantity per unit time, the article availability ratio, the article satisfaction ratio, the estimated article acquisition quantity set, and the quality attribute value set.
In some embodiments, the generating the estimated ordered quantity of the items in the preset future time period based on the existing micro-warehouse inventory, the total warehouse inventory, the replenishment quantity of the items, the acquisition quantity of the items in the unit time, the availability rate of the items, the satisfaction rate of the items, the set of estimated acquisition quantities of the items, and the set of quality assurance attribute values includes:
sequencing each article estimated acquisition quantity in the article estimated acquisition quantity set to obtain an article estimated acquisition quantity sequence;
generating a first micro-warehouse end inventory by the following formula:
D＝[max(max(G-g，0)+(X+x1×v×z+n)-Q1，0)]，
wherein D represents the end stock quantity of the first micro warehouse, G represents the existing stock quantity of the micro warehouse, G represents the quantity of the obtained articles in the unit time, X represents the existing stock quantity of the total warehouse, and X1Representing the 1 st item ex-warehouse quantity in the item ex-warehouse quantity sequence, v representing the item availability ratio, z representing the item satisfaction ratio, n representing the item replenishment quantity, Q1A predicted acquisition amount of the 1 st article in the sequence of predicted acquisition amounts of the articles]Denotes a rounding-down operation, max (G-G, 0) denotes the maximum of G-G and the value 0, max (max (G-G, 0) + (X + X)1×v×z+n)-Q10) represents max (G-G, 0) + (X + X1×v×z+n)-Q1And the maximum of the values 0;
and generating the estimated ordered goods quantity of the goods in the preset future time period based on the first micro-warehouse end inventory quantity, the goods availability ratio, the goods satisfaction ratio, the goods ex-warehouse quantity sequence, the estimated goods obtaining quantity sequence and the goods quality attribute value set.
In some embodiments, the generating an estimated ordered quantity of the item over the preset future time period based on the first micro-warehouse end inventory quantity, the item availability rate, the item fulfillment rate, the sequence of item ex-warehouse quantities, the sequence of estimated item acquisitions, and the set of item shelf-life attribute values comprises:
generating a second micro-warehouse end inventory by the following formula:
E＝[max(D+(x2×v×z)-Q2，0)]，
wherein E represents the second micro-warehouse end inventory amount, D represents the first micro-warehouse end inventory amount, x2Representing the 2 nd item ex-warehouse quantity in the item ex-warehouse quantity sequence, v representing the item availability ratio, Z representing the item satisfaction ratio, Q2Representing the estimated quantity sequence of the articlesThe 2 nd item in the row is estimated to be acquired, max (D + (x)2×v×z)-Q20) represents D + (x)2×v×z)-Q2And the maximum value of the value 0]Represents a rounding down operation;
and generating the estimated goods ordering amount in the preset future time period based on the second micro-warehouse end inventory amount, the goods availability ratio, the goods satisfaction ratio, the goods ex-warehouse amount sequence, the goods estimated acquisition amount sequence and the goods quality attribute value set.
In some embodiments, the generating an estimated ordered quantity of the item over the preset future time period based on the second micro-warehouse end inventory quantity, the item availability rate, the item fulfillment rate, the sequence of item ex-warehouse quantities, the sequence of estimated item acquisitions, and the set of item shelf-life attribute values comprises:
based on the item estimated acquisition quantity sequence, sequencing all the item quality keeping attribute values in the item quality keeping attribute value set to obtain an item quality keeping attribute value sequence;
generating an estimated ordering quantity of the articles in the preset future time period by the following formula:
M＝[max(Q3×q3-E-x3×v×z，0)/(v×z)]，
wherein M represents the estimated order quantity of the articles in the preset future time period, Q3Representing the 3 rd estimated acquisition quantity of the article in the sequence of estimated acquisition quantities of the article, q3Representing a quality attribute value of the 3 rd item in the sequence of quality attribute values, E representing an end of second micro-warehouse inventory amount, x3Representing the quantity of the 3 rd article out of the sequence, v representing the article availability rate, Z representing the article fulfillment rate, [ 2 ]]Denotes a rounding-down operation, max (Q)3×q3-E-x3X v x z, 0) denotes the values 0 and Q3×q3-E-x3Maximum value in x v x z.
In a third aspect, some embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon which, when executed by one or more processors, cause the one or more processors to implement the method as described in the first aspect.
In a fourth aspect, some embodiments of the disclosure provide a computer readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method as described in the first aspect.
