An RFID-based high-efficiency intelligent supply chain system and method

Abstract

The present invention relates to the technical field of supply chain management, and specifically to a high-efficiency intelligent supply chain system and method based on RFID. The present invention includes: a goods label allocation unit for obtaining the importance of goods according to the sales price, supply quantity, and vulnerability of the goods, and allocating RFID tags according to the importance; a goods information matching unit for obtaining the goods information matching degree according to the information matching values calculated under different transportation states; combining the goods information matching degree with the goods information matching threshold to obtain the goods information matching result; a goods transportation monitoring unit for managing the abnormal state of RFID tags and the goods state during transportation according to the RFID tag abnormal value and the transportation state monitoring value; a goods transportation route optimization unit for combining the importance, the historical goods information matching degree and the historical transportation state monitoring value of the transportation routes between supply chain nodes, and using a multi-objective goods transportation route optimization model to obtain the optimal transportation route.

Description

Technical Field

[0001] The present invention relates to the technical field of supply chain management, and particularly to a high-efficiency intelligent supply chain system and method based on RFID. Background Art

[0002] Compared with traditional supply chain systems, supply chain systems based on RFID have significantly improved the efficiency and reliability of supply chain management by virtue of advantages such as automatic identification and tracking, high transparency, less manual intervention, optimized inventory management, and high logistics efficiency. These advantages have made RFID technology an important tool in modern supply chain management.

[0003] Currently, the existing technology still has deficiencies in the security management of goods information and the abnormal management of RFID during transportation in supply chain systems based on RFID; on the one hand, the existing technology does not perform security management of goods information according to different logistics states; on the other hand, the existing technology only considers the sudden abnormal problems during the transportation of goods, but does not consider the abnormal problems of RFID tags during transportation, which makes it impossible to obtain the transportation status of goods in real time, thereby reducing the efficiency and reliability of the supply chain system.

[0004] Therefore, a high-efficiency intelligent supply chain system and method based on RFID are proposed. Summary of the Invention

[0005] The purpose of the present invention is to provide a high-efficiency intelligent supply chain system and method based on RFID. Specifically, it includes: a goods label allocation unit for obtaining the importance of goods according to the selling price, supply quantity, and vulnerability of the goods, and allocating RFID tags according to the importance; a goods information matching unit for obtaining the goods information matching degree according to the information matching value calculated under different transportation states; combining the goods information matching degree with the goods information matching threshold to obtain the goods information matching result; a goods transportation monitoring unit for managing the abnormal state of RFID tags and the goods state during transportation according to the RFID tag abnormal value and the transportation state monitoring value; a goods transportation route optimization unit for combining the importance, the historical goods information matching degree between supply chain nodes, and the historical transportation state monitoring value, and using a multi-objective goods transportation route optimization model to obtain the optimal transportation route.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A high-efficiency intelligent supply chain system based on RFID, comprising:

[0008] A goods label allocation unit for allocating corresponding RFID tags to goods; obtaining the importance of goods according to the selling price, supply quantity, and vulnerability of the goods, and allocating RFID tags according to the importance;

[0009] A goods information matching unit, which is used to match and proofread the information of goods; specifically: combining the first information matching value of the current supply chain node, the second information matching value at fixed intervals during the transportation process, and the third information matching value between the current supply chain node and the next node to obtain the goods information matching degree; combining the goods information matching degree and the goods information matching threshold to obtain the goods information matching result;

[0010] A goods transportation monitoring unit, which is used to manage the abnormal status of RFID tags and the status of goods during transportation; obtaining the RFID tag abnormal value according to the reading status, reading delay time and reading information comparison situation of the RFID reader; obtaining the transportation status monitoring value according to the comparison result between the RFID tag abnormal value and the tag abnormal threshold; obtaining the goods status information according to the transportation status monitoring value;

[0011] A goods transportation route optimization unit, which is used to optimize the transportation route of goods; combining the importance, the historical goods information matching degree and the historical transportation status monitoring value of the transportation route between supply chain nodes, and using a multi-objective goods transportation route optimization model to optimize the current transportation route to obtain the optimal transportation route.

[0012] Further, the specific process of the goods label allocation unit allocating RFID tags according to the importance of the goods includes:

[0013] Obtaining the vulnerability of the goods according to the proportion of the damaged quantity in the goods transportation quantity;

[0014] Evaluating the sales price, supply quantity and vulnerability of the goods to obtain the importance of the goods;

[0015] Combining the importance of the goods, and allocating corresponding RFID tags to the goods based on frequency selection, capacity selection and security selection.

[0016] Further, the process of the goods information matching unit obtaining the goods information matching result includes:

[0017] Obtaining the first information matching value according to the goods information at the input end and the output end in the current supply chain node;

[0018] Obtaining the second information matching value according to the goods information at fixed intervals during the transportation process and the goods information before transportation;

[0019] Obtaining the third information matching value according to the goods information at the output end of the current supply chain node and the input end of the next node;

[0020] Combine the first information matching value, the second information matching value, and the third information matching value; obtain the goods information matching degree; the calculation formula for the goods information matching degree is:

[0021] ;

[0022] where, is the goods information matching degree; is the first information matching weight value; is the first information matching value; is the second information matching weight value; is the second information matching value; is the third information matching weight value; is the third information matching value;

[0023] Compare the goods information matching degree with the goods information matching threshold to obtain the goods information matching result.

