CN116384853B

CN116384853B - Digital twin intelligent logistics management method and device

Info

Publication number: CN116384853B
Application number: CN202310205047.0A
Authority: CN
Inventors: 张磊; 周志刚; 卢阳; 李俊伟
Original assignee: Hubei Proge Technology Co ltd
Current assignee: Hubei Proge Technology Co ltd
Priority date: 2023-03-01
Filing date: 2023-03-01
Publication date: 2024-02-09
Anticipated expiration: 2043-03-01
Also published as: CN116384853A

Abstract

The invention relates to the technical field of intelligent logistics, and discloses a digital twin intelligent logistics management method and device, wherein the method comprises the following steps: calculating average logistics sorting quantity according to the total sorting quantity of the net points and standard logistics sorting quantity, obtaining a target transfer cargo set to be transferred in the current logistics sorting net points, judging whether the target transfer cargo set has the over-period cargo, transferring the over-period cargo if the target transfer cargo set has the over-period cargo, recording the transfer time of the target transfer cargo set if the target transfer cargo set does not have the over-period cargo, extracting the logistics transfer quantity of the upper logistics sorting net point set in the lower logistics sorting net point, simulating the logistics transfer quantity of the lower logistics sorting net point, calculating the logistics sorting index of the lower logistics sorting net point according to the current inventory quantity, the logistics transfer quantity and the logistics transfer quantity, and transferring the cargo set to be transferred to the target sorting net point according to the logistics sorting index. The invention mainly aims to solve the problems of low transportation efficiency and high cargo accumulation risk of the current cargo transportation mode.

Description

Digital twin intelligent logistics management method and device

Technical Field

The invention relates to a management method and device of digital twin intelligent logistics, and belongs to the technical field of intelligent logistics.

Background

With the development of new generation information technology, digital Twin (Digital Twin) establishes a multi-dimensional, multi-time-space-scale, multi-physical-quantity and multi-disciplinary dynamic virtual model of a physical entity in a Digital manner, and realizes the reproduction of the attribute, behavior and rule of the dynamic virtual model in a real environment.

With the development of electronic commerce, a large number of fragmented orders are generated, so that phenomena such as bin explosion, false delivery, missing delivery, violent sorting, express delivery loss and the like are frequent, the current goods are transported mainly from a delivery place to a delivery post near the receiving place through step-by-step sorting and forwarding through sorting centers at different levels, and when the sorting centers receive the goods sent by the sorting center at the upper level or the delivery place, the goods are accumulated to a certain degree and then are forwarded to the next sorting center or the delivery post through a logistics vehicle. However, the cargo forwarding mode is generally decided subjectively by sorting and transporting personnel, when idle transportation vehicles exist in a sorting center and a certain amount of cargoes to be transported exist in the sorting center, the cargoes to be transported are directly transported to the corresponding sorting center, and therefore the cargo transporting mode has the problems of low transportation efficiency, high cargo stacking risk and the like.

Disclosure of Invention

The invention provides a management method and device of digital twin intelligent logistics and a computer readable storage medium, and mainly aims to solve the problems of low transportation efficiency and high cargo accumulation risk of a cargo transportation mode.

In order to achieve the above object, the present invention provides a method for managing digital twin smart logistics, comprising:

creating a digital twin logistics model according to a pre-constructed logistics sorting net point set and a logistics line set, and obtaining net point sorting total amount of the digital twin logistics model;

obtaining standard logistics sorting quantity of each logistics sorting lattice point in the digital twin logistics model, and calculating average logistics sorting quantity of each logistics sorting lattice point according to the total sorting quantity of lattice points and the standard logistics sorting quantity;

extracting a current logistics sorting net point from the digital twin logistics model, and extracting a lower logistics sorting net point set of the current logistics sorting net point;

sequentially extracting lower-level logistics sorting net points in the lower-level logistics sorting net point set, and acquiring a target transfer cargo set which is required to be transferred to the lower-level logistics sorting net point in the current logistics sorting net point;

acquiring the current inventory of the subordinate logistics sorting network points, and judging whether the target transportation cargo set has overtime cargoes or not;

