A cloud-based digital management system and method for logistics supply

Abstract

This invention discloses a cloud-based digital management system and method for logistics supply, relating to the field of cloud platform logistics management technology. The invention acquires current goods logistics information through a cloud platform, constructs a logistics information form based on this information, and builds a corresponding information matrix for each good. Based on the goods' logistics transportation location information and historical regional logistics transportation route networks, it acquires logistics transfer stations in the corresponding regions. It performs periodic status assessments on each logistics transfer station; it iterates and generates current goods transportation routes based on historical data and the current goods logistics transportation location; it performs efficiency filtering on each transportation route in the route set based on the goods transportation cycle, evaluates the transportation route bias for each route, and outputs the optimal transportation route for the cycle based on the evaluation results; it outputs the corresponding goods information and the optimal transportation route for the corresponding cycle, and provides real-time feedback on the periodic status data of the corresponding transportation transfer stations.

Description

Technical Field

[0001] This invention relates to the field of cloud platform logistics management, specifically a cloud platform-based digital management system and method for logistics supply. Background Technology

[0002] Cloud-based digital management of logistics supply is a new management model that utilizes advanced technologies such as cloud computing, big data, and artificial intelligence to digitally and intelligently transform and upgrade the entire supply chain. By integrating all links of the supply chain, it achieves information sharing and intelligent decision-making, thereby improving the overall efficiency and competitiveness of the supply chain.

[0003] Logistics and transportation, as a crucial link in the logistics supply chain, has been an indispensable part of social development since ancient times, closely related to social progress and technological advancement. Traditional logistics and transportation relied heavily on manual experience for point-to-point transport throughout the entire process. However, in today's environment of rapidly increasing logistics volume, this model is no longer suitable and its efficiency is relatively low. Therefore, a new logistics and transportation model with multiple transfer points and multiple threads has replaced the traditional model. However, this model still has shortcomings in the current environment. Although it refines and improves the efficiency of point-to-point transportation through multiple transfers, it still relies heavily on experience and cannot effectively plan routes based on the real-time status of transfer stations. This leads to uneven operation of stations, waste of station resources, and low intelligence in transportation planning. Summary of the Invention

[0004] The purpose of this invention is to provide a cloud-based digital management system and method for logistics supply to solve the problems raised in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A cloud-based digital management method for logistics supply chain, comprising the following steps:

[0007] S100. Obtain the logistics information of the current batch of goods through the cloud platform information port, construct the logistics information form of the corresponding batch of goods based on the retrieved goods logistics information, and construct the corresponding information matrix based on the information of each goods.

[0008] S200. Based on the logistics transportation location information in each cargo information matrix and the historical regional logistics transportation route network, obtain the logistics transfer stations in the corresponding regions; conduct periodic status assessments of each logistics transfer station, and classify each logistics transfer station into different levels based on the assessment results.

[0009] S300: Based on the historical transit station path generation records and combined with the current cargo information and logistics transportation location information, the current cargo transportation routes are traversed and generated, and a route set is constructed; based on the cargo transportation cycle, the efficiency of each transportation route in the route set is filtered, and the transportation route bias is evaluated for each transportation route based on the filtered data, and the optimal transportation route for the cycle is output based on the evaluation results.

[0010] S400 outputs the corresponding cargo information and the optimal transportation route for the corresponding period, and provides real-time feedback on the periodic status data of the corresponding transportation transfer station.

[0011] The specific steps of S100 in obtaining the logistics information of the current batch of goods through the cloud platform information port, constructing the corresponding logistics information form of the batch of goods based on the retrieved goods logistics information, and constructing the corresponding information matrix based on the information of each goods are as follows:

[0012] S101. Obtain the current logistics status of each batch of goods by logging into the logistics information management port of the corresponding regional cloud platform; retrieve information on goods in the pre-transport batch; the logistics status of goods includes completed transportation, in transportation, pre-transport, and not yet transported;

[0013] S102. Based on the retrieved pre-transport batch goods information, the logistics information of each goods is coordinated and generated into a logistics information form corresponding to the current batch goods information by planning the corresponding logistics data column, and the logistics information matrix of each goods is constructed according to the logistics information form; wherein the logistics information matrix of each goods is constructed by integrating the logistics information of each independent goods in the logistics information form; the logistics information of the goods includes the starting position, ending position and transportation cycle information of the goods transportation.

[0014] The steps of S200, which combine logistics transportation location information in each cargo information matrix with historical regional logistics transportation route networks, to obtain logistics transfer stations in the corresponding regions; to conduct periodic status assessments of each logistics transfer station; and to classify each logistics transfer station into different levels based on the assessment results, are as follows:

[0015] S201. Based on the transportation location information of each item in the current batch, obtain the starting and ending transportation locations of each item; combined with the regional logistics transportation station distribution network, using the starting and ending points of each item's logistics transportation as constraints, mark the transportation logistics transfer stations between the two historical points, and obtain the adjacent historical period status data of each marked logistics transfer station; wherein the adjacent historical period status data is obtained by taking the time of data acquisition as a reference and the period length as the goods transportation cycle, and obtaining the periodic data of the historical data closest to the current time.