[0024] Further, the implementation process for the goods transportation monitoring unit to obtain the transportation status monitoring value includes:

[0025] Obtain the reading status, the reading delay time, and the reading information of the RFID reader during the goods transportation process;

[0026] According to the reading status, the reading position information and the reading goods information in the reading information, respectively obtain the reading status weight, the position information matching value, and the second information matching value;

[0027] Evaluate the reading status weight, the position information matching value, and the second information matching value to obtain the RFID tag anomaly value; the calculation formula for the RFID tag anomaly value is:

[0028] ;

[0029] where, is the RFID tag anomaly value; is the reading status weight; is the exponential function; is the reading delay time weight value; is the reading delay time threshold; is the reading delay time; is the position information matching weight value; is the position information matching value; is the goods information matching weight value; is the second information matching value;

[0030] Compare the RFID tag outlier with the tag outlier threshold. If it does not exceed the tag outlier threshold, perform feature matching on the location cargo data during transportation and the cargo data before transportation to obtain a transportation status monitoring value; otherwise, obtain the transportation status monitoring value based on the RFID tag outlier and feedback an outlier message.

[0031] Further, the process by which the cargo transportation route optimization unit obtains the optimal transportation route using the multi-objective cargo transportation route optimization model includes:

[0032] Obtain the importance of the cargo, the historical cargo information matching degree of the transportation route, and the historical transportation status monitoring value;

[0033] Construct the multi-objective cargo transportation route optimization model, with minimizing transportation cost and minimizing transportation time as optimization objectives, and combine the importance, the historical cargo information matching degree, and the historical transportation status monitoring value to obtain the comprehensive objective function of the multi-objective cargo transportation route optimization model;

[0034] The comprehensive objective function is expressed as:

[0035] ;

[0036] Where, is the comprehensive objective function; is the minimization operation; is the comprehensive objective function expression; is the importance of cargo g; is the historical cargo information matching degree of cargo g from node i to node j; is the historical transportation status monitoring value of cargo g from node i to node j; is the transportation cost from node i to node j; is the transportation time from node i to node j;

[0037] Solve the optimal transportation route according to the comprehensive objective function.

[0038] A high-efficiency intelligent supply chain method based on RFID includes:

[0039] Obtain the selling price, supply volume, and vulnerability of the cargo, and combine the importance calculation formula to obtain the importance of the cargo; allocate different RFID tags to the cargo according to the importance;

[0040] Based on the first information matching value of the current supply chain node, the second information matching value calculated at fixed intervals during transportation, and the third information matching value between the current supply chain node and the next node, the goods information matching degree is obtained; combining the goods information matching degree and the goods information matching threshold, the goods information matching result is obtained;

[0041] Based on the reading status of the RFID reader, the reading delay time, and the comparison of the read information, the RFID tag outlier is obtained; according to the comparison result between the RFID tag outlier and the tag outlier threshold, the transportation status monitoring value is obtained; according to the transportation status monitoring value, the goods status information is obtained;

[0042] Combining the importance, the historical goods information matching degree and the historical transportation status monitoring value of the transportation route between supply chain nodes, the current transportation route is optimized using a multi-objective goods transportation path optimization model to obtain the optimal transportation path.

[0043] Furthermore, the specific process of obtaining the goods information matching result by combining the goods information matching degree and the goods information matching threshold includes:

[0044] Based on the goods information of the input end and the output end in the current supply chain node, the first information matching value is obtained;

[0045] Based on the goods information at fixed intervals during transportation and the goods information before transportation, the second information matching value is obtained;

[0046] Based on the goods information of the output end of the current supply chain node and the input end of the next node, the third information matching value is obtained;

[0047] Combining the first information matching value, the second information matching value, and the third information matching value; the goods information matching degree is obtained; the calculation formula for the goods information matching degree is:

[0048] ;

[0049] where, is the goods information matching degree; is the first information matching weight value; is the first information matching value; is the second information matching weight value; is the second information matching value; is the third information matching weight value; is the third information matching value;

[0050] The goods information matching degree is compared with the goods information matching threshold to obtain the goods information matching result.

[0051] Further, according to the reading status of the RFID reader, the reading delay time, and the comparison of the read information, an RFID tag outlier is obtained; the process of obtaining the transportation status monitoring value according to the comparison result between the RFID tag outlier and the tag outlier threshold includes:

[0052] Obtain the reading status, the reading delay time, and the read information of the RFID reader during the transportation of the goods;

[0053] According to the reading status, the reading position information and the read cargo information in the read information, obtain the reading status weight, the position information matching value, and the second information matching value respectively;

[0054] Evaluate the reading status weight, the position information matching value, and the second information matching value to obtain the RFID tag outlier; the calculation formula of the RFID tag outlier is:

[0055] ;

[0056] Wherein, is the RFID tag outlier; is the reading status weight; is the exponential function; is the reading delay time weight value; is the reading delay time threshold; is the reading delay time; is the position information matching weight value; is the position information matching value; is the cargo information matching weight value; is the second information matching value;

[0057] Compare the RFID tag outlier with the tag outlier threshold. If it does not exceed the tag outlier threshold, perform feature matching on the located cargo data during transportation and the cargo data before transportation to obtain the transportation status monitoring value; otherwise, obtain the transportation status monitoring value according to the RFID tag outlier and feedback the abnormal information.

