CN110599078B - Logistics distribution information processing method and device and computer equipment - Google Patents
Logistics distribution information processing method and device and computer equipment Download PDFInfo
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- CN110599078B CN110599078B CN201910683855.1A CN201910683855A CN110599078B CN 110599078 B CN110599078 B CN 110599078B CN 201910683855 A CN201910683855 A CN 201910683855A CN 110599078 B CN110599078 B CN 110599078B
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Abstract
The application discloses a processing method, a processing device and computer equipment of logistics distribution information, relates to the technical field of information, and can effectively solve the problem that more accurate goods distribution time cannot be given in the prior art. The method comprises the following steps: acquiring first historical distribution record information of a distribution station where goods to be distributed are located; acquiring second historical delivery record information of a delivery party delivering the goods to be delivered; determining a first delivery duration of the goods to be delivered according to the first historical delivery record information and the second historical delivery record information, wherein the first delivery duration is a duration required from the delivery station to the delivery of the goods to be delivered; and determining the delivery time of the to-be-delivered goods on the same day according to the first delivery time and the starting delivery time point of the to-be-delivered goods. The method and the device are suitable for processing logistics distribution information.
Description
Technical Field
The present disclosure relates to the field of information technologies, and in particular, to a method and an apparatus for processing logistics distribution information, and a computer device.
Background
The logistics distribution is a commodity circulation mode seen from the commodity circulation operation mode. Is a modern circulation mode. The logistics distribution positioning is a logistics mode for providing services for clients of electronic commerce, carrying out unified information management and scheduling on the whole logistics distribution system according to the characteristics of the electronic commerce, carrying out goods management on a logistics base according to the ordering requirements of users, and delivering the well-distributed goods to a delivery person.
In the prior art, the delivery time of the goods is determined by using the quantity of the goods in each batch and the time when the goods reach the target warehouse, that is, the delivery time is the time when the goods can be delivered to the buyer by a predetermined quantity, and the delivery time corresponds to the time when the goods can be sent from the delivery station.
However, in an actual scene, the user is more concerned about how long to send the goods to the gate, and a certain time is required from the sending station to the user, so that the actual sending time of the goods is unknown, and the user does not know the more accurate sending time of the goods, which causes a certain inconvenience.
Disclosure of Invention
In view of this, the present application provides a method, an apparatus and a computer device for processing logistics distribution information, which mainly aims to solve the problem that in the prior art, more accurate time for distributing goods cannot be provided.
According to one aspect of the present application, there is provided a method for processing logistics distribution information, the method comprising:
acquiring first historical distribution record information of a distribution station where goods to be distributed are located; a kind of electronic device with high-pressure air-conditioning system
Acquiring second historical distribution record information of a distributor for distributing the goods to be distributed;
determining a first delivery duration of the goods to be delivered according to the first historical delivery record information and the second historical delivery record information, wherein the first delivery duration is a duration required from the delivery station to the delivery of the goods to be delivered;
and determining the delivery time of the to-be-delivered goods on the same day according to the first delivery time and the starting delivery time point of the to-be-delivered goods.
According to another aspect of the present application, there is provided a processing apparatus for logistics distribution information, the apparatus comprising:
the acquiring unit is used for acquiring first historical delivery record information of a delivery station where the goods to be delivered are located; a kind of electronic device with high-pressure air-conditioning system
Acquiring second historical distribution record information of a distributor for distributing the goods to be distributed;
the determining unit is used for determining a first delivery duration of the goods to be delivered according to the first historical delivery record information and the second historical delivery record information, wherein the first delivery duration is a duration required from the delivery of the goods to be delivered from the delivery station to the delivery;
the determining unit is further configured to determine a time of day for delivering the to-be-delivered item according to the first delivery duration and the starting delivery time point of the to-be-delivered item.
According to still another aspect of the present application, there is provided a non-volatile readable storage medium having stored thereon a computer program which when executed by a processor implements the above-described processing method of logistics distribution information.
According to still another aspect of the present application, there is provided a computer device including a nonvolatile readable storage medium, a processor, and a computer program stored on the nonvolatile readable storage medium and executable on the processor, the processor implementing the above-mentioned processing method of logistics distribution information when executing the program.
