CN112016859A - Method and device for determining configuration duration - Google Patents
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Abstract
The invention discloses a method and a device for determining configuration duration, and relates to the technical field of logistics. One embodiment of the method comprises: acquiring a historical line data set, dividing the historical line data set based on a preset cross validation rule, and generating at least one group of line training data set and line testing data set; generating a target configuration time length table according to the at least one group of line training data sets and the line testing data sets, wherein the configuration time length table comprises at least one line and configuration time length corresponding to the at least one line; and receiving and analyzing the configuration duration request to obtain a target line, and matching the configuration duration corresponding to the target line based on the target configuration duration table. According to the method and the device, the accuracy of determining the configuration duration can be improved, so that the ex-warehouse efficiency of the articles can be guaranteed, and the user experience is improved.
Description
Technical Field
The invention relates to the technical field of logistics, in particular to a method and a device for determining configuration duration.
Background
With the advent of the intelligent era, more and more users select online shopping and delivery to home shopping modes, which promotes the rapid development of the logistics distribution industry. In order to increase the distribution speed of the articles and improve the delivery efficiency of the articles, the same articles are usually stored in distribution centers of different regions. When goods are out of stock in a certain bin of a certain distribution center or the warehousing needs to be adjusted, the system can manually or automatically generate a goods configuration list, and the logistics system is responsible for conveying the goods, so that the goods can be allocated among the bins of different distribution centers. Therefore, in order not to affect the delivery of the articles, it is important to determine the accuracy of the configuration time of the articles among different distribution centers.
In the prior art, the configuration time of each line is configured and maintained manually, namely, the configuration staff sets the configuration time of the goods from the originating bin to the destination bin according to experience even in the absence of actual experience. However, in the prior art, random factors and too many lines in actual operation are considered, and it is difficult to manually adjust and optimize the configuration time of each configuration line, which may cause a certain deviation between the actual arrival time and the configuration arrival time, further affect the delivery efficiency of the articles, and reduce user experience.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for determining a configuration duration, which can improve accuracy of determining the configuration duration, thereby ensuring efficiency of delivering articles from a warehouse and improving user experience.
To achieve the above object, according to a first aspect of the embodiments of the present invention, a method for determining a configuration duration is provided.
The method for determining the configuration duration according to the embodiment of the invention comprises the following steps: acquiring a historical line data set, and dividing the historical line data set based on a preset cross validation rule to generate at least one group of line training data set and line testing data set; generating a target configuration time length table according to the at least one group of line training data sets and the line testing data sets, wherein the configuration time length table comprises at least one line and configuration time length corresponding to the at least one line; and receiving and analyzing a configuration duration request to obtain a target line, and matching the configuration duration corresponding to the target line based on the target configuration duration table.
Optionally, the generating a target configuration time length table according to the at least one group of line training data sets and line testing data sets includes: aiming at a group of line training data sets and line testing data sets in the at least one group of line training data sets and line testing data sets, training the line training data sets to obtain an alternative configuration time length set; selecting the optimal configuration time length of at least one line corresponding to the group of line training data sets and the line testing data sets from the alternative configuration time length sets according to the alternative configuration time length sets and the line testing data sets; calculating the average value or the maximum value of the optimal configuration duration of at least one line corresponding to each group of line training data sets and line testing data sets to obtain the configuration duration of the at least one line so as to generate a new configuration duration table; and updating the original configuration time length table by using the new configuration time length table to obtain the target configuration time length table.
Optionally, the training the line training data set to obtain an alternative configuration duration set includes: setting a training aggregation rule according to the number of the source distribution center, the target distribution center and the articles, and grouping the line training data sets according to the training aggregation rule to obtain at least one training line; and acquiring an alternative configuration time length set of the at least one training line according to the set time length initial value, the set time length step value and the set time length number of the at least one training line.
Optionally, the selecting, according to the candidate configuration duration set and the line test data set, an optimal configuration duration of at least one line corresponding to the group of line training data sets and the line test data set from the candidate configuration duration set includes: matching is carried out by utilizing the alternative configuration time length set and the line test data set based on the training aggregation rule to obtain a matched line test data set; setting a test aggregation rule according to a source distribution center warehouse, a target distribution center warehouse and the number of articles, and grouping the matched line test data sets according to the test aggregation rule to obtain the at least one line and an alternative configuration time set corresponding to the at least one line; and selecting the optimal configuration time length of the at least one line from the alternative configuration time length set corresponding to the at least one line according to a preset test index.