[0058] Further, the implementation process of obtaining the optimal transportation path by using the multi-objective cargo transportation path optimization model includes:

[0059] Obtain the importance of the goods, the historical cargo information matching degree of the transportation route, and the historical transportation status monitoring value;

[0060] Construct the multi-objective cargo transportation route optimization model, with minimizing transportation cost and minimizing transportation time as the optimization objectives, and combine the importance, the historical cargo information matching degree, and the historical transportation status monitoring value to obtain the comprehensive objective function of the multi-objective cargo transportation route optimization model; the comprehensive objective function is expressed as:

[0061] ;

[0062] where, is the comprehensive objective function; is the minimization operation; is the expression of the comprehensive objective function; is the importance of cargo g; is the historical cargo information matching degree of cargo g from node i to node j; is the historical transportation status monitoring value of cargo g from node i to node j; is the transportation cost from node i to node j; is the transportation time from node i to node j;

[0063] Solve to obtain the optimal transportation route according to the comprehensive objective function.

[0064] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0065] 1. The present invention proposes a cargo information matching function to ensure the information security of cargo under different logistics states; this function divides the cargo information matching into three stages: before transportation, during transportation, and after transportation; through the collection and comparison of cargo information in different stages, the first information matching value, the second information matching value, and the third information matching value are obtained; the information matching values of the three different stages are weighted and summed to obtain the cargo information matching value; this function can comprehensively measure the information integrity of the cargo under the logistics state by using the cargo information matching value, thereby improving the efficiency and reliability of the supply chain system.

[0066] 2. The present invention proposes a transportation status monitoring function to monitor the abnormal conditions of RFID tags and cargo status; this function first collects the reading status, reading delay time, and reading information of the RFID reader, compares the evaluated RFID tag abnormal value with the tag abnormal threshold, and performs feature matching on the cargo data during transportation and the cargo data before transportation according to the comparison result to obtain the transportation status monitoring value; this function can take into account both the RFID tag status monitoring and the cargo status monitoring, effectively solve the screening of the reasons for cargo status abnormalities, and effectively improve the efficiency and reliability of the supply chain system.

[0067] 3. The present invention proposes a multi-objective cargo transportation route optimization model to obtain the optimal transportation route. This model combines the importance of the cargo, the cargo information matching value of the transportation route, and the transportation status monitoring value, and takes the transportation cost and transportation time as optimization objectives to obtain the optimal solution, thereby determining the optimal transportation route. This model considers various factors such as the importance of the cargo, cargo information security, and cargo transportation status, and comprehensively selects the transportation route, thereby improving the efficiency and reliability of the supply chain system. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 is a schematic structural diagram of a high-efficiency intelligent supply chain system based on RFID according to the present invention;

[0069] Figure 2 is a schematic diagram of the acquisition process of the transportation status monitoring value of the present invention;

[0070] Figure 3 is a schematic flowchart of a high-efficiency intelligent supply chain method based on RFID according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0071] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0072] Next, a high-efficiency intelligent supply chain system and method based on RFID proposed by the present invention will be specifically described in conjunction with Embodiment 1 and Embodiment 2.

[0073] Embodiment 1

[0074] In order to improve the efficiency and intelligence of the clothing supply chain, and be able to timely feedback abnormal situations during transportation and intelligently optimize the transportation route, a certain clothing brand manufacturer introduced a high-efficiency intelligent supply chain system based on RFID proposed by the present invention. The structure of this system is as Figure 1 shown, and the specific implementation process is as follows:

[0075] The cargo label distribution unit is used to assign corresponding RFID tags to the cargo; according to the sales price, supply volume, and vulnerability of the cargo, the importance of the cargo is obtained, and RFID tags are assigned according to the importance.

[0076] Further, the specific process of the cargo label distribution unit assigning RFID tags according to the importance of the cargo includes:

[0077] The vulnerability of the goods is obtained based on the proportion of the damaged quantity in the total quantity of goods transported.

[0078] The importance of the goods is obtained by evaluating the selling price, supply quantity, and vulnerability of the goods.

[0079] Furthermore, the parameters related to the vulnerability of the goods need to be retrieved from the historical transportation data of the same type of goods.

[0080] Furthermore, the calculation formula for the importance of the goods is:

[0081] ;

[0082] Where is the importance of the goods, and the larger this value is, the higher the importance of the goods; is the arctangent function; is the selling price weight factor; is the selling price; is the standard value of the selling price; is the supply quantity weight factor; is the supply quantity; is the standard value of the supply quantity; is the vulnerability weight factor; is the damaged quantity; is the total quantity of goods transported;

[0083] Furthermore, the selling price weight factor, supply quantity weight factor, and vulnerability weight factor are set to 0.35, 0.3, and 0.35 respectively; the setting of the standard value of the selling price and the standard value of the supply quantity is related to factors such as the type of goods and production specifications, and needs to be adjusted according to the actual situation.

[0084] Combined with the importance of the goods, corresponding RFID tags are assigned to the goods based on frequency selection, capacity selection, and security selection.

