CN110322128A - Vehicle and goods matching method, apparatus and computer storage medium - Google Patents
Vehicle and goods matching method, apparatus and computer storage medium Download PDFInfo
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Abstract
The application case study on implementation provides a kind of vehicle and goods matching method, apparatus and computer storage medium, the described method includes: obtaining the essential attribute of cargo, the weight and volume of cargo, the essential information of vehicle are analyzed, by the fusion of data, the calculating of logic, carries out the transport matching of cargo；According to the essential information of the Attribute Association loading vehicles of cargo, matches schedulable vehicle and called for dominating；According to the matching result of cargo and vehicle, allotment decision is provided, and provides specific vehicle deploying scheme；The application can select that cost is few according to " freight " that can be called, and the high goods stock of charging ratio provides the loading pattern of cargo on each freight according to destination.Under the premise of ensuring that task is completed, transportation cost is reduced.
Description
Technical field
This application involves data processing fields, and in particular to a kind of vehicle and goods matching method, apparatus and computer storage medium.
Background technique
Have broad application prospects at present for applying for cargo intelligent Matching in logistic industry, logistics peak time is to object
For stream company, it will generate shipping wharf explosion, transport not in time, low efficiency, it is at high cost the problems such as, current Logistics Park is more
It is to consider manual sorting.Feature is: place demand is big, vehicle is enough, enough abundances of personnel etc..Logistics Market is for intelligence point
System is picked using not in place.So that entire cargo transport higher cost, client can not receive, accuracy rate is difficult to ensure, low efficiency.
Since shipping is there are many due to specification etc., current many logistics companies are formulating the warp that dispatcher is relied primarily on when transport project
It tests, when in face of complicated transport task, often low efficiency, error rate are high, and transportation cost is ideal not to the utmost.
Summary of the invention
For the problems of the prior art, the application provides a kind of vehicle and goods matching method, apparatus and computer storage medium,
It can select that cost is few according to " freight " that can be called, the high goods stock of charging ratio, and then provide each shipping
The loading pattern of cargo and destination on vehicle.Under the premise of ensuring that task is completed, transportation cost is reduced.
At least one of to solve the above-mentioned problems, the application the following technical schemes are provided:
In a first aspect, the application provides a kind of vehicle and goods matching method, comprising:
The essential attribute for obtaining cargo, analyzes the weight and volume of cargo, the loading information of vehicle, carries out the transport of cargo
Matching；
According to the essential information of the Attribute Association loading vehicles of cargo, matches schedulable vehicle and called for dominating；
According to the matching result of cargo and vehicle, allotment decision is provided, and provides specific vehicle deploying scheme.
Firstly, obtaining the essential attribute of the cargo, the weight and volume of cargo, the loading information of vehicle are analyzed, is carried out
Cargo, vehicle match, comprising:
Vehicle parking data, cargo basic attribute data are collected, to data filtering, compensates, do data transformation, enhance data
The robustness of quantity and model training, wherein the basic attribute data of the cargo includes volume, weight, length and width and senior middle school
It is at least one.
Secondly, the essential information of the Attribute Association loading vehicles according to cargo, matches schedulable vehicle for branch auxiliary tone
With, comprising:
Formulate the optimum allocation principle under the conditions of multi-objective restriction.
Again, the optimum allocation principle formulated under the conditions of multi-objective restriction, comprising:
Cargo, which is established, on the basis of given I vehicle and II vehicle, III vehicle matches corresponding solution；
Constraint is done to the upper and lower level of different shippings.
Finally, the upper and lower level to different shippings does constraint, comprising:
Establish objective function S.t min (∑ xi+∑yi)；
Establish constraint condition, wherein the constraint condition that 1-1 type shipping meets: meet in the case where only with 1-1 lower layer:
19-3.615≤(4.61+0.1)×m1i+(3.615+0.1)×n1i+(4.63+0.1)×k1i≤ 19, i=0,1,
2,3,4,5, the case where upper layer, meets: 19-3.615≤(4.61+0.1) × ε1i+(3.615+0.1)×η1i≤ 19,
The following conditions should be met when only using 1-2 type shipping:
The case where lower layer, meets:
24.3-3.615≤(4.61+0.1)×m2j+(3.615+0.1)×n2j+(4.63+0.1)×k2j≤ 24.3,
Wherein,
The case where upper layer, meets:
24.3-3.615≤(4.61+0.1)×ε2i+(3.615+0.1)×η2i≤ 24.3,
Second aspect, the application provide a kind of vehicle and goods matching device, comprising:
Data preparation module analyzes the weight and volume of cargo, the loading letter of vehicle for obtaining the essential attribute of cargo
Breath carries out the transport matching of cargo；
Vehicle and goods matching module matches schedulable vehicle for the essential information according to the Attribute Association loading vehicles of cargo
It is called for dominating；
Scheme determining module provides allotment decision for the matching result according to cargo and vehicle, and provides specific vehicle
Programs.
