CN115983753A - Logistics freight price adjusting method based on big data - Google Patents
Logistics freight price adjusting method based on big data Download PDFInfo
- Publication number
- CN115983753A CN115983753A CN202310076832.0A CN202310076832A CN115983753A CN 115983753 A CN115983753 A CN 115983753A CN 202310076832 A CN202310076832 A CN 202310076832A CN 115983753 A CN115983753 A CN 115983753A
- Authority
- CN
- China
- Prior art keywords
- information data
- adjustment
- adjustment information
- data
- price
- 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
Images
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a logistics freight price adjusting method based on big data, which comprises the following steps: automatically acquiring information data according to a preset frequency to acquire initial information data, wherein the initial information data comprises first initial information data and second initial information data; analyzing the initial information data to obtain adjustment information data, wherein the adjustment information data comprises first adjustment information data, second adjustment information data and third adjustment information data; and analyzing the third adjustment information data to obtain fourth adjustment information data and fifth adjustment information data, and obtaining logistics freight prices according to the expected aging information data, the fourth adjustment information data and the fifth adjustment information data, wherein the logistics freight prices comprise a first logistics freight price, a second logistics freight price and a third logistics freight price. The logistics freight price scheme which is more suitable for the user requirements and more diversified is provided for the user.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a logistics freight price adjusting method based on big data.
Background
With the development of internet and logistics, a batch of logistics platform companies appear at present, the platform companies have the greatest advantage of realizing automatic settlement, and the automatic settlement is based on quotation. Along with trade globalization, the demand of logistics is more and more, but the flow is long in the logistics, the link is many, the participant is various, and the degree of informatization is also very different, from the participant: factories, generations, supply chains, customs clearance, trailer companies, docks, ports, ships, airlines, container companies, etc., in terms of logistics: air transportation, sea transportation, vapour fortune, railway, express delivery, see from the trade mode: general trade, processing trade, trade of transferring, cross border electricity merchant, FBA etc. wherein individual logistics form divides into whole case and bulk cargo again, and its information data is very complicated.
Patent document No. 202010500720.X discloses a logistics route price updating method, device and system, comprising: the method comprises the steps of grabbing the price of a preset logistics line combination of a logistics line to be inquired in the same row under a weight to be inquired, wherein the line combination is obtained by the logistics line combination formed from each secondary area under a primary area to each secondary area under other primary areas different from the primary area; comparing the price of the currently grabbed logistics line combination under the weight to be inquired with the pre-estimated price of the prestored corresponding logistics line combination under the corresponding weight to be inquired one by one; and if the price of any current logistics line under the weight to be inquired is different from the pre-stored estimated price of the corresponding logistics line under the corresponding weight to be inquired, respectively acquiring each third-level area under two second-level areas forming the logistics line, and updating the prices of all logistics lines formed by each third-level area under the two second-level areas.
In the prior art, related logistics line price information is obtained by capturing the combined price of the logistics line, but the data form is single, and the logistics price scheme provided for the user is low in fitting degree.
Disclosure of Invention
The invention mainly aims to provide a logistics freight price adjusting method based on big data, which can provide a price scheme more suitable for user requirements.
In order to achieve the purpose, the invention adopts the technical scheme that:
a logistics freight price adjusting method based on big data comprises the following steps:
automatically acquiring information data according to a preset frequency to acquire initial information data, wherein the initial information data comprises first initial information data and second initial information data;
analyzing the initial information data to obtain adjustment information data, wherein the adjustment information data comprises first adjustment information data, second adjustment information data and third adjustment information data;
and analyzing the third adjustment information data to obtain fourth adjustment information data and fifth adjustment information data, and obtaining logistics freight prices according to the expected aging information data, the fourth adjustment information data and the fifth adjustment information data, wherein the logistics freight prices comprise a first logistics freight price, a second logistics freight price and a third logistics freight price.
As a preferred embodiment, the step of automatically acquiring information data according to a preset frequency to obtain initial information data, where the initial information data includes first initial information data and second initial information data includes:
the preset frequency is set by a manager as required, or a user triggers and inserts a new acquisition request to acquire information data to acquire initial information data, wherein the initial information data comprises first initial information data and second initial information data.
As a preferred embodiment, the initial information data is stored and analyzed by a first calculation formula, so as to obtain adjustment information data, wherein the first calculation formula includes a first formula D1, a second formula D2, and a third formula D3;
the first formula D1 is used for analyzing the initial information data to obtain first adjustment information data and first irrelevant information data;
the second equation D2 is used for analyzing the initial information data to obtain second adjustment information data and second irrelevant information data;
the third equation D3 is used to analyze the initial information data to obtain third adjustment information data and third irrelevant information data.
In a preferred embodiment, the first sub-formula D3 includes a factor Y of the first information price data function, a factor YS of the incidental information data function of the first information price data, a factor F of the first plan information data function, a factor W of the service provider information function, a factor T of the desired information dynamic data function, and a factor a of the second plan information data function;
the second equation D2 contains a factor S of the interval data function;
said third formula D3 comprises a factor M of the service provider's service satisfaction information data function, a factor L of the service provider's transportation strength information data function and a factor C of the service provider's integrity information data function.
As a preferred embodiment, first expected scenario information data f, expected service point information w, and second expected scenario information data a are preset, and when the first equation D1 analyzes the initial information data:
when | Y | > 0 and 3/2T > Y > 1/2T, F = F, W = W, and A = a, the initial information data is determined as first adjustment information data;
when one of Y =0, 3/2T is less than or equal to Y + YS, 1/2M is more than or equal to YS, F is not equal to F, W is not equal to W and A is not equal to a is established, the initial information data is judged to be first irrelevant information data;
presetting expected aging information data s, and when the second equation D2 analyzes the first adjustment information data:
when S is larger than S, judging that the first adjustment information data is second irrelevant information data;
when S is less than or equal to S, judging the first adjustment information data as second adjustment information data;
presetting desired service provider integrity information data c, desired transportation force information data l, and desired service satisfaction information data m, when the second adjustment information data is analyzed by the third equation D3:
when C is larger than or equal to C, L is larger than or equal to L or M is larger than or equal to M, the second adjustment information data is judged to be third adjustment information data;
and when C is less than C, L is less than L or M is less than M, judging that the second adjustment information data is third irrelevant information data.
In a preferred embodiment, the third adjustment information data is received and analyzed by a second calculation formula, where the second calculation formula includes a fourth expression D4 and a fifth expression D5:
the fourth equation D4 is used to analyze the third adjustment information data to obtain fourth adjustment information data;
the fifth equation D5 is used to analyze the third adjustment information data to obtain fifth adjustment information data;
the fourth equation D4 comprises a factor Y of the first information price data function, a factor YS of the incidental information data function of the first information price data, a factor DY of the first checking information data function and a factor DR of the second checking information data function;
the fifth equation D5 includes a factor V of the item occupation space information data function, a shadow factor G of the item quality information data function, a factor P of the item third scheme information data function, and a factor VG of the item occupation space and quality integration function.
In a preferred embodiment, when the fourth equation D4 analyzes the third adjustment information data:
when the first information price data needs to be verified, fourth adjustment information data = Y + YS;
when the first information price data does not need to be verified, fourth adjustment information data = Y + YS + DY + DR;
when the fifth equation D5 analyzes the third adjustment information data:
when VG is greater than G, the fifth adjustment information data is VG,
when VG is less than G, the fifth adjustment information data is G,
and when VG = G, the fifth adjustment information data is VG or G.
As a preferred embodiment, a first time value s1, a second time value s2, a third time value s3, and a fourth time value s4 are preset, and when the logistics freight price is adjusted according to the expected aging information data s, the fourth adjustment information data, and the fifth adjustment information data:
when s1 is not less than s2, the adjusted logistics freight price scheme is a first scheme, the first scheme at least comprises a first logistics freight price, and the first scheme is a speed scheme;
when s2 is not less than s3, the adjusted logistics freight price scheme is a second scheme, the second scheme at least comprises a second logistics freight price, and the second scheme is a comprehensive scheme;
and when s3 is less than or equal to s4, the adjusted logistics freight price scheme is a third scheme, the third scheme at least comprises a third logistics freight price, and the third scheme is a cheap scheme.
As a preferred embodiment, the method further comprises the following steps:
when the logistics transportation arrives at any service point in progress, automatically acquiring information data according to preset frequency to acquire initial information data, wherein the initial information data comprises third initial information data and fourth initial information data;
and analyzing the initial information data to obtain adjustment information data, wherein the adjustment information data comprises sixth adjustment information data, seventh adjustment information data and eighth adjustment information data.
As a preferred embodiment, the method further comprises the following steps:
and analyzing the eighth adjustment information data to obtain ninth adjustment information data and tenth adjustment information data, and obtaining logistics freight prices according to the expected timeliness information data, the ninth adjustment information data and the tenth adjustment information data, wherein the logistics freight prices comprise a fourth logistics freight price and a fifth logistics freight price.
Compared with the prior art, the invention has the following beneficial effects:
automatically acquiring information data from big data according to preset frequency, acquiring initial information data, analyzing and processing the initial information data through a first formula, a second formula and a third formula, dividing the initial information data into irrelevant information data, first adjustment information data, second adjustment information data and third adjustment information data, analyzing the third adjustment information data to acquire fourth adjustment information data and fifth adjustment information data, and acquiring logistics freight prices through expected aging information data, the fourth adjustment information data and the fifth adjustment information data, wherein the logistics freight prices are multiple and are in different schemes;
the whole process is carried out automatically at a high speed, so that the real-time performance of information acquisition can be kept, the price information in the scheme is more accurate, the information of a plurality of service providers is acquired, the information acquisition range is wider, more choices can be made, and the speed of providing the logistics freight price scheme is improved;
the first, second and third formulas are preset to analyze the obtained data, so that the initial information data can be efficiently filtered, the first, second and third formulas are provided with factors of a plurality of functions, the analysis of a user on a plurality of items of data related to logistics service is met, the preset mathematical relationship is required to be met at the same time, and the accuracy of a logistics freight price scheme is comprehensively guaranteed;
a fourth formula and a fifth formula are preset to analyze third adjustment information data to obtain fourth adjustment information data and fifth adjustment information data, so that the third adjustment information data is comprehensively utilized, and the logistics freight price is obtained;
and pushing various logistics freight price schemes to ensure a certain logistics transportation timeliness, wherein each scheme at least comprises logistics freight price information of a logistics service provider and information data of related service points of the logistics service provider, and the completeness of the pushed scheme and excellent service to users are ensured.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flow chart of a method for adjusting a logistics freight price based on big data according to the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a logistics freight price adjusting method based on big data includes the following steps:
the method comprises the following steps that S1, information data are automatically obtained according to a preset frequency, and initial information data are obtained, wherein the initial information data comprise first initial information data and second initial information data;
s2, analyzing the initial information data to obtain adjustment information data, wherein the adjustment information data comprises first adjustment information data, second adjustment information data and third adjustment information data;
and S3, analyzing the third adjustment information data to obtain fourth adjustment information data and fifth adjustment information data, and obtaining logistics freight prices according to the expected aging information data, the fourth adjustment information data and the fifth adjustment information data, wherein the logistics freight prices comprise a first logistics freight price, a second logistics freight price and a third logistics freight price.
The method comprises the steps of automatically acquiring information data from big data according to a preset frequency to acquire initial information data, analyzing and processing the initial information data through a first formula, a second formula and a third formula, dividing the initial information data into irrelevant information data, first adjustment information data, second adjustment information data and third adjustment information data, analyzing the third adjustment information data to acquire fourth adjustment information data and fifth adjustment information data, and acquiring logistics freight prices through expected aging information data, the fourth adjustment information data and the fifth adjustment information data, wherein the logistics freight prices are multiple and are in different schemes;
the step of automatically acquiring information data according to a preset frequency to acquire initial information data, wherein the initial information data including first initial information data and second initial information data comprises:
the preset frequency is set by a manager as required, or a user triggers and inserts a new acquisition request to acquire information data to acquire initial information data, wherein the initial information data comprises first initial information data and second initial information data.
The first initial information data is connected with a first information base and is acquired according to a preset frequency, the first information base at least has information data of one logistics transportation service provider, and the information data of the logistics transportation service provider comprises first arrangement information data, first interval information data, first information error data, first information updating data and first information price data.
The logistics transportation service provider is a shipping transportation service provider, the first arrangement information data is quantity information data which can be called by a transportation tool of the logistics transportation service provider, the first interval information data is time data which can be called by the transportation tool of the logistics transportation service provider, the information error data is abnormal information data of the transportation tool of the logistics transportation service provider, the first information updating data is burst information data, and the first information price data is transportation price information data of the transportation tool of the logistics transportation service provider.
The second initial information data is connected with a second information base and acquires data according to a preset frequency, the second information base at least has information data of one logistics transportation service provider, and the information data of the logistics transportation service provider comprises second arrangement information data, second interval information data, second information error data, second information updating data and second information price data.
The logistics transportation service provider is a land transportation service provider, the second arrangement information data is the quantity information data which can be called by the transportation tool, the second interval information data is the time data which can be called by the transportation tool, the information error data is the abnormal information data of the transportation tool, the second information updating data is the burst information data, and the second information price data is the transportation price information data of the transportation tool.
The whole process is carried out in a full-automatic high-speed mode, the real-time performance of information acquisition can be kept, the price information in the scheme is more accurate, the information of a plurality of service providers is acquired, the information acquisition range is wider, possible choices are more, and the speed of providing the logistics freight price scheme is improved.
Storing the initial information data and analyzing the initial information data through a first calculation formula to obtain adjustment information data, wherein the first calculation formula comprises a first formula D1, a second formula D2 and a third formula D3;
the first formula D1 is used for analyzing the initial information data to obtain first adjustment information data and first irrelevant information data;
the second equation D2 is used for analyzing the initial information data to obtain second adjustment information data and second irrelevant information data;
the third equation D3 is used to analyze the initial information data to obtain third adjustment information data and third irrelevant information data.
The first formula, the second formula and the third formula are preset to analyze the obtained data, initial information data can be efficiently filtered, the first formula, the second formula and the third formula are provided with factors of a plurality of functions, analysis of a user on a plurality of items of data related to logistics services is met, the preset mathematical relationship is required to be met at the same time, and the accuracy of a logistics freight price scheme is comprehensively guaranteed.
The first formula D3 includes a factor Y of the first information price data function, a factor YS of the incidental information data function of the first information price data, a factor F of the first scheme information data function, a factor W of the service provider information function, a factor T of the desired information dynamic data function, and a factor a of the second scheme information data function;
the second equation D2 contains a factor S of the interval data function;
the third equation D3 includes a factor M of the service provider's service satisfaction information data function, a factor L of the service provider's transportation strength information data function, and a factor C of the service provider's integrity information data function.
First expected scheme information data f, expected service point information w and second expected scheme information data a are preset, and when the first equation D1 analyzes the initial information data:
when | Y | > 0 and 3/2T > Y > 1/2T, F = F, W = W, and A = a, the initial information data is determined as first adjustment information data;
when one of Y =0, 3/2T is less than or equal to Y + YS, 1/2M is more than or equal to YS, F is not equal to F, W is not equal to W and A is not equal to a is established, the initial information data is judged to be first irrelevant information data;
presetting expected aging information data s, and when the second equation D2 analyzes the first adjustment information data:
when S is larger than S, judging that the first adjustment information data is second irrelevant information data;
when S is less than or equal to S, judging the first adjustment information data as second adjustment information data;
presetting desired service provider integrity information data c, desired transportation force information data l, and desired service satisfaction information data m, when the second adjustment information data is analyzed by the third equation D3:
when C is larger than or equal to C, L is larger than or equal to L or M is larger than or equal to M, the second adjustment information data is judged to be third adjustment information data;
and when C is less than C, L is less than L or M is less than M, judging that the second adjustment information data is third irrelevant information data.
Receiving the third adjustment information data, and analyzing the third adjustment information data by a second calculation formula, where the second calculation formula includes a fourth formula D4 and a fifth formula D5:
the fourth equation D4 is used to analyze the third adjustment information data to obtain fourth adjustment information data;
the fifth equation D5 is used to analyze the third adjustment information data to obtain fifth adjustment information data;
the fourth equation D4 comprises a factor Y of the first information price data function, a factor YS of the incidental information data function of the first information price data, a factor DY of the first checking information data function and a factor DR of the second checking information data function;
the fifth equation D5 includes a factor V of the item occupation space information data function, a shadow factor G of the item quality information data function, a factor P of the item third scheme information data function, and a factor VG of the item occupation space and quality integration function.
Wherein, when the fourth equation D4 analyzes the third adjustment information data:
when the first information price data needs to be verified, fourth adjustment information data = Y + YS;
when the first information price data does not need to be verified, fourth adjustment information data = Y + YS + DY + DR;
when the fifth equation D5 analyzes the third adjustment information data:
when the third adjustment information data is the first route, VG = V/6000;
when the third adjustment information data is the second route, VG = V/7000;
when VG-VGP > G, the fifth adjustment information data is VG-VGP,
when VG-VGP is less than G, the fifth adjustment information data is G,
and when VG-VGP = G, the fifth adjustment information data is VG-VGP or G.
The fourth and fifth formulas are preset to analyze the third adjustment information data, obtain the fourth adjustment information data and the fifth adjustment information data, complete the comprehensive utilization of the third adjustment information data, and obtain the logistics freight price.
Presetting a first time value s1, a second time value s2, a third time value s3 and a fourth time value s4, and when adjusting the logistics freight price according to the expected timeliness information data s, the fourth adjustment information data and the fifth adjustment information data:
when s is more than or equal to 3 and less than or equal to 4, the adjusted logistics freight price scheme is a first scheme, the first scheme at least comprises a first logistics freight price, and the first scheme is a speed scheme;
when s is more than or equal to 4 and less than or equal to 7, the adjusted logistics freight price scheme is a second scheme, the second scheme at least comprises a second logistics freight price, and the second scheme is a comprehensive scheme;
and when s is more than or equal to 8 and less than or equal to 10, the adjusted logistics freight price scheme is a third scheme, the third scheme at least comprises a third logistics freight price, and the third scheme is a cheap scheme.
And pushing various logistics freight price schemes to ensure a certain logistics transportation timeliness, wherein each scheme at least comprises logistics freight price information of a logistics service provider and information data of related service points of the logistics service provider, and the completeness of the pushed scheme and excellent service to users are ensured.
Wherein, still include the following step:
when the logistics transportation arrives at any service point in progress, automatically acquiring information data according to preset frequency to acquire initial information data, wherein the initial information data comprises third initial information data and fourth initial information data;
and analyzing the initial information data to obtain adjustment information data, wherein the adjustment information data comprises sixth adjustment information data, seventh adjustment information data and eighth adjustment information data.
Wherein, still include the following step:
and analyzing the eighth adjustment information data to obtain ninth adjustment information data and tenth adjustment information data, and obtaining logistics freight prices according to the expected timeliness information data, the ninth adjustment information data and the tenth adjustment information data, wherein the logistics freight prices comprise a fourth logistics freight price and a fifth logistics freight price.
When the logistics transportation arrives at any service point in progress, the information data are continuously and automatically acquired according to the preset frequency, and the scheme for providing the change scheme or finding the scheme more suitable for the user in time is ensured, the data are acquired in the whole process, the benefit of the user is timely maintained, and the satisfaction of the user is improved.
In the description of the present invention, it is to be understood that the terms "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are used merely for convenience of description and for simplicity of description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed in a particular orientation, and be operated, and thus, are not to be construed as limiting the present invention. In the description of the present invention, unless otherwise specified and limited, it is to be noted that the terms "mounted," "connected," and "connected" are to be interpreted broadly, and may be, for example, a mechanical connection or an electrical connection, a communication between two elements, a direct connection, or an indirect connection via an intermediate medium, and specific meanings of the terms may be understood by those skilled in the art according to specific situations.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions, improvements, etc. within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A logistics freight price adjusting method based on big data is characterized by comprising the following steps:
automatically acquiring information data according to a preset frequency to acquire initial information data, wherein the initial information data comprises first initial information data and second initial information data;
analyzing the initial information data to obtain adjustment information data, wherein the adjustment information data comprises first adjustment information data, second adjustment information data and third adjustment information data;
and analyzing the third adjustment information data to obtain fourth adjustment information data and fifth adjustment information data, and obtaining logistics freight prices according to the expected aging information data, the fourth adjustment information data and the fifth adjustment information data, wherein the logistics freight prices comprise a first logistics freight price, a second logistics freight price and a third logistics freight price.
2. The method for adjusting logistics freight price based on big data according to claim 1, wherein the step of automatically obtaining information data according to a preset frequency to obtain initial information data, wherein the step of obtaining the initial information data including the first initial information data and the second initial information data comprises the steps of:
the preset frequency is set by a manager as required, or a user triggers and inserts a new acquisition request to acquire information data to acquire initial information data, wherein the initial information data comprises first initial information data and second initial information data.
3. The logistics freight price adjustment method based on big data according to claim 2, wherein the initial information data is stored and analyzed through a first calculation formula to obtain adjustment information data, and the first calculation formula comprises a first formula D1, a second formula D2 and a third formula D3;
the first formula D1 is used for analyzing the initial information data to obtain first adjustment information data and first irrelevant information data;
the second equation D2 is used for analyzing the initial information data to obtain second adjustment information data and second irrelevant information data;
the third equation D3 is used to analyze the initial information data to obtain third adjustment information data and third irrelevant information data.
4. The logistics freight price adjustment method based on big data as claimed in claim 3, wherein the first type D3 comprises a factor Y of the first information price data function, a factor YS of the incidental information data function of the first information price data, a factor F of the first scheme information data function, a factor W of the service provider information function, a factor T of the desired information dynamic data function and a factor A of the second scheme information data function;
the second equation D2 contains a factor S of the interval data function;
the third equation D3 includes a factor M of the service provider's service satisfaction information data function, a factor L of the service provider's transportation strength information data function, and a factor C of the service provider's integrity information data function.
5. The method as claimed in claim 4, wherein a first expected plan information data f, an expected service point information w, and a second expected plan information data a are preset, and when the first equation D1 analyzes the initial information data:
when | Y | > 0 and 3/2T > Y > 1/2T, F = F, W = W, and A = a, the initial information data is determined as first adjustment information data;
when one of Y =0, 3/2T is less than or equal to Y + YS, 1/2M is more than or equal to YS, F is not equal to F, W is not equal to W and A is not equal to a is established, the initial information data is judged to be first irrelevant information data;
presetting expected aging information data s, and when the second equation D2 analyzes the first adjustment information data:
when S is larger than S, judging that the first adjustment information data is second irrelevant information data;
when S is less than or equal to S, judging the first adjustment information data as second adjustment information data;
presetting desired service provider integrity information data c, desired transportation strength information data l and desired service satisfaction information data m, and when the third equation D3 analyzes the second adjustment information data:
when C is larger than or equal to C, L is larger than or equal to L or M is larger than or equal to M, the second adjustment information data is judged to be third adjustment information data;
and when C is less than C, L is less than L or M is less than M, judging that the second adjustment information data is third irrelevant information data.
6. The big data based logistics freight price adjustment method according to claim 5, wherein the third adjustment information data is received, and the third adjustment information data is analyzed by a second calculation formula, wherein the second calculation formula comprises a fourth formula D4 and a fifth formula D5:
the fourth equation D4 is used to analyze the third adjustment information data to obtain fourth adjustment information data;
the fifth equation D5 is used to analyze the third adjustment information data to obtain fifth adjustment information data;
the fourth equation D4 comprises a factor Y of the first information price data function, a factor YS of the incidental information data function of the first information price data, a factor DY of the first checking information data function and a factor DR of the second checking information data function;
the fifth equation D5 includes a factor V of the item occupation space information data function, a shadow factor G of the item quality information data function, a factor P of the item third scheme information data function, and a factor VG of the item occupation space and quality integration function.
7. The logistics freight price adjustment method based on big data according to claim 6, wherein when the fourth equation D4 analyzes the third adjustment information data:
when the first information price data needs to be verified, fourth adjustment information data = Y + YS;
when the first information price data does not need to be verified, fourth adjustment information data = Y + YS + DY + DR;
when the fifth equation D5 analyzes the third adjustment information data:
when VG is greater than G, the fifth adjustment information data is VG,
when VG is less than G, the fifth adjustment information data is G,
and when VG = G, the fifth adjustment information data is VG or G.
8. The method for adjusting logistics freight price based on big data according to claim 7, wherein a first time value s1, a second time value s2, a third time value s3 and a fourth time value s4 are preset, and when the logistics freight price is adjusted according to the expected time information data s, the fourth adjustment information data and the fifth adjustment information data:
when s1 is not less than s2, the adjusted logistics freight price scheme is a first scheme, the first scheme at least comprises a first logistics freight price, and the first scheme is a speed scheme;
when s2 is not less than s3, the adjusted logistics freight price scheme is a second scheme, the second scheme at least comprises a second logistics freight price, and the second scheme is a comprehensive scheme;
and when s3 is larger than or equal to s4, the adjusted logistics freight price scheme is a third scheme, the third scheme at least comprises a third logistics freight price, and the third scheme is a cheap scheme.
9. The logistics freight price adjustment method based on big data as claimed in claim 8, further comprising the steps of:
when the logistics transportation arrives at any service point in progress, automatically acquiring information data according to preset frequency to acquire initial information data, wherein the initial information data comprises third initial information data and fourth initial information data;
and analyzing the initial information data to obtain adjustment information data, wherein the adjustment information data comprises sixth adjustment information data, seventh adjustment information data and eighth adjustment information data.
10. The logistics freight price adjustment method based on big data according to claim 9, characterized by further comprising the following steps:
and analyzing the eighth adjustment information data to obtain ninth adjustment information data and tenth adjustment information data, and obtaining logistics freight prices according to the expected timeliness information data, the ninth adjustment information data and the tenth adjustment information data, wherein the logistics freight prices comprise a fourth logistics freight price and a fifth logistics freight price.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310076832.0A CN115983753A (en) | 2023-01-17 | 2023-01-17 | Logistics freight price adjusting method based on big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310076832.0A CN115983753A (en) | 2023-01-17 | 2023-01-17 | Logistics freight price adjusting method based on big data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115983753A true CN115983753A (en) | 2023-04-18 |
Family
ID=85968018
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310076832.0A Pending CN115983753A (en) | 2023-01-17 | 2023-01-17 | Logistics freight price adjusting method based on big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115983753A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116664164A (en) * | 2023-06-01 | 2023-08-29 | 深圳深创建控股集团有限公司 | Freight quotation method and system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104978641A (en) * | 2015-03-04 | 2015-10-14 | 张军委 | Logistics information integration method and logistics information integration system |
| CN108492064A (en) * | 2018-03-12 | 2018-09-04 | 广州建翎电子技术有限公司 | A kind of logistics cost settlement system of bulk supply tariff |
| CN111950948A (en) * | 2019-05-16 | 2020-11-17 | 苏州费瑞兰户外用品科技有限公司 | Intelligent matching system applied to e-commerce logistics mode |
| CN114549119A (en) * | 2022-01-25 | 2022-05-27 | 荃豆数字科技有限公司 | Freight adjusting method and device for traditional Chinese medicine commodities and electronic equipment |
-
2023
- 2023-01-17 CN CN202310076832.0A patent/CN115983753A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104978641A (en) * | 2015-03-04 | 2015-10-14 | 张军委 | Logistics information integration method and logistics information integration system |
| CN108492064A (en) * | 2018-03-12 | 2018-09-04 | 广州建翎电子技术有限公司 | A kind of logistics cost settlement system of bulk supply tariff |
| CN111950948A (en) * | 2019-05-16 | 2020-11-17 | 苏州费瑞兰户外用品科技有限公司 | Intelligent matching system applied to e-commerce logistics mode |
| CN114549119A (en) * | 2022-01-25 | 2022-05-27 | 荃豆数字科技有限公司 | Freight adjusting method and device for traditional Chinese medicine commodities and electronic equipment |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116664164A (en) * | 2023-06-01 | 2023-08-29 | 深圳深创建控股集团有限公司 | Freight quotation method and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Guastaroba et al. | Intermediate facilities in freight transportation planning: a survey | |
| Popović et al. | Variable neighborhood search heuristic for the inventory routing problem in fuel delivery | |
| US7725406B2 (en) | Systems and methods for international shipping and brokerage operations support processing | |
| Chang et al. | Port competitiveness, efficiency, and supply chains: a literature review | |
| Tavasszy et al. | Emerging global logistics networks: implications for transport systems and policies | |
| CN101346738A (en) | Method for transporting physical objects, transportation system and transportation means | |
| CN115983753A (en) | Logistics freight price adjusting method based on big data | |
| CN107203859B (en) | Information processing method and device for warehouse and trunk article handover | |
| KR20180121636A (en) | Method and system for obtaining logistics information of international transportation | |
| CN102289735A (en) | Method and system for selecting service supplier | |
| Jensen et al. | Avocados crossing borders: the missing common information infrastructure for international trade | |
| Ferrucci | Pro-active dynamic vehicle routing: real-time control and request-forecasting approaches to improve customer service | |
| CN104636473A (en) | Data processing method and system based on electronic payment behaviors | |
| Capineri et al. | Freight transport, seamlessness, and competitive advantage in the global economy | |
| Pomfret et al. | Global value-chains and connectivity in developing Asia–With application to the Central and West Asian region | |
| CN116186142B (en) | Cross-border tax data service management system based on Internet of things | |
| CN107909326B (en) | Chain journey transportation method and system for international logistics | |
| CN116664029A (en) | Cold chain trunk line and floor matching integration method, device, equipment and storage medium | |
| CN113780941B (en) | Block chain-based document system for multi-mode intermodal | |
| Hilletofth et al. | Using Eurasian landbridge in logistics operations: building knowledge through case studies | |
| Janusz et al. | Center as a tool for logistics activities in support of the company on the example of SME’s enterprise X | |
| CN114298625B (en) | Intelligent cross-border marine procurement analysis system based on big data | |
| Daryanto et al. | Single vendor-buyer integrated inventory model for deteriorating items considering carbon emission | |
| CN111815221B (en) | Method for rapidly acquiring logistics electronic bill | |
| CN111091331A (en) | Shipping split-loading shipping management system based on Internet of things platform |
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 |