[0085] In this embodiment, by comprehensively evaluating the selling price, supply quantity, and vulnerability of the goods, the importance of the goods is obtained; and corresponding RFID tags are assigned to the goods according to the importance of the goods, so as to effectively classify and manage the goods, thereby improving the efficiency and reliability of supply chain management.

[0086] The goods information matching unit is used to match and proofread the information of the goods; specifically: combining the first information matching value of the current supply chain node, the second information matching value at fixed intervals during transportation, and the third information matching value between the current supply chain node and the next node, the goods information matching degree is obtained; combining the goods information matching degree with the goods information matching threshold, the goods information matching result is obtained.

[0087] Further, the process by which the goods information matching unit obtains the goods information matching result includes:

[0088] Obtaining a first information matching value according to the goods information at the input end and the output end in the current supply chain node;

[0089] Obtaining a second information matching value according to the goods information at fixed intervals during the transportation process and the goods information before transportation;

[0090] Obtaining a third information matching value according to the goods information at the output end of the current supply chain node and the input end of the next node;

[0091] Combining the first information matching value, the second information matching value, and the third information matching value; obtaining the goods information matching degree; the calculation formula for the goods information matching degree is:

[0092] ;

[0093] Wherein, is the goods information matching degree; is the first information matching weight value; is the first information matching value; is the second information matching weight value; is the second information matching value; is the third information matching weight value; is the third information matching value;

[0094] Further, the goods information in the supply chain node and during the transportation process is obtained by reading and parsing RFID tag data; the first information matching weight value, the second information matching weight value, and the third information matching weight value are respectively set to 0.35, 0.3, and 0.35; the fixed time can be flexibly set according to the actual situation;

[0095] Further, the first information matching value, the second information matching value, and the third information matching value can be expressed as:

[0096] ;

[0097] Wherein, , and are respectively the first information matching value, the second information matching value, and the third information matching value; is the matching quantity; is the minimum value of the data quantity in the goods information; is the intersection operation; N is the number of times of collecting the goods information during the transportation process; and are respectively the goods information at the input end and the output end in the current supply chain node; and The \(i\)-th piece of goods information collected during transportation and the goods information before transportation, respectively; The goods information at the input end of the next node;

[0098] Compare the goods information matching degree with the goods information matching threshold to obtain the goods information matching result.

[0099] To illustrate the goods information matching strategy proposed by the present invention, three different goods are randomly selected for goods information matching tests, which are respectively recorded as Test One, Test Two and Test Three; the goods information before, during and after transportation of each kind of goods is collected respectively, wherein the number of times of collecting the goods information during transportation is set to 20; combined with the calculation formulas of the first information matching value, the second information matching value, the third information matching value and the goods information matching degree, the goods information matching degree of each good is obtained; meanwhile, the goods information matching threshold is set to 0.9, and the goods information matching test results are shown in Table 1.

[0100] Table 1. Goods Information Matching Test Results

[0101]

[0102] By collecting and comparing the goods information in different transportation stages, the first information matching value, the second information matching value and the third information matching value are obtained; the information matching values in three different stages are weighted and summed to obtain the goods information matching value; the goods information matching value can comprehensively measure the information integrity in the goods logistics state, thereby improving the efficiency and reliability of the supply chain system.

[0103] The goods transportation monitoring unit is used to manage the abnormal state of RFID tags and the goods state during transportation; according to the reading state, reading delay time and reading information comparison situation of the RFID reader, the RFID tag abnormal value is obtained; according to the comparison result between the RFID tag abnormal value and the tag abnormal threshold, the transportation state monitoring value is obtained; according to the transportation state monitoring value, the goods state information is obtained;

[0104] Further, the acquisition process of the transportation state monitoring value can refer to Figure 2 , and the specific process is as follows:

[0105] Obtain the reading state, reading delay time and reading information of the RFID reader during the goods transportation process;

[0106] According to the reading state, the reading position information and the reading goods information in the reading information, the reading state weight, the position information matching value and the second information matching value are respectively obtained; the reading state weight and the position information matching value can be expressed as:

[0107] ;

[0108] Among them, is the read status weight; is the position information matching value; is the read position vector; is the actual position vector, and this position information is obtained through the GPS on the truck; represents the inner product of vectors;

[0109] Evaluate the read status weight, read delay time, position information matching value and second information matching value to obtain the RFID tag outlier value; the calculation formula of the RFID tag outlier value is:

[0110] ;

[0111] Among them, is the RFID tag outlier value; is the exponential function; is the read status weight; is the read delay time weight value; is the read delay time threshold; is the read delay time; is the position information matching weight value; is the position information matching value; is the cargo information matching weight value; is the second information matching value;

[0112] Furthermore, the read delay time weight value, position information matching weight value and cargo information matching weight value are set to 0.35, 0.3 and 0.35 respectively; the setting of the read delay time threshold is related to the RFID tag type and usage duration, and needs to be adjusted according to the actual situation;

[0113] Compare the RFID tag outlier value with the tag outlier threshold. If it does not exceed the tag outlier threshold, perform feature matching on the located cargo data during transportation and the cargo data before transportation to obtain the transportation status monitoring value; otherwise, obtain the transportation status monitoring value according to the RFID tag outlier value and feedback the abnormal information.