One of the above-described various embodiments of the present disclosure has the following advantageous effects: first, the item availability ratio and the item satisfaction ratio may be generated by processing the item order quantity set, the item delivery quantity set, and the item satisfaction quantity set. Therefore, a foundation is laid for predicting the estimated ordering quantity of the goods in the follow-up prediction according to the goods availability and the goods satisfaction rate. The higher the article availability and the article satisfaction rate are, the more the accuracy of the estimated ordering quantity of the subsequently predicted articles is improved. Then, an estimated ordered quantity of the goods in a preset future time period can be generated based on the existing micro-warehouse inventory, the total warehouse inventory, the goods replenishment quantity, the goods acquisition quantity in the unit time, the goods availability ratio, the goods satisfaction ratio, the estimated goods acquisition quantity set and the quality guarantee attribute value set. Optionally, the estimated ordered goods amount of the article is sent to a display device with a display function so as to be displayed. Optionally, the vehicle dispatching device in communication connection with the display device may be controlled to carry out vehicle dispatching based on the estimated goods ordering amount of the goods. Vehicle scheduling can be performed according to the estimated ordering quantity of the articles, and suitable vehicles can be arranged. Therefore, the goods transportation system is beneficial to orderly transporting and planning the transportation route of the goods, reasonably planning the transportation route, saving the transportation time and improving the turnover rate of the goods. For example, through the estimated ordering quantity of the articles, vehicles can be allocated in advance and transportation routes can be arranged, road congestion time periods are avoided, the transportation time of the articles is saved, and therefore the turnover efficiency of the articles is improved.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and features are not necessarily drawn to scale.
FIG. 1 is a schematic diagram of one application scenario of an information generation method according to some embodiments of the present disclosure;
FIG. 2 is a flow diagram of some embodiments of an information generation method according to the present disclosure;
FIG. 3 is a flow diagram of further embodiments of an information generation method according to the present disclosure;
FIG. 4 is a schematic block diagram of some embodiments of an information generating apparatus according to the present disclosure;
FIG. 5 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings. The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 is a schematic diagram of an application scenario of an information generation method according to some embodiments of the present disclosure.
In the application scenario of fig. 1, first, the computing device 101 may generate an item availability rate and an item satisfaction rate 105 according to the acquired item order quantity set 102, item ex-warehouse quantity set 103, and item satisfaction quantity set 104. Computing device 101 may then generate an item forecast order quantity 108 based on item availability and item fulfillment rates 105, item-related information 106, a set of item forecast acquisitions, and a set of item shelf attribute values 107. Finally, optionally, the computing device 101 may output the estimated order quantity 108 for the item for display on the display device 109. Alternatively, the computing device 101 may control a vehicle dispatch device 110 communicatively coupled to the display device 109 to dispatch vehicles based on the predicted order quantity 108 for the items.
The computing device 101 may be hardware or software. When the computing device is hardware, it may be implemented as a distributed cluster composed of multiple servers or terminal devices, or may be implemented as a single server or a single terminal device. When the computing device is embodied as software, it may be installed in the hardware devices enumerated above. It may be implemented, for example, as multiple software or software modules to provide distributed services, or as a single software or software module. And is not particularly limited herein.
It should be understood that the number of computing devices in FIG. 1 is merely illustrative. There may be any number of computing devices, as implementation needs dictate.
With continued reference to fig. 2, a flow 200 of some embodiments of an information generation method according to the present disclosure is shown. The method may be performed by the computing device 101 of fig. 1. The information generation method comprises the following steps:
In some embodiments, an executing body (such as the computing device shown in fig. 1) for the information generating method may obtain the set of estimated item acquisition amounts and the set of quality guarantee attribute values of the item in a preset future time period from the terminal through a wired connection manner or a wireless connection manner. The estimated quantity of the articles may be a predicted quantity of the article flow. For example, the number of purchased articles a in the next 1 hour is 10. The item shelf-life attribute value may refer to the length of time the shelf-life of the item is to be maintained. For example, the shelf life of article a is 10 days. Here, the set of item pre-estimate acquisition amounts and the set of item quality assurance attribute values for the item in the preset future time period may be a set of data stored in the terminal that is already pre-estimated to be completed.
As an example, the above-mentioned preset future time period may be "No. 5 month 4 to No. 5 month 6". 5/4, the estimated quantity of articles obtained for article a may be 15, and the quality attribute value for article a may be 10 days. 5/month 5, the estimated quantity of articles a may be 10, and the quality attribute value of articles a may be 9 days. 5/6, the estimated acquisition quantity of the article A can be 15, and the quality guarantee attribute value of the article A can be 8 days. In the preset future time period, the set of the estimated article acquisition quantity of the article a is "15, 10, 15", and the set of the article quality guarantee attribute value of the article a is "10, 9, 8".