By means of the technical scheme, the processing method, the processing device and the computer equipment for logistics distribution information are capable of determining distribution time of the goods to be distributed according to the first historical distribution record information of the distribution station where the goods to be distributed are located and the second historical distribution record information of the distribution party of the goods to be distributed, compared with the distribution time which is only calculated from the distribution station and is sent out by the goods to be distributed in the prior art, the distribution time is the time required from the distribution station to the distribution of the goods to be distributed until the distribution is achieved, and further the distribution time point of the goods to be distributed can be combined again to determine the distribution time of the goods to be distributed on the same day, the fact that a user calls again, sends short messages, and confirms the corresponding distribution time by utilizing instant communication software and the like in an active contact mode with a distributor is not needed, the user can know the distribution time of the goods to be more accurate, and accordingly self-travel can be arranged in advance, and user experience can be improved.
The foregoing description is merely an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the present application. In the drawings:
fig. 1 is a schematic flow chart of a method for processing logistics distribution information according to an embodiment of the present application;
fig. 2 is a schematic flow chart of another method for processing logistics distribution information according to an embodiment of the present application;
fig. 3 is a schematic flow chart of a processing device for logistics distribution information according to an embodiment of the present application;
fig. 4 is a schematic flow chart of another processing device for logistics distribution information according to an embodiment of the present application.
Detailed Description
The present application will be described in detail hereinafter with reference to the accompanying drawings in conjunction with embodiments. It should be noted that, without conflict, the embodiments and features of the embodiments in the present application may be combined with each other.
In order to solve the technical problem, the present embodiment provides a method for processing logistics distribution information, as shown in fig. 1, which includes:
101. the method comprises the steps of obtaining first historical delivery record information of a delivery station where an article to be delivered is located, and obtaining second historical delivery record information of a delivery party for delivering the article to be delivered.
The first historical distribution record information can comprise distribution record conditions of the distribution station every day, and specifically comprises the number of received goods and the number of distributed goods every day, wherein the number of large goods and the number of small goods; how many people the dispenser takes charge of dispensing every day, how many dispensing devices take charge of dispensing, the total time of dispensing these items a day, the duration of dispensing each item, etc. The dispenser may be a dispenser, a dispensing device (e.g., a dispensing vehicle, a dispensing drone, etc.), etc. The second historical delivery record information may include how many orders the delivery person/delivery device delivers each day, how many orders are large, how many orders are small, how much is the total time of day to deliver the items, how long each item is delivered, etc.
The execution body of the embodiment may be a processing device or equipment of logistics distribution information, which is used for estimating the more accurate current day distribution time of logistics, and may be configured at a server side or a client side, and may be specifically determined according to actual service requirements.
102. And determining a first delivery duration of the goods to be delivered according to the acquired first historical delivery record information and second historical delivery record information.
The first delivery time period is a time period required from the delivery of the goods to be delivered to the delivery station to the delivery of the goods to be delivered.
Because the user is concerned about how long to deliver the goods in the actual scene, for the embodiment, the first historical delivery record information of the delivery station where the goods to be delivered are located and the second historical delivery record information of the delivery party delivering the goods to be delivered can be combined to analyze and obtain the delivery time from the delivery station to the delivery according to the historical delivery habit, so that the delivery time from the delivery station to the delivery of the goods to be delivered can be estimated more accurately, the user can be helped to plan other arrangements according to the delivery time, unnecessary waiting time is reduced, and the user experience can be improved.
103. And determining the delivery time of the day of the goods to be delivered according to the determined first delivery time and the starting delivery time point of the goods to be delivered.
In this embodiment, the starting time point of the to-be-delivered item and the determined delivery time length may be added to obtain the time point of the item delivered on the day, that is, the delivery time of the item on the day.
For example, if the delivery time period from the start of delivery at the delivery station to the delivery is 5 hours and the delivery of the article a is started from 9 am according to the history delivery habit, it can be estimated that the article a can be delivered to the user at two pm, and the user can plan the schedule of the day in advance according to the time point, so that excessive intolerance waiting time is avoided.
Compared with the prior art, which only calculates the delivery time of the goods sent from the delivery station, the processing method of the logistics delivery information in the embodiment is based on big data analysis technology, and can determine the more accurate delivery time of the day according to the historical delivery habit of the delivery station where the goods to be delivered are located and the historical delivery habit of the delivery party for delivering the goods, so that the user does not need to make a call again, send a short message, actively contact with a delivery person by using instant messaging software and the like to confirm the corresponding delivery time, and the user can conveniently know the more accurate delivery time of the goods to get on the door so as to arrange own travel in advance, thereby improving the experience of the user.