If the target transported cargoes are concentrated and have the overtime cargoes, transporting the overtime cargoes to the lower logistics sorting network point;

if the target transport cargo set does not have the out-of-date cargo, recording transport duration of the target transport cargo set from the current logistics sorting net point to the subordinate logistics sorting net point in the digital twin logistics model in a simulated manner;

acquiring an upper-level logistics sorting net point set of the lower-level logistics sorting net point, and extracting the logistics transfer quantity of the upper-level logistics sorting net point set which can be transferred to the lower-level logistics sorting net point within the transfer time;

simulating the material flow output of a downstream material flow sorting net point in the transferring time period by using the digital twin material flow model;

calculating the goods forecast quantity of the lower-level logistics sorting net point according to the current inventory quantity, the logistics transfer quantity and the logistics transfer quantity of the lower-level logistics sorting net point;

calculating the logistics sorting index of the lower logistics sorting net point according to the average logistics sorting amount and the goods pre-measurement of the lower logistics sorting net point;

and screening out target sorting net points in the lower-level logistics sorting net points according to the logistics sorting indexes, identifying a cargo set to be transported in the current logistics sorting net points by the target sorting net points, transporting the cargo set to be transported to the target sorting net points, and completing management of digital twin intelligent logistics.

Optionally, the creating a digital twin logistics model according to the pre-constructed logistics sorting network point set and the logistics line set includes:

obtaining the geographic position of each logistics sorting net point in the logistics sorting net point set, and creating a digital twin net point model of each logistics sorting net point according to the geographic position;

sequentially extracting logistics sorting net points from the digital twin net point model, and obtaining the transfer range of the logistics sorting net points;

extracting a lower-level logistics sorting net point set of the logistics sorting net point in a digital twin net point model according to the transfer range;

obtaining a logistics line set of each lower logistics sorting lattice point in the logistics sorting lattice point and the lower logistics sorting lattice point set;

connecting the logistics sorting net points in the digital twin net point model by using a logistics line set of each logistics sorting net point in the digital twin net point model to obtain an initial digital twin logistics model;

and acquiring cargo sorting data of all logistics sorting sites in the initial digital twin logistics model and real-time transportation data on all logistics lines, and displaying the cargo sorting data and the real-time transportation data on the initial digital twin logistics model to obtain the digital twin logistics model.

Optionally, the calculating the average sorting amount of each sorting point according to the sorting total amount of the points and the standard sorting amount of the streams includes:

calculating the standard logistics sorting total amount according to the standard logistics sorting amount of each logistics sorting site;

calculating the average logistics sorting amount of each logistics sorting net point according to the standard logistics sorting amount, the standard logistics sorting total amount, the net point sorting total amount and a pre-constructed average logistics sorting amount calculation formula, wherein the average logistics sorting amount calculation formula is as follows:

wherein A is _i Representing the average logistics sorting amount of the ith logistics sorting net point, S _w Representing the sorting total amount of net points s _i Standard logistics sorting quantity representing ith logistics sorting net point S _I Representing a standard logistics sorting aggregateAmount of the components.

Optionally, the determining whether the target transported cargo set has an out-of-date cargo includes:

acquiring the transportation time limit and the transportation distance of each piece of goods in the target transported goods set;

calculating the cut-off time of each piece of goods at the current logistics sorting network point according to the transportation time limit and the transportation route by using a pre-constructed cut-off time calculation formula, wherein the cut-off time calculation formula is as follows:

Wherein t is _j Indicating the deadline, t, of the j-th item in the target shipment set _s T represents the time when the j-th article in the target transfer cargo set starts to be transported _x Representing the transportation time limit of the j-th goods in the target transported goods set, l _j Representing the transportation distance between the initial transportation site of the j-th goods in the target transportation goods set and the current logistics sorting network point, L _j And the transport path of the j-th cargo in the target transport cargo set from the start transport position to the end transport position is represented.

Acquiring current time and judging whether the current time exceeds a deadline or not;

if the current time does not exceed the deadline, no out-of-date goods exist in the target transport goods set;

and if the current time exceeds the deadline, the target transported goods are concentrated to have out-of-date goods.

Optionally, the transferring the overtime cargo to the subordinate logistics sorting website includes:

acquiring unit transportation quantity of the current logistics sorting network points;

sorting cargoes in the target transported cargo set according to the deadline of each cargo to obtain a cargo sequence to be transported;

extracting an over-period cargo set containing the over-period cargo from the cargo sequence to be transported according to the unit transport quantity;

And transferring the out-of-date cargo set to the lower logistics sorting network point.

Optionally, the extracting the flow transfer amount of the upper-level flow sorting dot set that can be transferred to the lower-level flow sorting dot set in the transfer duration includes:

modeling a transport vehicle of which the upper logistics sorting net point set moves within the transfer time period by utilizing the digital twin logistics simulation to obtain a transport vehicle set;

identifying transport vehicles which can reach the subordinate logistics sorting sites in the transport vehicle set within the transfer time period to obtain a target vehicle set;

and extracting the cargo transportation quantity of each target vehicle in the target vehicle set to obtain the logistics transfer quantity of the subordinate logistics sorting network points.