Optionally, the preset cross validation rule includes a preset division number and a preset division ratio; and the step of dividing the historical line data set based on a preset cross validation rule to generate at least one group of line training data set and line testing data set, which comprises the following steps: and dividing the historical line data set by using the preset dividing times and the preset dividing proportion to obtain at least one group of line training data set and line testing data set.
To achieve the above object, according to a second aspect of the embodiments of the present invention, there is provided an apparatus for determining a configuration duration.
The device for determining the configuration time length of the embodiment of the invention comprises the following steps: the system comprises a dividing module, a judging module and a judging module, wherein the dividing module is used for acquiring a historical line data set, dividing the historical line data set based on a preset cross validation rule and generating at least one group of line training data set and line testing data set; a generating module, configured to generate a target configuration time length table according to the at least one group of line training data sets and the line testing data sets, where the configuration time length table includes at least one line and a configuration time length corresponding to the at least one line; and the matching module is used for receiving and analyzing the configuration duration request to obtain a target line and matching the configuration duration corresponding to the target line based on the target configuration duration table.
Optionally, the generating module is further configured to: aiming at a group of line training data sets and line testing data sets in the at least one group of line training data sets and line testing data sets, training the line training data sets to obtain an alternative configuration time length set; selecting the optimal configuration time length of at least one line corresponding to the group of line training data sets and the line testing data sets from the alternative configuration time length sets according to the alternative configuration time length sets and the line testing data sets; calculating the average value or the maximum value of the optimal configuration duration of at least one line corresponding to each group of line training data sets and line testing data sets to obtain the configuration duration of the at least one line so as to generate a new configuration duration table; and updating the original configuration time length table by using the new configuration time length table to obtain the target configuration time length table.
Optionally, the generating module is further configured to: setting a training aggregation rule according to the number of the source distribution center, the target distribution center and the articles, and grouping the line training data sets according to the training aggregation rule to obtain at least one training line; and acquiring an alternative configuration time length set of the at least one training line according to the set time length initial value, the set time length step value and the set time length number of the at least one training line.
Optionally, the generating module is further configured to: matching is carried out by utilizing the alternative configuration time length set and the line test data set based on the training aggregation rule to obtain a matched line test data set; setting a test aggregation rule according to a source distribution center warehouse, a target distribution center warehouse and the number of articles, and grouping the matched line test data sets according to the test aggregation rule to obtain the at least one line and an alternative configuration time set corresponding to the at least one line; and selecting the optimal configuration time length of the at least one line from the alternative configuration time length set corresponding to the at least one line according to a preset test index.
Optionally, the preset cross validation rule includes a preset division number and a preset division ratio; and the partitioning module is further configured to: and dividing the historical line data set by using the preset dividing times and the preset dividing proportion to obtain at least one group of line training data set and line testing data set.
To achieve the above object, according to a third aspect of embodiments of the present invention, there is provided an electronic apparatus.
An electronic device of an embodiment of the present invention includes: one or more processors; the storage device is used for storing one or more programs, and when the one or more programs are executed by one or more processors, the one or more processors implement the method for determining the configuration duration according to the embodiment of the invention.
To achieve the above object, according to a fourth aspect of embodiments of the present invention, there is provided a computer-readable medium.
A computer-readable medium of an embodiment of the present invention stores thereon a computer program, and when the computer program is executed by a processor, the computer program implements a method for determining a configuration time length of an embodiment of the present invention.
One embodiment of the above invention has the following advantages or benefits: because the acquired historical line data set is analyzed based on the preset cross validation rule, the configuration duration corresponding to the target line can be inquired from the generated target configuration duration table, the technical problem that the line configuration duration obtained through manual configuration and maintenance has a certain deviation from the actual arrival time in the prior art is solved, the warehouse-out efficiency of the articles is guaranteed, and the user experience effect is improved. In addition, in the method for generating the target configuration time length table, the optimal configuration time length corresponding to each group of the line training data sets and the line testing data sets is calculated respectively, and then the target configuration time length table is generated by a method of solving the mean value or the maximum value, so that the accuracy of determining the configuration time length can be improved. In addition, in the method for acquiring the alternative configuration time length set by using the line training data set and the method for selecting the optimal configuration time length from the alternative configuration time length set according to the line testing data set, the training aggregation rule and the testing aggregation rule are respectively set according to specific conditions, so that the practicability of the technical scheme is improved.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
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The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a schematic diagram of the main steps of a method of determining a configured duration according to an embodiment of the invention;
FIG. 2 is a block diagram of a configuration table of line duration according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a main flow of a method of determining a configured duration according to an embodiment of the invention;
FIG. 4 is a schematic diagram of the main modules of an apparatus for determining a configured duration according to an embodiment of the present invention;
FIG. 5 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 6 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
At present, more and more people or manufacturers choose to adopt an online shopping and distribution shopping mode, which promotes the rapid development of the logistics industry. Meanwhile, in order to improve the warehouse-out efficiency of the articles, that is, when the article demand list is received, in order to select a nearby warehouse and quickly send out the articles from the warehouse, it is necessary to meet the requirement that the inventory of the articles in the warehouses of different distribution centers reaches a certain amount. Therefore, in the case that the stock quantity of the goods in the warehouse of some distribution centers is insufficient or in the case that the goods are required to be allocated, a logistics System ERP (i.e. Enterprise Resource Planning, a Management idea of a supply chain, which is a Management platform that is established on the basis of information technology and provides decision-making operation means for Enterprise decision-making layers and employees) generates an article configuration list, for example, an order shortage driver (automatic generation) and a WMS (i.e. a journey Management System, which is a Management System that comprehensively utilizes functions such as warehousing business, ex-Warehouse business, Warehouse allocation, inventory allocation, virtual Warehouse Management, real-time inventory Management and the like through functions such as warehousing business, ex-Warehouse business, inventory allocation, quality inspection Management, virtual Warehouse Management and the like) receives an article configuration list and takes charge of carrying articles from a source distribution center to a target Warehouse distribution center.