Further, as a refinement and extension of the specific implementation manner of the foregoing embodiment, in order to fully describe the specific implementation process in this embodiment, another method for processing logistics distribution information is provided, as shown in fig. 2, where the method includes:
201. the method comprises the steps of obtaining first historical delivery record information of a delivery station where an article to be delivered is located, and obtaining second historical delivery record information of a delivery party for delivering the article to be delivered.
The delivery station receives the article to be delivered and is then responsible for delivering the article, and may specifically assign a particular delivery party (e.g., a dispenser or a delivery device, etc.) in the delivery station to deliver. In this embodiment, each distribution station may record corresponding historical distribution record information and historical distribution record information of each distribution party, and specifically, each corresponding client may be configured in each distribution station and each distribution party, and then the client is utilized to combine with the logistics information of the network to record the historical distribution record of the distribution station and the historical distribution record of each distribution party.
202. And acquiring a first average goods delivery duration of the delivery station and a second average goods delivery duration corresponding to the goods type of the goods to be delivered from the first historical delivery record information.
When the average goods delivery duration is obtained, the goods delivery duration corresponding to the specific time period can be obtained according to the actual estimated demand, and then the average value is obtained. For example, if it is desired to estimate the time of delivery of an item on the day, which is Tuesday and which includes days adjacent to a day other than a shopping promotion, the time of delivery of the item on each Tuesday (days adjacent to a day other than a shopping promotion) may be taken and then averaged to obtain the average time of delivery of the item on the delivery station.
In addition, when the average article delivery duration is counted, a statistical calculation may be performed for the article types, so as to obtain an average article delivery duration corresponding to each article type, where the article types may include: large household appliances (such as refrigerators, washing machines, air conditioners, etc.), small household appliances (such as electric cookers, electric kettles, humidifiers, etc.), clothing, food, furniture, etc. For example, in general, for large household appliances, since the size of the goods is large, it takes more time to carry and transport each time they are delivered, and thus the delivery time of such goods is long; and for articles of clothing, the length of time for distribution is relatively small because of the relative ease of carrying and the high resistance to knocks.
203. And acquiring the third average goods delivery duration of the delivery party from the second historical delivery record information.
For example, if the dispenser is a dispenser, the average length of time that the dispenser has to dispense the items may be obtained by summing the lengths of time that the dispenser has to dispense the items each time and dividing by the number of times the items have been dispensed.
204. And acquiring other article information except the articles to be delivered, which are carried by the delivery party.
Wherein the other article information includes information of an article type, an article size, an article distribution place, and the like of the other articles.
In a specific application scenario, in order to improve the delivery efficiency of the goods and reduce the delivery cost, a delivery party often carries a plurality of goods to be delivered when delivering the goods once, and the goods are delivered successively. Therefore, when calculating the delivery time of the target goods, the time consumed by other rows when delivering the target goods is required to be judged, and the delivery time of the target goods can be accurately calculated.
205. And calculating the first delivery time of the to-be-delivered goods according to the acquired first average goods delivery time, second average goods delivery time, third average goods delivery time and other goods information.
In this embodiment, the average article delivery duration of the delivery station, the average article delivery duration of the same type of articles as the target article to be delivered, and the average article delivery duration of the actual delivery party may be combined, the delivery duration of the target article to be delivered may be accurately estimated and calculated, and then the delivery duration from the delivery station to the delivery may be calculated by combining the delivery duration of other articles delivered before the target article and the delivery location, and so on.
To illustrate the implementation of step 205, as an alternative, the step may specifically include: using a preset formula
Calculating a first delivery time length of the to-be-delivered goods, wherein T is the first delivery time length of the to-be-delivered goods, T1 is the first average goods delivery time length, T2 is the second average goods delivery time length, T3 is the third average goods delivery time length, n is the quantity of the to-be-delivered goods carried by the delivery party at this time, and T4 i For the second delivery duration of other goods delivered before the goods to be delivered at this time, k1, k2, k3 and k4 are weight coefficient values of various parameters, the weight coefficient values can be preset according to actual conditions, larger weight coefficient values can be configured for factors which actually affect the delivery duration of the target goods, smaller weight coefficient values can be configured for factors which actually affect the delivery duration of the target goods, and the weights can also meet specific rules to correct the calculation results, so that abnormal calculation results, such as that the sum of k1+k2+k3 is smaller than or equal to 1 or 1.5, are avoided.
