CN107357852A - A kind of determination methods of shipping driver to order wish - Google Patents
A kind of determination methods of shipping driver to order wish Download PDFInfo
- Publication number
- CN107357852A CN107357852A CN201710509005.0A CN201710509005A CN107357852A CN 107357852 A CN107357852 A CN 107357852A CN 201710509005 A CN201710509005 A CN 201710509005A CN 107357852 A CN107357852 A CN 107357852A
- Authority
- CN
- China
- Prior art keywords
- order
- dimension
- driver
- information data
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Probability & Statistics with Applications (AREA)
- Economics (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Fuzzy Systems (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Operations Research (AREA)
- Marketing (AREA)
- Human Resources & Organizations (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Quality & Reliability (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Traffic Control Systems (AREA)
Abstract
The present invention provides a kind of determination methods of shipping driver to order wish, and methods described includes：A) service end obtains sequence information data from delivery end, and history order information data is obtained from driver end according to the sequence information data；B) the history order information data that driver end obtains is ranked up, extracts the order preference data at driver end；C) the order information data and the order preference data are calculated to the dimensional parameter of different dimensions by following formula；D) the multiple dimensional parameters calculated in step c) are combined and combination parameter is calculated, and combination parameter is calculated to the order wish value at driver end by logistic regression function；E) the order wish value to the driver end described in step d) is ranked up, and the order wish value at the driver end in pre-set interval is effective order wish value.The determination methods of order wish provided by the invention obtain more accurate order wish, can effectively improve the success rate of order push.
Description
Technical field
The present invention relates to Internet technical field, determination methods of more particularly to a kind of shipping driver to order wish.
Background technology
There is the huge freight market of 30,000,000 truck men at present according to statistics, and China more than 85% is large-scale
Lorry is all self-employed worker's operation, and the logistics transport power overwhelming majority relies on 7,000,000 middle-long distance lorries and nearly 20,000,000 of decentralized management
Short-distance lorry, every year because lorry empty driving brings huge energy waste and environmental pollution.Traditional freight market is information-based
Degree is not high, and part truck man can only rely on intrinsic inner circle of people --- and the every place of driver can all look for friend introduction industry
Business.For long distance line forwarding, the enterprise of only one way transport amount accounts for 59%；Have round transport business accounts for 13%, and
Freight volume, which comes and goes, to be mismatched.
Recently as the continuous development of Internet telephony, new blood is filled with to traditional cargo transport industry, is made
More quickly and easily service is provided during cargo transport for delivery side and transporter.Platform is transported by speed, user can obtain
More broadly driver services for it around getting, and pricing system is more transparent, and service quality can also obtain platform guarantee, save
The middle and cumbersome information communication process of driver is removed.But the push for order is only according to driver end in the prior art
Order wish of the historical data simple forecast driver to order, often there is deviation, order push in the order wish of its driver
Efficiency is low, and driver's order probability of transaction is low, the problem of integrally being difficult to be effectively matched order during cargo transport still be present.
Therefore, in order to solve the above problems, it is desirable to be able to a kind of accurate shipping driver couple for judging the single wish of driver's termination
The determination methods of order wish.
The content of the invention
A kind of determination methods it is an object of the invention to provide shipping driver to order wish, methods described include：
A) service end obtains sequence information data from delivery end, and history is obtained from driver end according to the sequence information data
Order information data；
B) the history order information data that driver end obtains is ranked up, extracts the order preference data at driver end；
C) the order information data and the order preference data are calculated to the dimensional parameter of different dimensions by following formula：
L=a × b, wherein L are dimensional parameter, and a is a certain dimension data in sequence information data, and b is and the order
Dimension data in order preference data corresponding to a certain dimension data in information data；
D) the multiple dimensional parameters calculated in step c) are combined and combination parameter is calculated, and combination parameter is led to
The order wish value that logistic regression function calculates driver end is crossed, wherein
Z=∑ α L, Z are combination parameter, and α is coefficient, and L is dimensional parameter；
G (Z)=1/ (1+e-z), G (Z) is the order wish value at driver end, and Z is combination parameter；
The order wish value at multiple driver ends that e) step d) is calculated is ranked up, in pre-set interval
The order wish value at the driver end be effective order wish value.
Preferably, the sequence information data include but is not limited to price dimension, distance of freight carried dimension, road conditions dimension, goods
Transport time dimension, weather dimension, red-letter day dimension.