Optionally, the calculating the logistics sorting index of the lower logistics sorting site according to the average logistics sorting amount and the goods pre-measurement of the lower logistics sorting site includes:

calculating the logistics sorting index of the lower logistics sorting net point by using the average logistics sorting amount and the goods pre-measurement of the lower logistics sorting net point according to a pre-constructed logistics sorting index formula, wherein the logistics sorting index formula is as follows:

Wherein k is _i A stream sort index, a, representing the i-th subordinate stream sort point _i Representing the forecast amount of cargo at the ith downstream sorting point.

Optionally, the screening out the target sorting sites in the lower-level logistics sorting site set according to the logistics sorting index includes:

extracting the minimum logistics sorting index from the logistics sorting indexes of each subordinate logistics sorting net point;

and identifying the lower-level logistics sorting net point corresponding to the minimum logistics sorting index, and taking the lower-level logistics sorting net point corresponding to the minimum logistics sorting index as the target sorting net point.

Optionally, the extracting the lower-level logistics sorting network point set of the current logistics sorting network point includes:

determining the transfer range of the current logistics sorting network point;

and extracting all lower-level logistics sorting net points of the current logistics sorting net point according to the transferring range to obtain the lower-level logistics sorting net point set.

In order to solve the above problems, the present invention also provides a management device for digital twin smart logistics, the device comprising:

the average logistics sorting amount calculating module is used for creating a digital twin logistics model according to the pre-constructed logistics sorting net point set and the logistics line set, and obtaining net point sorting total amount of the digital twin logistics model; obtaining standard logistics sorting quantity of each logistics sorting lattice point in the digital twin logistics model, and calculating average logistics sorting quantity of each logistics sorting lattice point according to the total sorting quantity of lattice points and the standard logistics sorting quantity;

The over-period cargo transferring module is used for extracting current logistics sorting net points from the digital twin logistics model and extracting a lower logistics sorting net point set of the current logistics sorting net points; sequentially extracting lower-level logistics sorting net points in the lower-level logistics sorting net point set, and acquiring a target transfer cargo set which is required to be transferred to the lower-level logistics sorting net point in the current logistics sorting net point; acquiring the current inventory of the subordinate logistics sorting network points, and judging whether the target transportation cargo set has overtime cargoes or not; if the target transported cargoes are concentrated and have the overtime cargoes, transporting the overtime cargoes to the lower logistics sorting network point;

the cargo prediction simulation calculation module is used for recording the transfer duration of the target transfer cargo set from the current logistics sorting website to the subordinate logistics sorting website in the digital twin logistics model if the target transfer cargo set does not have the out-of-date cargo; acquiring an upper-level logistics sorting net point set of the lower-level logistics sorting net point, and extracting the logistics transfer quantity of the upper-level logistics sorting net point set which can be transferred to the lower-level logistics sorting net point within the transfer time; simulating the material flow output of a downstream material flow sorting net point in the transferring time period by using the digital twin material flow model; calculating the goods forecast quantity of the lower-level logistics sorting net point according to the current inventory quantity, the logistics transfer quantity and the logistics transfer quantity of the lower-level logistics sorting net point;

The cargo set transfer module to be transferred is used for calculating the logistics sorting index of the lower logistics sorting net point according to the average logistics sorting amount of the lower logistics sorting net point and the cargo pre-measurement; and screening out target sorting net points in the lower-level logistics sorting net points according to the logistics sorting indexes, identifying a to-be-transported cargo set of the target sorting net points in the current logistics sorting net points, and transporting the to-be-transported cargo set to the target sorting net points.

In order to solve the above-mentioned problems, the present invention also provides an electronic apparatus including:

at least one processor; and a memory communicatively coupled to the at least one processor; wherein,

the memory stores instructions executable by the at least one processor to implement the method of managing digital twin smart streams described above.

In order to solve the above-mentioned problems, the present invention also provides a computer-readable storage medium having at least one instruction stored therein, the at least one instruction being executed by a processor in an electronic device to implement the above-mentioned management method of digital twin smart logistics.