Firstly, the data preparation module includes:
Data pre-processing unit, for collecting vehicle parking data, cargo basic attribute data, to data filtering, compensation,
Data transformation is done, the robustness of data bulk and model training is enhanced.
Secondly, the vehicle and goods matching module includes:
Matching unit is extracted in regularization, for formulating the optimum allocation principle under the conditions of multi-objective restriction.
As shown from the above technical solution, the application provides a kind of vehicle and goods matching method, apparatus and computer storage medium, leads to
It crosses the scheduling of automatic adaptation combination physicals and adaptively provides loading pattern, when in face of complicated transport task, be able to solve
Inefficiency, and the very high problem of transportation cost, and propose to establish cargo, vehicle adaptation network, construct cargo, information of vehicles
Chain is fitted fill up the gap data using data, enables cargo and information of vehicles preferable for no matched data point
Matching.
Detailed description of the invention
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is the application
Some embodiments for those of ordinary skill in the art without creative efforts, can also basis
These attached drawings obtain other attached drawings.
Fig. 1 is the flow diagram of the vehicle and goods matching method in the embodiment of the present application；
Fig. 2 is the structural schematic diagram of the vehicle and goods matching device in the embodiment of the present application.
Specific embodiment
To keep the purposes, technical schemes and advantages of the embodiment of the present application clearer, below in conjunction with the embodiment of the present application
In attached drawing, technical solutions in the embodiments of the present application carries out clear, complete description, it is clear that described embodiment is
Some embodiments of the present application, instead of all the embodiments.Based on the embodiment in the application, those of ordinary skill in the art
Every other embodiment obtained without creative efforts, shall fall in the protection scope of this application.
Have broad application prospects in view of being directed to applying for cargo intelligent Matching at present in logistic industry, when logistics peak
Phase is for logistics company, it will generate shipping wharf explosion, transport not in time, low efficiency, it is at high cost the problems such as, current Logistics Park
It is more to consider manual sorting.Feature is: place demand is big, vehicle is enough, enough abundances of personnel etc..Logistics Market for
Intelligent sorting system is using not in place.So that entire cargo transport higher cost, client can not receive, accuracy rate is difficult to ensure,
Low efficiency.Since shipping is there are many due to specification etc., current many logistics companies rely primarily on scheduling when formulating transport project
The experience of personnel, when in face of complicated transport task, often low efficiency, error rate are high, and transportation cost is ideal not to the utmost
The problem of, the application provides a kind of vehicle and goods matching method, apparatus and computer storage medium, passes through automatic adaptation and combines practical goods
Object scheduling adaptively provides loading pattern, when in face of complicated transport task, is able to solve inefficiency, and transportation cost
Very high problem, and propose to establish cargo, vehicle adaptation network, cargo, information of vehicles chain are constructed, for no matched number
Strong point is fitted fill up the gap data using data, cargo and information of vehicles is preferably matched.
Cost is few in order to being selected according to " freight " that can call, the high goods stock of charging ratio, and then gives
The loading pattern of cargo and destination on each freight out.Under the premise of ensuring that task is completed, transportation cost is reduced, this
Application provides a kind of embodiment of vehicle and goods matching method, and referring to Fig. 1, the vehicle and goods matching method specifically includes following content:
Step S101: obtaining the essential attribute of cargo, analyzes the weight and volume of cargo, the loading information of vehicle, carries out
The transport of cargo matches.
Step S102: according to the essential information of the Attribute Association loading vehicles of cargo, schedulable vehicle is matched for branch auxiliary tone
With.
Step S103: according to the matching result of cargo and vehicle, allotment decision is provided, and provides specific vehicle deploying side
Case.