The time nodes from the generation of the item configuration list to the completion of the item configuration list relate to a plurality of links, including WMS receiving time, delivery time, item acceptance time and item shelf loading time. The WMS receiving time refers to the time for putting articles on shelves after receiving the article configuration list by the logistics party; the delivery time refers to the time when the goods are sent out and begin to be transported; the acceptance time refers to the time when the target center warehouse receives the article acceptance; the shelf loading time refers to the time when the goods are completely loaded in the target center warehouse and become the spot goods. The corresponding time length is calculated according to the time node, for example, the time for the goods to be put on shelf is predicted by taking the receiving time, the delivery time or the goods acceptance time of the in-transit goods as the starting point, namely, the configuration time length corresponding to the route is determined to be a matter of concern, so that the time for the goods to reach the target central warehouse can be calculated, and the influence on the goods delivery efficiency can be reduced.
Fig. 1 is a schematic diagram of the main steps of a method for determining a configured duration according to an embodiment of the present invention. As a reference embodiment of the present invention, as shown in fig. 1, the main steps of the method for determining the configured duration according to the embodiment of the present invention may include steps S101, S102, and S103.
Step S101: and acquiring a historical line data set, dividing the historical line data set based on a preset cross validation rule, and generating at least one group of line training data set and line testing data set.
The historic route data set refers to an item configuration list data set that has been delivered within a certain time, such as the item configuration list data set that has been delivered in the last week. The article configuration list can be generated by automatic order driving, return warehouse of other city warehouse, replenishment internal matching of city warehouse, manual generation and the like, and one article configuration list can contain a plurality of articles, and the articles in one article configuration list are all delivered from one delivery center warehouse to another delivery center warehouse, for example, from the warehouse A of Beijing delivery center to the warehouse B of Shanghai delivery center. In addition, an item configuration list corresponds to a route which is composed of a warehouse under a target distribution center and a warehouse of a source distribution center, and in a large distribution system, there are usually more than 6000 routes. The transfer of one item needs different departments to cooperate, the ERP system pays attention to the dimension of the item configuration list, and the WMS system is responsible for transportation and pays attention to the dimension of the container. Item configuration lists and containers do not correspond one-to-one, and items in one item configuration list are likely to be scattered into multiple containers for shipment with other item configuration list items.
The predetermined cross-validation rules in step 101 (i.e. taking out most samples for modeling, leaving a small portion of samples for prediction with the just-built model, calculating the prediction error of the small portion of samples, and recording the sum of their squares) may include the predetermined number of divisions and the predetermined division ratio. The preset dividing times refer to the times of dividing the historical line data set, and the preset dividing proportion refers to the step of dividing the historical line data set according to a certain proportion. Assuming that the preset dividing times are 3, the preset dividing proportion is 3: 2, the historic route data sets are D1, D2, D3, D4, D5, then the resulting 3 sets of route training data sets and route test data sets may be (D1, D2, D3) and (D4, D5), (D1, D4, D5) and (D2, D3), (D2, D3, D4) and (D1, D5). In the embodiment of the invention, the historical line data sets are randomly divided to obtain at least one group of line training data sets and line testing data sets, so that each group of line training data sets and line testing data sets can be respectively processed, and the average value or the maximum value of the processing result is obtained, thereby improving the accuracy of determining the configuration time.