[0016] S202. Based on the labeled historical periodic status data of each logistics transfer station, perform periodic status evaluation on the adjacent historical periodic status data of each logistics transfer station. The calculation formula is as follows:

[0017]

[0018] Wherein, Dr(n) is the periodic inventory backlog rate of logistics transit station with label number n within the corresponding period; M(D,n) is the maximum inventory backlog quantity of logistics transit station with label number n within the corresponding period; M(n) is the maximum storage quantity of logistics transit station with label number n; Er(n) is the periodic turnover rate of logistics transit station with label number n within the corresponding period; M(E,n) is the total turnover quantity of logistics transit station with label number n within the corresponding period; M(A,n) is the total storage quantity of logistics transit station with label number n within the corresponding period; where the maximum inventory backlog quantity is the maximum untransported quantity of goods at the corresponding logistics transit station within the corresponding period; the total turnover quantity is the cumulative quantity of transported goods at the corresponding logistics transit station within the corresponding period; and the total storage quantity is the cumulative quantity of stored goods at the corresponding logistics transit station within the corresponding period.

[0019] Based on the analysis data of the periodic delay rate and transfer rate of each logistics transit station, a comprehensive evaluation and analysis of the periodic operation status of each logistics transit station is conducted. The calculation formula is as follows:

[0020]

[0021] Wherein, Ov(n) is the comprehensive evaluation value of the periodic operation status of the logistics transit station with label number n within the corresponding period; ave[Dr(n)] and ave[Er(n)] correspond to the historical average backlog rate and transfer rate of the logistics transit station with label number n, respectively;

[0022] Based on the comprehensive evaluation data of the periodic operation status of each logistics transfer station within the cycle, the status comparison parameters Ov(α) and Ov(β) are set. If Ov(n) > Ov(β), the corresponding logistics transfer station is judged to be in good condition; if Ov(α) ≤ Ov(n) ≤ Ov(β), the corresponding logistics transfer station is judged to be in normal condition; if Ov(n) < Ov(α), the corresponding logistics transfer station is judged to be in congested condition.

[0023] The S300 generates current cargo transportation routes by combining historical transit station path records with current cargo information and logistics transportation location information, and constructs a route set. Based on the cargo transportation cycle, it performs efficiency filtering on each transportation route in the route set, evaluates the transportation route bias based on the filtered data, and outputs the optimal transportation route based on the evaluation results. The specific steps are as follows:

[0024] S301. Combining historical regional logistics and transportation network data, using the current logistics and transportation start and end points of each product as key retrieval data, traverse historical transportation routes in the historical regional logistics and transportation route network, and construct a set of reference transportation routes for the current corresponding products based on the traversed historical transportation routes.

[0025] Based on a set of reference transportation routes, and using the current corresponding cargo transportation cycle as a filtering criterion, each reference transportation route in the set is filtered by cycle; the transportation time of each reference transportation route is analyzed and calculated.

[0026]

[0027] Where t(i) is the predicted transportation time for the transportation route with label i; s(i) is the total distance of the transportation route with label i; ave(v) is the average speed of goods transportation based on historical data; L, C, and Y correspond to the periodic states of good, normal, and congested logistics transfer points, respectively; h(j,i) is the goods transfer time of the logistics transfer station with state j in the transportation route with label i; z(j,i) is the number of logistics transfer stations with state j in the transportation route with label i; where j takes the values ​​L, C, and Y.

[0028] S302. Based on the predicted transportation time analysis data of each comparison transportation route, and combined with the transportation cycle of the corresponding goods, each comparison transportation route is screened; if t(i) > T, it is determined that the current comparison transportation route does not meet the transportation requirements and is screened out; if t(i) ≤ T, the current comparison transportation route is retained; according to the screening operation, the retained comparison transportation routes for the corresponding goods are obtained, and a set of pre-transportation routes is constructed; where T is the transportation cycle time of the corresponding goods;

[0029] Based on the reference transportation routes in the pre-transportation route set for the corresponding goods, and comprehensively considering the periodic operational status evaluation data of each logistics transfer station on each reference transportation route, as well as the route transportation time efficiency and the location distribution of each station, a transportation status bias analysis is performed on each reference transportation route. The calculation formula is as follows:

[0030]

[0031] Where, Ts(p) is the transport state bias analysis value of the reference transport route labeled p in the corresponding pre-transport route set; t(p) is the predicted transport time of the reference transport route labeled p in the corresponding pre-transport route set; Ov(n,p) is the comprehensive evaluation value of the periodic operation status of the logistics transfer station labeled n on the reference transport route labeled p in the corresponding pre-transport route set; k(j,n,p) is the state parameter of state j corresponding to the logistics transfer station labeled n on the reference transport route labeled p in the corresponding pre-transport route set; Q[(x,y)] n →(x,y)0] and Q[(x,y) n →(x,y)1] represents the coordinates (x,y) respectively. n The coordinate distance between (x, y) and 0 and the coordinates (x, y) n The coordinate distance between (x, y)1 and the coordinates; where (x, y) n The coordinates of the logistics transfer station labeled p in the pre-transport route set and labeled n on the corresponding transportation route are given; (x,y)0 and (x,y)1 correspond to the coordinates of the starting point and the ending point of the goods transportation, respectively.

[0032] Based on the transportation state bias analysis data of each reference transportation route in the pre-transportation route set, the reference transportation route corresponding to the maximum value of the transportation state bias analysis is taken as the optimal transportation route for the current corresponding goods in the cycle.

[0033] The specific steps of S400 in outputting the corresponding cargo information and the optimal transportation route for the corresponding period, and in real-time feedback of the periodic status data of the corresponding transportation transfer station are as follows:

[0034] S401. Output the corresponding product information and the optimal transportation route for the corresponding period through the cloud platform display terminal, and perform transportation planning based on the route;

[0035] S402. Real-time annotation and display of comprehensive evaluation data on the cyclical operation status of each logistics transfer station in the optimal transportation route for goods.