Here, T1 corresponds to an average article delivery duration of a delivery station where a target article is located, where the size of T1 is affected by factors such as a geographic location of the delivery station, a range responsible for delivery, a surrounding traffic environment, an average number of articles to be delivered per day, and an owned number of dispensers/delivery devices, and average article delivery durations of different delivery stations may vary.
T2 is an average article-delivery-period of an article corresponding to the type of the target article to be delivered, and if the type of article is larger in size, heavier in weight, and belongs to a fragile article, the delivery period thereof is relatively longer in consideration of the transportation requirement.
T3 corresponds to an average article delivery time period of the dispenser/dispenser or the like, and the size of T3 is dependent on factors such as the number of articles delivered by the dispenser/dispenser each time and the number of places to be delivered, and generally, the larger the number of articles and the larger the place to be delivered, the longer the article delivery time period.
T4 is the sum of the delivery time lengths of the goods delivered and carried according to the delivery Fang Yici and arranged in front of the current target goods according to the delivery sequence, and the goods are overlapped layer by layer according to the similar processing mode. The delivery order may be determined according to how far the delivery person is from each delivery location, such as higher delivery priority from a near delivery location, lower delivery priority from a far delivery location, etc., and may be adjusted by determining the delivery order of each item in combination with the user reservation record, thereby determining the final delivery order. For example, if the target article is determined to be the third article, the article-to-article delivery duration is k1×t1+k2×t2+k3×t3, and the sum of the article-to-article delivery durations of the first two articles is added.
By adopting the calculation mode of the optional mode, various factors which influence the delivery time of the goods are considered, and the delivery time of the goods to be delivered from the delivery station to the user can be calculated more accurately.
206. And determining the delivery time of the day of the goods to be delivered according to the first delivery time of the goods to be delivered and the starting delivery time point of the goods to be delivered.
For example, the time point at which the delivery starts is added to this delivery time period, and the obtained time point is taken as the delivery time of the day of the target article to be delivered. This approach allows the user to more accurately obtain what time of day can be delivered than in the prior art where the user is only informed of the delivery on that day. The experience of the user is improved, so that the user can grasp the time and avoid excessive waiting time.
In an actual application scene, the time length of goods delivery is also related to real-time weather conditions, logistics road condition information and other factors, for example, a logistics delivery vehicle in snowy days is affected by weather, so that the logistics delivery time length is prolonged; and when the road condition is congested, the logistics distribution time can be prolonged. Thus, as a preferred manner, prior to step 206, it may further comprise: acquiring real-time weather information and real-time logistics traffic information of the day of delivering the goods to be delivered; then correcting the first delivery duration of the goods to be delivered according to the acquired real-time weather information and real-time logistics traffic information; accordingly, step 206 may specifically include: and determining the delivery time of the to-be-delivered goods according to the corrected first delivery time length and the starting delivery time point of the to-be-delivered goods.
For the optional mode, the influence of factors such as real-time weather, logistics road conditions and the like on the delivery time of the target goods is considered, and the delivery time of the target goods obtained after correction according to the two factors is more accurate. It should be noted that, in addition to the manner of considering the influence of the two factors at the same time, the method can also be modified independently according to the actual requirement, that is, according to the acquired real-time weather information or real-time logistics traffic information, the first delivery duration of the goods to be delivered is modified, for example, the influence of the real-time road condition factors on the logistics delivery process of the delivery unmanned aerial vehicle can be ignored.
Further, to illustrate the above specific implementation procedure of correcting the first delivery duration of the to-be-delivered item, as an alternative manner, the procedure may specifically include: acquiring a real-time weather type from the acquired real-time weather information; the congestion degree grade of the real-time logistics traffic is obtained from the obtained real-time logistics traffic information; and multiplying the first delivery time length of the goods to be delivered by a first preset multiple coefficient corresponding to the real-time weather type and multiplying the first delivery time length by a second preset multiple coefficient corresponding to the congestion degree level to obtain a corrected first delivery time length, wherein different weather types have the first preset multiple coefficient corresponding to each other, and different congestion degree levels have the second preset multiple coefficient corresponding to each other.