As another reference embodiment of the present invention, the dividing the historical line data set based on the preset cross validation rule to generate at least one set of line training data set and line testing data set may include: and dividing the historical line data set by using the preset dividing times and the preset dividing proportion to obtain at least one group of line training data set and line testing data set.
Step S102: and generating a target configuration time length table according to the at least one group of line training data set and line testing data set. The configuration time length table may include at least one line and a configuration time length corresponding to the at least one line. Through step S101, at least one set of line training data set and line testing data set may be obtained, and then in step S102, a target configuration time table may be generated according to the line training data set and the line testing data set. The generation of the target configuration time length table is a main innovation point of the embodiment of the present invention through the description, and the generation process of the target configuration time length table is described in detail below, and will not be described repeatedly here.
Step S103: after receiving a request for determining the configuration duration of the target line, acquiring a target configuration duration table, and determining the configuration duration corresponding to the target line based on the target configuration duration table. After the target configuration duration table is obtained in step S102, the configuration duration corresponding to the target line may be queried from the target configuration duration table according to the received request for determining the configuration duration of the target line.
The generation of the target configuration time length table mentioned in step S102 is a main innovation point of the embodiment of the present invention, and the generation process of the target configuration time length table is specifically described next. As a further reference example of the embodiment of the present invention, generating a target configuration time length table according to at least one group of line training data sets and line testing data sets may include:
step S1021: training the line training data set aiming at a group of line training data sets and line testing data sets in at least one group of line training data sets and line testing data sets to obtain an alternative configuration time length set;
step S1022: selecting the optimal configuration time length of at least one line corresponding to a group of line training data sets and line testing data sets from the alternative configuration time length sets according to the alternative configuration time length sets and the line testing data sets;
step S1023: calculating the average value or the maximum value of the optimal configuration time length of at least one line corresponding to each group of line training data sets and line testing data sets to obtain the configuration time length of at least one line so as to generate a new configuration time length table;
step S1024: and updating the original configuration time length table by using the new configuration time length table to obtain a target configuration time length table.
Fig. 2 is a schematic diagram of an architecture of a line duration configuration table according to an embodiment of the present invention. As shown in fig. 2, in the embodiment of the present invention, in step S101, the historical route DATA set (INPUT DATA) is randomly generated into two parts, i.e., the route training DATA set (TRAIN DATA) and the route testing DATA set (VALIDATE DATA), according to the preset ratio (N% and 100% -N%). The line training data set (TRAIN DATA) is used for generating an alternative configuration duration set, and then an optimal configuration duration is selected from the alternative configuration duration set by combining the line testing data set (VALIDATE DATA), so that a line duration configuration table can be generated. Compared with the historical line data set which is not distinguished, the two processes of generating the alternative configuration time length set and selecting the optimal configuration time length from the alternative configuration time length set are respectively generated by using different data sets, so that overfitting can be prevented. Meanwhile, the proportion of the line training data set and the line testing data set can be adjusted for debugging. In addition, in the embodiment of the present invention, by dividing by a preset number of times (i.e., multiple cycles in fig. 2), an optimal time length average value or a maximum value of each division is taken, so that an influence caused by an abnormal value with a small probability occurring in a certain cycle process can be avoided.
In step S1021, training the line training data set to obtain the candidate configuration duration set may include: setting a training aggregation rule according to the number of the source distribution center, the target distribution center and the articles, and grouping the line training data sets according to the training aggregation rule to obtain at least one training line; and acquiring an alternative configuration time length set of at least one training line according to the set time length initial value, the set time length step value and the set time length number of the at least one training line.
Considering that in actual production, the number of articles contained in one article configuration list affects the final implementation manner of transportation, such as transportation in the same wave, or transportation in different containers in different times, and the number of articles affects the shelf loading time of the articles in the article configuration list, a flag field is added, and the articles are distinguished according to the number of article details in the article configuration list, and one group with the number greater than 40 may be set, where flag is 1, and the rest is another group with flag is 0. Meanwhile, the flag field is required to be ensured to be simply obtained, other information is not required to be called under the condition that the existing frame is kept unchanged, and the accuracy of configuration time can be improved. Therefore, in the embodiment of the present invention, a threshold adjustment result obtained by grouping the item detail numbers in the item configuration list is output, and this threshold is also one of the parameters.