[0114] Furthermore, when the RFID tag outlier value does not exceed the tag outlier threshold, locate the cargo data to be matched through the RFID tag, and then input both the located cargo data and the cargo data before transportation into the pre-trained VGG19 model to obtain their respective features and calculate the transportation status monitoring value; the transportation status monitoring value can be expressed as:

[0115] ;

[0116] Among them, is the monitoring value of the transportation status; M is the number of characteristic samples; is the L2 norm; is the characteristic of the goods in transit of the j-th sample; is the characteristic of the goods before transportation of the j-th sample;

[0117] Further, when the RFID tag outlier exceeds the tag outlier threshold, the complement of the RFID tag outlier with respect to 1 is used as the monitoring value of the transportation status;

[0118] Further, the monitoring value of the transportation status is compared with the transportation status monitoring threshold to obtain the transportation status monitoring result; the transportation status monitoring threshold is set to 0.7.

[0119] To illustrate the effectiveness of the transportation status monitoring proposed by the present invention, 3 different goods during transportation are randomly selected for transportation status monitoring, and the goods are on different trucks, denoted as test sample one, test sample two, and test sample three; the reading status, reading delay time, and reading information of the RFID reader under different samples are collected, and combined with the calculation formula of the RFID tag outlier, the RFID tag outlier of each sample is obtained; the tag outlier threshold is set to 0.68, and according to the comparison result between the RFID tag outlier and the tag outlier threshold, the monitoring value of the transportation status of each is obtained; the transportation status monitoring test results are shown in Table 2.

[0120] Table 2. Transportation Status Monitoring Test Results

[0121]

[0122] In this embodiment, by comparing the RFID tag outlier evaluated from the reading status, reading delay time, and reading information of the RFID reader with the tag outlier threshold, and based on the comparison result, the characteristics of the goods data during transportation and before transportation are matched to obtain the monitoring value of the transportation status; in this way, both the RFID tag status monitoring and the goods status monitoring can be taken into account, effectively solving the screening of the reasons for the abnormal goods status, and effectively improving the efficiency and reliability of the supply chain system.

[0123] The goods transportation path optimization unit is used to optimize the transportation path of the goods; by combining the importance, the historical goods information matching degree between supply chain nodes, and the historical transportation status monitoring value, the current transportation path is optimized using the multi-objective goods transportation path optimization model to obtain the optimal transportation path.

[0124] Further, the process of the goods transportation path optimization unit obtaining the optimal transportation path using the multi-objective goods transportation path optimization model includes:

[0125] Obtain the importance of the goods, the historical goods information matching degree of the transportation route, and the historical transportation status monitoring value;

[0126] Construct a multi-objective goods transportation route optimization model with minimizing transportation cost and minimizing transportation time as the optimization objectives, and combine the importance, historical goods information matching degree, and historical transportation status monitoring value to obtain the comprehensive objective function of the multi-objective goods transportation route optimization model;

[0127] The comprehensive objective function is expressed as:

[0128] ;

[0129] Among them, is the comprehensive objective function; is the minimization operation; is the comprehensive objective function expression; is the importance of goods g; is the historical goods information matching degree of goods g from node i to node j; is the historical transportation status monitoring value of goods g from node i to node j; is the transportation cost from node i to node j; is the transportation time from node i to node j; , and are the objective functions , objective function and objective function 's weights respectively;

[0130] Furthermore, , and are set to 0.3, 0.35, and 0.35 respectively;

[0131] Furthermore, the expressions of the objective function , objective function and objective function are respectively:

[0132] ;

[0133] Among them, is the goods set; is the transportation route set; is the transportation cost from node i to node j; is the decision variable. If the goods pass through the transportation route , the value is 1, otherwise it is 0; is the transportation time from node i to node j; is the importance weight factor; is the importance degree of the goods ; is the weight factor of the goods information is the historical goods information matching degree of the goods g from node i to node j is the weight factor of the transportation status is the historical transportation status monitoring value of the goods g from node i to node j

[0134] Furthermore, the importance weight factor, the goods information weight factor and the transportation status weight factor are respectively set to 0.3, 0.35 and 0.35.

[0135] In this embodiment, the multi-objective goods transportation path optimization model combines the importance degree of the goods, the goods information matching value of the transportation route and the transportation status monitoring value, and takes the transportation cost and the transportation time as the optimization objectives to obtain the optimal solution, so as to determine the optimal transportation path; this model considers various factors such as the importance degree of the goods, the goods information security and the goods transportation status, and comprehensively selects the transportation path, thereby improving the efficiency and reliability of the supply chain system.

[0136] According to the comprehensive objective function, the optimal transportation path is obtained by solving.

[0137] In this embodiment, a high-efficiency intelligent supply chain system based on RFID is proposed. The system includes: a goods label distribution unit for obtaining the importance degree of the goods according to the sales price, supply quantity and vulnerability of the goods, and allocating RFID labels according to the importance degree; a goods information matching unit for obtaining the goods information matching degree according to the information matching values calculated under different transportation statuses; combining the goods information matching degree with the goods information matching threshold to obtain the goods information matching result; a goods transportation monitoring unit for managing the abnormal status of the RFID label and the goods status during the transportation process according to the RFID label abnormal value and the transportation status monitoring value; a goods transportation path optimization unit for combining the importance degree and the historical goods information matching degree and the historical transportation status monitoring value of the transportation route between supply chain nodes, and obtaining the optimal transportation path by using the multi-objective goods transportation path optimization model; using this system can effectively improve the efficiency and reliability of supply chain management.