As can be seen from the above description, vehicle and goods matching method provided by the embodiments of the present application, it being capable of the practical goods of automatic adaptation combination
Object scheduling adaptively provides loading pattern, when in face of complicated transport task, is able to solve inefficiency, and transportation cost
Very high problem, and propose to establish cargo, vehicle adaptation network, cargo, information of vehicles chain are constructed, for no matched number
Strong point is fitted fill up the gap data using data, cargo and information of vehicles is preferably matched.
Specific detailed step is as follows:
(1) data preparation: in data preprocessing phase, collect vehicle parking data, cargo basic attribute data (volume,
Weight, length), it to data filtering, compensates, do data transformation, enhance the robustness of data bulk and model training.
Logistics company will transport different model cargo, the application in view of during vanning scheduling decision there are many may,
According to optimum allocation principle under the conditions of multi-objective restriction.Guarantee to distribute in the case where all transport tasks completions as few as possible
Vehicle transports, here, allocation plan of the application selection in the case where shipping is as fully loaded as possible.It can reduce so a large amount of
Matrix operation and program runtime and variable the number of iterations.In view of making full use of cargo space, meeting the requirements
Under the premise of the application use the form that loads in mixture of different automobile types, the use number of heavy goods vehicles can be reduced to a certain extent in this way
Amount.
Establish objective function:
S.t min(∑xi+∑yi),
Establish constraint condition:
1) constraint condition that the shipping of 1-1 type meets:
19-3.615≤(4.61+0.1)×a1i+(3.615+0.1)×b1i≤ 19, i=1,2,3,4,5,
24.3-3.615≤(4.61+0.1)×a2j+(3.615+0.1)×b1j≤ 24.3, j=1,2,3,4,5,6,
2) shipping of 1-2 type should also meet the following conditions under this constraint condition:
3) meet following constraint condition simultaneously:
(2) cargo is established on the basis of given I vehicle and II vehicle, III vehicle matches corresponding solution, but this Shen
Constraint please be done to the upper and lower level of different shippings, since it is considered that guaranteeing shipping smooth ride.It is limited by layer height, height is super
Crossing 1.7 meters of passenger car can only be mounted in 1-1,1-2 type lower layer, so the application is established with drag:
Establish objective function:
S.t min(∑xi+∑yi),
Establish constraint condition:
1) constraint condition that the shipping of 1-1 type meets:
Meet in the case where only with 1-1 lower layer: wherein
19-3.615≤(4.61+0.1)×m1i+(3.615+0.1)×n1i+(4.63+0.1)×k1i≤ 19, i=0,1,
2,3,4,5, the case where upper layer, meets:
19-3.615≤(4.61+0.1)×ε1i+(3.615+0.1)×η1i≤ 19,
The following conditions should be met when only using 1-2 type shipping:
The case where lower layer, meets:
24.3-3.615≤(4.61+0.1)×m2j+(3.615+0.1)×n2j+(4.63+0.1)×k2j≤ 24.3,
Wherein
The case where upper layer, meets:
The load mode of specific cargo is provided by calculating.
Here the application analyzes ship data according to above- mentioned information, and classifies to shipping, to obtain 10
The main riding vehicle of class, since the length of different type shipping changes greatly, shipping is no longer classified, and is solved here
Juche idea be still length according to shipping, width provides corresponding constraint condition, establishes integral linear programming, however here
Even if largely reducing the number of variable, so it should be noted that having carried out preferable mode classification to passenger car
And the algorithm of common solution integral linear programming is also not easy to realize.Similar problems the application can be added with enumerative technique and be followed
The optimal solution of the available problem of some restrictive conditions in ring, and use the more easy calculating knot of the algorithm of branch-and-bound
Fruit；By analyzing the passenger car needed to Layer assignment different number different automobile types above and below shipping, variables number can be increased, this
When enumerative technique no longer be applicable in；The general algorithm for solving linear programming can all encounter that time-consuming, the problems such as being as a result difficult to realize.Therefore
It is preferably solved in order to problem of implementation, can be from the classification analysis of data, optimization algorithm, or increase more effectively, rationally
Ground constraint condition and the estimation of some hypothesis is carried out from problem, convenient for simplifying problem.Here the application is mainly to shipping number
According to reasonably being classified, then to the layering progress in problem it is assumed that simplified model, that is, simplify objective function；Then exist
Each scheme is screened again by the judgement of space utilization rate in program, does so and not only simplifies from some angle analysis
The linear programming model, and preferably avoid the problem that those are missed close to the scheme of optimal solution.In view of variable
More problems.