For example, the respective corresponding multiple coefficients may be configured in advance for various weather types, such as 1 in sunny days, 1.2 in rainy days, 1.4 in medium rain/fog/haze, 1.6 in heavy rains, 1.5 in small snow, 2 in large snow, 0 in heavy snow/typhoon, and the like; similarly, the corresponding multiple coefficients of the various logistics traffic road conditions are configured in advance, for example, the degree of traffic jam in the delivery time period in the range of the area responsible for delivery of the target delivery station can be divided into 1.1, 1.2, 1.3 and the like. And then according to the actual weather conditions and logistics traffic conditions, multiplying the delivery duration calculated in the steps by corresponding multiple coefficients, for example, the weather is raining, the traffic jam degree corresponds to the multiple coefficient of 1.2, and multiplying the delivery duration of the target goods to be delivered calculated in the steps by 1.2 and then by 1.2 to obtain the corrected delivery duration.
Further, in order to calculate the corresponding complete delivery time from the time when the target goods are received from the goods package until the corresponding complete delivery time is reached, as an alternative, based on the foregoing solution, the method of this embodiment may further include: calculating the number of days from the collection of the goods to be delivered to the delivery station to the transportation of the goods to be delivered according to the logistics information of the goods to be delivered; calculating the retention days of the goods to be delivered in the delivery station according to the quantity of the goods to be delivered, the quantity of the existing delivery parties and the average daily maximum quantity of the goods which can be delivered by each delivery party from the start of receiving the goods to be delivered by the delivery station; and determining the time from the collection of the goods to the corresponding complete delivery according to the calculated number of the goods transportation days, the calculated number of the residence days and the calculated time of the day of the goods to be delivered in the process.
For the calculation mode of the number of the goods transportation days, the transportation time length of different transportation modes of different logistics companies can be calculated through the historical transportation records, wherein the transportation time length is the goods transportation time length from the collection of the goods to the delivery of the goods to the local target distribution station of the user. And then finding out the corresponding transportation days according to the logistics company, the goods type and the transportation mode corresponding to the target goods. The number of days of transportation may be further modified in connection with the traffic situation of the transportation route, whether it is a distribution period corresponding to the sales promotion period of the shopping mall, etc. If the corresponding delivery period is during the shopping promotion period, the transportation days are multiplied by the corresponding lengthening coefficient (such as 1.5) to obtain the corrected transportation days of the goods.
After the number of the transportation days and the number of the retention days of the goods and the delivery time of the day of the goods to be delivered calculated in the process are calculated, adding the three times to obtain the corresponding complete delivery time from the collection and the receiving of the goods (delivery time of a merchant) of the goods. By the method, not only can the day delivery of the goods be estimated, but also the delivery time of the goods can be further accurate to the specific time of the day, and the user can be helped to know the more accurate delivery time of the goods. It should be noted that, when the complete delivery time is estimated in advance, there may be an unknown which of the delivery parties actually delivers the article, and for this purpose, one of the delivery parties existing in the delivery station may be selected to perform the above calculation process. The rule of selecting the delivery party can be determined according to the actual situation, for example, one delivery party with the highest attendance rate can be selected, one delivery party with the attendance on the same day can be selected according to the scheduling rule of the delivery party, and the like.
To illustrate the above process of calculating the number of days of retention, as an alternative, the process may specifically include: calculating the product between the number of existing dispensers at the dispensing station and the average daily maximum amount of goods that each dispenser can dispense; the number of articles to be dispensed from the start of receiving articles to be dispensed from the dispensing station is then divided by the product to obtain the number of days the articles to be dispensed remain in the dispensing station.
In a specific implementation, the default delivery station delivers in order of time from the early to the late. The delivery station may be configured to calculate the number of items to be delivered from the time of receiving the items to be delivered/(the number of existing deliverers × the maximum number of items that can be delivered per each deliverer average per day) =the number of stay days. By the method, the actual situation of logistics distribution is considered, and the retention time of the target goods can be calculated more accurately.
According to the processing method of logistics distribution information, based on the big data analysis technology, the distribution time of the to-be-distributed goods on the same day can be estimated, and the corresponding complete distribution time from the time of receiving the goods from the goods to the time of delivering the to-be-distributed goods can be finally calculated based on the calculation result.
Further, as a specific implementation of the method shown in fig. 1 to fig. 2, the embodiment provides a processing apparatus for logistics distribution information, as shown in fig. 3, where the apparatus includes: an acquisition unit 31, a determination unit 32.