Compared with the prior art that the cargo transportation mode has the problems of low transportation efficiency and high cargo accumulation risk, in order to embody the real-time logistics transportation condition, the embodiment of the invention firstly creates a digital twin logistics model according to the pre-constructed logistics sorting net point set and the logistics line set, then calculates the average logistics sorting amount of each logistics sorting net point according to the net point sorting total amount and the standard logistics sorting amount extracted from the digital twin logistics model, firstly extracts the lower logistics sorting net point set of the current logistics sorting net point in order to determine the cargo transportation condition of the current logistics sorting net point, then screens out the target sorting net point in the lower logistics sorting net point, and when the target sorting net point is specifically determined, firstly judges whether the target transportation net point has the out-of-period cargo, because the priority of the out-period cargo should be the highest, if the object transfer cargo set does not exist, recording the transfer time length of the object transfer cargo set from the current logistics sorting net point to the lower logistics sorting net point in the digital twin logistics model to obtain the simulated time length, acquiring an upper logistics sorting net point set of the lower logistics sorting net point, extracting the logistics transfer quantity of the upper logistics sorting net point set which can be transferred to the lower logistics sorting net point in the transfer time length, simulating the logistics transfer quantity of the lower logistics sorting net point in the transfer time length by using the digital twin logistics model, finally calculating the cargo pre-measurement quantity of the lower logistics sorting net point according to the current inventory quantity, the logistics transfer quantity and the logistics transfer quantity of the lower logistics sorting net point, and calculating the logistics sorting index of the lower logistics sorting net point according to the average logistics sorting amount and the goods pre-measurement of the lower logistics sorting net point, screening out target sorting net points in the lower logistics sorting net point according to the logistics sorting index, identifying the goods set to be transported in the current logistics sorting net point by the target sorting net point, transporting the goods set to be transported to the target sorting net point, and completing the management of digital twin intelligent logistics. Therefore, the management method, the management device, the electronic equipment and the computer readable storage medium of the digital twin intelligent logistics mainly aim to solve the problems of low transportation efficiency and high cargo accumulation risk of a cargo transportation mode.

Drawings

FIG. 1 is a flow chart of a method for managing digital twin-wisdom flows according to an embodiment of the present invention;

FIG. 2 is a functional block diagram of a management device for digital twin intelligent logistics according to an embodiment of the present invention;

fig. 3 is a schematic structural diagram of an electronic device for implementing the method for managing digital twin-wisdom logistics according to an embodiment of the present invention.

The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.

Detailed Description

It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.

The embodiment of the application provides a management method of digital twin intelligent logistics. The execution subject of the digital twin smart stream management method includes, but is not limited to, at least one of a server, a terminal, and the like, which can be configured to execute the method provided by the embodiments of the present application. In other words, the management method of the digital twin smart stream may be performed by software or hardware installed at a terminal device or a server device. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.

Example 1:

referring to fig. 1, a flow chart of a method for managing digital twin-wisdom flows according to an embodiment of the invention is shown. In this embodiment, the method for managing digital twin smart logistics includes:

s1, creating a digital twin logistics model according to a pre-constructed logistics sorting net point set and a logistics line set, and obtaining net point sorting total amount of the digital twin logistics model.

The logistic sorting network point set refers to a sorting center set of cargoes in the transferring process, for example: transfer stations or stagers where the express delivery needs to be sorted during transportation, etc. The logistics line set refers to a line set of goods in the transportation process, for example: a plurality of logistics lines are usually arranged between two logistics sorting points of the transportation line of the express. The digital twin logistics model can display the position distribution condition of the logistics sorting net point set, the cargo sorting data of each logistics sorting net point, the route distribution of the logistics line set, the vehicle information being transported on each logistics line and other data. The net point sorting total amount refers to the total amount of cargo being transported in the digital twin logistics model, for example: the goods temporarily stored and sorted in the sorting center, the goods transported on the logistics line and the like.

In the embodiment of the invention, the creating of the digital twin logistics model according to the pre-constructed logistics sorting network point set and the logistics line set comprises the following steps:

Further, the transfer range of the logistics sorting dots refers to a transfer area of the logistics sorting dots, so that each logistics sorting dot has a corresponding transfer area in order to avoid exceeding the logistics transfer range, and different other logistics sorting dots may exist in the transfer area. The lower-level logistics sorting net point set refers to a logistics sorting net point set in the transferring range.

The cargo sorting data can be explained to be the number of sorted cargos, the number of to-be-sorted cargos, the cargo sorting progress and the like of the logistics sorting network point cargos. The real-time transportation data refers to the data of vehicle information, real-time position information, the number of cargos carried by the vehicle, the transportation speed of the vehicle, driver information of the vehicle, a transportation destination, a transportation starting place and the like of the cargos transported on the logistics line.

S2, obtaining standard logistics sorting quantity of each logistics sorting lattice point in the digital twin logistics model, and calculating average logistics sorting quantity of each logistics sorting lattice point according to the lattice point sorting total quantity and the standard logistics sorting quantity.

It should be explained that the standard logistics sorting amount refers to a cargo sorting capability determined according to a construction scale of each logistics sorting site, for example: the standard logistics sorting quantity of each logistics sorting site can be determined according to the data such as the number of personnel, the floor area, the configuration number of sorting machine equipment and the like of the logistics sorting sites, and the standard logistics sorting quantity of the logistics sorting sites is generally larger as the number of personnel, the configuration number of the sorting machine equipment and the floor area are larger.