The application with solve multivariable integral linear programming, and variable number control then combine before classification with
And some condition limitations in cyclic process；By not considering excessively meticulously upper and lower level side to certain form of vehicle in the problem
Case analysis, but be considered as unanimously, to reduce the number of variable (scheme), then determine that variable number carries out optimality analysis, most
The application slightly adjusts result obtained above according in the empirical and cost of topic afterwards.
Cost is few in order to being selected according to " freight " that can call, the high goods stock of charging ratio, and then gives
The loading pattern of cargo and destination on each freight out.Under the premise of ensuring that task is completed, transportation cost is reduced, this
Application provides a kind of embodiment of the vehicle and goods matching device of all or part of the content for realizing the vehicle and goods matching method, ginseng
See Fig. 2, the vehicle and goods matching device specifically includes following content:
Data preparation module 10 analyzes the weight and volume of cargo, the loading of vehicle for obtaining the essential attribute of cargo
Information carries out the transport matching of cargo.
Vehicle and goods matching module 20 matches schedulable vehicle for the essential information according to the Attribute Association loading vehicles of cargo
For dominate call.
Scheme determining module 30 provides allotment decision for the matching result according to cargo and vehicle, and provides specific
Vehicle deploying scheme.
As can be seen from the above description, the embodiment of the present application provides vehicle and goods matching device, it being capable of automatic adaptation combination physicals
Scheduling adaptively provides loading pattern, when in face of complicated transport task, is able to solve inefficiency, and transportation cost is very
High problem, and propose to establish cargo, vehicle adaptation network, cargo, information of vehicles chain are constructed, for no matched data
Point is fitted fill up the gap data using data, cargo and information of vehicles is preferably matched.
In embodiments herein, the data preparation module 10 includes:
Data pre-processing unit 11 to data filtering, is mended for collecting vehicle parking data, cargo basic attribute data
It repays, do data transformation, enhance the robustness of data bulk and model training.
In embodiments herein, the vehicle and goods matching module 20 includes:
Matching unit 21 is extracted in regularization, for formulating the optimum allocation principle under the conditions of multi-objective restriction.
All the embodiments in this specification are described in a progressive manner, same and similar portion between each embodiment
Dividing may refer to each other, and each embodiment focuses on the differences from other embodiments.Especially for hardware+
For program class embodiment, since it is substantially similar to the method embodiment, so being described relatively simple, related place is referring to side
The part of method embodiment illustrates.
It is above-mentioned that this specification specific embodiment is described.Other embodiments are in the scope of the appended claims
It is interior.In some cases, the movement recorded in detail in the claims or step can be come according to the sequence being different from embodiment
It executes and desired result still may be implemented.In addition, process depicted in the drawing not necessarily require show it is specific suitable
Sequence or consecutive order are just able to achieve desired result.In some embodiments, multitasking and parallel processing be also can
With or may be advantageous.
Although this application provides the method operating procedure as described in embodiment or flow chart, based on conventional or noninvasive
The labour for the property made may include more or less operating procedure.The step of enumerating in embodiment sequence is only numerous steps
One of execution sequence mode, does not represent and unique executes sequence.It, can when device or client production in practice executes
To execute or parallel execute (such as at parallel processor or multithreading according to embodiment or method shown in the drawings sequence
The environment of reason).
System, device, module or the unit that above-described embodiment illustrates can specifically realize by computer chip or entity,
Or it is realized by the product with certain function.It is a kind of typically to realize that equipment is computer.Specifically, computer for example may be used
Think personal computer, laptop computer, vehicle-mounted human-computer interaction device, cellular phone, camera phone, smart phone, individual
Digital assistants, media player, navigation equipment, electronic mail equipment, game console, tablet computer, wearable device or
The combination of any equipment in these equipment of person.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
In a typical configuration, calculating equipment includes one or more processors (CPU), input/output interface, net
Network interface and memory.