The acquiring unit 31 is configured to acquire first historical distribution record information of a distribution station where the to-be-distributed goods are located; acquiring second historical delivery record information of a delivery party for delivering the goods to be delivered;
a determining unit 32, configured to determine a first delivery duration of the to-be-delivered item according to the first historical delivery record information and the second historical delivery record information, where the first delivery duration is a duration required from the delivery of the to-be-delivered item at the delivery station until delivery is completed;
the determining unit 32 may be further configured to determine a time of day for delivering the to-be-delivered item according to the first delivery duration and the starting delivery time point of the to-be-delivered item.
In a specific application scenario, the determining unit 32 is specifically configured to obtain, from the first historical delivery record information, a first average delivery duration of the delivery station and a second average delivery duration of the delivery station corresponding to a type of the article to be delivered; acquiring a third average goods delivery duration of the delivery party from the second historical delivery record information; acquiring other article information except articles to be delivered, which is carried by a delivery party; and calculating the first delivery time of the to-be-delivered goods according to the first average goods delivery time, the second average goods delivery time, the third average goods delivery time and other goods information.
In a specific application scenario, the determining unit 32 may be further configured to use a preset formula
Calculating a first delivery time length of the to-be-delivered goods, wherein T is the first delivery time length of the to-be-delivered goods, T1 is the first average goods delivery time length, T2 is the second average goods delivery time length, T3 is the third average goods delivery time length, n is the quantity of the to-be-delivered goods carried by the delivery party at this time, and T4 i For the second delivery duration of other goods delivered before the goods to be delivered, k1, k2, k3 and k4 are weight coefficient values of various parameters.
In a specific application scenario, as shown in fig. 4, the present apparatus may further include: a correction unit 33;
the obtaining unit 31 is further configured to obtain real-time weather information and real-time logistics traffic information on a day of delivering the goods to be delivered;
a correction unit 33, configured to correct the first delivery duration according to the real-time weather information and the real-time logistics traffic information;
the determining unit 32 is specifically configured to determine the delivery time of the to-be-delivered item according to the modified first delivery duration and the starting delivery time point of the to-be-delivered item.
In a specific application scenario, the correction unit 33 may be specifically configured to obtain a real-time weather type from the real-time weather information; acquiring the congestion degree grade of real-time logistics traffic from the real-time logistics traffic information; and multiplying the first delivery duration by a first preset multiple coefficient corresponding to the real-time weather type and multiplying the first delivery duration by a second preset multiple coefficient corresponding to the congestion degree level to obtain a corrected first delivery duration, wherein different weather types all have the corresponding first preset multiple coefficient, and different congestion degree levels all have the corresponding second preset multiple coefficient.
In a specific application scenario, as shown in fig. 4, the present apparatus may further include: a calculation unit 34;
a calculating unit 34, configured to calculate, according to the logistics information of the to-be-delivered goods, the number of days of goods transportation from the collection of the to-be-delivered goods to the delivery station; calculating the retention days of the goods to be delivered in the delivery station according to the quantity of the goods to be delivered, the quantity of the existing delivery parties and the average daily maximum quantity of the goods which can be delivered by each delivery party from the start of receiving the goods to be delivered by the delivery station;
the determining unit 32 may be further configured to determine, according to the number of days of transporting the goods, the number of days of residence, and the time of delivery of the goods on the same day, that the goods to be delivered are delivered until the corresponding complete delivery time is reached.
In a specific application scenario, the calculating unit 34 may be specifically configured to calculate a product between the number of existing dispensers and the maximum amount of goods; dividing the number of items by the product yields the number of days the items to be dispensed remain at the dispensing station.
It should be noted that, for other corresponding descriptions of each functional unit related to the processing device for logistics distribution information provided in this embodiment, reference may be made to corresponding descriptions in fig. 1 to fig. 2, and no further description is given here.
Based on the above-mentioned methods shown in fig. 1 and 2, correspondingly, the embodiments of the present application further provide a storage medium, on which a computer program is stored, where the program is executed by a processor to implement the above-mentioned method for processing logistics distribution information shown in fig. 1 and 2.
Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.), and includes several instructions for causing a computer device (may be a personal computer, a server, or a network device, etc.) to perform the method of each implementation scenario of the present application.
Based on the methods shown in fig. 1 and fig. 2 and the virtual device embodiments shown in fig. 3 and fig. 4, in order to achieve the above objects, the embodiments of the present application further provide a computer device, which may specifically be a personal computer, a server, a smart phone, a tablet computer, a smart watch, or other network devices, where the physical device includes a storage medium and a processor; a storage medium storing a computer program; and a processor for executing a computer program to implement the above-mentioned processing method of logistics distribution information as shown in fig. 1 and 2.