In some embodiments, the execution subject may obtain the article-related information of the article from a terminal. Wherein the item-related information includes: the present amount of the micro warehouse corresponding to the article, the present amount of the total warehouse corresponding to the article, the replenishment amount of the article corresponding to the article, and the acquisition amount of the article per unit time corresponding to the article. The existing micro-warehouse inventory corresponding to the above-mentioned items refers to the existing quantity of the items a in the micro-warehouse B (for example, the quantity of the items a stored in the micro-warehouse B is 20), wherein the micro-warehouse may be a single physical store or a virtual store, or a single small warehouse. The total stock quantity of the total warehouse corresponding to the above items refers to the existing quantity of the items a in the total warehouse C (for example, the quantity of the items a stored in the total warehouse C is 100), wherein the total warehouse may refer to a large storage warehouse and may store many items. The article replenishment amount corresponding to the above-described article may refer to the number of articles a sent from the total bin to the micro bin. The item acquisition amount per unit time refers to the number of circulation of items per unit time (for example, the number of purchased items a is 20 in 24 hours).
As an example, the existing stock quantity of micro-silos corresponding to the above items may be "20". The total stock available in the warehouse corresponding to the above items may be "50". The supplement amount of the item corresponding to the above item may be "10". The article pickup amount per unit time corresponding to the above-described article may be "5".
In some embodiments, the execution subject may obtain, from a terminal, an item order quantity set, an item ex-warehouse quantity set, and an item satisfaction quantity set of the item within a preset historical time period. Wherein the duration of the preset historical time period is equal to the duration of the preset future time period. The above item order quantity refers to the quantity of the items ordered from the micro-warehouse to the main warehouse (for example, the quantity of the items A ordered from the micro-warehouse B to the main warehouse C is 20, that is, the order quantity is 20). Here, the quantity of the articles discharged refers to the number of articles a sent from the total bin to the micro-bin (for example, the number of articles a sent from the total bin C to the micro-bin B is 18). The article satisfaction amount refers to the number of articles satisfying the condition in the article delivery amount (for example, the delivery amount of article a is 18, and the number of articles a satisfying the condition is 16, that is, the article satisfaction amount is 16).
As an example, the above-mentioned preset history period may be "No. 5 month 1 to No. 5 month 3". No. 5/month 1, the item order amount for item a may be 20, the item ex-warehouse amount may be 18, and the item satisfaction amount may be 16. No. 5/2, the article order amount of article a may be 15, the article ex-warehouse amount may be 14, and the article full amount may be 13. No. 5/3, the item order amount of item a may be 18, the item ex-warehouse amount may be 18, and the item satisfaction amount may be 16. The item order quantity set for item a is "20, 15, 18" during the predetermined historical time period. The above-mentioned collection of the article shipment amounts for article a is "18, 14, 18". The above item satisfaction volume set for item a is "16, 13, 16".
And step 204, generating the item availability and the item satisfaction rate based on the item order quantity set, the item ex-warehouse quantity set and the item satisfaction quantity set.
In some embodiments, the executing agent may generate the item availability rate and the item satisfaction rate by:
first, determining the sum of the order quantity of each item in the order quantity set.
As an example, the above item order quantity set may be "20, 15, 18". It is determined that the sum of the individual order quantities in the above item order quantity set is "53".
And secondly, determining the sum of each item ex-warehouse quantity in the item ex-warehouse quantity set.
By way of example, the set of inventory amounts may be "18, 14, 18". It is determined that the sum of the inventory amounts of the respective items in the set of inventory amounts is "50".
And thirdly, determining the sum of the full quantities of all the articles in the article satisfaction quantity set.
As an example, the above-mentioned item satisfaction volume set may be "16, 13, 16". The sum of the sufficiency of each item in the above-mentioned item satisfaction volume set is determined to be "45".
And fourthly, determining the ratio of the sum of each goods delivery quantity in the goods delivery quantity set to the sum of each goods order quantity in the goods order quantity set as the goods availability ratio. Here, the ratio retains two significant digits after the decimal point.
As an example, the sum of the inventory amounts of the respective items in the above-described set of inventory amounts may be "50". The sum of the individual order quantities in the above-described item order quantity set may be "53". The division of "50" by "53" yields a ratio of "0.94". The ratio "0.94" is determined as the item availability.
And fifthly, determining the ratio of the sum of the full quantity of each article in the article satisfaction quantity set to the sum of the delivery quantity of each article in the article delivery quantity set as an article satisfaction rate.
By way of example, the sum of the above-described quantity satisfaction for each item in the quantity set may be "45". The sum of the delivery amounts of the respective items in the set of delivery amounts may be "50". The division of "45" by "50" yields a ratio of "0.9". The ratio "0.9" was determined as the item satisfaction rate.
In some optional implementations of some embodiments, the executing agent may generate the item availability rate and the item satisfaction rate by:
firstly, ordering each item order quantity in the item order quantity set to obtain an item order quantity sequence. Here, the sorting manner may be sorting in chronological order.