[0138] Embodiment 2

[0139] The present invention also provides a high-efficiency intelligent supply chain method based on RFID. The process of this method can refer to Figure 3 , including:

[0140] S10. Obtain the sales price, supply quantity and vulnerability of the goods, and combine the calculation formula of the importance degree to obtain the importance degree of the goods; allocate different RFID labels to the goods according to the importance degree;

[0141] Furthermore, the specific process of the goods label distribution unit for RFID label distribution according to the importance of the goods includes:

[0142] Obtain the vulnerability of the goods according to the proportion of the damaged quantity in the quantity of goods transported;

[0143] Evaluate the selling price, supply quantity, and vulnerability of the goods to obtain the importance of the goods;

[0144] The calculation formula for the importance of the goods is:

[0145] ;

[0146] wherein, is the importance of the goods, and the larger this value is, the higher the importance of the goods; is the arctangent function; is the selling price weight factor; is the selling price; is the standard value of the selling price; is the supply quantity weight factor; is the supply quantity; is the standard value of the supply quantity; is the vulnerability weight factor; is the damaged quantity; is the quantity of goods transported;

[0147] Combined with the importance of the goods, allocate corresponding RFID tags to the goods based on frequency selection, capacity selection, and security selection.

[0148] To illustrate the process of the present invention for allocating RFID tags according to the importance of the goods, three different types of goods data are randomly selected for label allocation testing, which are respectively recorded as test data one, test data two, and test data three; according to the types and production specifications of each good, set the standard value of the selling price and the standard value of the supply quantity, and at the same time obtain the importance of each good according to the proportion of the damaged quantity, selling price, and supply quantity in each good data; set the importance threshold to 0.8, and select a suitable RFID tag for each good according to the importance threshold, and the label allocation test results are shown in Table 3.

[0149] S20. Obtain the goods information matching degree according to the first information matching value of the current supply chain node, the second information matching value calculated every fixed time during transportation, and the third information matching value between the current supply chain node and the next node; combine the goods information matching degree and the goods information matching threshold to obtain the goods information matching result;

[0150] Furthermore, the specific process of combining the goods information matching degree and the goods information matching threshold to obtain the goods information matching result includes:

[0151] Obtain a first information matching value according to the goods information at the input end and the output end in the current supply chain node;

[0152] Obtain a second information matching value according to the goods information at fixed intervals during transportation and the goods information before transportation;

[0153] Obtain a third information matching value according to the goods information at the output end in the current supply chain node and the input end in the next node;

[0154] Table 3. Label Assignment Test Results

[0155]

[0156] Combine the first information matching value, the second information matching value, and the third information matching value; obtain the goods information matching degree; the calculation formula for the goods information matching degree is:

[0157] ;

[0158] where, is the goods information matching degree; is the first information matching weight value; is the first information matching value; is the second information matching weight value; is the second information matching value; is the third information matching weight value; is the third information matching value;

[0159] Compare the goods information matching degree with the goods information matching threshold to obtain the goods information matching result.

[0160] S30. Obtain an RFID tag outlier according to the reading status, reading delay time, and reading information comparison of the RFID reader; obtain a transportation status monitoring value according to the comparison result between the RFID tag outlier and the tag outlier threshold; obtain the goods status information according to the transportation status monitoring value;

[0161] Further, the process of obtaining an RFID tag outlier according to the reading status, reading delay time, and reading information comparison of the RFID reader and obtaining a transportation status monitoring value according to the comparison result between the RFID tag outlier and the tag outlier threshold includes:

[0162] Obtain the reading status, reading delay time, and reading information of the RFID reader during the transportation of the goods;

[0163] According to the reading status, the reading position information and the reading cargo information in the reading information, obtain the reading status weight, the position information matching value, and the second information matching value respectively;

[0164] Evaluate the reading status weight, the position information matching value, and the second information matching value to obtain the RFID tag outlier value; The calculation formula for the RFID tag outlier value is:

[0165] ;

[0166] where, is the RFID tag outlier value; is the exponential function; is the reading status weight; is the reading delay time weight value; is the reading delay time threshold; is the reading delay time; is the position information matching weight value; is the position information matching value; is the cargo information matching weight value; is the second information matching value;

[0167] Compare the RFID tag outlier value with the tag outlier threshold. If it does not exceed the tag outlier threshold, perform feature matching on the located cargo data during transportation and the cargo data before transportation to obtain the transportation status monitoring value; Otherwise, obtain the transportation status monitoring value based on the RFID tag outlier value and feedback the abnormal information.

[0168] S40. Combine the importance, the historical cargo information matching degree and the historical transportation status monitoring value between supply chain nodes, and use the multi-objective cargo transportation path optimization model to optimize the current transportation path to obtain the optimal transportation path.