Optionally, the computer device may also include a user interface, a network interface, a camera, radio Frequency (RF) circuitry, sensors, audio circuitry, WI-FI modules, and the like. The user interface may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), etc., and the optional user interface may also include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (e.g., bluetooth interface, WI-FI interface), etc.
It will be appreciated by those skilled in the art that the computer device structure provided in this embodiment is not limited to this physical device, and may include more or fewer components, or may combine certain components, or may be arranged in different components.
The storage medium may also include an operating system, a network communication module. The operating system is a program that manages the physical device hardware and software resources of the logistics distribution information process, supporting the execution of information processing programs and other software and/or programs. The network communication module is used for realizing communication among all components in the storage medium and communication with other hardware and software in the entity equipment.
From the above description of the embodiments, it will be apparent to those skilled in the art that the present application may be implemented by means of software plus necessary general hardware platforms, or may be implemented by hardware. According to the technical scheme, based on the big data analysis technology, the more accurate day delivery time of the goods to be delivered can be estimated, and the corresponding complete delivery time from the time of receiving the goods from the goods to the time of delivering the goods can be finally calculated based on the calculation result.
Those skilled in the art will appreciate that the drawings are merely schematic illustrations of one preferred implementation scenario, and that the modules or flows in the drawings are not necessarily required to practice the present application. Those skilled in the art will appreciate that modules in an apparatus in an implementation scenario may be distributed in an apparatus in an implementation scenario according to an implementation scenario description, or that corresponding changes may be located in one or more apparatuses different from the implementation scenario. The modules of the implementation scenario may be combined into one module, or may be further split into a plurality of sub-modules.
The foregoing application serial numbers are merely for description, and do not represent advantages or disadvantages of the implementation scenario. The foregoing disclosure is merely a few specific implementations of the present application, but the present application is not limited thereto and any variations that can be considered by a person skilled in the art shall fall within the protection scope of the present application.
Claims (8)
1. The processing method of the logistics distribution information is characterized by comprising the following steps:
acquiring first historical distribution record information of a distribution station where goods to be distributed are located; a kind of electronic device with high-pressure air-conditioning system
Acquiring second historical distribution record information of a distributor for distributing the goods to be distributed;
determining a first delivery duration of the goods to be delivered according to the first historical delivery record information and the second historical delivery record information, wherein the first delivery duration is a duration required from the delivery station to the delivery of the goods to be delivered;
determining the current day delivery time of the goods to be delivered according to the first delivery time and the starting delivery time point of the goods to be delivered;
the determining, according to the first historical distribution record information and the second historical distribution record information, a first distribution duration of the to-be-distributed goods specifically includes:
acquiring a first average goods delivery duration of the delivery station and a second average goods delivery duration corresponding to the goods type of the goods to be delivered from the first historical delivery record information;
acquiring a third average goods delivery duration of the delivery party from the second historical delivery record information;
acquiring other article information except the article to be delivered, which is carried by the delivering party;
calculating the first delivery duration of the to-be-delivered goods according to the first average goods delivery duration, the second average goods delivery duration, the third average goods delivery duration and the other goods information, specifically including:
using a preset formula
Calculating the first delivery duration of the to-be-delivered goods, wherein T is the first delivery duration of the to-be-delivered goods, T1 is the first average goods delivery duration, T2 is the second average goods delivery duration, T3 is the third average goods delivery duration, n is the quantity of the goods to be delivered carried by the delivery party this time, and T4 i For the second delivery duration of the other goods delivered before the goods to be delivered, k1, k2, k3 and k4 are weight coefficient values of various parameters.
2. The method of claim 1, wherein prior to said determining a delivery time of said item to be delivered based on said first delivery duration and a starting delivery time point of said item to be delivered, said method further comprises:
acquiring real-time weather information and real-time logistics traffic information of the day of delivering the goods to be delivered;
correcting the first distribution duration according to the real-time weather information and the real-time logistics traffic information;
the determining the delivery time of the to-be-delivered goods according to the first delivery time and the starting delivery time point of the to-be-delivered goods specifically includes:
and determining the delivery time of the goods to be delivered according to the corrected first delivery time and the starting delivery time point of the goods to be delivered.