Preferably, the history order information data includes but is not limited to price dimension, distance of freight carried dimension, road conditions are tieed up
Degree, shipment month dimension, weather dimension, red-letter day dimension.
Preferably, before the dimensional parameter calculating that different dimensions are carried out in the step c), different dimensions are carried out discrete
Change is handled.
Preferably, history order information data is ranked up according to the order number of different dimensions described in the step b),
The dimension that order number is more than predetermined threshold value is order preference data.
Preferably, driver end is divided into according to the effectively order wish value in the step e) it is multigroup, successively to each
Group driver end push sequence information.
Preferably, the time interval successively to each group of shipping driver push order is 4~12 seconds.
A kind of shipping driver provided by the invention is to the determination methods of order wish, by order information data and order preference
Data are combined calculating by calculating the dimensional parameter of different dimensions to multiple dimensional parameters, make to be calculated what is obtained
Order wish value is of a relatively high.Meanwhile the present invention is ranked up by the order wish value to driver end, will be located at pre-set interval
Interior order wish value is effective order wish value, makes the order wish that is calculated and the real order wish of driver more
Match somebody with somebody.
It should be appreciated that foregoing description substantially and follow-up description in detail are exemplary illustration and explanation, should not
As the limitation to the claimed content of the present invention.
Brief description of the drawings
With reference to the accompanying drawing enclosed, the present invention more purpose, function and advantages will pass through the as follows of embodiment of the present invention
Description is illustrated, wherein：
Fig. 1 diagrammatically illustrates the system block diagram to the determination methods of order wish for shipping driver of the present invention；
Fig. 2 shows FB(flow block) of the shipping driver of the present invention to the determination methods of order wish.
Embodiment
By reference to one exemplary embodiment, the purpose of the present invention and function and the side for realizing these purposes and function
Method will be illustrated.However, the present invention is not limited to one exemplary embodiment as disclosed below；Can by multi-form come
It is realized.The essence of specification is only to aid in the detail of the various equivalent modifications Integrated Understanding present invention.
Hereinafter, embodiments of the invention will be described with reference to the drawings, relevant technical terms should be people in the art
Known to member.In the accompanying drawings, identical reference represents same or similar part, or same or like step,
Unless otherwise indicated.
A kind of shipping driver provided by the invention is entered to the determination methods of order wish with reference to specific embodiment
Row describes in detail, in order that the present invention is able to more clearly illustrate, the system for serving the present invention is illustrated first, such as
System block diagram shown in Fig. 1 for shipping driver of the present invention to the determination methods of order wish, the present invention by service end 100 with
Data transfer is carried out between delivery end 300 and driver end 200, is handled by 100 complete paired data of service end and order wish is sentenced
It is disconnected, sequence information is fed back to by driver end 200 by service end 100 according to the order wish after judgement.Delivery end 300 is to be installed on
The user equipment (such as cell phone application or PC ends) delivered is needed, driver's equipment that 200, driver end is installed on order (such as
Cell phone application or PC ends).
The present invention obtains the sequence information data at delivery end and the history order letter at driver end 200 by service end 100
Data are ceased, to data processing and more accurate order wish is calculated, order push is carried out according to more order wish.Under
Face is explained in detail, and shipping driver of the present invention as shown in Figure 2 is to the FB(flow block)s of the determination methods of order wish, according to this hair
Bright, a kind of shipping driver comprises the following steps to the determination methods method of order wish in the present embodiment：
S101, service end obtain order data and history order information data
Service end obtains sequence information data from delivery end, and obtaining history from driver end according to the sequence information data connects
Single information data.Sequence information data include but is not limited to price dimension, distance of freight carried dimension, road conditions dimension, shipment month dimension
Degree, weather dimension, red-letter day dimension.The history at driver end of the service end near the delivery address acquisition in sequence information data
Order information data.History order information data includes but is not limited to price dimension, distance of freight carried dimension, road conditions dimension, shipping
Time dimension, weather dimension, red-letter day dimension.
S102, the order preference data for extracting driver end
The history order information data that driver end obtains is ranked up, extracts the order preference data at driver end.History
Order information data is ranked up according to the order number of different dimensions, and the dimension that order number is more than predetermined threshold value is order preference number
According to.For example, in embodiment exemplified by price dimension, distance of freight carried dimension and road conditions dimension, the history at the first driver end of extraction
The order number of different dimensions is ranked up in the way of table one in order data.