When training a line training data set and acquiring an alternative configuration time length set, each line is determined by the combination of the number of objects flag in a source distribution center, a target distribution center and an object configuration list, namely, a training aggregation rule is set. The combination mode is also one of the model parameters, and the number flag of the articles in the source distribution center warehouse, the target distribution center warehouse and the article configuration list or different combinations of the source distribution center warehouse and the target distribution center warehouse can be changed to determine a route. In the embodiment of the invention, a combination of the source distribution center, the target distribution center and the number flag of the articles in the article configuration list is adopted to determine a route, because the duration of the route is mainly determined by the distance between the source distribution center and the target distribution center, for example, the durations of Beijing Shanghai and Shenzhen to Guangzhou are definitely different from the current delivery capacity. The influence from the distribution center to the warehouse has random factors such as manual operation and production wave number, so that the reconstruction of data is difficult, the probability of random results is increased by using the source distribution center warehouse and the target distribution center warehouse, the combination set is increased, and larger historical data amount is needed, so that the aggregation rule from the distribution center to the distribution center is selected at present.
In addition, the missing value is filled by the following method, for the case that the distribution center a to the distribution center B may have the following condition, only the number of items flag in the item configuration list is 0 in the historical data, and at this time, the missing alternative configuration time set of the distribution center a + the distribution center B + the number of items flag in the item configuration list being 1 may be replaced by the alternative configuration time set generated under the combination of the distribution center a + the distribution center B + the number of items flag in the item configuration list being 0. The number of elements and the strategy in the alternative configuration time length set in the embodiment of the invention can be adjusted and changed. The time length distribution characteristics of different lines are possibly different, and the alternative value generation strategy is selected to cover the optimal value under the condition of ensuring that the number of the alternative values is not redundant as far as possible. At present, a certain decimal value of each line is used as an initial value, different step lengths are set for each line according to the dispersion degree of time length, and the dispersion degree is large and the corresponding step length is also large. Then based on step length, according to different proportions, the method is superposed on the initial value to form a set of configuration alternative values of each line. For example, for a certain line, the initial value is a, the step size is b, the vector v is [1,3, … ], the alternative value is a + b v, and different alternative values can be obtained by setting or changing the length and value of the vector v.
Step S1021 is to generate an alternative configuration duration set by using the line training data set. In step S1022, an optimal configuration duration of at least one line is generated by combining the candidate configuration duration set and the line test data set, and the specific implementation method includes: matching is carried out by utilizing the alternative configuration time length set and the line test data set based on the training aggregation rule to obtain a matched line test data set; setting a test aggregation rule according to the source distribution center warehouse, the target distribution center warehouse and the number of the articles, and grouping the matched line test data sets according to the test aggregation rule to obtain at least one line and an alternative configuration time set corresponding to the at least one line; and selecting the optimal configuration time length of at least one line from the alternative configuration time length set corresponding to at least one line according to a preset test index.
The preset test index in the embodiment of the present invention may include a performance rate and an accurate performance rate. The fulfillment refers to that the item allocation achievement date in an item allocation list is earlier than the actual achievement date; the performance rate is the ratio of the number of actual performance items to the total number of actual performance items. Accurate performance means that the difference between the actual achievement duration and the configuration achievement duration of the article in an article configuration list is within a certain range, such as within 12 hours; the accurate performance rate is the ratio of the number of actual accurate performing articles to the total number of articles. According to the embodiment of the invention, the line test data set and the alternative configuration time length set are used for matching according to the training aggregation rule, and then the line test data set is used for obtaining the optimal configuration time length under the aggregation level of the number flag of the articles in the source distribution center warehouse, the target distribution center warehouse and the article configuration list, namely under the test aggregation rule, under the condition that the guarantee performance rate reaches a certain value (for example, 90 percent), the accurate guarantee rate is maximized.
After the optimal configuration duration of at least one line corresponding to each group of line training data sets and line testing data sets is obtained through steps S1021 and S1022, the average value or the maximum value of the optimal configuration duration of at least one line corresponding to each group of line training data sets and line testing data sets is calculated to obtain the configuration duration of at least one line, so that a new configuration duration table can be generated. And then, executing step S1024, and updating the original configuration time length table by using the new configuration time length table to obtain a target configuration time length table. This has the advantage that the configuration time table can be updated regularly instead of manually performing configuration maintenance.
Fig. 3 is a schematic diagram of a main flow of a method for determining a configured duration according to an embodiment of the present invention. As shown in fig. 3, the main process of the method for determining the configured duration according to the embodiment of the present invention may include:
step S301: acquiring a historical line data set, and dividing the historical line data set by using a preset dividing frequency and a preset dividing proportion to obtain at least one group of line training data set and line testing data set;
step S302: selecting a set of line training data sets and line testing data sets from the at least one set of line training data sets and line testing data sets;
step S303: training the selected line training data set to obtain an alternative configuration duration set;
step S304: selecting the optimal configuration time length of at least one line corresponding to the group of line training data sets and the line testing data sets from the alternative configuration time length sets according to the alternative configuration time length sets and the selected line testing data sets;
step S305: judging whether the optimal configuration duration of at least one line corresponding to each group of line training data sets and line testing data sets is obtained through calculation, if so, executing a step S306;
step S306: calculating the average value or the maximum value of the optimal configuration duration of at least one line corresponding to each group of line training data sets and line testing data sets to obtain the optimal configuration duration of at least one line so as to generate a new configuration duration table, wherein the configuration duration table can comprise at least one line and the configuration duration corresponding to at least one line;
step S307: updating the original configuration time length table by using the new configuration time length table to obtain a target configuration time length table;
step S308: after receiving a request for determining the configuration duration of the target line, acquiring a target configuration duration table, and determining the configuration duration corresponding to the target line based on the target configuration duration table.