3. The method according to claim 2, wherein the correcting the first delivery duration according to the real-time weather information and the real-time logistics traffic information specifically includes:
acquiring a real-time weather type from the real-time weather information;
acquiring the congestion degree grade of real-time logistics traffic from the real-time logistics traffic information;
and multiplying the first delivery duration by a first preset multiple coefficient corresponding to the real-time weather type and multiplying the first delivery duration by a second preset multiple coefficient corresponding to the congestion degree level to obtain the corrected first delivery duration, wherein different weather types have respective corresponding first preset multiple coefficients, and different congestion degree levels have respective corresponding second preset multiple coefficients.
4. The method according to claim 1, wherein the method further comprises:
calculating the number of days of goods transportation from the collection of the goods to be delivered to the delivery station according to the logistics information of the goods to be delivered;
calculating the retention days of the goods to be delivered at the delivery station according to the quantity of the goods to be delivered, the quantity of the existing delivery parties and the average daily maximum quantity of the goods which can be delivered by each delivery party from the start of receiving the goods to be delivered by the delivery station;
and determining the complete delivery time from the goods receiving to the delivery according to the goods transportation days, the retention days and the delivery time of the day.
5. The method according to claim 4, wherein calculating the number of days of residence of the goods to be delivered at the delivery station based on the number of goods to be delivered from the time of receiving the goods to be delivered by the delivery station, the number of existing delivery parties, and the average daily maximum amount of goods that can be delivered per delivery party, specifically comprises:
calculating a product between the number of existing dispensers and the maximum quantity of goods;
dividing the product by the number of the goods to obtain the retention days of the goods to be delivered at the delivery station.
6. A processing apparatus for logistics distribution information, comprising:
the acquiring unit is used for acquiring first historical delivery record information of a delivery station where the goods to be delivered are located; a kind of electronic device with high-pressure air-conditioning system
Acquiring second historical distribution record information of a distributor for distributing the goods to be distributed;
the determining unit is used for determining a first delivery duration of the goods to be delivered according to the first historical delivery record information and the second historical delivery record information, wherein the first delivery duration is a duration required from the delivery of the goods to be delivered from the delivery station to the delivery;
the determining unit is further configured to determine a time of day for delivering the to-be-delivered item according to the first delivery duration and a time point for starting delivery of the to-be-delivered item;
the determining, according to the first historical distribution record information and the second historical distribution record information, a first distribution duration of the to-be-distributed goods specifically includes:
acquiring a first average goods delivery duration of the delivery station and a second average goods delivery duration corresponding to the goods type of the goods to be delivered from the first historical delivery record information;
acquiring a third average goods delivery duration of the delivery party from the second historical delivery record information;
acquiring other article information except the article to be delivered, which is carried by the delivering party;
calculating the first delivery duration of the to-be-delivered goods according to the first average goods delivery duration, the second average goods delivery duration, the third average goods delivery duration and the other goods information, specifically including:
using a preset formula
Calculating the first delivery duration of the to-be-delivered goods, wherein T is the first delivery duration of the to-be-delivered goods, T1 is the first average goods delivery duration, T2 is the second average goods delivery duration, T3 is the third average goods delivery duration, n is the quantity of the goods to be delivered carried by the delivery party this time, and T4 i For the second delivery duration of the other goods delivered before the goods to be delivered, k1, k2, k3 and k4 are weight coefficient values of various parameters.
7. A non-transitory readable storage medium having stored thereon a computer program, wherein the program when executed by a processor implements the method of processing logistics distribution information of any one of claims 1 to 5.
8. A computer device comprising a non-volatile readable storage medium, a processor and a computer program stored on the non-volatile readable storage medium and executable on the processor, characterized in that the processor implements the method of processing logistics distribution information according to any one of claims 1 to 5 when executing the program.
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| CN113313439B (en) * | 2020-02-26 | 2024-04-05 | 北京京东振世信息技术有限公司 | Method and device for calculating time length of tall-in-hand |
| CN113792951B (en) * | 2020-12-24 | 2024-01-12 | 北京京东振世信息技术有限公司 | Logistics distribution method and device, storage medium and electronic equipment |
| CN112862398B (en) * | 2021-02-08 | 2024-01-26 | 北京顺达同行科技有限公司 | Logistics distribution adjustment method and device and computer readable storage medium |
| CN113033924A (en) * | 2021-05-06 | 2021-06-25 | 杭州师范大学 | Method for predicting delivery duration of package driven by historical data based on Boosting algorithm |
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