CN116307770B - Logistics supply chain dynamic management system and method based on Internet of things - Google Patents
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Abstract
The invention discloses a logistics supply chain dynamic management system and method based on the Internet of things, and belongs to the technical field of the Internet of things. The unified identification and coding are carried out on each processing link, so that the association between the protocol and the data flow between the data can be effectively unified and traced; establishing association connection in the dynamic state, and searching for the symbiotic relation between the data; screening the centralization and bordering of each processing link, analyzing the cross processing links and the non-cross processing links through the excavation of the data stream, and calculating the relevance of the central processing links, the influence of the isolated processing links and the comprehensive evaluation value of the logistics supply chain; based on the comprehensive evaluation value of the logistics supply chain, the dynamic monitoring early warning binding relation is obtained, and then the logistics supply chain is subjected to dynamic early warning, so that information sharing and data communication can be carried out among enterprises, the overall balance of the logistics supply chain system is ensured, and an effective balance decision reference is provided for the logistics supply chain system.
Description
Technical Field
The invention relates to the technical field of the Internet of things, in particular to a logistics supply chain dynamic management system and method based on the Internet of things.
Background
The supply chain is an organic networked organization, and the value and the efficiency of the whole supply chain can be improved under the guidance of supply chain management; the logistics management is used as a part of the supply chain management, and the logistics management plays a role in uniformly scheduling and planning logistics activities in the supply chain and timely feeding back information to each related supply chain link so as to play a role in planning and coordination. In the specific operation and management process, firstly, the law of related logistics activities is mastered, then, the thought and method of logistics management are applied to conduct unified command and dispatch on related activities such as purchasing, transporting, distributing and storing, so that coordination and cooperation of all the activities are realized, the logistics management is more focused on the management of an operation layer, the logistics activities are preferentially coordinated, the management of a supply chain is more preferentially managed on a strategic layer, and the cooperation and coordination among enterprises are preferentially realized, so that the efficiency and benefit of the whole supply chain are improved; second, supply chain management converts relationships between upstream and downstream enterprises into collaborative relationships, thereby converting contradictory relationships between enterprise logistics into symbiotic relationships.
With the rise of big data and internet of things technology and the continuous upgrading of modern enterprise development modes, the opposite relationship among enterprises also comprises symbiotic relationship, and especially in a logistics supply chain system, one enterprise logistics supply chain often influences another enterprise logistics supply chain system, the future of modern and digital enterprise development is not the sealing of a single enterprise logistics supply chain any more, and information sharing and data communication become the necessary trend of logistics supply chain system integration.
Disclosure of Invention
The invention aims to provide a logistics supply chain dynamic management system and method based on the Internet of things, which are used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme:
logistics supply chain dynamic management system based on Internet of things, the system comprises: the system comprises a dynamic sensing module, an associated data stream analysis module, a screening result processing module and a dynamic early warning module;
the dynamic sensing module is used for acquiring record data in a logistics supply chain of each authorized binding enterprise, and identifying and marking all processing links on the logistics supply chain; based on each processing link on the logistics supply chain, carrying out data flow association on record data in the logistics supply chain of each authorized binding enterprise; the recorded data is based on data generated by transmission of the internet of things technology;
The associated data flow analysis module is used for analyzing associated data flows, dividing processing links into a central processing link and an isolated processing link, carrying out centralized screening on each processing link with data flow crossing operation, and carrying out boundary screening on each processing link without data flow crossing operation;
the screening result processing module is used for respectively calculating the relevance of the central processing link and the influence of the isolated processing link based on the centralized screening result and the borderline screening result;
the dynamic early warning module calculates a comprehensive evaluation value of the logistics supply chain based on the relevance of the central processing link and the influence of the isolated processing link; and dynamically monitoring the logistics supply chain according to the comprehensive evaluation value of the logistics supply chain, and outputting dynamic monitoring and early warning information.