It should be noted that the above step S303 of obtaining the alternative configuration time duration set according to the line training data set is specifically explained in the above step S1021, and will not be repeated here. Further, the step S304 selects the optimal configuration duration from the candidate configuration duration set according to the candidate configuration duration set and the selected line test data set, which is also specifically explained in the step S1022, and is not repeated here.
According to the technical scheme for determining the configuration time length, the acquired historical line data set is analyzed based on the preset cross validation rule, so that the configuration time length corresponding to the target line can be inquired from the generated target configuration time length table, the technical problem that certain deviation exists between the line configuration time length obtained through manual configuration and maintenance and the actual arrival time in the prior art is solved, the warehouse-out efficiency of the articles is guaranteed, and the user experience effect is improved. In addition, in the method for generating the target configuration time length table, the optimal configuration time length corresponding to each group of the line training data sets and the line testing data sets is calculated respectively, and then the target configuration time length table is generated by a method of solving the mean value or the maximum value, so that the accuracy of determining the configuration time length can be improved. In addition, in the method for acquiring the alternative configuration time length set by using the line training data set and the method for selecting the optimal configuration time length from the alternative configuration time length set according to the line testing data set, the training aggregation rule and the testing aggregation rule are respectively set according to specific conditions, so that the practicability of the technical scheme is improved.
Fig. 4 is a schematic diagram of main blocks of an apparatus for determining a configured duration according to an embodiment of the present invention. As shown in fig. 4, the apparatus 400 for determining a configured duration according to an embodiment of the present invention mainly includes the following modules: a partitioning module 401, a generating module 402 and a determining module 403.
The dividing module 401 may be configured to obtain a historical line data set, and divide the historical line data set based on a preset cross validation rule to generate at least one group of line training data set and line testing data set. The generating module 402 may be configured to generate a target configuration time length table according to at least one group of line training data sets and line testing data sets, where the configuration time length table includes at least one line and configuration time length corresponding to the at least one line. The matching module 403 may be configured to receive and analyze the configuration duration request to obtain a target line, and match the configuration duration corresponding to the target line based on the target configuration duration table.
In this embodiment of the present invention, the generating module 402 may further be configured to: training the line training data set aiming at a group of line training data sets and line testing data sets in at least one group of line training data sets and line testing data sets to obtain an alternative configuration time length set; selecting the optimal configuration time length of at least one line corresponding to a group of line training data sets and line testing data sets from the alternative configuration time length sets according to the alternative configuration time length sets and the line testing data sets; calculating the average value or the maximum value of the optimal configuration time length of at least one line corresponding to each group of line training data sets and line testing data sets to obtain the configuration time length of at least one line so as to generate a new configuration time length table; and updating the original configuration time length table by using the new configuration time length table to obtain a target configuration time length table.
In this embodiment of the present invention, the generating module 402 may further be configured to: setting a training aggregation rule according to the number of the source distribution center, the target distribution center and the articles, and grouping the line training data sets according to the training aggregation rule to obtain at least one training line; and acquiring an alternative configuration time length set of at least one training line according to the set time length initial value, the set time length step value and the set time length number of the at least one training line.
In this embodiment of the present invention, the generating module 402 may further be configured to: matching is carried out by utilizing the alternative configuration time length set and the line test data set based on the training aggregation rule to obtain a matched line test data set; setting a test aggregation rule according to the source distribution center warehouse, the target distribution center warehouse and the number of the articles, and grouping the matched line test data sets according to the test aggregation rule to obtain at least one line and an alternative configuration time set corresponding to the at least one line; and selecting the optimal configuration time length of at least one line from the alternative configuration time length set corresponding to at least one line according to a preset test index.
In the embodiment of the present invention, the preset cross validation rule may include a preset division number and a preset division ratio. And the partitioning module 401 may be further operable to: and dividing the historical line data set by using the preset dividing times and the preset dividing proportion to obtain at least one group of line training data set and line testing data set.