Memory may include the non-volatile memory in computer-readable medium, random access memory (RAM) and/or
The forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flash RAM).Memory is computer-readable medium
Example.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology come realize information store.Information can be computer readable instructions, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase change memory (PRAM), static random access memory (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), flash memory or other memory techniques, read-only disc read only memory (CD-ROM) (CD-ROM),
Digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape magnetic disk storage or other magnetic storage devices
Or any other non-transmission medium, can be used for storage can be accessed by a computing device information.As defined in this article, it calculates
Machine readable medium does not include temporary computer readable media (transitory media), such as the data-signal and carrier wave of modulation.
It will be understood by those skilled in the art that the embodiment of this specification can provide as the production of method, system or computer program
Product.Therefore, in terms of this specification embodiment can be used complete hardware embodiment, complete software embodiment or combine software and hardware
Embodiment form.
This specification embodiment can describe in the general context of computer-executable instructions executed by a computer,
Such as program module.Generally, program module includes routines performing specific tasks or implementing specific abstract data types, journey
Sequence, object, component, data structure etc..This specification embodiment can also be practiced in a distributed computing environment, in these points
Cloth calculates in environment, by executing task by the connected remote processing devices of communication network.In distributed computing ring
In border, program module can be located in the local and remote computer storage media including storage equipment.
All the embodiments in this specification are described in a progressive manner, same and similar portion between each embodiment
Dividing may refer to each other, and each embodiment focuses on the differences from other embodiments.Especially for system reality
For applying example, since it is substantially similar to the method embodiment, so being described relatively simple, related place is referring to embodiment of the method
Part explanation.In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ",
The description of " specific example " or " some examples " etc. means specific features described in conjunction with this embodiment or example, structure, material
Or feature is contained at least one embodiment or example of this specification embodiment.In the present specification, to above-mentioned term
Schematic representation be necessarily directed to identical embodiment or example.Moreover, description specific features, structure, material or
Person's feature may be combined in any suitable manner in any one or more of the embodiments or examples.In addition, in not conflicting feelings
Under condition, those skilled in the art by different embodiments or examples described in this specification and different embodiment or can show
The feature of example is combined.
The foregoing is merely the embodiments of this specification, are not limited to this specification embodiment.For ability
For field technique personnel, this specification embodiment can have various modifications and variations.It is all this specification embodiment spirit and
Any modification, equivalent replacement, improvement and so within principle should be included in the scope of the claims of this specification embodiment
Within.
Claims (8)
1. a kind of vehicle and goods matching method, which is characterized in that the described method includes:
The essential attribute for obtaining cargo, analyzes the weight and volume of cargo, the loading information of vehicle, carries out the transport of cargo
Match；
According to the essential information of the Attribute Association loading vehicles of cargo, matches schedulable vehicle and called for dominating；
According to the matching result of cargo and vehicle, allotment decision is provided, and provides specific vehicle deploying scheme.
2. vehicle and goods matching method according to claim 1, which is characterized in that the essential attribute for obtaining cargo, analysis
The loading information of the weight and volume of cargo, vehicle carries out the transport matching of cargo, comprising:
Vehicle parking data, cargo basic attribute data are collected, to data filtering, compensates, do data transformation, enhance data bulk
With the robustness of model training, wherein the basic attribute data of the cargo include volume, weight, length and width and senior middle school at least
It is a kind of.
3. vehicle and goods matching method according to claim 1, which is characterized in that the Attribute Association load wagon according to cargo
Essential information, match schedulable vehicle for dominate call, comprising:
Formulate the optimum allocation principle under the conditions of multi-objective restriction.
4. vehicle and goods matching method according to claim 3, which is characterized in that under the conditions of the formulation multi-objective restriction most
Excellent distribution principle, comprising:
Cargo, which is established, on the basis of given I vehicle and II vehicle, III vehicle matches corresponding solution；
Constraint is done to the upper and lower level of different shippings.