Further, the dynamic sensing module further comprises a data identification unit and a data stream association relation judgment unit;
the data identification unit is used for identifying and marking all the processing links in the logistics supply chain system, uniformly coding the processing links, and generating a processing link code set which is recorded as { I } 1 ，I 2 ，...，I U }, wherein I 1 ，I 2 ，...，I U Respectively representing the processing links of the U codes; acquiring record data in a logistics supply chain of each authorized binding enterprise, correspondingly identifying each processing link on the logistics supply chain based on the record data, marking the identification result and generating an enterprise processing link set to be marked as V X Wherein V is X Representing a set of processing links contained by an X-th authorized binding enterprise, and
the data stream association relation judging unit is used for acquiring a set of processing links contained in the Y-th authorized binding enterprise and marking the set as V Y And (2) andif the relation exists between the set of processing links contained in the X-th authorized binding enterprise and the set of processing links contained in the Y-th authorized binding enterprise +.>X is not equal to Y, and the relationship between the X-th authorized binding enterprise and the Y-th authorized binding enterprise in the data stream is indicated; designating a set of all authorized-binding enterprise-generated data stream-associated enterprises associated with the X-th authorized-binding enterprise-presence data stream as V X 。
Further, the associated data stream analysis module further comprises a processing link dividing unit and a data stream crossing operation capturing unit;
the processing link dividing unit is used for extracting an intersection set V of a set of processing links contained in the X-th authorized binding enterprise and a set of processing links contained in the Y-th authorized binding enterprise XY Marking the set as a central processing link set; obtaining an isolated processing link set of an X-th authorized binding enterprise to be recorded as V XY1 And V is XY1 ＝V X -V XY Acquiring an isolated processing link set of a Y-th authorized binding enterprise as V XY2 And V is XY2 ＝V Y -V XY ；
The data flow cross operation capturing unit is used for capturing data flow of the processing links contained in each authorized binding enterprise and capturing the processing link I a To processing link I b The transmitted record data is recorded as R, and the processing link I c To processing link I b The transmitted record data is recorded as r; if there is coincidence data between the record data R and the record data R, the processing link I is represented a Processing procedure I b And processing link I c Data flow cross operation exists between the two, centralized screening is carried out, and a processing link I is processed a Processing procedure I b And processing link I c Marking as a cross processing link; if there is no coincidence data between the record data R and the record data R, the processing link I is represented a Processing procedure I b And processing link I c No data flow cross operation exists between the two, boundary screening is carried out, and the link I is processed a Processing procedure I b And processing link I c Marking as non-cross processing links; wherein I is a 、I b 、I c ∈{I 1 ，I 2 ，...，I U A noteq.b noteq.c; and respectively carrying out centralized screening and borderline screening on the center processing link set corresponding to the X-th authorized binding enterprise, respectively carrying out centralized screening and borderline screening on the isolated processing link set corresponding to the X-th authorized binding enterprise, and respectively carrying out cross processing link extraction and non-cross processing link extraction on the center processing link set and the isolated processing link set corresponding to the X-th authorized binding enterprise.
Further, the screening result processing module further comprises a central processing link relevance calculating unit and an isolated processing link influence calculating unit;
the central processing link association degree calculating unit is used for binding the X-th authorization to a central processing link set V corresponding to the enterprise XY The cross processing links extracted through centralized screening generate a central cross processing link set which is marked as S 1 (X) generating a central non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the central non-cross processing link set as S 2 (X); binding the Y-th authorization with a center processing link set V corresponding to the enterprise XY The cross processing links extracted through centralized screening generate a central cross processing link set which is marked as S 1 (Y) generating a central non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the central non-cross processing link set as S 2 (Y); the relevance of the processing links of the center is calculated, and the specific calculation formula is as follows:
wherein G is XY Representing the degree of association of central processing links, FS 1 (X)∪S 1 (Y)]Represent S 1 (X)∪S 1 (Y) the number of elements in the set, F [ S ] 2 (X)∪S 2 (Y)]Represent S 2 (X)∪S 2 (Y) the number of elements in the set, F [ S ] 1 (X)∩S 1 (Y)]Represent S 1 (X)∩S 1 (Y) the number of elements in the set, F [ S ] 1 (X)∩S 2 (Y)]Represent S 1 (X)∩S 2 (Y) the number of elements in the set, F [ S ] 2 (X)∩S 1 (Y)]Represent S 2 (X)∩S 1 (Y) the number of elements in the set, F [ S ] 2 (X)∩S 2 (Y)]Represent S 2 (X)∩S 2 (Y) the number of elements in the collection;
the isolation processing link influence degree calculation unit is used for binding the X-th authorization with the isolation processing link set V corresponding to the enterprise XY1 Generating isolated intersections by centralising extracted intersection processing linksThe processing link set is marked as H 1 (X) generating an isolated non-cross processing link set by boundary screening and extracting non-cross processing links and marking the isolated non-cross processing link set as H 2 (X); binding the Y-th authorization with a center processing link set V corresponding to the enterprise XY2 Generating an isolated cross processing link set by the cross processing links extracted through centralized screening and marking the isolated cross processing link set as H 1 (Y) generating an isolated non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the isolated non-cross processing link set as H 2 (Y); calculating influence degree of the isolated processing link, wherein a specific calculation formula is as follows:
wherein Q is XY Representing the influence of isolated processing link, F [ H ] 1 (X)∪H 1 (Y)]Represents H 1 (X)∪H 1 (Y) the number of elements in the set, FH 2 (X)∪H 2 (Y)]Represents H 2 (X)∪H 2 (Y) the number of elements in the set, FH 1 (X)]Represents H 1 (X) the number of elements in the collection, FH 2 (X)]Represents H 2 (X) number of elements in the collection.