In detail, the average logistics sorting amount refers to the logistics sorting amount correspondingly born by each logistics sorting net point in the net point sorting total amount according to the standard logistics sorting amount of each logistics sorting net point, and the higher the standard logistics sorting amount is, the larger the average logistics sorting amount of the logistics sorting net point is.

In the embodiment of the present invention, the calculating the average sorting amount of each sorting point according to the sorting total amount of the points and the standard sorting amount of the streams includes:

wherein A is _i Representing the average logistics sorting amount of the ith logistics sorting net point, S _w Representing the sorting total amount of net points s _i Standard logistics sorting quantity representing ith logistics sorting net point S _I Indicating the total amount of standard stream sorting.

It can be understood that when the rapid increase of the express delivery amount occurs, the sorting amount of the logistics borne by each logistics sorting site is different, the possible logistics sorting amount of the logistics sorting site greatly exceeds the standard logistics sorting amount, and the logistics sorting amount of the logistics sorting site does not reach the standard logistics sorting amount, so that the sorting pressure of cargoes can be relieved to the greatest extent only when all the logistics sorting sites bear the corresponding logistics sorting amount according to the standard logistics sorting amount of the logistics sorting sites in proportion, and the condition that extreme logistics sorting amount occurs in some logistics sorting sites is avoided.

S3, extracting current logistics sorting net points from the digital twin logistics model, and extracting a lower logistics sorting net point set of the current logistics sorting net points.

In the embodiment of the present invention, the extracting the lower-level logistics sorting network point set of the current logistics sorting network point includes:

determining the transfer range of the current logistics sorting network point;

S4, sequentially extracting the lower-level logistics sorting net points in the lower-level logistics sorting net point set, and acquiring a target transfer cargo set which is required to be transferred to the lower-level logistics sorting net point in the current logistics sorting net point.

In this embodiment of the present invention, each piece of goods in the current logistics sorting site has an initial delivery site and a target receiving site, so that there may be a plurality of known transportation routes between the initial delivery site and the target receiving site, corresponding to a plurality of different logistics sorting sites, which may cause a situation that a piece of goods needs to pass through one or more subordinate logistics sorting sites in the subordinate logistics sorting site set in the current logistics sorting site, for example: the current logistics sorting net point is an A sorting net point, the lower logistics sorting net point set of the A sorting net point is a B sorting net point, a C sorting net point, a D sorting net point and an E sorting net point, and at the moment, cargoes a and cargoes B exist in the A sorting net point, wherein the cargoes a can be transported through the C sorting net point, the D sorting net point and the E sorting net point; the C sorting net point can be skipped, and the transfer can be directly carried out from the D sorting net point and the E sorting net point; the C sorting net point and the D sorting net point can be skipped, and the goods are directly transferred from the E sorting net point, so that the goods a have three different transferring modes, and the goods a can be transferred as targets of the C sorting net point, the D sorting net point and the E sorting net point. Only the transfer of the goods B from the B sorting site refers to one line, and therefore the goods B can only be used as the target transfer goods of the B sorting site.

S5, acquiring the current inventory of the subordinate logistics sorting network points, and judging whether the target transportation cargo sets have overtime cargoes or not.

It can be understood that the current inventory of the lower-level logistics sorting network point refers to the quantity of cargos such as cargos being sorted and cargos waiting to be sorted in the lower-level logistics sorting network point.

In the embodiment of the present invention, the determining whether the target transported cargo set has an overtime cargo includes:

It can be explained that, in order to approximate whether the goods are out of date, they can be distributed according to the transport path according to the transport duration, and when half of the transport path is reached, the transport time should be less than or equal to half of the transport duration.

And if the target transported cargoes are concentrated and have the out-of-date cargoes, executing S6, and transporting the out-of-date cargoes to the lower logistics sorting network point.

In an embodiment of the present invention, the transferring the out-of-date cargo to the lower-level logistics sorting website includes:

In the embodiment of the present invention, the cargo sequence to be transported refers to a cargo sequence obtained by sorting cargoes according to a transportation period, for example: the cut-off time of the goods a is 1 point of 2 nd month in 2020, the cut-off time of the goods b is 3 points of 2 nd month in 2020, the cut-off time of the goods c is 1 point of 3 nd month in 2020, the cut-off time of the goods d is 1 point of 4 th month in 2020, etc., the goods to be transported are the goods d, the goods c, the goods b and the goods a, etc., and if the unit transportation amount is 1000 goods, the over-period goods set is the first 1000 goods set in the goods to be transported.