Table one：The order number sequencing table of different dimensions
| Sequence number | Dimension | Order number |
| 1 | Price is more than M members | 25 is single |
| 2 | Price is more than N members and is less than M members | 20 is single |
| 3 | Distance of freight carried is less than c kilometers | 20 is single |
| 4 | Distance of freight carried is more than c kilometers | 15 is single |
| 5 | Based on shipment process highway | 12 is single |
| 6 | Based on shipment process dirt road | 10 is single |
According to the present invention, set the threshold value of order number single for 10 in embodiment.It is more than 10 according to the sequence order number of table one
There are price dimension, distance of freight carried dimension and road conditions dimension in single history information data, then the order preference data at the driver end
For price dimension, distance of freight carried dimension and road conditions dimension.
S103, the dimensional parameter for calculating different dimensions
Sequence information data and order preference data are calculated to the dimensional parameter of different dimensions by formula (1).
L=a × b (1)
Wherein L is dimensional parameter, and a is a certain dimension data in sequence information data, b be with sequence information data
Dimension data in order preference data corresponding to a certain dimension data.
In embodiment, by taking the price dimension that first driver is terminated in single preference data as an example.Price dimension data is with order number
Corresponding price weighted calculation obtains, in the present embodiment, b=M γ1+Nγ2, wherein, γ1With 10 γ2For weight coefficient.Should
Understanding, the calculating for dimension data in order preference data calculates according to specific circumstances, such as distance of freight carried
Dimension can pass through order number weighted calculation.In the present embodiment by taking the price dimension in order preference data as an example, order is believed
Price dimension in breath data is calculated with order preference data by formula (1), and what end of being delivered in the present embodiment was filled in orders
Price dimension data in single information data is P members, then a=P members, by the dimensional parameter L1 that price dimension is calculated.Together
Sample, the dimensional parameter that distance of freight carried dimension is calculated is L2 and the dimensional parameter of road conditions dimension is L3.According to the present invention, enter
, it is necessary to carry out sliding-model control to different dimensions before the dimensional parameter of row different dimensions calculates.
It should be noted that the present embodiment in order to clearly illustrate, only have chosen a driver end and a delivery
End carries out dimension calculating, it should be appreciated that is not limited to this, the sequence information sent to a delivery end, according to delivery address
Multiple driver ends nearby are extracted to be calculated.In certain embodiments, it can be multiple sequence information data and multiple drivers
The history order data at end carry out calculated crosswise.
S104, calculate combination parameter and order wish value
The multiple dimensional parameters calculated in step S103 are combined combination parameter is calculated, and combination parameter is led to
The order wish value that logistic regression function calculates driver end is crossed, wherein
Z=∑ α L (2)
Z is combination parameter, and α is coefficient, and L is dimensional parameter；
G (Z)=1/ (1+e-z) (3)
G (Z) is the order wish value at driver end, and Z is combination parameter.
In the present embodiment, multiple dimensional parameter L1, L2, L3 ... are calculated by step S103 method, wherein L1 is
The dimensional parameter for the price dimension being calculated, L2 are the dimensional parameter that range dimension is calculated, and L3 is the road being calculated
The dimensional parameter of condition dimension.Multiple dimensional parameters (L1, L2, L3) are combined by formula (2) combination parameter is calculated
Z.Combination parameter Z is calculated to the order wish value G (Z) at driver end by the logistic regression function of formula (3).
S105, extract valid order wish value
The order wish value at multiple driver ends to being calculated in step S104 is ranked up, in pre-set interval
The order wish value at the driver end is effective order wish value.
According to the present invention, the order wish value at multiple driver ends to being calculated in step S104 is ranked up, such as
The order wish value that first driver end is calculated in the present embodiment is G (Z)1=0.8, order wish value is calculated in second driver end
For G (Z)2=0.75, the order wish value that the third driver end is calculated is G (Z)3=0.7, the order that fourth driver end is calculated
Wish value is G (Z)4=0.69.Then it is ordered as：G(Z)1=0.8, G (Z)2=0.75, G (Z)3=0.7, G (Z)4=0.69.
According to the present invention, order wish is worth pre-set interval to be 0.7~0.98 in embodiment, then order wish value, the second at first driver end
The order wish value of driver and the order wish value of the third driver are effective order wish value.
Driver end is divided into according to effective order wish value multigroup, pushes sequence information to each group of driver end successively, according to
The secondary time interval that order is pushed to each group of shipping driver is 4~12 seconds.Such as there is effective order wish in the present embodiment
Value driver has 3, and first driver end, second driver end and the third driver end are divided into first group of driver, second group of driver, the 3rd group of department,
Order is pushed to each group of driver successively.