Further, the dynamic early warning module further comprises a logistics supply chain comprehensive evaluation value calculation unit and an early warning monitoring object selection unit;
the comprehensive evaluation value calculation unit of the logistics supply chain calculates the comprehensive evaluation value L of the logistics supply chain based on the relevance of the central processing link and the influence of the isolated processing link XY ＝G XY *Q XY ；
The early warning monitoring object selecting unit is used for associating the data flow with the enterprise set V X Calculating a comprehensive evaluation value of a logistics supply chain by each data flow associated enterprise, and selecting the corresponding data flow associated enterprise when the comprehensive evaluation value of the logistics supply chain is maximum as an early warning monitoring object of an X-th authorized binding enterprise; calculating the comprehensive evaluation value of the logistics supply chain of the Y-th authorized binding enterprise, and selecting the data stream associated enterprise corresponding to the maximum comprehensive evaluation value of the logistics supply chain as the Y-th authorized binding enterpriseEarly warning monitoring objects; if the early warning monitoring object of the X-th authorized binding enterprise is the Y-th authorized binding enterprise and the early warning monitoring object of the Y-th authorized binding enterprise is the X-th authorized binding enterprise, a dynamic monitoring early warning binding relationship is formed between the X-th authorized binding enterprise and the Y-th authorized binding enterprise, and dynamic monitoring early warning information is output and sent to the X-th authorized binding enterprise and the Y-th authorized binding enterprise.
A logistics supply chain dynamic management method based on the Internet of things comprises the following steps:
step S100: acquiring record data in a logistics supply chain of each authorized binding enterprise, and identifying and marking all processing links on the logistics supply chain; based on each processing link on the logistics supply chain, carrying out data flow association on record data in the logistics supply chain of each authorized binding enterprise; the recorded data is based on data generated by transmission of the internet of things technology;
Step S200: analyzing the associated data stream, dividing the processing links into a central processing link and an isolated processing link, carrying out centralized screening on each processing link with data stream crossing operation, and carrying out boundary screening on each processing link without data stream crossing operation;
step S300: calculating the relevance of the central processing link and the influence of the isolated processing link respectively based on the centralized screening result and the borderline screening result;
step S400: calculating a comprehensive evaluation value of the logistics supply chain based on the relevance of the central processing link and the influence of the isolated processing link; and dynamically monitoring the logistics supply chain according to the comprehensive evaluation value of the logistics supply chain, and outputting dynamic monitoring and early warning information.