And if the target transfer cargo set does not have the out-of-date cargo, executing S, and recording the transfer duration of the target transfer cargo set from the current logistics sorting net point to the subordinate logistics sorting net point in the digital twin logistics model in a simulation manner.

It can be appreciated that the simulated transportation refers to the transportation of the target transportation cargo set from the current logistics sorting website to the subordinate logistics sorting website, and the speed of the wagon for the simulated transportation can be estimated according to the current time, the current weather, the speed limit condition of the logistics line, the congestion condition of the logistics line and other data, for example: the speed of the train in rainy and snowy weather is low. The speed of the train is set by integrating various external transportation condition data, and the transportation distance between the current logistics sorting network point and the subordinate logistics sorting network point is calculated, so that the transportation time length is calculated. The truck speed can also be predicted based on previous transit times under various transportation conditions.

S8, acquiring an upper-level logistics sorting net point set of the lower-level logistics sorting net point, and extracting logistics transfer quantity of the upper-level logistics sorting net point set which can be transferred to the lower-level logistics sorting net point in the transfer time.

It can be appreciated that, since each logistics sorting site in the logistics line generally has a lower logistics sorting site and an upper logistics sorting site, the lower logistics sorting site may have a plurality of upper logistics sorting sites, where the current logistics sorting site is only one of the plurality of upper logistics sorting sites.

In the embodiment of the present invention, the extracting the flow transfer amount of the upper-level flow sorting dot set that can be transferred to the lower-level flow sorting dot set in the transfer duration includes:

Further, the collection of transport vehicles may be vehicles that are currently being transported and vehicles that will be transported during the transit time period. Because of inconsistent departure times of trucks, situations may occur when departure times are late, such as, for example, when the lower logistics sorting sites cannot be reached within a transit time period: the transfer duration is 9:00-15:00, the transport vehicle in the upper level logistics sorting point a is expected to start from 12:00, and the estimated time from the upper level logistics sorting point a to the lower level logistics sorting point a is 5 hours, so that the estimated time will be 17:00 arrives when the transport vehicle cannot be the target vehicle.

And S9, simulating the material flow output of the downstream material flow sorting net point in the transferring time period by using the digital twin material flow model.

The logistics transfer amount can be explained to be the total amount of goods transferred to other logistics sorting sites in the transfer range of the subordinate logistics sorting sites in the transfer time period.

In the embodiment of the invention, the simulation mode of the material flow quantity of the lower-level material flow sorting net point in the transferring time period is the same as the transferring mode of the current material flow sorting net point, namely the lower-level material flow sorting net point is used as the current material flow sorting net point for simulation, and the cargo transferring mode of the current material flow sorting net point is determined according to the cargo storing quantity of the lower-level material flow sorting net point, and the cargo storing quantity of the lower-level material flow sorting net point is determined according to the cargo transferring mode of the lower-level material flow sorting net point, so that the cargo transferring of all the material flow sorting net points depends on the cargo storing quantity of the material flow sorting net point closest to the destination, and when the cargo storing quantity of the material flow sorting net point is smaller, the probability of being used as a transferring target is larger. After the goods transfer mode of the logistics sorting network point closest to the destination is determined, all the transfer modes of the logistics sorting network point are driven, so that the simulation possibility is realized.

And S10, calculating the goods forecast quantity of the lower-level logistics sorting net point according to the current inventory quantity, the logistics transfer quantity and the logistics transfer quantity of the lower-level logistics sorting net point.

In the embodiment of the present invention, the cargo forecast amount may be calculated according to the following formula:

h _y ＝h _n -h _out +h _in

wherein h is _y Indicating the predicted amount of goods, h _n Indicating the current inventory, h _out Represents the flow output of the object flow, h _in Indicating the amount of transfer of the stream.

S11, calculating the logistics sorting index of the lower logistics sorting net point according to the average logistics sorting amount and the goods pre-measurement of the lower logistics sorting net point.

The logistics sorting index is used for indicating the saturation of the stored cargoes in the lower logistics sorting network point after the target transportation cargo set arrives.

In the embodiment of the present invention, the calculating the logistics sorting index of the lower logistics sorting site according to the average logistics sorting amount and the goods pre-measurement of the lower logistics sorting site includes:

S12, screening out target sorting net points in the lower-level logistics sorting net point concentrate according to the logistics sorting index, identifying a cargo set to be transported in the current logistics sorting net point by the target sorting net point, transporting the cargo set to be transported to the target sorting net point, and completing management of digital twin intelligent logistics.