As an example, the above item order quantity set may be "18, 20, 15". And sequencing the order quantities of all the items in the order quantity set according to the sequence of time, wherein the obtained order quantity sequence of the items is 20,15 and 18.
And secondly, determining the ratio of each item order quantity in the item order quantity sequence to the item ex-warehouse quantity in the item ex-warehouse quantity set corresponding to the item order quantity to obtain a ratio sequence as a first ratio sequence. Here, the ratio retains the three significant digits after the decimal point.
By way of example, the above-described item order quantity sequence may be "20, 15, 18". The set of inventory amounts for the items is "18, 14, 18". The article ex-warehouse quantity '18' is divided by the corresponding article order quantity '20', and the ratio '0.9' is obtained. The article ex-warehouse quantity '14' and the corresponding article order quantity '15' are subjected to division processing, and the ratio '0.933' is obtained. The article delivery amount "18" is divided by the above article order amount "18" to obtain a ratio "1". By the above-described processing, the ratio sequence "0.9, 0.933, 1" was obtained. And taking the ratio sequence as a first ratio sequence.
And thirdly, determining the average value of all the ratios in the first ratio sequence as the article availability ratio.
As an example, the first ratio sequence may be "0.9, 0.933, 1". The average value of the respective ratios in the above-described first ratio series is "0.944". "0.944" is determined as item availability.
And fourthly, sequencing the warehouse-out quantities of all the articles in the warehouse-out quantity set to obtain an article warehouse-out quantity sequence.
By way of example, the set of inventory amounts may be "18, 18, 14". And sequencing the warehouse-out quantities of all the articles in the warehouse-out quantity set according to the sequence of time, wherein the obtained sequence of the warehouse-out quantities of the articles is '18, 14 and 18'.
And fifthly, determining the ratio of each article delivery quantity in the article delivery quantity sequence to the article full quantity in the article satisfaction quantity set corresponding to the article delivery quantity, and obtaining a ratio sequence as a second ratio sequence.
As an example, the above-described sequence of the quantity of the items out of the warehouse may be "18, 14, 18". The above-mentioned item satisfaction volume set may be "16, 13, 16". The product full "16" is divided by the product out "18" to produce a ratio "0.889". The full quantity of the product "13" is divided by the quantity of the product "14" to generate a ratio "0.928". The product full "16" is divided by the product out "18" to produce a ratio "0.889". The ratio sequence "0.889, 0.928, 0.889" was obtained as the second ratio sequence.
And sixthly, determining the average value of all ratios in the second ratio sequence as the product satisfaction rate.
As an example, the second ratio sequence may be "0.889, 0.928, 0.889". The average value of the respective ratios in the above-described second ratio sequence is "0.902". "0.902" is determined as the item satisfaction rate.
In some embodiments, the executing agent may generate the predicted ordered quantity of the articles in the preset future time period by:
the first step is to determine the average value of each estimated article acquisition quantity in the estimated article acquisition quantity set. Here, the result of the averaging takes an integer.
As an example, the above-mentioned item pre-estimate acquisition amount set may be "15, 10, 15". And determining the average value of the estimated acquisition quantity of each article in the estimated acquisition quantity set of the articles as '13'.
And secondly, determining the mean value of the quality guarantee attribute values of all the articles in the quality guarantee attribute value set of the articles.
As an example, the set of item shelf-life attribute values may be "10, 9, 8". And determining the average value of the quality guarantee attribute values of the products in the product quality guarantee attribute value set to be 9.
Thirdly, generating the estimated ordering quantity of the articles in the preset future time period by the following formula:
N＝max(A×B+G-X-n×v×z-g，0)。
wherein N represents the estimated ordering quantity of the goods. A represents the average value of the estimated acquisition quantity of each article in the estimated acquisition quantity set of the articles. And B represents the mean value of the quality guarantee attribute values of the products in the product quality guarantee attribute value set. G represents the existing stock quantity of the micro warehouse. X represents the existing stock of the above-mentioned total bin. n represents the above supplement amount. v represents the item availability rate. Z represents the above-mentioned article satisfaction rate. g represents the amount of the article taken per unit time. Here, the numerical value of the estimated order quantity of the article is an integer.
As an example, the average value a of each estimated quantity of the articles in the set of estimated quantities of articles may be "13". The mean value B of the individual product quality attribute values in the set of product quality attribute values may be "9". The existing inventory G of the micro-warehouse may be "20". The total stock quantity X may be "50". The above-mentioned item replenishment amount n may be "10". The above item availability ratio v may be "0.94". The article satisfaction rate Z may be "0.9". The above-mentioned article pickup amount g per unit time may be "5". Generating an estimated ordered quantity of the articles within the preset future time period by the following formula:
N＝max(13×9+20-50-10×0.94×0.9-5，0)＝73。
optionally, the estimated ordered goods amount of the article is sent to a display device with a display function for displaying. And controlling vehicle dispatching equipment in communication connection with the display equipment to dispatch the vehicle based on the estimated ordering quantity of the articles.