Further, the specific implementation process of the step S100 includes:
step S101: identifying and marking all processing links in a logistics supply chain system, uniformly coding the processing links to generate a processing link code set which is marked as { I } 1 ，I 2 ，...，I U }, wherein I 1 ，I 2 ，...，I U Respectively represent1, 2., where, U coding processing links; acquiring record data in a logistics supply chain of each authorized binding enterprise, correspondingly identifying each processing link on the logistics supply chain based on the record data, marking the identification result and generating an enterprise processing link set to be marked as V X Wherein V is X Representing a set of processing links contained by an X-th authorized binding enterprise, and
step S102: acquiring a set of processing links contained in a Y-th authorized binding enterprise as V Y And (2) and if the relation exists between the set of processing links contained in the X-th authorized binding enterprise and the set of processing links contained in the Y-th authorized binding enterprise +.>X is not equal to Y, and the relationship between the X-th authorized binding enterprise and the Y-th authorized binding enterprise in the data stream is indicated; designating a set of all authorized-binding enterprise-generated data stream-associated enterprises associated with the X-th authorized-binding enterprise-presence data stream as V X 。
According to the method, a plurality of links exist in a logistics supply chain system, the connection and transmission of data of each link are realized through the technology of the Internet of things, and under the addition of the industrial standard, the requirements on the positioning and the attribute of each link are more and more clear; and then carry on the unified identification mark and code to each processing link, make the association between agreement and data flow between the data can be unified and traced back effectively; in different stage periods, when different businesses are docked, the processing links among enterprises often change, the dynamic processing links reflect the associated uncertainty among the enterprises, the uncertainty is very unfavorable for sharing data, the opposition of the logistics supply chains of the enterprises is more obvious, and therefore, the associated connection needs to be established in the dynamic state, the symbiotic relation among the data is found, and the whole logistics supply chain system is balanced;
Further, the specific implementation process of the step S200 includes:
step S201: extracting an intersection set V of a set of processing links contained in the X-th authorized binding enterprise and a set of processing links contained in the Y-th authorized binding enterprise XY Marking the set as a central processing link set; obtaining an isolated processing link set of an X-th authorized binding enterprise to be recorded as V XY1 And V is XY1 ＝V X -V XY Acquiring an isolated processing link set of a Y-th authorized binding enterprise as V XY2 And V is XY2 ＝V Y -V XY ；
Step S202: capturing data flow of processing links contained in each authorized binding enterprise, and processing link I a To processing link I b The transmitted record data is recorded as R, and the processing link I c To processing link I b The transmitted record data is recorded as r; if there is coincidence data between the record data R and the record data R, the processing link I is represented a Processing procedure I b And processing link I c Data flow cross operation exists between the two, centralized screening is carried out, and a processing link I is processed a Processing procedure I b And processing link I c Marking as a cross processing link; if there is no coincidence data between the record data R and the record data R, the processing link I is represented a Processing procedure I b And processing link I c No data flow cross operation exists between the two, boundary screening is carried out, and the link I is processed a Processing procedure I b And processing link I c Marking as non-cross processing links; wherein I is a 、I b 、I c ∈{I 1 ，I 2 ，...，I U A noteq.b noteq.c;
step S203: and respectively carrying out centralized screening and borderline screening on the center processing link set corresponding to the X-th authorized binding enterprise, respectively carrying out centralized screening and borderline screening on the isolated processing link set corresponding to the X-th authorized binding enterprise, and respectively carrying out cross processing link extraction and non-cross processing link extraction on the center processing link set and the isolated processing link set corresponding to the X-th authorized binding enterprise.
According to the method, the central processing links reflect that direct association exists between the logistics supply chains of enterprises, and the isolated processing links are connected with each other through the central processing links, so that the isolated processing links play roles in indirect association and indirect influence in a logistics supply chain system; further carrying out centralized and borderline screening on each processing link, and analyzing cross processing links and non-cross processing links through mining of data streams;
further, the implementation process of the step S300 includes:
step S301: binding the X-th authorization with a center processing link set V corresponding to an enterprise XY The cross processing links extracted through centralized screening generate a central cross processing link set which is marked as S 1 (X) generating a central non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the central non-cross processing link set as S 2 (X); binding the Y-th authorization with a center processing link set V corresponding to the enterprise XY The cross processing links extracted through centralized screening generate a central cross processing link set which is marked as S 1 (Y) generating a central non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the central non-cross processing link set as S 2 (Y); the relevance of the processing links of the center is calculated, and the specific calculation formula is as follows:
wherein G is XY Representing the degree of association of central processing links, FS 1 (X)∪S 1 (Y)]Represent S 1 (X)∪S 1 (Y) the number of elements in the set, F [ S ] 2 (X)∪S 2 (Y)]Represent S 2 (X)∪S 2 (Y) the number of elements in the set, F [ S ] 1 (X)∩S 1 (Y)]Represent S 1 (X)∩S 1 (Y) the number of elements in the set, F [ S ] 1 (X)∩S 2 (Y)]Represent S 1 (X)∩S 2 (Y) the number of elements in the set, F [ S ] 2 (X)∩S 1 (Y)]Represent S 2 (X)∩S 1 (Y) the number of elements in the set, F [ S ] 2 (X)∩S 2 (Y)]Represent S 2 (X)∩S 2 (Y) the number of elements in the collection;
step S302: the X-th authorization is bound with an isolated processing link set V corresponding to an enterprise XY1 Generating an isolated cross processing link set by the cross processing links extracted through centralized screening and marking the isolated cross processing link set as H 1 (X) generating an isolated non-cross processing link set by boundary screening and extracting non-cross processing links and marking the isolated non-cross processing link set as H 2 (X); binding the Y-th authorization with a center processing link set V corresponding to the enterprise XY2 Generating an isolated cross processing link set by the cross processing links extracted through centralized screening and marking the isolated cross processing link set as H 1 (Y) generating an isolated non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the isolated non-cross processing link set as H 2 (Y); calculating influence degree of the isolated processing link, wherein a specific calculation formula is as follows:
wherein Q is XY Representing the influence of isolated processing link, F [ H ] 1 (X)∪H 1 (Y)]Represents H 1 (X)∪H 1 (Y) the number of elements in the set, FH 2 (X)∪H 2 (Y)]Represents H 2 (X)∪H 2 (Y) the number of elements in the set, FH 1 (X)]Represents H 1 (X) the number of elements in the collection, FH 2 (X)]Represents H 2 (X) number of elements in the collection.