[0036] A cloud-based digital management system for logistics supply, the system comprising a goods information processing module, a logistics station status assessment module, a transportation route comprehensive analysis module, and a data output module;

[0037] The cargo information processing module obtains the current batch of cargo logistics information through the cloud platform information port, constructs a logistics information form for the corresponding batch of cargo based on the retrieved cargo logistics information, and constructs a corresponding information matrix based on the cargo information. The logistics station status assessment module obtains the logistics transfer stations in the corresponding region based on the logistics transportation location information in each cargo information matrix and the historical regional logistics transportation route network. It performs periodic status assessments on each logistics transfer station and classifies each logistics transfer station into different levels based on the assessment results. The transportation route comprehensive analysis module generates transportation routes for each cargo based on the historical regional transfer station path generation records and the current cargo information logistics transportation location information, and constructs a route set. It performs efficiency screening on each transportation route in the route set based on the cargo transportation cycle, and performs transportation route bias assessment on each transportation route based on the screening data. Based on the assessment results, it outputs the optimal transportation route for the cycle. The data output module outputs the corresponding cargo information and the optimal transportation route for the corresponding cycle, and provides real-time feedback on the periodic status data of the corresponding transportation transfer stations.

[0038] The product information processing module includes a product information retrieval unit and a product information processing unit;

[0039] The goods information retrieval unit obtains the current logistics status of each batch of goods by logging into the logistics information management port of the corresponding regional cloud platform; and retrieves information on goods in the pre-transport batch.

[0040] The goods information processing unit, based on the retrieved pre-transport batch goods information, coordinates the logistics information of each goods by planning the corresponding logistics data column to generate a logistics information form for each goods in the current batch, and constructs a logistics information matrix for each goods according to the logistics information form.

[0041] The logistics station status assessment module includes a logistics station acquisition unit and a logistics station periodic data assessment unit.

[0042] The logistics station acquisition unit obtains the transportation start and end points of each product based on the transportation location information of each product in the current batch; combined with the regional logistics transportation station distribution network, and using the logistics transportation start and end points of each product as constraints, it marks the transportation logistics transfer stations between two historical points and obtains the adjacent historical period status data of each marked logistics transfer station.

[0043] The logistics station periodic data evaluation unit evaluates the periodic status of each logistics transfer station based on the adjacent historical periodic status data of each labeled logistics transfer station; it also performs a comprehensive evaluation and analysis of the periodic operation status of each logistics transfer station based on the periodic backlog rate and transfer rate analysis data within each period; and it judges the current periodic operation status of each logistics transfer station by setting status comparison parameters based on the comprehensive evaluation data of the periodic operation status of each logistics transfer station within the period.

[0044] The comprehensive transportation route analysis module includes a transportation route planning unit and a comprehensive transportation route analysis unit.

[0045] The transportation route planning unit combines historical regional logistics transportation network data, using the current logistics transportation start and end points of each product as key retrieval data. It traverses historical transportation routes in the historical regional logistics transportation route network, and constructs a set of reference transportation routes for the corresponding current products. Based on the set of reference transportation routes, it performs period filtering on each reference transportation route in the set, using the current corresponding product's transportation cycle as the filtering condition. Finally, it analyzes the transportation time of each reference transportation route.

[0046] The comprehensive transportation route analysis unit filters each comparison transportation route based on the predicted transportation time analysis data of each comparison transportation route and the transportation cycle of the corresponding goods. It then obtains the retained comparison transportation routes for the corresponding goods based on the filtering operation and constructs a pre-transportation route set. Based on each comparison transportation route in the pre-transportation route set, it performs a transportation state bias analysis on each comparison transportation route by comprehensively considering the cycle status operation evaluation data of each logistics transfer station on each comparison transportation route, the route transportation time efficiency, and the location distribution of each station. Finally, based on the transportation state bias analysis data of each comparison transportation route in the pre-transportation route set, the comparison transportation route corresponding to the maximum value of the transportation state bias analysis is selected as the optimal cycle transportation route for the current corresponding goods.

[0047] The data output module includes a route output unit and a station status feedback unit;

[0048] The route output unit outputs the corresponding cargo information and the optimal transportation route for the corresponding period through the cloud platform display terminal, and performs transportation planning based on the route;

[0049] The site status feedback unit displays in real time the comprehensive evaluation data of the cycle operation status of each logistics transfer station in the optimal transportation route of the goods cycle.

[0050] Compared with the prior art, the beneficial effects of the present invention are:

[0051] This invention enables data monitoring of regional logistics networks through a cloud platform, and utilizes cloud computing to analyze and calculate data during the logistics transportation process to achieve intelligent planning of logistics transportation. This invention retrieves cargo information and, with constraints, retrieves information on regional logistics transfer stations, comprehensively analyzes the cyclical status of each transfer station, and generates regional transportation routes by traversing historical data. Routes are then filtered based on the cargo transportation cycle. Based on the filtering results, a comprehensive transportation status bias analysis is performed on the remaining routes, and the optimal transportation route for the corresponding cargo cycle is output based on the analysis data. This invention, by combining historical transportation experience data, utilizes a cloud platform to monitor the data status of all logistics stations throughout the process, and combines station status with effective route planning, improving the current situation of over-reliance on experience in transportation and enhancing the autonomous intelligence of the transportation supply chain. Attached Figure Description

[0052] Figure 1 This is a schematic diagram of the structure of a cloud-based digital logistics supply management system according to the present invention. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] Example: Figure 1 As shown, the present invention provides a technical solution:

[0055] A cloud-based digital management method for logistics supply chain, comprising the following steps:

[0056] S100. Obtain the logistics information of the current batch of goods through the cloud platform information port, construct the logistics information form of the corresponding batch of goods based on the retrieved goods logistics information, and construct the corresponding information matrix based on the information of each goods.