A kind of shipping driver provided by the invention finds to the determination methods of order wish from numerous order wish dimensions
Combination, by combination parameter calculation order wish value, substantially increases the matching of order.Such as part driver end to order price and
Distance of freight carried is all insensitive, but effectively the decision-making driver whether can be ready order after both combine.
A kind of shipping driver provided by the invention is to the determination methods of order wish, by order information data and order preference
Data are combined calculating by calculating the dimensional parameter of different dimensions to multiple dimensional parameters, make to be calculated what is obtained
Order wish value is of a relatively high.Meanwhile the present invention is ranked up by the order wish value to driver end, will be located at pre-set interval
Interior order wish value is effective order wish value, makes the order wish that is calculated and the real order wish of driver more
Match somebody with somebody.
With reference to the explanation of the invention disclosed here and practice, other embodiment of the invention is for those skilled in the art
It all will be readily apparent and understand.Illustrate and embodiment is to be considered only as exemplary, of the invention true scope and purport is equal
It is defined in the claims.
Claims (7)
1. a kind of shipping driver is to the determination methods of order wish, it is characterised in that methods described includes：
A) service end obtains sequence information data from delivery end, and history order is obtained from driver end according to the sequence information data
Information data；
B) the history order information data that driver end obtains is ranked up, extracts the order preference data at driver end；
C) the sequence information data and the order preference data are calculated to the dimensional parameter of different dimensions by following formula：
L=a × b, wherein L are dimensional parameter, and a is a certain dimension data in sequence information data, and b is and the sequence information
Dimension data in order preference data corresponding to a certain dimension data in data；
D) the multiple dimensional parameters calculated in step c) are combined and combination parameter is calculated, and by combination parameter by patrolling
The order wish value that regression function calculates driver end is collected, wherein
Z=∑ α L, Z are combination parameter, and α is coefficient, and L is dimensional parameter；
G (Z)=1/ (1+e-z), G (Z) is the order wish value at driver end, and Z is combination parameter；
The order wish value at multiple driver ends that e) step d) is calculated is ranked up, the driver end in pre-set interval
The order wish value be effective order wish value.
2. determination methods according to claim 1, it is characterised in that the sequence information data include but is not limited to price
Dimension, distance of freight carried dimension, road conditions dimension, shipment month dimension, weather dimension, red-letter day dimension.
3. determination methods according to claim 1, it is characterised in that the history order information data includes but is not limited to
Price dimension, distance of freight carried dimension, road conditions dimension, shipment month dimension, weather dimension, red-letter day dimension.
4. determination methods according to claim 1, it is characterised in that the dimension ginseng of different dimensions is carried out in the step c)
Before number calculates, sliding-model control is carried out to different dimensions.
5. determination methods according to claim 1, it is characterised in that history order information data described in the step b)
It is ranked up according to the order number of different dimensions, the dimension that order number is more than predetermined threshold value is order preference data.
6. determination methods according to claim 1, it is characterised in that according to the effectively order wish in the step e)
Driver end is divided into multigroup by value, pushes sequence information to each group of driver end successively.
7. determination methods according to claim 6, it is characterised in that push order to each group of shipping driver successively
Time interval be 4~12 seconds.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710509005.0A CN107357852A (en) | 2017-06-28 | 2017-06-28 | A kind of determination methods of shipping driver to order wish |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710509005.0A CN107357852A (en) | 2017-06-28 | 2017-06-28 | A kind of determination methods of shipping driver to order wish |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107357852A true CN107357852A (en) | 2017-11-17 |