[0169] Furthermore, the implementation process of obtaining the optimal transportation path using the multi-objective cargo transportation path optimization model includes:

[0170] Obtain the importance of the cargo, the historical cargo information matching degree of the transportation route, and the historical transportation status monitoring value;

[0171] Construct a multi-objective cargo transportation path optimization model with minimizing transportation cost and minimizing transportation time as the optimization objectives, and combine the importance, the historical cargo information matching degree and the historical transportation status monitoring value to obtain the comprehensive objective function of the multi-objective cargo transportation path optimization model; The comprehensive objective function is expressed as:

[0172] ;

[0173] where, is the comprehensive objective function; is the minimization operation; is the comprehensive objective function expression; is the importance of cargo g; is the historical cargo information matching degree of cargo g from node i to node j; is the historical transportation status monitoring value of cargo g from node i to node j; is the transportation cost from node i to node j; is the transportation time from node i to node j;

[0174] According to the comprehensive objective function, the optimal transportation path is obtained by solving.

[0175] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A high-efficiency intelligent supply chain system based on RFID, characterized in that: include: The cargo label allocation unit is used to allocate corresponding RFID labels to the cargo; the importance of the cargo is obtained according to the sales price, supply quantity and vulnerability of the cargo, and the RFID labels are allocated according to the importance; The cargo information matching unit is used to match and proofread the cargo information; specifically: combining the first information matching value of the current supply chain node, the second information matching value at fixed intervals during transportation, and the third information matching value between the current supply chain node and the next node to obtain the cargo information matching degree; combining the cargo information matching degree and the cargo information matching threshold to obtain the cargo information matching result; The cargo transportation monitoring unit is used to manage the abnormal state of the RFID tag and the cargo state during transportation; obtain the abnormal value of the RFID tag according to the reading state, reading delay time and reading information of the RFID reader; obtain the transportation state monitoring value according to the abnormal value of the RFID tag and the abnormal threshold of the tag; Obtain cargo status information based on transportation status monitoring values; The process of obtaining the transport status monitoring value includes: obtaining a reading status weight, a position information matching value, and a second information matching value respectively according to the reading status, the reading position information in the reading information, and the reading cargo information; The reading state weight, reading delay time, location information matching value and second information matching value are evaluated to obtain the RFID tag abnormal value, and the abnormal value is compared with the tag abnormal threshold. If it does not exceed the tag abnormal threshold, the positioning cargo data during transportation is feature matched with the cargo data before transportation to obtain the transportation state monitoring value; otherwise, the transportation state monitoring value is obtained according to the RFID tag abnormal value; The cargo transportation path optimization unit is used to optimize the cargo transportation path; it combines the importance and the historical cargo information matching degree of the transportation routes between supply chain nodes and the historical transportation status monitoring values, and uses the multi-objective cargo transportation path optimization model to optimize the current transportation path to obtain the optimal transportation path.

2. According to claim 1, a high-efficiency intelligent supply chain system based on RFID is characterized in that: The specific process of the cargo label allocation unit allocating RFID labels according to the importance of the cargo includes: The vulnerability of the goods is obtained according to the proportion of the damaged goods in the transported goods; Evaluate the sales price, supply quantity and vulnerability of the goods to obtain the importance of the goods; In combination with the importance of the goods, corresponding RFID tags are allocated to the goods on the basis of frequency selection, capacity selection and security selection.

3. The high-efficiency intelligent supply chain system based on RFID according to claim 1 is characterized in that: The process of the cargo information matching unit obtaining the cargo information matching result includes: Obtaining a first information matching value according to the product information at the input end and the output end of the current supply chain node; Obtaining a second information matching value according to the product information at fixed intervals during transportation and the product information before transportation; Obtaining a third information matching value according to the product information at the output end of the current supply chain node and the input end of the next node; Combine the first information matching value, the second information matching value and the third information matching value to obtain the cargo information matching degree. The calculation formula of the cargo information matching degree is: ； in, is the matching degree of the cargo information; is the first information matching weight value; is the first information matching value; matching weight value for the second information; is the second information matching value; A weight value for matching the third information; is the third information matching value; The cargo information matching degree is compared with a cargo information matching threshold to obtain a cargo information matching result.

4. The high-efficiency intelligent supply chain system based on RFID according to claim 1 is characterized in that: The process of implementing the cargo transportation monitoring unit to obtain the transportation status monitoring value includes: Acquire the reading status, the reading delay time and the reading information of the RFID reader during cargo transportation; According to the read state, the read position information in the read information, and the read cargo information, respectively obtain a read state weight, a position information matching value, and the second information matching value; The reading state weight, the reading delay time, the position information matching value and the second information matching value are evaluated to obtain the RFID tag abnormal value; the calculation formula of the RFID tag abnormal value is: ； in, is the abnormal value of the RFID tag; is the read state weight; is an exponential function; To read the delay time weight value; is the read latency threshold; is the read delay time; Matching weight value for location information; is the location information matching value; Matching weight value for cargo information; is the second information matching value; The RFID tag abnormal value is compared with the tag abnormal threshold. If it does not exceed the tag abnormal threshold, the positioning cargo data during transportation is feature matched with the cargo data before transportation to obtain the transportation status monitoring value; otherwise, the transportation status monitoring value is obtained according to the RFID tag abnormal value and abnormal information is fed back.