[0057] S200. Based on the logistics transportation location information in each cargo information matrix and the historical regional logistics transportation route network, obtain the logistics transfer stations in the corresponding regions; conduct periodic status assessments of each logistics transfer station, and classify each logistics transfer station into different levels based on the assessment results.

[0058] S300: Based on the historical transit station path generation records and combined with the current cargo information and logistics transportation location information, the current cargo transportation routes are traversed and generated, and a route set is constructed; based on the cargo transportation cycle, the efficiency of each transportation route in the route set is filtered, and the transportation route bias is evaluated for each transportation route based on the filtered data, and the optimal transportation route for the cycle is output based on the evaluation results.

[0059] S400 outputs the corresponding cargo information and the optimal transportation route for the corresponding period, and provides real-time feedback on the periodic status data of the corresponding transportation transfer station.

[0060] The specific steps of S100 in obtaining the logistics information of the current batch of goods through the cloud platform information port, constructing the corresponding logistics information form of the batch of goods based on the retrieved goods logistics information, and constructing the corresponding information matrix based on the information of each goods are as follows:

[0061] S101. Obtain the current logistics status of each batch of goods by logging into the logistics information management port of the corresponding regional cloud platform; retrieve information on goods in the pre-transport batch.

[0062] S102. Based on the retrieved pre-transport batch goods information, the logistics information of each goods is coordinated by planning the corresponding logistics data column to generate a logistics information form corresponding to the current batch of goods information, and the logistics information matrix of each goods is constructed according to the logistics information form.

[0063] The steps of S200, which combine logistics transportation location information in each cargo information matrix with historical regional logistics transportation route networks, to obtain logistics transfer stations in the corresponding regions; to conduct periodic status assessments of each logistics transfer station; and to classify each logistics transfer station into different levels based on the assessment results, are as follows:

[0064] S201. Based on the transportation location information of each item in the current batch, obtain the transportation start and end location information of each item; combined with the regional logistics transportation station distribution network, and using the logistics transportation start and end points of each item as constraints, mark the transportation logistics transfer stations between two historical points, and obtain the adjacent historical period status data of each marked logistics transfer station.

[0065] S202. Based on the labeled historical periodic status data of each logistics transfer station, perform periodic status evaluation on the adjacent historical periodic status data of each logistics transfer station. The calculation formula is as follows:

[0066]

[0067] Wherein, Dr(n) is the periodic backlog rate of the logistics transit station with label number n in the corresponding period; M(D,n) is the maximum backlog quantity of the logistics transit station with label number n in the corresponding period; M(n) is the maximum storage quantity of the logistics transit station with label number n; Er(n) is the periodic turnover rate of the logistics transit station with label number n in the corresponding period; M(E,n) is the total turnover of the logistics transit station with label number n in the corresponding period; and M(A,n) is the total storage of the logistics transit station with label number n in the corresponding period.

[0068] Based on the analysis data of the periodic delay rate and transfer rate of each logistics transit station, a comprehensive evaluation and analysis of the periodic operation status of each logistics transit station is conducted. The calculation formula is as follows:

[0069]

[0070] Wherein, Ov(n) is the comprehensive evaluation value of the periodic operation status of the logistics transit station with label number n within the corresponding period; ave[Dr(n)] and ave[Er(n)] correspond to the historical average backlog rate and transfer rate of the logistics transit station with label number n, respectively;

[0071] Based on the comprehensive evaluation data of the periodic operation status of each logistics transfer station within the cycle, the status comparison parameters Ov(α) and Ov(β) are set. If Ov(n) > Ov(β), the corresponding logistics transfer station is judged to be in good condition; if Ov(α) ≤ Ov(n) ≤ Ov(β), the corresponding logistics transfer station is judged to be in normal condition; if Ov(n) < Ov(α), the corresponding logistics transfer station is judged to be in congested condition.

[0072] The S300 generates current cargo transportation routes by combining historical transit station path records with current cargo information and logistics transportation location information, and constructs a route set. Based on the cargo transportation cycle, it performs efficiency filtering on each transportation route in the route set, evaluates the transportation route bias based on the filtered data, and outputs the optimal transportation route based on the evaluation results. The specific steps are as follows:

[0073] S301. Combining historical regional logistics and transportation network data, using the current logistics and transportation start and end points of each product as key retrieval data, traverse historical transportation routes in the historical regional logistics and transportation route network, and construct a set of reference transportation routes for the current corresponding products based on the traversed historical transportation routes.

[0074] Based on a set of reference transportation routes, and using the current corresponding cargo transportation cycle as a filtering criterion, each reference transportation route in the set is filtered by cycle; the transportation time of each reference transportation route is analyzed and calculated.

[0075]

[0076] Where t(i) is the predicted transportation time for the transportation route with label i; s(i) is the total distance of the transportation route with label i; ave(v) is the average speed of goods transportation based on historical data; L, C, and Y correspond to the periodic states of good, normal, and congested logistics transfer points, respectively; h(j,i) is the goods transfer time of the logistics transfer station with state j in the transportation route with label i; z(j,i) is the number of logistics transfer stations with state j in the transportation route with label i; where j takes the values ​​L, C, and Y.