As can be seen from the above description, the device for determining configuration duration in the embodiment of the present invention can analyze the acquired historical line data set based on the preset cross validation rule, so as to query the configuration duration corresponding to the target line from the generated target configuration duration table, thereby overcoming the technical problem in the prior art that a certain deviation exists between the line configuration duration obtained through manual configuration and maintenance and the actual arrival time, further achieving the effects of ensuring the ex-warehouse efficiency of the article, and improving the user experience. In addition, the device for determining the configuration duration in the embodiment of the invention can respectively calculate the optimal configuration duration corresponding to each group of line training data sets and line testing data sets, and then generate the target configuration duration table by a method of solving the mean value or the maximum value, thereby improving the accuracy of determining the configuration duration. In addition, in the apparatus for determining configuration duration according to the embodiment of the present invention, in the method of acquiring the candidate configuration duration set by using the line training data set and the method of selecting the optimal configuration duration from the candidate configuration duration set according to the line test data set, the training aggregation rule and the test aggregation rule are set in combination with specific situations, so that the practicability of the technical scheme is improved.
Fig. 5 illustrates an exemplary system architecture 500 to which the method of determining a configured duration or the apparatus for determining a configured duration of an embodiment of the present invention may be applied.
As shown in fig. 5, the system architecture 500 may include terminal devices 501, 502, 503, a network 504, and a server 505. The network 504 serves to provide a medium for communication links between the terminal devices 501, 502, 503 and the server 505. Network 504 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 501, 502, 503 to interact with a server 505 over a network 504 to receive or send messages or the like. The terminal devices 501, 502, 503 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 501, 502, 503 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 505 may be a server providing various services, such as a background management server (for example only) providing support for shopping websites browsed by users using the terminal devices 501, 502, 503. The backend management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (for example, target push information, product information — just an example) to the terminal device.
It should be noted that the method for determining the configured duration provided by the embodiment of the present invention is generally executed by the server 505, and accordingly, the apparatus for determining the configured duration is generally disposed in the server 505.
It should be understood that the number of terminal devices, networks, and servers in fig. 5 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 6, a block diagram of a computer system 600 suitable for use with a terminal device implementing an embodiment of the invention is shown. The terminal device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU)601 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the system 600 are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, 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 such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 601.
It should be noted that the computer readable medium shown in the present invention can 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 the present invention, 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 the present invention, 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: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
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 invention. 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 or flowchart illustration, and combinations of blocks in the block diagrams 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 modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes a partitioning module, a generating module, and a matching module. For example, the dividing module may be further described as a module that acquires a historical line data set and divides the historical line data set based on a preset cross validation rule to generate at least one set of line training data set and line testing data set.
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise: acquiring a historical line data set, dividing the historical line data set based on a preset cross validation rule, and generating at least one group of line training data set and line testing data set; generating a target configuration time length table according to the at least one group of line training data sets and the line testing data sets, wherein the configuration time length table comprises at least one line and configuration time length corresponding to the at least one line; and receiving and analyzing the configuration duration request to obtain a target line, and matching the configuration duration corresponding to the target line based on the target configuration duration table.
According to the technical scheme of the embodiment of the invention, the acquired historical line data set is analyzed based on the preset cross validation rule, so that the configuration duration corresponding to the target line can be inquired from the generated target configuration duration table, the technical problem that certain deviation exists between the line configuration duration obtained through artificial configuration and maintenance and the actual arrival time in the prior art is solved, the delivery efficiency of the articles is ensured, and the effect of user experience is improved. In addition, in the method for generating the target configuration time length table, the optimal configuration time length corresponding to each group of the line training data sets and the line testing data sets is calculated respectively, and then the target configuration time length table is generated by a method of solving the mean value or the maximum value, so that the accuracy of determining the configuration time length can be improved. In addition, in the method for acquiring the alternative configuration time length set by using the line training data set and the method for selecting the optimal configuration time length from the alternative configuration time length set according to the line testing data set, the training aggregation rule and the testing aggregation rule are respectively set according to specific conditions, so that the practicability of the technical scheme is improved.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (12)
1. A method for determining a configuration duration, comprising:
acquiring a historical line data set, and dividing the historical line data set based on a preset cross validation rule to generate at least one group of line training data set and line testing data set;
generating a target configuration time length table according to the at least one group of line training data sets and the line testing data sets, wherein the configuration time length table comprises at least one line and configuration time length corresponding to the at least one line;
and receiving and analyzing a configuration duration request to obtain a target line, and matching the configuration duration corresponding to the target line based on the target configuration duration table.