As an example, the estimated order quantity "73" of the article a is sent to the display device B to be displayed. And controlling a vehicle dispatching device '001' in communication connection with the display device B to allocate the estimated ordering quantity of the articles transported by the vehicle A.
One of the above-described various embodiments of the present disclosure has the following advantageous effects: first, the item availability ratio and the item satisfaction ratio may be generated by processing the item order quantity set, the item delivery quantity set, and the item satisfaction quantity set. Therefore, a foundation is laid for predicting the estimated ordering quantity of the goods in the follow-up prediction according to the goods availability and the goods satisfaction rate. The higher the article availability and the article satisfaction rate are, the more the accuracy of the estimated ordering quantity of the subsequently predicted articles is improved. Then, an estimated ordered quantity of the goods in a preset future time period can be generated based on the existing micro-warehouse inventory, the total warehouse inventory, the goods replenishment quantity, the goods acquisition quantity in the unit time, the goods availability ratio, the goods satisfaction ratio, the estimated goods acquisition quantity set and the quality guarantee attribute value set. Optionally, the estimated ordered goods amount of the article is sent to a display device with a display function so as to be displayed. Optionally, the vehicle dispatching device in communication connection with the display device may be controlled to carry out vehicle dispatching based on the estimated goods ordering amount of the goods. Vehicle scheduling can be performed according to the estimated ordering quantity of the articles, and suitable vehicles can be arranged. Therefore, the goods transportation system is beneficial to orderly transporting and planning the transportation route of the goods, reasonably planning the transportation route, saving the transportation time and improving the turnover rate of the goods. For example, through the estimated ordering quantity of the articles, vehicles can be allocated in advance and transportation routes can be arranged, road congestion time periods are avoided, the transportation time of the articles is saved, and therefore the turnover efficiency of the articles is improved. The above optional matters serve as an inventive point of the present disclosure, thereby solving the technical problem two mentioned in the background art.
With further reference to fig. 3, a flow 300 of further embodiments of an information generation method according to the present disclosure is shown. The method may be performed by the computing device 101 of fig. 1. The information generation method comprises the following steps:
And 304, generating the item availability and the item satisfaction rate based on the item order quantity set, the item ex-warehouse quantity set and the item satisfaction quantity set.
In some embodiments, the specific implementation manner and technical effects of steps 301 and 304 may refer to steps 201 and 204 in the embodiments corresponding to fig. 2, which are not described herein again.
In some embodiments, the execution main body may sequence the estimated acquisition amount of each article in the estimated acquisition amount set of articles according to a chronological order to obtain an estimated acquisition amount sequence of articles.
As an example, the above-mentioned item pre-estimate acquisition amount set is "10, 15, 15". And sequencing each estimated article acquisition quantity in the estimated article acquisition quantity set according to the time sequence, wherein the obtained estimated article acquisition quantity sequence is '15, 10, 15'.
And step 306, generating a first micro-warehouse end inventory through a formula.
In some embodiments, the execution entity may generate the first micro-warehouse end-of-term inventory amount by:
D＝[max(max(G-g，0)+(X+x1×v×z+n)-Q1，0)]。
where D represents the first micro-warehouse end inventory amount. G represents the existing stock quantity of the micro warehouse. g represents the amount of the article taken per unit time. X represents the existing stock of the above-mentioned total bin. x is the number of1The 1 st article delivery amount in the article delivery amount sequence is shown. v represents the item availability rate. z represents the above-mentioned article satisfaction rate. n represents the above supplement amount. Q1The estimated acquisition quantity of the 1 st article in the estimated acquisition quantity sequence of the articles is shown. []Indicating a rounding down operation. max (G-G, 0) represents the maximum of G-G and the value 0.
max(max(G-g，0)+(X+x1×v×z+n)-Q10) represents max (G-G, 0) + (X + X1×v×z+n)-Q1And the maximum value of the values 0.
As an example, the above-described existing micro-warehouse stock amount G may be "20". The above-mentioned article pickup amount g per unit time may be "5". The total stock quantity X may be "50". The 1 st article delivery amount x in the article delivery amount sequence1Is "18". The above item availability ratio v may be "0.94". The above-mentioned article satisfaction rate z may be "0.9". The above-mentioned item replenishment amount n may be "10". The estimated acquisition quantity Q of the 1 st article in the estimated acquisition quantity sequence of the articles1Is "15". The first micro-warehouse end inventory is generated by:
D＝[max(max(20-5，0)+(50+18×0.94×0.9+10)-15，0)]＝75。
and 307, generating the estimated ordered goods quantity of the goods in the preset future time period based on the end-of-micro-warehouse stock quantity, the goods availability ratio, the goods satisfaction ratio, the goods delivery quantity sequence, the estimated goods quantity sequence and the quality guarantee attribute value set of the goods.