[0077] S302. Based on the predicted transportation time analysis data of each comparison transportation route, and combined with the transportation cycle of the corresponding goods, each comparison transportation route is screened; if t(i) > T, it is determined that the current comparison transportation route does not meet the transportation requirements and is screened out; if t(i) ≤ T, the current comparison transportation route is retained; according to the screening operation, the retained comparison transportation routes for the corresponding goods are obtained, and a set of pre-transportation routes is constructed; where T is the transportation cycle time of the corresponding goods;

[0078] Based on the reference transportation routes in the pre-transportation route set for the corresponding goods, and comprehensively considering the periodic operational status evaluation data of each logistics transfer station on each reference transportation route, as well as the route transportation time efficiency and the location distribution of each station, a transportation status bias analysis is performed on each reference transportation route. The calculation formula is as follows:

[0079]

[0080] Where, Ts(p) is the transport state bias analysis value of the reference transport route labeled p in the corresponding pre-transport route set; t(p) is the predicted transport time of the reference transport route labeled p in the corresponding pre-transport route set; Ov(n,p) is the comprehensive evaluation value of the periodic operation status of the logistics transfer station labeled n on the reference transport route labeled p in the corresponding pre-transport route set; k(j,n,p) is the state parameter of state j corresponding to the logistics transfer station labeled n on the reference transport route labeled p in the corresponding pre-transport route set; Q[(x,y)] n →(x,y)0] and Q[(x,y) n →(x,y)1] represents the coordinates (x,y) respectively. n The coordinate distance between (x, y) and 0 and the coordinates (x, y) n The coordinate distance between (x, y)1 and the coordinates; where (x, y) nThe coordinates of the logistics transfer station labeled p in the pre-transport route set and labeled n on the corresponding transportation route are given; (x,y)0 and (x,y)1 correspond to the coordinates of the starting point and the ending point of the goods transportation, respectively.

[0081] Based on the transportation state bias analysis data of each reference transportation route in the pre-transportation route set, the reference transportation route corresponding to the maximum value of the transportation state bias analysis is taken as the optimal transportation route for the current corresponding goods in the cycle.

[0082] The specific steps of S400 in outputting the corresponding cargo information and the optimal transportation route for the corresponding period, and in real-time feedback of the periodic status data of the corresponding transportation transfer station are as follows:

[0083] S401. Output the corresponding product information and the optimal transportation route for the corresponding period through the cloud platform display terminal, and perform transportation planning based on the route;

[0084] S402. Real-time annotation and display of comprehensive evaluation data on the cyclical operation status of each logistics transfer station in the optimal transportation route for goods.

[0085] A cloud-based digital management system for logistics supply, the system comprising a goods information processing module, a logistics station status assessment module, a transportation route comprehensive analysis module, and a data output module;

[0086] The cargo information processing module obtains the current batch of cargo logistics information through the cloud platform information port, constructs a logistics information form for the corresponding batch of cargo based on the retrieved cargo logistics information, and constructs a corresponding information matrix based on the cargo information. The logistics station status assessment module obtains the logistics transfer stations in the corresponding region based on the logistics transportation location information in each cargo information matrix and the historical regional logistics transportation route network. It performs periodic status assessments on each logistics transfer station and classifies each logistics transfer station into different levels based on the assessment results. The transportation route comprehensive analysis module generates transportation routes for each cargo based on the historical regional transfer station path generation records and the current cargo information logistics transportation location information, and constructs a route set. It performs efficiency screening on each transportation route in the route set based on the cargo transportation cycle, and performs transportation route bias assessment on each transportation route based on the screening data. Based on the assessment results, it outputs the optimal transportation route for the cycle. The data output module outputs the corresponding cargo information and the optimal transportation route for the corresponding cycle, and provides real-time feedback on the periodic status data of the corresponding transportation transfer stations.

[0087] The product information processing module includes a product information retrieval unit and a product information processing unit;

[0088] The goods information retrieval unit obtains the current logistics status of each batch of goods by logging into the logistics information management port of the corresponding regional cloud platform; and retrieves information on goods in the pre-transport batch.

[0089] The goods information processing unit, based on the retrieved pre-transport batch goods information, coordinates the logistics information of each goods by planning the corresponding logistics data column to generate a logistics information form for each goods in the current batch, and constructs a logistics information matrix for each goods according to the logistics information form.

[0090] The logistics station status assessment module includes a logistics station acquisition unit and a logistics station periodic data assessment unit.

[0091] The logistics station acquisition unit obtains the transportation start and end points of each product based on the transportation location information of each product in the current batch; combined with the regional logistics transportation station distribution network, and using the logistics transportation start and end points of each product as constraints, it marks the transportation logistics transfer stations between two historical points and obtains the adjacent historical period status data of each marked logistics transfer station.

[0092] The logistics station periodic data evaluation unit evaluates the periodic status of each logistics transfer station based on the adjacent historical periodic status data of each labeled logistics transfer station; it also performs a comprehensive evaluation and analysis of the periodic operation status of each logistics transfer station based on the periodic backlog rate and transfer rate analysis data within each period; and it judges the current periodic operation status of each logistics transfer station by setting status comparison parameters based on the comprehensive evaluation data of the periodic operation status of each logistics transfer station within the period.

[0093] The comprehensive transportation route analysis module includes a transportation route planning unit and a comprehensive transportation route analysis unit.

[0094] The transportation route planning unit combines historical regional logistics transportation network data, using the current logistics transportation start and end points of each product as key retrieval data. It traverses historical transportation routes in the historical regional logistics transportation route network, and constructs a set of reference transportation routes for the corresponding current products. Based on the set of reference transportation routes, it performs period filtering on each reference transportation route in the set, using the current corresponding product's transportation cycle as the filtering condition. Finally, it analyzes the transportation time of each reference transportation route.