5. The high-efficiency intelligent supply chain system based on RFID according to claim 1 is characterized in that: The process of obtaining the optimal transportation path by the cargo transportation path optimization unit using the multi-objective cargo transportation path optimization model includes: Obtaining the importance of the cargo and the historical cargo information matching degree and historical transportation status monitoring value of the transportation route; Constructing the multi-objective cargo transportation path optimization model, taking minimizing transportation cost and minimizing transportation time as optimization objectives, and combining the importance, the historical cargo information matching degree and the historical transportation status monitoring value to obtain the comprehensive objective function of the multi-objective cargo transportation path optimization model; The comprehensive objective function is expressed as: ； in, is the comprehensive objective function; To minimize operations; is the comprehensive objective function expression; is the importance of the cargo g; is the matching degree of the historical cargo information of cargo g from node i to node j; is the historical transportation status monitoring value of cargo g from node i to node j; is the transportation cost from node i to node j; is the transportation time from node i to node j; According to the comprehensive objective function, the optimal transportation path is solved.

6. A high-efficiency intelligent supply chain method based on RFID, characterized in that: include: Obtain the sales price, supply and fragility of the goods, and combine them with the calculation formula of importance to obtain the importance of the goods; assigning different RFID tags to the goods according to the importance; Obtaining a cargo information matching degree according to a first information matching value of a current supply chain node, a second information matching value calculated at fixed intervals during transportation, and a third information matching value between the current supply chain node and the next node; and obtaining a cargo information matching result by combining the cargo information matching degree with a cargo information matching threshold; According to the reading state, reading delay time and reading information comparison of the RFID reader, an RFID tag abnormal value is obtained; according to the comparison result between the RFID tag abnormal value and the tag abnormal threshold, a transportation status monitoring value is obtained; according to the transportation status monitoring value, cargo status information is obtained; Combining the importance and the historical cargo information matching degree and historical transportation status monitoring value of the transportation routes between supply chain nodes, a multi-objective cargo transportation path optimization model is used to optimize the current transportation path to obtain the optimal transportation path.

7. The high-efficiency intelligent supply chain method based on RFID according to claim 6 is characterized in that: The specific process of obtaining the cargo information matching result by combining the cargo information matching degree and the cargo information matching threshold includes: Obtaining a first information matching value according to the product information at the input end and the output end of the current supply chain node; Obtaining a second information matching value according to the product information at fixed intervals during transportation and the product information before transportation; Obtaining a third information matching value according to the product information at the output end of the current supply chain node and the input end of the next node; Combine the first information matching value, the second information matching value and the third information matching value to obtain the cargo information matching degree. The calculation formula of the cargo information matching degree is: ； in, is the matching degree of the cargo information; is the first information matching weight value; is the first information matching value; matching weight value for the second information; is the second information matching value; A weight value for matching the third information; is the third information matching value; The cargo information matching degree is compared with a cargo information matching threshold to obtain a cargo information matching result.

8. The high-efficiency intelligent supply chain method based on RFID according to claim 6 is characterized in that: According to the reading status of the RFID reader, the reading delay time and the reading information comparison, the abnormal value of the RFID tag is obtained; The process of obtaining the transport status monitoring value according to the comparison result between the RFID tag abnormal value and the tag abnormal threshold value includes: Acquire the reading status, the reading delay time and the reading information of the RFID reader during cargo transportation; According to the read state, the read position information in the read information, and the read cargo information, respectively obtain a read state weight, a position information matching value, and the second information matching value; The reading state weight, the position information matching value and the second information matching value are evaluated to obtain the RFID tag abnormal value; the calculation formula of the RFID tag abnormal value is: ； in, is the abnormal value of the RFID tag; is the read state weight; is an exponential function; To read the delay time weight value; is the read latency threshold; is the read delay time; Matching weight value for location information; is the location information matching value; Matching weight value for cargo information; is the second information matching value; The RFID tag abnormal value is compared with the tag abnormal threshold. If it does not exceed the tag abnormal threshold, the positioning cargo data during transportation is feature matched with the cargo data before transportation to obtain the transportation status monitoring value; otherwise, the transportation status monitoring value is obtained according to the RFID tag abnormal value and abnormal information is fed back.

9. The high-efficiency intelligent supply chain method based on RFID according to claim 6, characterized in that: The implementation process of obtaining the optimal transportation path by using the multi-objective cargo transportation path optimization model includes: Obtaining the importance of the cargo and the historical cargo information matching degree and historical transportation status monitoring value of the transportation route; The multi-objective cargo transportation path optimization model is constructed, with minimizing transportation cost and minimizing transportation time as optimization objectives, and the importance, the historical cargo information matching degree and the historical transportation status monitoring value are combined to obtain the comprehensive objective function of the multi-objective cargo transportation path optimization model; the comprehensive objective function is expressed as: ； in, is the comprehensive objective function; To minimize operations; is the comprehensive objective function expression; is the importance of the cargo g; is the matching degree of the historical cargo information of cargo g from node i to node j; is the historical transportation status monitoring value of cargo g from node i to node j; is the transportation cost from node i to node j; is the transportation time from node i to node j; According to the comprehensive objective function, the optimal transportation path is solved.

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