2. The method of claim 1, wherein generating a target configuration time table from the at least one set of line training data sets and line testing data sets comprises:
aiming at a group of line training data sets and line testing data sets in the at least one group of line training data sets and line testing data sets, training the line training data sets to obtain an alternative configuration time length set;
selecting the optimal configuration time length of at least one line corresponding to the group of line training data sets and the line testing data sets from the alternative configuration time length sets according to the alternative configuration time length sets and the line testing data sets;
calculating the average value or the maximum value of the optimal configuration duration of at least one line corresponding to each group of line training data sets and line testing data sets to obtain the configuration duration of the at least one line so as to generate a new configuration duration table;
and updating the original configuration time length table by using the new configuration time length table to obtain the target configuration time length table.
3. The method of claim 2, wherein the training the line training dataset to obtain an alternative configured duration set comprises:
setting a training aggregation rule according to the number of the source distribution center, the target distribution center and the articles, and grouping the line training data sets according to the training aggregation rule to obtain at least one training line;
and acquiring an alternative configuration time length set of the at least one training line according to the set time length initial value, the set time length step value and the set time length number of the at least one training line.
4. The method according to claim 3, wherein selecting an optimal configuration duration of at least one line corresponding to the group of line training data sets and line testing data sets from the candidate configuration duration set according to the candidate configuration duration set and the line testing data set comprises:
matching is carried out by utilizing the alternative configuration time length set and the line test data set based on the training aggregation rule to obtain a matched line test data set;
setting a test aggregation rule according to a source distribution center warehouse, a target distribution center warehouse and the number of articles, and grouping the matched line test data sets according to the test aggregation rule to obtain the at least one line and an alternative configuration time set corresponding to the at least one line;
and selecting the optimal configuration time length of the at least one line from the alternative configuration time length set corresponding to the at least one line according to a preset test index.
5. The method according to claim 1, wherein the preset cross validation rule comprises a preset dividing number and a preset dividing proportion; and
the method for generating at least one group of line training data sets and line testing data sets by dividing the historical line data sets based on preset cross validation rules comprises the following steps:
and dividing the historical line data set by using the preset dividing times and the preset dividing proportion to obtain at least one group of line training data set and line testing data set.
6. An apparatus for determining a configuration time duration, comprising:
the system comprises a dividing module, a judging module and a judging module, wherein the dividing module is used for acquiring a historical line data set, dividing the historical line data set based on a preset cross validation rule and generating at least one group of line training data set and line testing data set;
a generating module, configured to generate a target configuration time length table according to the at least one group of line training data sets and the line testing data sets, where the configuration time length table includes at least one line and a configuration time length corresponding to the at least one line;
and the matching module is used for receiving and analyzing the configuration duration request to obtain a target line and matching the configuration duration corresponding to the target line based on the target configuration duration table.
7. The apparatus of claim 6, wherein the generating module is further configured to:
aiming at a group of line training data sets and line testing data sets in the at least one group of line training data sets and line testing data sets, training the line training data sets to obtain an alternative configuration time length set;
selecting the optimal configuration time length of at least one line corresponding to the group of line training data sets and the line testing data sets from the alternative configuration time length sets according to the alternative configuration time length sets and the line testing data sets;
calculating the average value or the maximum value of the optimal configuration duration of at least one line corresponding to each group of line training data sets and line testing data sets to obtain the configuration duration of the at least one line so as to generate a new configuration duration table;
and updating the original configuration time length table by using the new configuration time length table to obtain the target configuration time length table.
8. The apparatus of claim 7, wherein the generating module is further configured to:
setting a training aggregation rule according to the number of the source distribution center, the target distribution center and the articles, and grouping the line training data sets according to the training aggregation rule to obtain at least one training line;
and acquiring an alternative configuration time length set of the at least one training line according to the set time length initial value, the set time length step value and the set time length number of the at least one training line.
9. The apparatus of claim 8, wherein the generating module is further configured to:
matching is carried out by utilizing the alternative configuration time length set and the line test data set based on the training aggregation rule to obtain a matched line test data set;
setting a test aggregation rule according to a source distribution center warehouse, a target distribution center warehouse and the number of articles, and grouping the matched line test data sets according to the test aggregation rule to obtain the at least one line and an alternative configuration time set corresponding to the at least one line;
and selecting the optimal configuration time length of the at least one line from the alternative configuration time length set corresponding to the at least one line according to a preset test index.
10. The apparatus of claim 6, wherein the preset cross validation rule comprises a preset dividing number and a preset dividing proportion; and
the partitioning module is further configured to: and dividing the historical line data set by using the preset dividing times and the preset dividing proportion to obtain at least one group of line training data set and line testing data set.
11. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-5.
12. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-5.
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