In some embodiments, the executing agent may generate the predicted ordered quantity of the articles in the preset future time period by:
first, generating a second micro-warehouse end inventory through the following formula:
E＝[max(D+(x2×v×z)-Q2，0)]。
where E represents the second micro-warehouse end inventory amount. D represents the first micro-warehouse end inventory amount. x is the number of2And the 2 nd article delivery quantity in the article delivery quantity sequence is represented. v represents the item availability rate. z represents the above-mentioned article satisfaction rate. Q2The estimated acquisition quantity of the 2 nd article in the estimated acquisition quantity sequence of the articles is shown. max (D + (x)2×v×z)-Q20) represents D + (x)2×v×z)-Q2And the maximum value of the values 0. []Indicating a rounding down operation.
As an example, the above-described first micro-warehouse end inventory amount D may be "75". The 2 nd article delivery quantity x in the article delivery quantity sequence2May be "14". The above item availability ratio v may be "0.94". The above-mentioned article satisfaction rate z may be "0.9". The 2 nd estimated quantity Q in the above sequence2May be "10". Generating a second micro-warehouse end inventory by:
E＝[max(75+(14×0.94×0.9)-10，0)]＝76。
and secondly, generating the estimated goods ordering quantity of the goods in the preset future time period based on the second micro-warehouse end inventory quantity, the goods availability ratio, the goods satisfaction ratio, the goods ex-warehouse quantity sequence, the estimated goods acquiring quantity sequence and the quality guarantee attribute value set of the goods.
In some embodiments, the second step may include the following sub-steps:
in the first sub-step, the execution body may sort the quality guarantee attribute values of the respective products in the set of product quality guarantee attribute values based on the sequence of pre-estimated product acquisition amounts to obtain a sequence of product quality guarantee attribute values. Here, the above-mentioned sequence of estimated article acquisition amounts is to sort the estimated article acquisition amounts of the same article in chronological order.
As an example, the above predicted quantity-to-be-acquired sequence of the article may be "10, 15, 15". The set of article quality attribute values may be "9, 10, 8". And sequencing the quality guarantee attribute values of the articles in the quality guarantee attribute value set of the articles, wherein the obtained quality guarantee attribute value sequence is '10, 9 and 8'.
The second substep, through the following formula, produce the goods in the time slot of reserving in the future in advance and predict the order quantity:
M＝[max(Q3×q3-E-x3×v×z，0)/(v×z)]。
wherein M represents the estimated ordered quantity of the items within the preset future time period. Q3The estimated acquisition quantity of the 3 rd article in the estimated acquisition quantity sequence of the article is shown. q. q.s3Representing the 3 rd item quality assurance attribute value in the sequence of item quality assurance attribute values. E represents the second micro-warehouse end inventory. x is the number of3And 3, the delivery quantity of the 3 rd item in the delivery quantity sequence is represented. v represents the item availability rate. z represents the above-mentioned article satisfaction rate. []Indicating a rounding down operation.
max(Q3×q3-E-x3X v x z, 0) denotes the values 0 and Q3×q3-E-x3Maximum value in x v x z.