According to the method, in the central processing link and the isolated processing link, the cross processing link and the non-cross processing link are respectively subjected to deep analysis, so that the relevance of the central processing link and the influence of the isolated processing link are calculated; when calculating the degree of association of the central processing links, the left-hand division of the equation multiplication is based on the cross processing links as the underlying data for mining, the left-hand division of the equation multiplication is the element number of the union of the cross processing links in the two enterprise central processing links, and the numerator is the element number of the intersection of the cross processing link in the X-th enterprise central processing link and the cross processing link in the Y-th enterprise central processing link plus the element number of the intersection of the cross processing link in the X-th enterprise central processing link and the non-cross processing link in the Y-th enterprise central processing link, so as to find the relationship between two enterprises by taking the cross processing links as the underlying data; in contrast, the equation multiplication number right-hand side part is based on the relation of excavation and searching for the bottom data in the non-cross processing link; digging the central processing links, wherein the purpose of the multiplication calculation of the formula is to analyze the degree of direct association between the central processing links;
Further, the specific implementation process of the step S400 includes:
step S401: calculating a comprehensive evaluation value L of the logistics supply chain based on the relevance of the central processing link and the influence of the isolated processing link XY ＝G XY *Q XY ；
Step S402: associating enterprise set V for data streams X Calculating a comprehensive evaluation value of a logistics supply chain by each data flow associated enterprise, and selecting the corresponding data flow associated enterprise when the comprehensive evaluation value of the logistics supply chain is maximum as an early warning monitoring object of an X-th authorized binding enterprise;
step S403: calculating a comprehensive evaluation value of a logistics supply chain of a Y-th authorized binding enterprise, and selecting a data stream associated enterprise corresponding to the maximum comprehensive evaluation value of the logistics supply chain as an early warning monitoring object of the Y-th authorized binding enterprise; if the early warning monitoring object of the X-th authorized binding enterprise is the Y-th authorized binding enterprise and the early warning monitoring object of the Y-th authorized binding enterprise is the X-th authorized binding enterprise, a dynamic monitoring early warning binding relationship is formed between the X-th authorized binding enterprise and the Y-th authorized binding enterprise, and dynamic monitoring early warning information is output and sent to the X-th authorized binding enterprise and the Y-th authorized binding enterprise;
according to the method, when the influence degree of the isolated processing links is calculated, the cross processing links and the non-cross processing links are respectively subjected to deep analysis, and the analysis results of the cross processing links and the non-cross processing links are added to analyze the indirect influence degree between the isolated processing links.