5. vehicle and goods matching method according to claim 4, which is characterized in that the upper and lower level to different shippings does condition
Constraint, comprising:
Establish objective function S.t min (∑ xi+∑yi)；
Establish constraint condition, wherein the constraint condition that 1-1 type shipping meets: meet in the case where only with 1-1 lower layer:
19-3.615≤(4.61+0.1)×m1i+(3.615+0.1)×n1i+(4.63+0.1)×k1i≤ 19, i=0,1,2,3,
4,5, the case where upper layer, meets: 19-3.615≤(4.61+0.1) × ε1i+(3.615+0.1)×η1i≤ 19,
The following conditions should be met when only using 1-2 type shipping:
The case where lower layer, meets:
24.3-3.615≤(4.61+0.1)×m2j+(3.615+0.1)×n2j+(4.63+0.1)×k2j≤ 24.3,
Wherein,
The case where upper layer, meets:
24.3-3.615≤(4.61+0.1)×ε2i+(3.615+0.1)×η2i≤ 24.3,
6. a kind of vehicle and goods matching device characterized by comprising
Data preparation module analyzes the weight and volume of cargo, the loading information of vehicle for obtaining the essential attribute of cargo,
Carry out the transport matching of cargo；
Vehicle and goods matching module matches schedulable vehicle for branch for the essential information according to the Attribute Association loading vehicles of cargo
With calling；
Scheme determining module provides allotment decision for the matching result according to cargo and vehicle, and provides specific vehicle tune
With scheme.
7. vehicle and goods matching device according to claim 6, which is characterized in that the data preparation module includes:
Data pre-processing unit, to data filtering, compensates for collecting vehicle parking data, cargo basic attribute data, does number
According to transformation, enhance the robustness of data bulk and model training.
8. vehicle and goods matching device according to claim 6, which is characterized in that the vehicle and goods matching module includes:
Matching unit is extracted in regularization, for formulating the optimum allocation principle under the conditions of multi-objective restriction.
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| CN111415104A (en) * | 2020-04-27 | 2020-07-14 | 上海东普信息科技有限公司 | Vehicle scheduling method, device, equipment and storage medium |
| CN111445180A (en) * | 2020-03-23 | 2020-07-24 | 海南金盘智能科技股份有限公司 | Method and device for optimizing goods placement mode in freight vehicle and electronic equipment |
| CN111626578A (en) * | 2020-05-18 | 2020-09-04 | 上海东普信息科技有限公司 | Distribution method, device, equipment and storage medium of logistics truck |
| CN111652551A (en) * | 2020-05-29 | 2020-09-11 | 上海东普信息科技有限公司 | Method and device for transporting and boxing goods |
| CN112418552A (en) * | 2020-12-04 | 2021-02-26 | 沙师弟(重庆)网络科技有限公司 | Work method for carrying out optimized dispatching on manifest and carrier vehicle based on dispatching requirement |
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| CN111222819B (en) * | 2019-10-21 | 2023-11-21 | 北京旷视机器人技术有限公司 | Method for determining a cargo vehicle, warehouse management device, system, device and medium |
| CN113361837A (en) * | 2020-03-03 | 2021-09-07 | 中国移动通信集团贵州有限公司 | Material assembly strategy determining method and device and electronic equipment |
| CN111445180A (en) * | 2020-03-23 | 2020-07-24 | 海南金盘智能科技股份有限公司 | Method and device for optimizing goods placement mode in freight vehicle and electronic equipment |
| CN111415104A (en) * | 2020-04-27 | 2020-07-14 | 上海东普信息科技有限公司 | Vehicle scheduling method, device, equipment and storage medium |
| CN111626578A (en) * | 2020-05-18 | 2020-09-04 | 上海东普信息科技有限公司 | Distribution method, device, equipment and storage medium of logistics truck |
| CN111652551A (en) * | 2020-05-29 | 2020-09-11 | 上海东普信息科技有限公司 | Method and device for transporting and boxing goods |
| CN113762562A (en) * | 2020-07-03 | 2021-12-07 | 北京京东振世信息技术有限公司 | Method, device and storage medium for generating stowage information |
| CN113762562B (en) * | 2020-07-03 | 2023-11-07 | 北京京东振世信息技术有限公司 | Method, device and storage medium for generating load information |
| CN112418552A (en) * | 2020-12-04 | 2021-02-26 | 沙师弟(重庆)网络科技有限公司 | Work method for carrying out optimized dispatching on manifest and carrier vehicle based on dispatching requirement |
| CN113627726A (en) * | 2021-07-08 | 2021-11-09 | 广州峰华货运有限公司 | Vehicle type matching method and device and storage medium |
| CN115239252A (en) * | 2022-09-20 | 2022-10-25 | 中国铁道科学研究院集团有限公司电子计算技术研究所 | Method, device and equipment for determining loading information of railway freight transportation |
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