As an example, the above-mentioned item pre-estimated acquisition quantity Q of the 3 rd item in the item pre-estimated acquisition quantity sequence3May be "15". The 3 rd quality-keeping attribute value q in the above-mentioned quality-keeping attribute value sequence3May be "8". The second end-of-micro-bin inventory level E is "76". The 3 rd article delivery quantity x in the article delivery quantity sequence3Is "18". The above item availability ratio v may be "0.94". The above-mentioned article satisfaction rate z may be "0.9". Generating an estimated ordered quantity of the articles within the preset future time period by the following formula:
M＝[max(15×8-76-18×0.94×0.9，0)/(0.94×0.9)]＝34。
one of the above-described various embodiments of the present disclosure has the following advantageous effects: the step 305-307 generates the formula of the estimated order quantity of the goods as an invention point of the present disclosure, thereby solving the technical problem one mentioned in the background art. First, the item availability ratio and the item satisfaction ratio may be generated by processing the item order quantity set, the item delivery quantity set, and the item satisfaction quantity set. Therefore, a foundation is laid for predicting the estimated ordering quantity of the goods in the follow-up prediction according to the goods availability and the goods satisfaction rate. The higher the article availability and the article satisfaction rate are, the more the accuracy of the estimated ordering quantity of the subsequently predicted articles is improved. Next, the execution body may generate a micro-warehouse end inventory amount based on the micro-warehouse existing inventory amount, the total warehouse existing inventory amount, the replenishment quantity, the quantity of acquired articles per unit time, the availability rate of articles, the satisfaction rate of articles, the set of estimated quantity of acquired articles, and the set of quality attribute values of articles. Thus, an estimated ordered quantity of items over a preset future time period is generated. Here, the influence of the estimated goods acquisition amount, the shelf life of the goods, the end stock of the micro-warehouse and the goods availability ratio and the goods satisfaction ratio on the whole goods ordering amount is considered. The influence factor of the estimated and obtained quantity of the goods is considered to determine the end stock of the micro-warehouse. The shelf life of the goods is considered to prevent the goods from being ordered too much, which leads to overstocking of the goods and thus to overdue the goods. The end stock of the micro-warehouse is considered to be used for laying the order quantity of subsequent articles and preventing the order quantity of the articles from being excessive. The item availability rate and the item fulfillment rate are considered in order to determine the actual ordered amount of the item. If the article availability and the article satisfaction are too low, the article ordering amount at the next stage is increased. Thus, the accuracy of the estimated order quantity of the articles can be improved. Then, the estimated ordering amount of the articles can be sent to a display device with a display function for displaying. Therefore, the vehicle dispatching device in communication connection with the display device can be controlled to carry out vehicle dispatching based on the estimated ordering quantity of the articles. Thus, an appropriate vehicle can be arranged according to the estimated order quantity of the articles. Therefore, the goods transportation system is beneficial to orderly transporting and planning the transportation route of the goods, reasonably planning the transportation route, saving the transportation time and improving the turnover rate of the goods. For example, through the estimated ordering quantity of the articles, vehicles can be allocated in advance and transportation routes can be arranged, road congestion time periods are avoided, the transportation time of the articles is saved, and therefore the turnover efficiency of the articles is improved.
With further reference to fig. 4, as an implementation of the above-described method for the above-described figures, the present disclosure provides some embodiments of an information generating apparatus, which correspond to those of the method embodiments described above for fig. 2, and which may be applied in various electronic devices in particular.
As shown in fig. 4, the information generating apparatus 400 of some embodiments includes: an acquisition unit 401, a second acquisition unit 402, a third acquisition unit 403, a first generation unit 404, and a second generation unit 405. Wherein, the first obtaining unit 401 is configured to obtain a set of pre-estimated item acquisition amounts and a set of item quality assurance attribute values of the item within a preset future time period. A second obtaining unit 402, configured to obtain item-related information of the item, where the item-related information includes: the present amount of the micro warehouse corresponding to the article, the present amount of the total warehouse corresponding to the article, the replenishment amount of the article corresponding to the article, and the acquisition amount of the article per unit time corresponding to the article. A third obtaining unit 403, configured to obtain an item order quantity set, an item ex-warehouse quantity set, and an item satisfaction quantity set of the item within a preset historical time period, where a duration of the preset historical time period is equal to a duration of the preset future time period. A first generating unit 404 configured to generate an item availability rate and an item satisfaction rate based on the item order quantity set, the item ex-warehouse quantity set, and the item satisfaction quantity set. A second generating unit 405 configured to generate an estimated ordered quantity of the items in the preset future time period based on the micro-warehouse existing inventory quantity, the total warehouse existing inventory quantity, the item replenishment quantity, the item acquisition quantity per unit time, the item availability ratio, the item satisfaction ratio, the set of estimated item acquisition quantities, and the set of item quality attribute values.
It will be understood that the elements described in the apparatus 400 correspond to various steps in the method described with reference to fig. 2. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 400 and the units included therein, and will not be described herein again.
Referring now to FIG. 5, a block diagram of an electronic device (e.g., computing device 101 of FIG. 1)500 suitable for use in implementing some embodiments of the present disclosure is shown. The server shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 5, electronic device 500 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM 502, and the RAM503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
Generally, the following devices may be connected to the I/O interface 505: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; storage devices 508 including, for example, magnetic tape, hard disk, etc.; and a communication device 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 5 illustrates an electronic device 500 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 5 may represent one device or may represent multiple devices as desired.
In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network via the communication means 509, or installed from the storage means 508, or installed from the ROM 502. The computer program, when executed by the processing device 501, performs the above-described functions defined in the methods of some embodiments of the present disclosure.