Compared with the prior art, the invention has the following beneficial effects: in the logistics supply chain dynamic management system and method based on the Internet of things, the unified identification marking and encoding are carried out on each processing link, so that the association between the protocol and the data flow between the data can be effectively unified and traced; in different stage periods, when different businesses are docked, the processing links among enterprises often change, the dynamic processing links reflect the associated uncertainty among the enterprises, the uncertainty is very unfavorable for sharing data, the opposition of the logistics supply chains of the enterprises is more obvious, thus the associated connection is established in the dynamic state, the symbiotic relation among the data is found, and the whole logistics supply chain system is balanced; the central processing links reflect that direct association exists between the logistics supply chains of enterprises, and the isolated processing links are connected with each other through the central processing links, so that the isolated processing links play roles of indirect association and indirect influence in a logistics supply chain system; further carrying out centralized and borderline screening on each processing link, and analyzing cross processing links and non-cross processing links through mining of data streams; in the central processing link and the isolated processing link, respectively carrying out deep analysis on the cross processing link and the non-cross processing link, and further calculating the relevance of the central processing link, the influence of the isolated processing link and the comprehensive evaluation value of the logistics supply chain; based on the comprehensive evaluation value of the logistics supply chain, the dynamic monitoring early warning binding relation is obtained, and then the logistics supply chain is subjected to dynamic early warning, so that information sharing and data communication can be carried out among enterprises, the overall balance of the logistics supply chain system is ensured, and an effective balance decision reference is provided for the logistics supply chain system.
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The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic structural diagram of a logistics supply chain dynamic management system based on the Internet of things;
FIG. 2 is a schematic diagram of steps of a method for dynamically managing a logistics supply chain based on the Internet of things;
fig. 3 is a schematic diagram of an implementation of a method for dynamically managing a logistics supply chain based on the internet of things.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-3, the present invention provides the following technical solutions:
referring to fig. 1, in a first embodiment: the utility model provides a commodity circulation supply chain dynamic management system based on thing networking, this system includes: the system comprises a dynamic sensing module, an associated data stream analysis module, a screening result processing module and a dynamic early warning module;
The dynamic sensing module is used for acquiring record data in a logistics supply chain of each authorized binding enterprise, and identifying and marking all processing links on the logistics supply chain; based on each processing link on the logistics supply chain, carrying out data flow association on record data in the logistics supply chain of each authorized binding enterprise; recording data generated by transmitting the data based on the internet of things technology;
the dynamic sensing module further comprises a data identification unit and a data stream association relation judging unit;
the data identification unit is used for identifying and marking all the processing links in the logistics supply chain system, uniformly coding the processing links, and generating a processing link code set which is marked as { I } 1 ，I 2 ，...，I U }, wherein I 1 ，I 2 ，...，I U Respectively representing the processing links of the U codes; acquiring record data in a logistics supply chain of each authorized binding enterprise, correspondingly identifying each processing link on the logistics supply chain based on the record data, marking the identification result and generating an enterprise processing link set to be marked as V X Wherein V is X Representing a set of processing links contained by an X-th authorized binding enterprise, and
the data stream association relation judging unit is used for acquiring a set of processing links contained in the Y-th authorized binding enterprise and marking the set as V Y And (2) andif the relation exists between the set of processing links contained in the X-th authorized binding enterprise and the set of processing links contained in the Y-th authorized binding enterprise +.>X is not equal to Y, and the relationship between the X-th authorized binding enterprise and the Y-th authorized binding enterprise in the data stream is indicated; designating a set of all authorized-binding enterprise-generated data stream-associated enterprises associated with the X-th authorized-binding enterprise-presence data stream as V X 。
The associated data stream analysis module is used for analyzing associated data streams, dividing processing links into a central processing link and an isolated processing link, carrying out centralized screening on the processing links with data stream crossing operation, and carrying out boundary screening on the processing links without data stream crossing operation;
the associated data stream analysis module further comprises a processing link dividing unit and a data stream cross operation capturing unit;
a processing link dividing unit for extracting the set of processing links contained in the X-th authorized binding enterprise and the Y-th authorized bindingIntersection set V of set of processing links contained in fixed enterprise XY Marking the set as a central processing link set; obtaining an isolated processing link set of an X-th authorized binding enterprise to be recorded as V XY1 And V is XY1 ＝V X -V XY Acquiring an isolated processing link set of a Y-th authorized binding enterprise as V XY2 And V is XY2 ＝V Y -V XY ；
The data flow cross operation capturing unit is used for capturing the data flow of the processing links contained in each authorized binding enterprise and capturing the processing link I a To processing link I b The transmitted record data is recorded as R, and the processing link I c To processing link I b The transmitted record data is recorded as r; if there is coincidence data between the record data R and the record data R, the processing link I is represented a Processing procedure I b And processing link I c Data flow cross operation exists between the two, centralized screening is carried out, and a processing link I is processed a Processing procedure I b And processing link I c Marking as a cross processing link; if there is no coincidence data between the record data R and the record data R, the processing link I is represented a Processing procedure I b And processing link I c No data flow cross operation exists between the two, boundary screening is carried out, and the link I is processed a Processing procedure I b And processing link I c Marking as non-cross processing links; wherein I is a 、I b 、I c ∈{I 1 ，I 2 ，...，I U A noteq.b noteq.c; and respectively carrying out centralized screening and borderline screening on the center processing link set corresponding to the X-th authorized binding enterprise, respectively carrying out centralized screening and borderline screening on the isolated processing link set corresponding to the X-th authorized binding enterprise, and respectively carrying out cross processing link extraction and non-cross processing link extraction on the center processing link set and the isolated processing link set corresponding to the X-th authorized binding enterprise.