Family
ID=60272648
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710509005.0A Pending CN107357852A (en) | 2017-06-28 | 2017-06-28 | A kind of determination methods of shipping driver to order wish |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107357852A (en) |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108898306A (en) * | 2018-06-26 | 2018-11-27 | 泰康保险集团股份有限公司 | Order allocation method, device, medium and electronic equipment |
| CN108985599A (en) * | 2018-07-03 | 2018-12-11 | 武汉斑马快跑科技有限公司 | A kind of order allocation method and device |
| CN109117989A (en) * | 2018-07-26 | 2019-01-01 | 北京云鸟科技有限公司 | Prediction technique and device when a kind of task matches |
| CN109214551A (en) * | 2018-08-08 | 2019-01-15 | 北京三快在线科技有限公司 | A kind of distribution scheduling method and device |
| CN109242320A (en) * | 2018-09-17 | 2019-01-18 | 北京同城必应科技有限公司 | Order allocation method, device, server and storage medium |
| CN109377317A (en) * | 2018-10-26 | 2019-02-22 | 天津五八到家科技有限公司 | Data processing method and device |
| CN109726960A (en) * | 2018-12-29 | 2019-05-07 | 拉扎斯网络科技（上海）有限公司 | Order processing method and device, electronic equipment and computer readable storage medium |
| CN110009287A (en) * | 2019-04-15 | 2019-07-12 | 北京闪送科技有限公司 | Premium determines method, apparatus, equipment and storage medium |
| CN110119928A (en) * | 2019-05-07 | 2019-08-13 | 宏图物流股份有限公司 | A kind of vehicle match recommended method based on driver's feature |
| CN110297544A (en) * | 2019-06-28 | 2019-10-01 | 联想(北京)有限公司 | Input information response's method and device, computer system and readable storage medium storing program for executing |
| CN110969500A (en) * | 2018-09-28 | 2020-04-07 | 北京嘀嘀无限科技发展有限公司 | Method and device for pushing taxi calling order |
| CN111899061A (en) * | 2020-03-10 | 2020-11-06 | 北京畅行信息技术有限公司 | Order recommendation method, device, equipment and storage medium |
| CN112465602A (en) * | 2020-12-11 | 2021-03-09 | 深圳依时货拉拉科技有限公司 | Order pushing method and device, computer equipment and computer readable storage medium |
| CN112488806A (en) * | 2020-12-18 | 2021-03-12 | 深圳依时货拉拉科技有限公司 | Method and device for predicting order willingness, computer equipment and computer-readable storage medium |
| CN112613813A (en) * | 2020-12-22 | 2021-04-06 | 天津五八到家货运服务有限公司 | Method, equipment and medium for pushing freight work scheme |
| CN113312334A (en) * | 2021-05-28 | 2021-08-27 | 海南超船电子商务有限公司 | Modeling analysis method and system for big data of shipping user |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104537502A (en) * | 2015-01-15 | 2015-04-22 | 北京嘀嘀无限科技发展有限公司 | Method and device for processing orders |
| CN105096166A (en) * | 2015-08-27 | 2015-11-25 | 北京嘀嘀无限科技发展有限公司 | Method and device for order allocation |
-
2017
- 2017-06-28 CN CN201710509005.0A patent/CN107357852A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104537502A (en) * | 2015-01-15 | 2015-04-22 | 北京嘀嘀无限科技发展有限公司 | Method and device for processing orders |
| CN105096166A (en) * | 2015-08-27 | 2015-11-25 | 北京嘀嘀无限科技发展有限公司 | Method and device for order allocation |
Cited By (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108898306A (en) * | 2018-06-26 | 2018-11-27 | 泰康保险集团股份有限公司 | Order allocation method, device, medium and electronic equipment |
| CN108985599A (en) * | 2018-07-03 | 2018-12-11 | 武汉斑马快跑科技有限公司 | A kind of order allocation method and device |
| CN109117989A (en) * | 2018-07-26 | 2019-01-01 | 北京云鸟科技有限公司 | Prediction technique and device when a kind of task matches |
| CN109117989B (en) * | 2018-07-26 | 2021-06-11 | 北京云鸟科技有限公司 | Prediction method and device during task matching |
| CN109214551A (en) * | 2018-08-08 | 2019-01-15 | 北京三快在线科技有限公司 | A kind of distribution scheduling method and device |
| CN109242320A (en) * | 2018-09-17 | 2019-01-18 | 北京同城必应科技有限公司 | Order allocation method, device, server and storage medium |
| CN110969500A (en) * | 2018-09-28 | 2020-04-07 | 北京嘀嘀无限科技发展有限公司 | Method and device for pushing taxi calling order |
| CN109377317A (en) * | 2018-10-26 | 2019-02-22 | 天津五八到家科技有限公司 | Data processing method and device |
| CN109377317B (en) * | 2018-10-26 | 2021-03-30 | 天津五八到家科技有限公司 | Data processing method and device |
| CN109726960A (en) * | 2018-12-29 | 2019-05-07 | 拉扎斯网络科技（上海）有限公司 | Order processing method and device, electronic equipment and computer readable storage medium |
| CN110009287A (en) * | 2019-04-15 | 2019-07-12 | 北京闪送科技有限公司 | Premium determines method, apparatus, equipment and storage medium |