It should be noted that the computer readable medium described above in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the apparatus; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring an article estimated acquisition quantity set and an article quality guarantee attribute value set of an article in a preset future time period; acquiring article-related information of the article, wherein the article-related information includes: a micro-warehouse existing stock quantity corresponding to the article, a total warehouse existing stock quantity corresponding to the article, an article replenishment quantity corresponding to the article, and an article acquisition quantity per unit time corresponding to the article; acquiring an item order quantity set, an item ex-warehouse quantity set and an item satisfaction quantity set of the items in a preset historical time period, wherein the duration of the preset historical time period is equal to the duration of the preset future time period; generating an item availability ratio and an item satisfaction ratio based on the item order quantity set, the item ex-warehouse quantity set and the item satisfaction quantity set; and generating the estimated ordered goods quantity of the goods in the preset future time period based on the existing micro-warehouse inventory quantity, the total warehouse inventory quantity, the goods replenishment quantity, the goods acquisition quantity in the unit time, the goods availability ratio, the goods satisfaction ratio, the estimated goods acquisition quantity set and the quality guarantee attribute value set.
Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in some embodiments of the present disclosure may be implemented by software, and may also be implemented by hardware. The described units may also be provided in a processor, and may be described as: a processor includes a first acquisition unit, a second acquisition unit, a third acquisition unit, a first generation unit, and a second generation unit. The names of these units do not in some cases constitute a limitation to the unit itself, and for example, the first generation unit may be further described as "a unit that generates an item availability rate and an item satisfaction rate based on the item order quantity set, the item ex-warehouse quantity set, and the item satisfaction quantity set".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept as defined above. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.
Claims (6)
1. An information generating method, comprising:
acquiring an article estimated acquisition quantity set and an article quality guarantee attribute value set of an article in a preset future time period;
acquiring article-related information of the article, wherein the article-related information comprises: an existing micro-warehouse inventory amount corresponding to the item, a total warehouse inventory amount corresponding to the item, an item replenishment amount corresponding to the item, and an item acquisition amount per unit time corresponding to the item;
acquiring an item order quantity set, an item ex-warehouse quantity set and an item satisfaction quantity set of the items in a preset historical time period, wherein the duration of the preset historical time period is equal to the duration of the preset future time period;
generating an item availability ratio and an item satisfaction ratio based on the item order quantity set, the item ex-warehouse quantity set and the item satisfaction quantity set;
and generating the estimated goods ordering amount of the goods in the preset future time period based on the existing inventory of the micro-warehouse, the existing inventory of the total warehouse, the goods supplement amount, the goods acquisition amount in unit time, the goods availability ratio, the goods satisfaction rate, the estimated goods acquisition amount set and the quality guarantee attribute value set of the goods.
2. The method of claim 1, wherein the method further comprises:
sending the estimated ordering quantity of the articles to a display device with a display function for displaying;
and controlling a vehicle scheduling device in communication connection with the display device to perform vehicle scheduling based on the estimated ordering quantity of the articles.
3. The method of claim 2, wherein generating an item availability rate and an item fulfillment rate based on the set of item order quantities, the set of item ex-warehouse quantities, and the set of item fulfillment quantities comprises:
sequencing each item order quantity in the item order quantity set to obtain an item order quantity sequence;
determining the ratio of each item order quantity in the item order quantity sequence to the item ex-warehouse quantity in the item ex-warehouse quantity set corresponding to the item order quantity to obtain a ratio sequence as a first ratio sequence;
determining the average value of all the ratios in the first ratio sequence as the item availability ratio;
sequencing each article ex-warehouse quantity in the article ex-warehouse quantity set to obtain an article ex-warehouse quantity sequence;
determining the ratio of each article ex-warehouse quantity in the article ex-warehouse quantity sequence to the full quantity of articles in the article satisfaction quantity set corresponding to the article ex-warehouse quantity, and obtaining a ratio sequence as a second ratio sequence;
and determining the average value of all ratios in the second ratio sequence as the article satisfaction rate.
4. An information generating apparatus comprising:
a first obtaining unit configured to obtain a set of article pre-estimation obtaining amounts and a set of article quality guarantee attribute values of an article in a preset future time period;
a second acquisition unit configured to acquire item-related information of the item, wherein the item-related information includes: an existing micro-warehouse inventory amount corresponding to the item, a total warehouse inventory amount corresponding to the item, an item replenishment amount corresponding to the item, and an item acquisition amount per unit time corresponding to the item;
a third obtaining unit configured to obtain an item order quantity set, an item ex-warehouse quantity set, and an item satisfaction quantity set of the item within a preset historical time period, wherein a duration of the preset historical time period is equal to a duration of the preset future time period;
a first generation unit configured to generate an item availability rate and an item satisfaction rate based on the item order quantity set, the item ex-warehouse quantity set, and the item satisfaction quantity set;
a second generation unit configured to generate an estimated ordered quantity of the items in the preset future time period based on the existing micro-warehouse inventory, the total warehouse inventory, the replenishment quantity of the items, the quantity of the acquired items per unit time, the availability rate of the items, the satisfaction rate of the items, the set of estimated acquired items of the items, and the set of quality assurance attribute values.
5. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon;
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-3.
6. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1-3.
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