The to-be-transported cargo set can be explained to be a cargo set which can be transported to the target sorting site in the current logistics sorting site.

In the embodiment of the present invention, the screening the target sorting sites in the lower-level logistics sorting site set according to the logistics sorting index includes:

It should be understood that, the lower-level logistics sorting net point corresponding to the smallest logistics sorting index indicates that the cargo saturation of the lower-level logistics sorting net point is the smallest, that is, the cargo storage sorting amount of the net point does not reach reasonable use, and most of the net points are in a vacant state, so that the lower-level logistics sorting net point corresponding to the smallest logistics sorting index should be used as the target sorting net point. Thereby effectively balancing the goods storage sorting amount of each logistics sorting net point.

It can be appreciated that after the target sorting site is determined, the cargo set to be transferred can be transferred from the current logistics sorting site.

Example 2:

fig. 2 is a functional block diagram of a management device for digital twin intelligent logistics according to an embodiment of the present invention.

The management device 100 for digital twin intelligent logistics can be installed in electronic equipment. According to the implemented functions, the management device 100 for digital twin smart logistics may include an average logistics sorting amount calculation module 101, an over-period cargo transferring module 102, a cargo prediction amount simulation calculation module 103, and a cargo set transferring module 104 to be transferred. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.

The average logistics sorting amount calculation module 101 is configured to create a digital twin logistics model according to a pre-constructed logistics sorting net point set and a logistics line set, and obtain net point sorting total amount of the digital twin logistics model; obtaining standard logistics sorting quantity of each logistics sorting lattice point in the digital twin logistics model, and calculating average logistics sorting quantity of each logistics sorting lattice point according to the total sorting quantity of lattice points and the standard logistics sorting quantity;

The over-period cargo transferring module 102 is configured to extract a current logistics sorting network point from the digital twin logistics model, and extract a lower logistics sorting network point set of the current logistics sorting network point; sequentially extracting lower-level logistics sorting net points in the lower-level logistics sorting net point set, and acquiring a target transfer cargo set which is required to be transferred to the lower-level logistics sorting net point in the current logistics sorting net point; acquiring the current inventory of the subordinate logistics sorting network points, and judging whether the target transportation cargo set has overtime cargoes or not; if the target transported cargoes are concentrated and have the overtime cargoes, transporting the overtime cargoes to the lower logistics sorting network point;

the cargo prediction simulation calculation module 103 is configured to record a transfer duration of the target transfer cargo set from the current logistics sorting website to the subordinate logistics sorting website in the digital twin logistics model if no out-of-date cargo exists in the target transfer cargo set; acquiring an upper-level logistics sorting net point set of the lower-level logistics sorting net point, and extracting the logistics transfer quantity of the upper-level logistics sorting net point set which can be transferred to the lower-level logistics sorting net point within the transfer time; simulating the material flow output of a downstream material flow sorting net point in the transferring time period by using the digital twin material flow model; calculating the goods forecast quantity of the lower-level logistics sorting net point according to the current inventory quantity, the logistics transfer quantity and the logistics transfer quantity of the lower-level logistics sorting net point;

The cargo set transferring module 104 is configured to calculate a logistics sorting index of the lower logistics sorting site according to the average logistics sorting amount and the cargo pre-measurement of the lower logistics sorting site; and screening out target sorting net points in the lower-level logistics sorting net points according to the logistics sorting indexes, identifying a to-be-transported cargo set of the target sorting net points in the current logistics sorting net points, and transporting the to-be-transported cargo set to the target sorting net points.

In detail, the modules in the device 100 for managing digital twin-wisdom flows in the embodiment of the present invention use the same technical means as the method for managing digital twin-wisdom flows in fig. 1, and can produce the same technical effects, which are not described herein.

Example 3:

fig. 3 is a schematic structural diagram of an electronic device for implementing a method for managing digital twin-wisdom logistics according to an embodiment of the present invention.

The electronic device 1 may comprise a processor 10, a memory 11, a bus 12 and a communication interface 13, and may further comprise a computer program stored in the memory 11 and executable on the processor 10, such as a management program for digital twinning smart streams.

The memory 11 includes at least one type of readable storage medium, including flash memory, a mobile hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. The memory 11 may in other embodiments also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic device 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 may be used not only for storing application software installed in the electronic device 1 and various types of data, such as codes of a management program of a digital twin smart stream, etc., but also for temporarily storing data that has been output or is to be output.