[0095] The comprehensive transportation route analysis unit filters each comparison transportation route based on the predicted transportation time analysis data of each comparison transportation route and the transportation cycle of the corresponding goods. It then obtains the retained comparison transportation routes for the corresponding goods based on the filtering operation and constructs a pre-transportation route set. Based on each comparison transportation route in the pre-transportation route set, it performs a transportation state bias analysis on each comparison transportation route by comprehensively considering the cycle status operation evaluation data of each logistics transfer station on each comparison transportation route, the route transportation time efficiency, and the location distribution of each station. Finally, based on the transportation state bias analysis data of each comparison transportation route in the pre-transportation route set, the comparison transportation route corresponding to the maximum value of the transportation state bias analysis is selected as the optimal cycle transportation route for the current corresponding goods.

[0096] The data output module includes a route output unit and a station status feedback unit;

[0097] The route output unit outputs the corresponding cargo information and the optimal transportation route for the corresponding period through the cloud platform display terminal, and performs transportation planning based on the route;

[0098] The site status feedback unit displays in real time the comprehensive evaluation data of the cycle operation status of each logistics transfer station in the optimal transportation route of the goods cycle.

[0099] In the embodiment:

[0100] A logistics and transportation company needs to monitor its logistics and transportation model. It adopts the cloud-based digital logistics supply management system of this invention. It obtains the current logistics status of each batch of goods by logging into the logistics information management port of the corresponding regional cloud platform; retrieves information on goods in the pre-transport batch; based on the retrieved pre-transport batch goods information, it coordinates the logistics information of each goods by planning the corresponding logistics data column to generate a logistics information form for each goods in the current batch, and constructs a logistics information matrix for each goods according to the logistics information form.

[0101] Based on the transportation location information of each item in the current batch, the starting and ending points of transportation for each item are obtained. Combining this with the regional logistics transportation station distribution network, and using the starting and ending points of each item's logistics transportation as constraints, historical logistics transfer stations between these two points are marked, and adjacent historical periodic status data for each marked transfer station is obtained. Based on the adjacent historical periodic status data of each marked transfer station, a periodic status evaluation is performed on the adjacent historical periodic status data of each transfer station, calculated using the following formula:

[0102]

[0103] Based on the analysis data of the periodic delay rate and transfer rate of each logistics transit station, a comprehensive evaluation and analysis of the periodic operation status of each logistics transit station is conducted. The calculation formula is as follows:

[0104]

[0105] Based on the comprehensive evaluation data of the periodic operation status of each logistics transfer station within the period, the status comparison parameters Ov(α) and Ov(β) are set. If Ov(n) > Ov(β), the corresponding logistics transfer station is judged to be in good condition; if Ov(α) ≤ Ov(n) ≤ Ov(β), the corresponding logistics transfer station is judged to be in normal condition; if Ov(n) < Ov(α), the corresponding logistics transfer station is judged to be in congested condition.

[0106] By combining historical regional logistics and transportation network data, and using the current logistics and transportation start and end points of each product as key data for retrieval, historical transportation routes are traversed in the historical regional logistics and transportation route network. The traversed historical transportation routes are used as the corresponding transportation routes for the current products, and a set of corresponding transportation routes is constructed.

[0107] Based on a set of reference transportation routes, and using the current corresponding cargo transportation cycle as a filtering criterion, each reference transportation route in the set is filtered by cycle; the transportation time of each reference transportation route is analyzed and calculated.

[0108]

[0109] Based on the predicted transportation time analysis data of each comparison transportation route, and combined with the transportation cycle of the corresponding goods, each comparison transportation route is screened; if t(i)>T, it is determined that the current comparison transportation route does not meet the transportation requirements and is screened out; if t(i)≤T, the current comparison transportation route is retained; the retained comparison transportation routes for the corresponding goods are obtained according to the screening operation, and a set of pre-transportation routes is constructed; where T is the transportation cycle time of the corresponding goods;

[0110] Based on the reference transportation routes in the pre-transportation route set for the corresponding goods, and comprehensively considering the periodic operational status evaluation data of each logistics transfer station on each reference transportation route, as well as the route transportation time efficiency and the location distribution of each station, a transportation status bias analysis is performed on each reference transportation route. The calculation formula is as follows:

[0111]

[0112] Based on the transportation status bias analysis data of each reference transportation route in the pre-transportation route set, the reference transportation route corresponding to the maximum value of the transportation status bias analysis is taken as the current cycle-optimal transportation route for the corresponding goods; the corresponding goods information and the corresponding cycle-optimal transportation route are output through the cloud platform display terminal, and transportation planning is carried out according to the route; the cycle operation status comprehensive evaluation data of each logistics transfer station in the cycle-optimal transportation route of the goods are marked and displayed in real time.

[0113] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A cloud-based digital management method for logistics supply, characterized in that: The method includes the following steps: S100. Obtain the logistics information of the current batch of goods through the cloud platform information port, construct the logistics information form of the corresponding batch of goods based on the retrieved goods logistics information, and construct the corresponding information matrix based on the information of each goods. S200. Based on the logistics transportation location information in each cargo information matrix and the historical regional logistics transportation route network, obtain the logistics transfer stations in the corresponding regions; conduct periodic status assessments of each logistics transfer station, and classify each logistics transfer station into different levels based on the assessment results. S300: Based on the historical transit station path generation records and combined with the current cargo information and logistics transportation location information, the current cargo transportation routes are traversed and generated, and a route set is constructed; based on the cargo transportation cycle, the efficiency of each transportation route in the route set is filtered, and the transportation route bias is evaluated for each transportation route based on the filtered data, and the optimal transportation route for the cycle is output based on the evaluation results. S400 outputs the corresponding cargo information and the optimal transportation route for the corresponding period, and provides real-time feedback on the periodic status data of the corresponding transportation transfer station. The S300 generates current cargo transportation routes by combining historical transit station path records with current cargo information and logistics transportation location information, and constructs a route set. Based on the cargo transportation cycle, it performs efficiency filtering on each transportation route in the route set, evaluates the transportation route bias based on the filtered data, and outputs the optimal transportation route based on the evaluation results. The specific steps are as follows: S301. Combining historical regional logistics and transportation network data, using the current logistics and transportation start and end points of each product as key retrieval data, traverse historical transportation routes in the historical regional logistics and transportation route network, and construct a set of reference transportation routes for the current corresponding products based on the traversed historical transportation routes. Based on a set of reference transportation routes, and using the current corresponding cargo transportation cycle as a filtering criterion, each reference transportation route in the set is filtered by cycle; the transportation time of each reference transportation route is analyzed and calculated. ； Where t(i) is the predicted transportation time for the transportation route with label i; s(i) is the total distance of the transportation route with label i; ave(v) is the average speed of goods transportation based on historical data; L, C, and Y correspond to the periodic states of good, normal, and congested logistics transfer points, respectively; h(j,i) is the goods transfer time of the logistics transfer station with state j in the transportation route with label i; z(j,i) is the number of logistics transfer stations with state j in the transportation route with label i; where j takes the values ​​L, C, and Y. S302. Based on the predicted transportation time analysis data of each comparison transportation route, and combined with the transportation cycle of the corresponding goods, each comparison transportation route is screened; if t(i) > T, it is determined that the current comparison transportation route does not meet the transportation requirements and is screened out; if t(i) ≤ T, the current comparison transportation route is retained; according to the screening operation, the retained comparison transportation routes for the corresponding goods are obtained, and a set of pre-transportation routes is constructed; where T is the transportation cycle time of the corresponding goods; Based on the reference transportation routes in the pre-transportation route set for the corresponding goods, and comprehensively considering the periodic operational status evaluation data of each logistics transfer station on each reference transportation route, as well as the route transportation time efficiency and the location distribution of each station, a transportation status bias analysis is performed on each reference transportation route. The calculation formula is as follows: ； Where, Ts(p) is the transport state bias analysis value of the reference transport route labeled p in the corresponding pre-transport route set; t(p) is the predicted transport time of the reference transport route labeled p in the corresponding pre-transport route set; Ov(n,p) is the comprehensive evaluation value of the periodic operation status of the logistics transfer station labeled n on the reference transport route labeled p in the corresponding pre-transport route set; k(j,n,p) is the state parameter of state j corresponding to the logistics transfer station labeled n on the reference transport route labeled p in the corresponding pre-transport route set; Q[(x,y)] n →(x,y)0] and Q[(x,y) n →(x,y)1] represents the coordinates (x,y) respectively. n The coordinate distance between (x, y) and 0 and the coordinates (x, y) n The coordinate distance between (x, y)1 and the coordinates; where (x, y) n The coordinates of the logistics transfer station labeled p in the pre-transport route set and labeled n on the corresponding transportation route are given; (x,y)0 and (x,y)1 correspond to the coordinates of the starting point and the ending point of the goods transportation, respectively. Based on the transportation state bias analysis data of each reference transportation route in the pre-transportation route set, the reference transportation route corresponding to the maximum value of the transportation state bias analysis is taken as the optimal transportation route for the current corresponding goods in the cycle.

2. The cloud-based digital management method for logistics supply as described in claim 1, characterized in that: The specific steps of S100 in obtaining the logistics information of the current batch of goods through the cloud platform information port, constructing the corresponding logistics information form of the batch of goods based on the retrieved goods logistics information, and constructing the corresponding information matrix based on the information of each goods are as follows: S101. Obtain the current logistics status of each batch of goods by logging into the logistics information management port of the corresponding regional cloud platform; retrieve information on goods in the pre-transport batch. S102. Based on the retrieved pre-transport batch goods information, the logistics information of each goods is coordinated by planning the corresponding logistics data column to generate a logistics information form corresponding to the current batch of goods information, and the logistics information matrix of each goods is constructed according to the logistics information form.

3. The cloud-based digital management method for logistics supply as described in claim 2, characterized in that: The steps of S200, which combine logistics transportation location information in each cargo information matrix with historical regional logistics transportation route networks, to obtain logistics transfer stations in the corresponding regions; to conduct periodic status assessments of each logistics transfer station; and to classify each logistics transfer station into different levels based on the assessment results, are as follows: S201. Based on the transportation location information of each item in the current batch, obtain the transportation start and end location information of each item; combined with the regional logistics transportation station distribution network, and using the logistics transportation start and end points of each item as constraints, mark the transportation logistics transfer stations between two historical points, and obtain the adjacent historical period status data of each marked logistics transfer station. S202. Based on the labeled historical periodic status data of each logistics transfer station, perform periodic status evaluation on the adjacent historical periodic status data of each logistics transfer station. The calculation formula is as follows: ； ； Wherein, Dr(n) is the periodic backlog rate of the logistics transit station with label number n in the corresponding period; M(D,n) is the maximum backlog quantity of the logistics transit station with label number n in the corresponding period; M(n) is the maximum storage quantity of the logistics transit station with label number n; Er(n) is the periodic turnover rate of the logistics transit station with label number n in the corresponding period; M(E,n) is the total turnover of the logistics transit station with label number n in the corresponding period; and M(A,n) is the total storage of the logistics transit station with label number n in the corresponding period. Based on the analysis data of the periodic delay rate and transfer rate of each logistics transit station, a comprehensive evaluation and analysis of the periodic operation status of each logistics transit station is conducted. The calculation formula is as follows: ； Wherein, Ov(n) is the comprehensive evaluation value of the periodic operation status of the logistics transit station with label number n within the corresponding period; ave[Dr(n)] and ave[Er(n)] correspond to the historical average backlog rate and transfer rate of the logistics transit station with label number n, respectively; Based on the comprehensive evaluation data of the periodic operation status of each logistics transfer station within the cycle, the status comparison parameters Ov(α) and Ov(β) are set. If Ov(n) > Ov(β), the corresponding logistics transfer station is judged to be in good condition; if Ov(α) ≤ Ov(n) ≤ Ov(β), the corresponding logistics transfer station is judged to be in normal condition; if Ov(n) < Ov(α), the corresponding logistics transfer station is judged to be in congested condition.

4. The cloud-based digital management method for logistics supply as described in claim 3, characterized in that: The specific steps of S400 in outputting the corresponding cargo information and the optimal transportation route for the corresponding period, and in real-time feedback of the periodic status data of the corresponding transportation transfer station are as follows: S401. Output the corresponding product information and the optimal transportation route for the corresponding period through the cloud platform display terminal, and perform transportation planning based on the route; S402. Real-time annotation and display of comprehensive evaluation data on the cyclical operation status of each logistics transfer station in the optimal transportation route for goods.

5. A cloud-based digital logistics supply management system, used to implement the cloud-based digital logistics supply management method as described in claim 1, characterized in that: The system includes a cargo information processing module, a logistics station status assessment module, a transportation route comprehensive analysis module, and a data output module. The goods information processing module obtains the current batch of goods logistics information through the cloud platform information port, constructs a logistics information form for the corresponding batch of goods based on the retrieved goods logistics information, and constructs a corresponding information matrix based on the information of each goods; the logistics station status assessment module obtains the logistics transfer stations in the corresponding area based on the logistics transportation location information in each goods information matrix and the historical regional logistics transportation route network; performs periodic status assessments on each logistics transfer station, and classifies each logistics transfer station into different levels according to the assessment results; The comprehensive transportation route analysis module generates transportation routes for each commodity by combining historical transit station path records with current logistics transportation location information, and constructs a route set. Based on the commodity transportation cycle, it performs efficiency filtering on each transportation route in the route set, and evaluates the transportation route bias based on the filtered data. Based on the evaluation results, it outputs the optimal transportation route for the cycle. The data output module outputs the corresponding commodity information and the optimal transportation route for the corresponding cycle, and provides real-time feedback on the cycle status data of the corresponding transit stations.

6. The cloud-based digital logistics supply management system according to claim 5, characterized in that: The product information processing module includes a product information retrieval unit and a product information processing unit; The goods information retrieval unit obtains the current logistics status of each batch of goods by logging into the logistics information management port of the corresponding regional cloud platform; and retrieves information on goods in the pre-transport batch. The goods information processing unit, based on the retrieved pre-transport batch goods information, coordinates the logistics information of each goods by planning the corresponding logistics data column to generate a logistics information form for each goods in the current batch, and constructs a logistics information matrix for each goods according to the logistics information form.

7. The cloud-based digital logistics supply management system according to claim 6, characterized in that: The logistics station status assessment module includes a logistics station acquisition unit and a logistics station periodic data assessment unit. The logistics station acquisition unit obtains the transportation start and end points of each product based on the transportation location information of each product in the current batch; combined with the regional logistics transportation station distribution network, and using the logistics transportation start and end points of each product as constraints, it marks the transportation logistics transfer stations between two historical points and obtains the adjacent historical period status data of each marked logistics transfer station. The logistics station periodic data evaluation unit evaluates the periodic status of each logistics transfer station based on the labeled adjacent historical periodic status data of each logistics transfer station. Based on the analysis data of the periodic delay rate and transfer rate of each logistics transit station within the cycle, a comprehensive evaluation and analysis of the periodic operation status of each logistics transit station is carried out; based on the comprehensive evaluation data of the periodic operation status of each logistics transit station within the cycle, the current periodic operation status of each logistics transit station is judged by setting status comparison parameters.

8. The cloud-based digital logistics supply management system according to claim 7, characterized in that: The comprehensive transportation route analysis module includes a transportation route planning unit and a comprehensive transportation route analysis unit. The transportation route planning unit combines historical regional logistics transportation network data, uses the current logistics transportation start and end positions of each product as key retrieval data, traverses historical transportation routes in the historical regional logistics transportation route network, and constructs a set of reference transportation routes for the current corresponding products by using the traversed historical transportation routes as reference transportation routes. Based on the set of reference transportation routes, the current corresponding cargo transportation cycle is used as the filtering condition to perform cycle filtering on each reference transportation route in the set. The transit time for each comparison route was analyzed separately; The comprehensive transportation route analysis unit filters each comparison transportation route based on the predicted transportation time analysis data of each comparison transportation route and the transportation cycle of the corresponding goods. It then obtains the retained comparison transportation routes for the corresponding goods based on the filtering operation and constructs a pre-transportation route set. Based on each comparison transportation route in the pre-transportation route set, it performs a transportation state bias analysis on each comparison transportation route by comprehensively considering the cycle status operation evaluation data of each logistics transfer station on each comparison transportation route, the route transportation time efficiency, and the location distribution of each station. Finally, based on the transportation state bias analysis data of each comparison transportation route in the pre-transportation route set, the comparison transportation route corresponding to the maximum value of the transportation state bias analysis is selected as the optimal cycle transportation route for the current corresponding goods.

9. A cloud-based digital logistics supply management system according to claim 8, characterized in that: The data output module includes a route output unit and a station status feedback unit; The route output unit outputs the corresponding cargo information and the optimal transportation route for the corresponding period through the cloud platform display terminal, and performs transportation planning based on the route; The site status feedback unit displays in real time the comprehensive evaluation data of the cycle operation status of each logistics transfer station in the optimal transportation route of the goods cycle.

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