| CN110119928A (en) * | 2019-05-07 | 2019-08-13 | 宏图物流股份有限公司 | A kind of vehicle match recommended method based on driver's feature |
| CN110119928B (en) * | 2019-05-07 | 2021-01-01 | 宏图物流股份有限公司 | Vehicle matching recommendation method based on driver characteristics |
| CN110297544A (en) * | 2019-06-28 | 2019-10-01 | 联想(北京)有限公司 | Input information response's method and device, computer system and readable storage medium storing program for executing |
| CN111899061A (en) * | 2020-03-10 | 2020-11-06 | 北京畅行信息技术有限公司 | Order recommendation method, device, equipment and storage medium |
| CN111899061B (en) * | 2020-03-10 | 2024-04-16 | 北京畅行信息技术有限公司 | Order recommendation method, device, equipment and storage medium |
| CN112465602A (en) * | 2020-12-11 | 2021-03-09 | 深圳依时货拉拉科技有限公司 | Order pushing method and device, computer equipment and computer readable storage medium |
| CN112465602B (en) * | 2020-12-11 | 2023-12-15 | 深圳依时货拉拉科技有限公司 | Order pushing method, order pushing device, computer equipment and computer readable storage medium |
| CN112488806A (en) * | 2020-12-18 | 2021-03-12 | 深圳依时货拉拉科技有限公司 | Method and device for predicting order willingness, computer equipment and computer-readable storage medium |
| CN112613813A (en) * | 2020-12-22 | 2021-04-06 | 天津五八到家货运服务有限公司 | Method, equipment and medium for pushing freight work scheme |
| CN113312334A (en) * | 2021-05-28 | 2021-08-27 | 海南超船电子商务有限公司 | Modeling analysis method and system for big data of shipping user |
| CN113312334B (en) * | 2021-05-28 | 2023-05-26 | 海南超船电子商务有限公司 | Modeling analysis method and system for big data of shipping user |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107357852A (en) | A kind of determination methods of shipping driver to order wish | |
| CN110047279B (en) | Method for determining shared bicycle dispatching quantity based on order data | |
| Poliak et al. | New paradigms of quantification of economic efficiency in the transport sector | |
| CN107341636A (en) | Method is subsidized in a kind of shipping driver competition for orders | |
| CN103927639A (en) | Steel product logistics system and scheduling method thereof based on real-time information | |
| CN104766473A (en) | Traffic trip feature extraction method based on multi-mode public transport data matching | |
| CN106803136A (en) | A kind of fresh dispatching real-time optimization method based on genetic algorithm | |
| CN107564270A (en) | A kind of intelligent public transportation dispatching method for running | |
| CN104021488A (en) | Goods freight calculating method and device, and mobile terminal | |
| CN105741540A (en) | Linear scheduling realizing method and linear scheduling realizing system of commercial concrete vehicle | |
| CN107358386A (en) | A kind of shipping driver and the matching process and matching system of order | |
| CN114140040A (en) | Intelligent logistics system platform based on big data | |
| CN110570259A (en) | Accurate marketing system and method for gas station | |
| CN115375234A (en) | GNSS-based transportation vehicle operation track planning method | |
| CN112465384A (en) | Transportation capacity scheduling method and device, computer equipment and computer readable storage medium | |
| CN109685410A (en) | A kind of share-car method for light alveolitoid cargo transport | |
| CN114723248A (en) | Intelligent scheduling and distribution method | |
| CN103870949B (en) | A kind of metallurgical production Process Tracking system and method | |
| CN115796732B (en) | Regional logistics delivery and entry distribution management method based on e-commerce platform commodity | |
| CN115293390A (en) | System and method for planning logistics outside plant | |
| CN117010881A (en) | Logistics freight quotation prediction method | |
| CN111539674A (en) | Order combining method for logistics transportation of engineering machinery rental scene | |
| CN111385355A (en) | Method for improving 4S shop maintenance and arrival rate based on location service | |
| Leonardi et al. | Feasibility study of a network of consolidation centres in Luxembourg | |
| CN115760187A (en) | Transportation capacity cost estimation method and device, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20190430 Address after: 300450 Jinzuo Square 802, No. 5 Meiyuan Road, Binhai High-tech Zone, Tianjin Applicant after: Tianjin May 8th Home Freight Service Co., Ltd. Address before: No. 721 Chaoyang Road, Xinminzhou, Jingkou District, Zhenjiang City, Jiangsu Province Applicant before: Zhenjiang 58 home supply chain management services Co., Ltd. |
|
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20171117 |