The processor 10 may be comprised of integrated circuits in some embodiments, for example, a single packaged integrated circuit, or may be comprised of multiple integrated circuits packaged with the same or different functions, including one or more central processing units (Central Processing unit, CPU), microprocessors, digital processing chips, graphics processors, combinations of various control chips, and the like. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various parts of the entire electronic device using various interfaces and lines, executes programs or modules (e.g., a management program of digital twin smart logistics, etc.) stored in the memory 11 by running or executing the programs or modules, and invokes data stored in the memory 11 to perform various functions of the electronic device 1 and process the data.

The bus may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory 11 and at least one processor 10 etc.

Fig. 3 shows only an electronic device with components, it being understood by a person skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or may combine certain components, or may be arranged in different components.

For example, although not shown, the electronic device 1 may further include a power source (such as a battery) for supplying power to each component, and preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management, and the like are implemented through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device 1 may further include various sensors, bluetooth modules, wi-Fi modules, etc., which will not be described herein.

Further, the electronic device 1 may also comprise a network interface, optionally the network interface may comprise a wired interface and/or a wireless interface (e.g. WI-FI interface, bluetooth interface, etc.), typically used for establishing a communication connection between the electronic device 1 and other electronic devices.

The electronic device 1 may optionally further comprise a user interface, which may be a Display, an input unit, such as a Keyboard (Keyboard), or a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device 1 and for displaying a visual user interface.

It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.

The management program of the digital twin-wisdom stream stored in the memory 11 of the electronic device 1 is a combination of instructions that, when executed in the processor 10, can implement:

Specifically, the specific implementation method of the above instruction by the processor 10 may refer to descriptions of related steps in the corresponding embodiments of fig. 1 to 2, which are not repeated herein.

Further, the modules/units integrated in the electronic device 1 may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).

The present invention also provides a computer readable storage medium storing a computer program which, when executed by a processor of an electronic device, can implement:

The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.

It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.

Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method of managing digital twin smart logistics, the method comprising:

obtaining standard logistics sorting quantity of each logistics sorting lattice point in the digital twin logistics model, and calculating average logistics sorting quantity of each logistics sorting lattice point according to the total sorting quantity of lattice points and the standard logistics sorting quantity; calculating the average logistics sorting amount of each logistics sorting net point according to the net point sorting total amount and the standard logistics sorting amount, including:

wherein A is _i Representing the average logistics sorting amount of the ith logistics sorting net point, S _w Representing the sorting total amount of net points s _i Standard logistics sorting quantity representing ith logistics sorting net point S _I Representing the total amount of standard stream sorting;

calculating the logistics sorting index of the lower logistics sorting net point according to the average logistics sorting amount and the goods pre-measurement of the lower logistics sorting net point; calculating the logistics sorting index of the lower logistics sorting net point according to the average logistics sorting amount and the goods pre-measurement of the lower logistics sorting net point, comprising:

Wherein k is _i A stream sort index, a, representing the i-th subordinate stream sort point _i Representing a cargo forecast amount of an ith subordinate logistics sorting site; a is that _i Representing the average flow sorting amount of the ith flow sorting net point;

screening out target sorting net points in the lower-level logistics sorting net points according to the logistics sorting indexes, identifying a cargo set to be transported in the current logistics sorting net points by the target sorting net points, transporting the cargo set to be transported to the target sorting net points, and completing management of digital twin intelligent logistics;

the step of screening out target sorting sites in the lower-level logistics sorting sites according to the logistics sorting index comprises the following steps:

2. The method for managing digital twin smart logistics according to claim 1, wherein creating a digital twin logistics model from the pre-constructed logistics sorting network point set and logistics line set comprises:

3. The method of claim 1, wherein determining whether the target shipment set has an out-of-date shipment comprises:

wherein t is _j Indicating the deadline, t, of the j-th item in the target shipment set _s T represents the time when the j-th article in the target transfer cargo set starts to be transported _x Representing the transportation time limit of the j-th goods in the target transported goods set, l _j Representing the transportation distance between the initial transportation site of the j-th goods in the target transportation goods set and the current logistics sorting network point, L _j A transport path indicating a start transport location distance from an end transport location of a j-th cargo in the target shipment set;

4. A method of managing digital twin wisdom logistics according to claim 3, wherein the transferring the out-of-date cargo to the subordinate logistics sorting sites comprises:

5. The method for managing digital twin intelligent logistics according to claim 4, wherein said extracting the amount of transfer of said upper logistics sorting dot set to said lower logistics sorting dot set within said transfer period comprises:

6. The method for managing digital twin intelligent logistics according to claim 2, wherein said extracting a downstream logistics sorting grid set of said current logistics sorting grid comprises:

Determining the transfer range of the current logistics sorting network point;

7. A device for managing a digital twin smart stream, characterized in that it is used for applying the method for managing a digital twin smart stream according to any one of claims 1 to 6, said device comprising: