A Logistics Data Analysis and Processing Method and System

Abstract

The present invention provides a method and system for analyzing and processing logistics data, belonging to the technical field of data processing. Specifically, it includes: determining the change situation of the delivery routes of logistics delivery orders in a specified area based on the analysis results of order data on different dates. When the change situation of the delivery routes of logistics delivery orders in the specified area meets the requirements, obtaining the allocation data of freight vehicles in the adjacent areas of the specified area. Based on the allocation data of freight vehicles, the adjacent areas, and the order data in the specified area, determining the dates when the freight vehicles do not meet the requirements and taking them as freight deviation dates. When the deviation situations of freight vehicles on different freight deviation dates do not meet the requirements, determining the allocation strategy of freight vehicles in the specified area and the adjacent areas by using the freight demand coefficients of logistics delivery orders in the specified area and the adjacent areas, thereby reducing the transportation cost.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and particularly relates to a method and system for analyzing and processing logistics data. Background Art

[0002] For logistics platform enterprises, they often use the acquisition results of order data of different order users to optimize the scheduling of freight vehicles. However, in the actual scheduling process, there often appears the technical problem that the distribution of freight vehicles does not match the distribution of orders. This makes it an urgent technical problem to carry out the scheduling of freight vehicles based on the analysis results of order data.

[0003] In order to realize the scheduling of freight vehicles, in the invention patent application CN202411248136.4 "An Optimization Method for Predictive Scheduling of Bulk Logistics Transportation Based on Data Analysis", through the comprehensive analysis of multi-source data and the application of deep learning models, the accuracy and real-time performance of logistics transportation path planning are realized, and the transportation cost is effectively reduced. However, there are the following technical problems:

[0004] In the process of optimizing the scheduling of freight vehicles, there are significant differences in the distribution of order users in different regions. At the same time, there are also significant differences in the distribution of distribution routes of logistics orders of order users in different regions. This leads to significant differences in the demand for freight vehicles in different regions. Therefore, if a differentiated scheduling strategy cannot be generated according to the distribution of order users and the distribution of logistics orders in different regions, the matching degree of freight vehicles and logistics data cannot be improved.

[0005] In view of the above technical problems, the present invention provides a method and system for analyzing and processing logistics data. Summary of the Invention

[0006] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0007] According to one aspect of the present invention, a method for analyzing and processing logistics data is provided.

[0008] A method for analyzing and processing logistics data specifically includes:

[0009] S1 Based on the acquisition data of logistics distribution orders on different dates in a specified area, determine the order data of logistics distribution orders on different dates, and when the freight demand coefficient of the logistics distribution orders in the specified area is within a preset range determined by the order data on different dates, proceed to the next step;

[0010] S2 determines the change situation of the delivery routes of the logistics delivery orders in the specified area based on the analysis results of the order data of different dates. When the change situation of the delivery routes of the logistics delivery orders in the specified area meets the requirements, it proceeds to the next step;

[0011] S3 obtains the allocation data of the freight vehicles in the adjacent area of the specified area. Based on the allocation data of the freight vehicles, the adjacent area, and the order data in the specified area, it determines the dates when the freight vehicles do not meet the requirements and takes them as the freight deviation dates;

[0012] S4 When the deviation situations of the freight vehicles on different freight deviation dates do not meet the requirements, it determines the allocation strategy of the freight vehicles in the specified area and the adjacent area by using the freight demand coefficients of the logistics delivery orders in the specified area and the adjacent area.

[0013] The beneficial effects of the present invention are as follows:

[0014] By judging whether the deviation situations of the freight vehicles on different freight deviation dates meet the requirements, it avoids the technical problem of inaccurate judgment of freight reliability caused by solely considering the freight demand in the specified area. Thus, it realizes determining the deviation situations of the freight vehicles on different dates based on the allocation data of the freight vehicles in the adjacent area, and also lays a foundation for determining the allocation strategy of the freight vehicles in the specified area in a differentiated manner.

[0015] Determining the allocation strategy of the freight vehicles in the specified area and the adjacent area by using the freight demand coefficients of the logistics delivery orders in the specified area and the adjacent area avoids the technical problem of insufficient freight reliability caused by the non - compliance of the freight vehicles. At the same time, by further combining the freight demand coefficients of the logistics delivery orders in the specified area and the adjacent area, it realizes the dynamic adjustment of the allocation quantity of the freight vehicles in different areas according to the freight demand coefficients of different areas.

[0016] A further technical solution is that the obtained data of the logistics delivery orders is determined according to the order record data of the logistics delivery orders on the logistics delivery platform.

[0017] A further technical solution is that the order data of the logistics delivery orders includes the delivery volume of the logistics delivery orders.

[0018] A further technical solution is that the method for determining the freight demand coefficient of the logistics delivery orders in the specified area is as follows:

[0019] Based on the order data of different dates, determine the delivery volume of the logistics delivery orders for different dates, and determine the total delivery volume of the logistics delivery orders for different dates according to the delivery volume of the logistics delivery orders for different dates;

[0020] Determine the dates when the total delivery volume is greater than the preset delivery volume threshold according to the total delivery volume of the logistics delivery orders for different dates, and use them as the delivery demand dates;

[0021] Determine the freight demand coefficient of the logistics delivery orders in the specified area according to the proportion of the number of delivery demand dates.

[0022] A further technical solution is that the value range of the freight demand coefficient of the logistics delivery orders in the specified area is between 0 and 1. Among them, when the freight demand coefficient of the logistics delivery orders in the specified area is larger, the freight demand degree of the logistics delivery orders in the specified area is higher.

[0023] A further technical solution is that the method for determining the distribution strategy of freight vehicles in the specified area and its adjacent areas is as follows:

[0024] Based on the freight demand coefficient of the logistics delivery orders in the specified area and its adjacent areas, determine the required number of freight vehicles in the specified area and its adjacent areas;

[0025] Determine the distribution strategy of the freight vehicles in the specified area and its adjacent areas according to the required number.

[0026] A further technical solution is that the required number of freight vehicles in the specified area is determined according to the product of the freight demand coefficient and the preset demand ratio factor. Specifically, the product of the freight demand coefficient and the preset demand ratio factor determines the matching number of freight vehicles, and the matching number is used as the required number of freight vehicles in the specified area.

[0027] In a second aspect, the present invention provides a computer system, including: a memory and a processor connected by communication, and a computer program stored on the memory and capable of running on the processor. When the processor runs the computer program, it executes the above-mentioned logistics data analysis and processing method.

[0028] Other features and advantages will be described in the following description. The objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the description and the drawings.

[0029] To make the above objectives, features, and advantages of the present invention more obvious and understandable, the following specifically enumerates preferred embodiments and, in conjunction with the accompanying drawings, makes a detailed description as follows. Description of the Drawings

[0030] The above and other features and advantages of the present invention will become more apparent by describing in detail its exemplary embodiments with reference to the accompanying drawings.

[0031] Figure 1 is a flowchart of a method for analyzing and processing logistics data;

[0032] Figure 2 is a flowchart of a method for determining the freight demand coefficient of logistics distribution orders in a specified area;

[0033] Figure 3 is a flowchart for determining whether the change in the distribution route of logistics distribution orders in a specified area meets the requirements;

[0034] Figure 4 is a flowchart of a method for determining the freight deviation date;

[0035] Figure 5 is a framework diagram of a computer system. Detailed Embodiments

[0036] In order to enable those skilled in the art of this technology to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all the embodiments. Based on the embodiments of this specification, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the scope of protection of this specification.

[0037] During the process of optimizing the scheduling of freight vehicles, there are significant differences in the distribution of order users in different regions. Therefore, it is necessary to generate differentiated scheduling strategies based on the distribution of order users in different regions and the distribution of logistics orders, thereby reducing freight costs.

[0038] Freight demand coefficient of logistics distribution orders in a specified area: Determine the total distribution volume of logistics distribution orders on different dates according to the distribution volume of logistics distribution orders on different dates. Determine the dates when the total distribution volume is greater than the preset distribution volume threshold according to the total distribution volume of logistics distribution orders on different dates, and use them as the distribution demand dates. Determine the freight demand coefficient of the logistics distribution orders in the specified area by the proportion of the number of distribution demand dates.

[0039] When the freight demand coefficient is between 0.5 and 0.8, it is determined that the freight demand coefficient is within the preset range.

[0040] Determine whether the change situation of the delivery routes of the logistics delivery orders in the specified area meets the requirements: Based on the delivery routes of the logistics delivery orders in the specified area on different dates, determine the coincidence data of the delivery routes of different logistics delivery orders. Based on the coincidence data of the delivery routes of different logistics delivery orders, determine the delivery routes of the most orders on different dates, and use it as the matching delivery route. Based on the deviation situation of the matching delivery routes between different dates and the adjacent dates, determine the deviation dates. Determine whether the change situation of the delivery routes of the logistics delivery orders in the specified area meets the requirements according to the proportion of the number of deviation dates;

[0041] Specifically, when the proportion of the number of deviation dates is greater than 0.5, it is determined that the change situation of the delivery routes of the logistics delivery orders in the specified area does not meet the requirements.

[0042] Freight deviation date: Based on the order data in the adjacent area and the specified area, determine the required quantity of freight vehicles on different dates, and use the deviation between the allocated quantity and the required quantity of freight vehicles in the adjacent area to determine the dates when the freight vehicles do not meet the requirements.

[0043] Allocation strategy of freight vehicles in the specified area and the adjacent area: Based on the freight demand coefficients of the logistics delivery orders in the specified area and the adjacent area, determine the required quantity of freight vehicles in the specified area and the adjacent area, and determine the allocation strategy of the freight vehicles in the specified area and the adjacent area according to the required quantity.

[0044] Embodiment 1 To solve the above problems, according to one aspect of the present invention, as Figure 1 shown, the first aspect is provided. The present invention provides a method for analyzing and processing logistics data, specifically including:

[0045] S1 Based on the acquired data of the logistics delivery orders in the specified area on different dates, determine the order data of the logistics delivery orders on different dates, and when the freight demand coefficient of the logistics delivery orders in the specified area determined by the order data on different dates is within the preset range, proceed to the next step;

[0046] S2 Based on the analysis results of the order data on different dates, determine the change situation of the delivery routes of the logistics delivery orders in the specified area. When the change situation of the delivery routes of the logistics delivery orders in the specified area meets the requirements, transfer to the next step;

[0047] S3 Obtain the allocation data of the freight vehicles in the adjacent area of the specified area. Based on the allocation data of the freight vehicles, the order data in the adjacent area and the specified area, determine the dates when the freight vehicles do not meet the requirements, and use it as the freight deviation date;

[0048] S4 When the deviation situations of freight vehicles with different freight deviation dates do not meet the requirements, the distribution strategies of freight vehicles in the specified area and its adjacent areas are determined by using the freight demand coefficients of logistics distribution orders in the specified area and its adjacent areas.

[0049] Further, the obtained data of the logistics distribution order is determined according to the order record data of the logistics distribution order on the logistics distribution platform.

[0050] Specifically, the order data of the logistics distribution order includes the distribution volume of the logistics distribution order.

[0051] It should be noted that, as Figure 2 shown, the method for determining the freight demand coefficient of the logistics distribution order in the specified area is:

[0052] Based on the order data of different dates, determine the distribution volume of the logistics distribution order of different dates, and determine the total distribution volume of the logistics distribution order of different dates according to the distribution volume of the logistics distribution order of different dates;

[0053] Determine the dates when the total distribution volume is greater than the preset distribution volume threshold according to the total distribution volume of the logistics distribution order of different dates, and take them as the distribution demand dates;

[0054] Determine the freight demand coefficient of the logistics distribution order in the specified area according to the proportion of the number of distribution demand dates.

[0055] Optionally, the value range of the freight demand coefficient of the logistics distribution order in the specified area is between 0 and 1. Among them, the greater the freight demand coefficient of the logistics distribution order in the specified area, the higher the freight demand degree of the logistics distribution order in the specified area.

[0056] In another embodiment, when the freight demand coefficient of the logistics distribution order in the specified area is not within the preset interval, it is also necessary to judge whether the average value of the total distribution volume of the logistics distribution order of different dates is greater than the preset distribution volume. If so, it is determined that the specified area needs to allocate freight vehicles. If not, it is determined that the specified area does not need to allocate freight vehicles.

[0057] Optionally, the method for determining the freight demand coefficient of the logistics distribution order in the specified area is:

[0058] Based on the order data of different dates, determine the distribution volume of the logistics distribution order of different dates, and determine the distribution demand coefficient of different dates according to the distribution volume of the logistics distribution order of different dates and the order volume of the logistics distribution order;

[0059] Determine the distribution demand dates according to the distribution demand coefficients of different dates;

[0060] Determine the freight demand coefficient of the logistics distribution orders in the specified area according to the proportion of the quantity of the delivery demand date.

[0061] In one of the embodiments, the method for determining the freight demand coefficient of the logistics distribution orders in the specified area is as follows:

[0062] S11 Based on the order data of different dates, determine the delivery volume of the logistics distribution orders of different dates. According to the delivery volume of the logistics distribution orders of different dates and the order volume of the logistics distribution orders, determine the delivery demand coefficient of different dates;

[0063] Optionally, the above step S11 includes the following content:

[0064] S111 Based on the order data of different dates, obtain the order volume of the logistics distribution orders of different dates. When the order volume of the logistics distribution orders of different dates is less than the preset order volume, it is determined that the freight demand coefficient of the logistics distribution orders in the specified area is not within the preset interval. When there is a date when the order volume of the logistics distribution order is not less than the preset order volume, go to step S112;

[0065] S112 Determine the dates when the total delivery volume determined by the delivery volume of the logistics distribution orders of different dates is greater than the preset delivery volume, then go to step S113. When there is no date when the total delivery volume is greater than the preset delivery volume, go to step S114;

[0066] S113 When the number of dates when the total delivery volume is greater than the preset delivery volume is not within the preset date number interval, it is determined that the freight demand coefficient of the logistics distribution orders in the specified area is not within the preset interval. When the number of dates when the total delivery volume is greater than the preset delivery volume is within the preset date number interval, go to step S114;

[0067] S114 According to the delivery volume of the logistics distribution orders of different dates and the order volume of the logistics distribution orders, determine the delivery demand coefficient of different dates. When the average value of the delivery demand coefficients of different dates is greater than the preset coefficient threshold, it is determined that the freight demand coefficient of the logistics distribution orders in the specified area is not within the preset interval. When the average value of the delivery demand coefficients of different dates is not greater than the preset coefficient threshold, go to step S12.

[0068] S12 Determine the delivery demand dates according to the delivery demand coefficients of different dates;

[0069] Optionally, the above step S12 includes the following content:

[0070] If it is determined according to the delivery demand coefficients on different dates that there is no delivery demand date, then it is determined that the freight demand coefficient of the logistics delivery orders in the specified area is not within the preset range. When there is a delivery demand date, proceed to step S122;

[0071] S122 Obtain the number of delivery demand dates. When the number of delivery demand dates is greater than the preset number of delivery dates, then it is determined that the freight demand coefficient of the logistics delivery orders in the specified area is not within the preset range. When the number of delivery demand dates is not greater than the preset number of delivery dates, proceed to step S123;

[0072] S123 Obtain the number of delivery demand dates within the preset time period. When the number of delivery demand dates within the preset time period does not meet the requirements, then it is determined that freight vehicles need to be allocated in the specified area. When the number of delivery demand dates within the preset time period meets the requirements, proceed to step S13.

[0073] S13 Determine the freight demand coefficient of the logistics delivery orders in the specified area according to the delivery demand coefficients on different delivery demand dates and the proportion of the number of delivery demand dates.

[0074] Furthermore, the change situation of the delivery routes of the logistics delivery orders is determined according to the change situations of the delivery routes of the logistics delivery orders on different dates.

[0075] Specifically, as Figure 3 shown, determining that the change situation of the delivery routes of the logistics delivery orders in the specified area meets the requirements specifically includes:

[0076] Based on the order data of the logistics delivery orders in the specified area, determine the delivery routes of the logistics delivery orders in the specified area on different dates. According to the delivery routes of the logistics delivery orders in the specified area on different dates, determine the overlapping data of the delivery routes of different logistics delivery orders;

[0077] Based on the overlapping data of the delivery routes of different logistics delivery orders, determine the matching delivery routes on different dates;

[0078] Determine whether the change situation of the delivery routes of the logistics delivery orders in the specified area meets the requirements according to the deviation situation of the matching delivery routes between different dates.

[0079] Furthermore, the matching delivery route is the delivery route with the largest number of overlapping logistics delivery orders.

[0080] It should be noted that determining whether the change situation of the delivery routes of the logistics delivery orders in the specified area meets the requirements according to the deviation situation of the matching delivery routes between different dates specifically includes:

[0081] Determine the deviation date based on the deviation of the matching delivery routes between different dates and the adjacent dates.

[0082] Determine whether the change of the delivery route of the logistics delivery orders in the specified area meets the requirements according to the proportion of the number of the deviation dates.

[0083] Optionally, determining that the change of the delivery route of the logistics delivery orders in the specified area meets the requirements specifically includes:

[0084] S21 Based on the order data of the logistics delivery orders in the specified area, determine the delivery routes of the logistics delivery orders in the specified area on different dates. According to the delivery routes of the logistics delivery orders in the specified area on different dates, determine the coincidence data of the delivery routes of different logistics delivery orders.

[0085] S22 Based on the coincidence data of the delivery routes of different logistics delivery orders, determine the distribution dispersion coefficient of the delivery routes of the logistics delivery orders on different dates. Determine the comprehensive dispersion coefficient according to the distribution dispersion coefficient of the delivery routes of the logistics delivery orders on different dates.

[0086] S23 Based on the coincidence data of the delivery routes of different logistics delivery orders, determine the matching delivery routes on different dates and the corresponding logistics delivery orders of the matching delivery routes, and determine the change coefficient of the delivery routes of the logistics delivery orders with the matching delivery routes on different dates and the corresponding logistics delivery orders of the matching delivery routes.

[0087] S24 Determine the discrete evaluation quantity of the logistics delivery orders in the specified area with the comprehensive dispersion coefficient and the change coefficient of the delivery routes of the logistics delivery orders, and use the discrete evaluation quantity to determine whether the change of the delivery route meets the requirements.

[0088] Optionally, the following content is included in the above step S22:

[0089] S221 Based on the coincidence data of the delivery routes of different logistics delivery orders, determine the distribution dispersion coefficient of the delivery routes of the logistics delivery orders on different dates, obtain the average value of the distribution dispersion coefficients of the delivery routes of the logistics delivery orders on different dates. When the average value of the distribution dispersion coefficients of the delivery routes of the logistics delivery orders on different dates does not meet the requirements, it is determined that the change of the delivery route does not meet the requirements. When the average value of the distribution dispersion coefficients of the delivery routes of the logistics delivery orders on different dates meets the requirements, proceed to step S222.

[0090] S222 When there are dates with distribution dispersion coefficients not meeting the requirements, proceed to step S223; when there are no dates with distribution dispersion coefficients not meeting the requirements, proceed to step S224;

[0091] S223 Obtain the number of dates with distribution dispersion coefficients not meeting the requirements. When the number of dates with distribution dispersion coefficients not meeting the requirements is greater than the preset number of dates, it is determined that the change situation of the delivery route does not meet the requirements. When the number of dates with distribution dispersion coefficients not meeting the requirements is not greater than the preset number of dates, proceed to step S224;

[0092] S224 Determine the comprehensive dispersion coefficient based on the distribution dispersion coefficients of the delivery routes of the logistics delivery orders on different dates. When the comprehensive dispersion coefficient does not meet the requirements, it is determined that the change situation of the delivery route does not meet the requirements. When the comprehensive dispersion coefficient meets the requirements, proceed to step S23.

[0093] Optionally, the above step S23 includes the following content:

[0094] S231 Based on the overlapping data of the delivery routes of different logistics delivery orders, determine the matching delivery routes for different dates, and determine the proportion of the number of dates corresponding to different matching delivery routes. When the proportion of the number of dates corresponding to different matching delivery routes is less than the preset proportion of the number of dates, it is determined that the change situation of the delivery route does not meet the requirements. When there are matching delivery routes with a proportion of the number of dates not less than the preset proportion of the number of dates, proceed to step S232;

[0095] S232 Determine the deviation dates based on the deviation situations of the matching delivery routes between different dates and the adjacent dates. When the proportion of the number of deviation dates is greater than the preset proportion of the number of deviation dates, it is determined that the change situation of the delivery routes of the logistics delivery orders in the specified area does not meet the requirements. When the proportion of the number of deviation dates is not greater than the preset proportion of the number of deviation dates, proceed to step S233;

[0096] S233 Determine the change coefficient of the delivery routes of the logistics delivery orders based on the matching delivery routes of different dates and the corresponding logistics delivery orders. When the change coefficient of the delivery routes of the logistics delivery orders does not meet the requirements, it is determined that the change situation of the delivery routes of the logistics delivery orders in the specified area does not meet the requirements. When the change coefficient of the delivery routes of the logistics delivery orders meets the requirements, proceed to step S234;

[0097] S234 When the change coefficient of the delivery routes of the logistics delivery orders is within the preset change coefficient range, proceed to step S235; when the change coefficient of the delivery routes of the logistics delivery orders is not within the preset change coefficient range, proceed to step S23;

[0098] When the comprehensive dispersion coefficient is within the preset dispersion coefficient range, it is determined that the change situation of the delivery route of the logistics delivery order in the specified area does not meet the requirements. When the comprehensive dispersion coefficient is not within the preset dispersion coefficient range, go to step S23.

[0099] Furthermore, when the number of corresponding dates of different matching delivery routes is less than the preset number of dates, it is determined that the change situation of the delivery route of the logistics delivery order in the specified area does not meet the requirements.

[0100] Specifically, the adjacent area is an area whose distance from the specified area is within the preset distance range.

[0101] It should be noted that the distribution data of the freight vehicles in the adjacent area includes the number of freight vehicles in the adjacent area.

[0102] Specifically, as Figure 4 shown, the method for determining the freight deviation date is:

[0103] Using the distribution data of the freight vehicles to determine the number of freight vehicles in different adjacent areas on the date, and using the order data of the adjacent area and the specified area on the date to determine the total delivery volume of the logistics delivery orders in the adjacent area and the specified area on the date;

[0104] According to the total delivery volume of the logistics delivery orders in the adjacent area and the specified area on the date, and the number of freight vehicles in different adjacent areas on the date, determine the deviation number of freight vehicles on the date;

[0105] Based on the deviation number of freight vehicles on the date, determine whether the date is a freight deviation date.

[0106] Furthermore, the method for determining the deviation number of freight vehicles on the date is:

[0107] According to the total delivery volume of the logistics delivery orders in the adjacent area and the specified area on the date, determine the required number of freight vehicles for the total delivery volume;

[0108] Using the required number and the number of freight vehicles to determine the deviation number of freight vehicles on the date.

[0109] Specifically, when the deviation number of freight vehicles on the date does not meet the requirements, it is determined that the date belongs to the freight deviation date.

[0110] Optionally, the deviation situation of the freight vehicles for determining the freight deviation date does not meet the requirements, specifically including:

[0111] Determine the proportion of the number of freight deviation dates based on the deviation situations of freight vehicles with different freight deviation dates, and determine the deviation proportion factor by using the proportion of the number of freight deviation dates;

[0112] Obtain the deviation amounts of freight vehicles with different freight deviation dates, and determine the freight deviation coefficient by using the average value of the deviation amounts of freight vehicles with different freight deviation dates;

[0113] Determine the comprehensive deviation coefficient according to the deviation proportion factor and the freight deviation coefficient, and determine whether the deviation situation of the freight vehicles on the freight deviation date meets the requirements by using the comprehensive deviation coefficient.

[0114] Further, the freight deviation coefficient is determined according to the ratio of the average value of the deviation amounts of freight vehicles with different freight deviation dates to the number of freight vehicles in different adjacent areas.

[0115] It should be noted that when the comprehensive deviation coefficient is greater than the preset deviation coefficient threshold, it is determined that the deviation situation of the freight vehicles on the freight deviation date does not meet the requirements.

[0116] Optionally, when the deviation situation of the freight vehicles on the freight deviation date meets the requirements, there is no need to allocate freight vehicles in the specified area.

[0117] Specifically, the method for determining the distribution strategy of freight vehicles in the specified area and adjacent areas is as follows:

[0118] Based on the freight demand coefficients of the logistics distribution orders in the specified area and adjacent areas, determine the required number of freight vehicles in the specified area and adjacent areas;

[0119] Determine the distribution strategy of the freight vehicles in the specified area and adjacent areas according to the required number.

[0120] Further, the required number of freight vehicles in the specified area is determined according to the product of the freight demand coefficient and the preset demand proportion factor. Specifically, the product of the freight demand coefficient and the preset demand proportion factor determines the matching number of freight vehicles, and the matching number is used as the required number of freight vehicles in the specified area.

[0121] Embodiment 2 Second aspect, as Figure 5 shown, the present invention provides a computer system, including: a memory and a processor connected by communication, and a computer program stored on the memory and capable of running on the processor. When the processor runs the computer program, it executes the above-mentioned logistics data analysis and processing method.

[0122] In another embodiment, the deviation situation of the freight vehicle for determining the freight deviation date does not meet the requirements, specifically including:

[0123] Based on the deviation situations of freight vehicles with different freight deviation dates, determine the number of freight deviation dates. When the number of the freight deviation dates does not meet the requirements, it is determined that the deviation situation of the freight vehicle for the freight deviation date does not meet the requirements;

[0124] When the number of the freight deviation dates meets the requirements:

[0125] Obtain the deviation amounts of freight vehicles with different freight deviation dates, and use the freight deviation dates with deviation amounts greater than the preset deviation amount as the screened deviation dates. When the number of the screened deviation dates does not meet the requirements, it is determined that the deviation situation of the freight vehicle for the freight deviation date does not meet the requirements;

[0126] When the number of the screened deviation dates meets the requirements:

[0127] Based on the number of the freight deviation dates and the proportion of the number of freight deviation dates, determine the basic deviation coefficient. When the basic deviation coefficient does not meet the requirements, it is determined that the deviation situation of the freight vehicle for the freight deviation date does not meet the requirements;

[0128] When the basic deviation coefficient meets the requirements:

[0129] When the basic deviation coefficient is within the preset deviation coefficient range:

[0130] Based on the deviation amounts of freight vehicles with different freight deviation dates, determine the average value of the deviation amounts of freight vehicles with different freight deviation dates. When the average value of the deviation amounts of freight vehicles with different freight deviation dates is greater than the preset deviation amount threshold, it is determined that the deviation situation of the freight vehicle for the freight deviation date does not meet the requirements;

[0131] When the basic deviation coefficient is not within the preset deviation coefficient range or the average value of the deviation amounts of freight vehicles with different freight deviation dates is not greater than the preset deviation amount threshold:

[0132] Obtain the deviation amounts of freight vehicles with different freight deviation dates, and use the average value of the deviation amounts of freight vehicles with different freight deviation dates to determine the freight deviation coefficient;

[0133] Determine the comprehensive deviation coefficient according to the basic deviation coefficient and the freight deviation coefficient, and use the comprehensive deviation coefficient to determine whether the deviation situation of the freight vehicle for the freight deviation date meets the requirements.

[0134] Each embodiment in this specification is described in a progressive manner. For the parts that are the same or similar among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the embodiments of the device, equipment, and non-volatile computer storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and reference can be made to the corresponding parts of the method embodiments for relevant content.

[0135] The specific embodiments of this specification are described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be executed in a different order from that in the embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0136] The above description is only for one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, various modifications and changes can be made to one or more embodiments of this specification. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of one or more embodiments of this specification shall be included within the scope of the claims of this specification.

Claims

1. A logistics data analysis and processing method, characterized in that: Specifically include: Based on the acquired data of logistics delivery orders on different dates in the designated area, order data of logistics delivery orders on different dates are determined, and when the freight demand coefficient of the logistics delivery orders in the designated area is determined to be within a preset range based on the order data on different dates, the next step is entered; Determine the change of the delivery route of the logistics delivery order in the designated area based on the analysis results of the order data of different dates, and proceed to the next step when the change of the delivery route of the logistics delivery order in the designated area meets the requirements; Obtaining the allocation data of freight vehicles in the adjacent areas of the designated area, and determining the date on which the freight vehicles do not meet the requirements based on the allocation data of the freight vehicles, the adjacent areas and the order data in the designated area, and using the date as the freight deviation date; When the deviation of freight vehicles on different freight deviation dates does not meet the requirements, the freight demand coefficients of the logistics delivery orders in the designated area and the adjacent areas are used to determine the allocation strategy of the freight vehicles in the designated area and the adjacent areas; The method for determining the freight demand coefficient of the logistics delivery order in the specified area is: Based on the order data of different dates, determine the delivery volume of the logistics delivery orders on different dates, and determine the total delivery volume of the logistics delivery orders on different dates according to the delivery volume of the logistics delivery orders on different dates; According to the total delivery volume of logistics delivery orders on different dates, determine the date when the total delivery volume is greater than the preset delivery volume threshold, and use it as the delivery demand date; Determining the freight demand coefficient of the logistics delivery orders in the specified area according to the quantity ratio of the delivery demand date; When the freight demand coefficient of the logistics delivery orders in the designated area is not within the preset range, it is also necessary to determine whether the average of the total delivery volume of the logistics delivery orders on different dates is greater than the preset delivery volume. If so, it is determined that the designated area needs to be allocated with freight vehicles. If not, it is determined that the designated area does not need to be allocated with freight vehicles. The method for determining the allocation strategy of freight vehicles in the designated area and adjacent areas is: Determine the required number of freight vehicles in the designated area and adjacent areas based on the freight demand coefficient of logistics delivery orders in the designated area and adjacent areas; Determine a distribution strategy for freight vehicles in the designated area and adjacent areas according to the demand quantity; Determining whether changes in the delivery routes of the logistics delivery orders in the designated area meet the requirements, specifically includes: Based on the order data of the logistics delivery orders in the designated area, the delivery routes of the logistics delivery orders in the designated area on different dates are determined, and according to the delivery routes of the logistics delivery orders in the designated area on different dates, the overlapping data of the delivery routes of different logistics delivery orders are determined; Based on the overlapping data of delivery routes of different logistics delivery orders, determine the matching delivery routes for different dates; Determine whether the change of the delivery route of the logistics delivery order in the designated area meets the requirements according to the deviation of the matching delivery routes between different dates.

2. The logistics data analysis and processing method according to claim 1, characterized in that: The acquisition data of the logistics delivery order is determined according to the order record data of the logistics delivery order of the logistics delivery platform.

3. The logistics data analysis and processing method according to claim 1, characterized in that: The order data of the logistics delivery order includes the delivery quantity of the logistics delivery order.

4. The logistics data analysis and processing method according to claim 1, characterized in that: The freight demand coefficient of the logistics delivery orders in the designated area ranges from 0 to 1, wherein the larger the freight demand coefficient of the logistics delivery orders in the designated area, the higher the freight demand level of the logistics delivery orders in the designated area.

5. The logistics data analysis and processing method according to claim 1, characterized in that: The changes in the delivery routes of the logistics delivery orders are determined based on the changes in the delivery routes of the logistics delivery orders on different dates.

6. The logistics data analysis and processing method according to claim 1, characterized in that: The demand quantity of freight vehicles in the designated area is determined based on the product of the freight demand coefficient and a preset demand proportional factor. The specific product of the freight demand coefficient and the preset demand proportional factor determines the matching quantity of freight vehicles, and the matching quantity is used as the demand quantity of freight vehicles in the designated area.

7. A computer system comprising: A memory and a processor that are communicatively connected, and a computer program stored in the memory and capable of running on the processor, characterized in that the processor executes a logistics data analysis and processing method as described in any one of claims 1-6 when running the computer program.

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