The screening result processing module is used for respectively calculating the relevance of the central processing link and the influence of the isolated processing link based on the centralized screening result and the borderline screening result;
the screening result processing module further comprises a central processing link relevance calculating unit and an isolated processing link influence calculating unit;
the central processing link association degree calculating unit is used for binding the X-th authorization to the central processing link set V corresponding to the enterprise XY The cross processing links extracted through centralized screening generate a central cross processing link set which is marked as S 1 (X) generating a central non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the central non-cross processing link set as S 2 (X); binding the Y-th authorization with a center processing link set V corresponding to the enterprise XY The cross processing links extracted through centralized screening generate a central cross processing link set which is marked as S 1 (Y) generating a central non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the central non-cross processing link set as S 2 (Y); the relevance of the processing links of the center is calculated, and the specific calculation formula is as follows:
wherein G is XY Representing the degree of association of central processing links, FS 1 (X)∪S 1 (Y)]Represent S 1 (X)∪S 1 (Y) the number of elements in the set, F [ S ] 2 (X)∪S 2 (Y)]Represent S 2 (X)∪S 2 (Y) the number of elements in the set, F [ S ] 1 (X)∩S 1 (Y)]Represent S 1 (X)∩S 1 (Y) the number of elements in the set, F [ S ] 1 (X)∩S 2 (Y)]Represent S 1 (X)∩S 2 (Y) the number of elements in the set, F [ S ] 2 (X)∩S 1 (Y)]Represent S 2 (X)∩S 1 (Y) the number of elements in the set, F [ S ] 2 (X)∩S 2 (Y)]Represent S 2 (X)∩S 2 (Y) the number of elements in the collection;
an isolated processing link influence degree calculation unit for binding the X-th authorization with an isolated processing link set V corresponding to the enterprise XY1 Generating isolated intersections by centralising extracted intersection processing linksThe processing link set is marked as H 1 (X) generating an isolated non-cross processing link set by boundary screening and extracting non-cross processing links and marking the isolated non-cross processing link set as H 2 (X); binding the Y-th authorization with a center processing link set V corresponding to the enterprise XY2 Generating an isolated cross processing link set by the cross processing links extracted through centralized screening and marking the isolated cross processing link set as H 1 (Y) generating an isolated non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the isolated non-cross processing link set as H 2 (Y); calculating influence degree of the isolated processing link, wherein a specific calculation formula is as follows:
wherein Q is XY Representing the influence of isolated processing link, F [ H ] 1 (X)∪H 1 (Y)]Represents H 1 (X)∪H 1 (Y) the number of elements in the set, FH 2 (X)∪H 2 (Y)]Represents H 2 (X)∪H 2 (Y) the number of elements in the set, FH 1 (X)]Represents H 1 (X) the number of elements in the collection, FH 2 (X)]Represents H 2 (X) number of elements in the collection.
The dynamic early warning module is used for calculating a comprehensive evaluation value of the logistics supply chain based on the relevance of the central processing link and the influence of the isolated processing link; dynamically monitoring the logistics supply chain according to the comprehensive evaluation value of the logistics supply chain, and outputting dynamic monitoring and early warning information;
The dynamic early warning module further comprises a logistics supply chain comprehensive evaluation value calculation unit and an early warning monitoring object selection unit;
the comprehensive evaluation value calculation unit of the logistics supply chain calculates the comprehensive evaluation value L of the logistics supply chain based on the relevance of the central processing link and the influence of the isolated processing link XY ＝G XY *Q XY ；
The early warning monitoring object selection unit is used for associating the data flow with the enterprise set V X Each data flow related enterprise calculates the comprehensive evaluation value of the logistics supply chain, and the corresponding data flow related enterprise is selected when the comprehensive evaluation value of the logistics supply chain is maximumThe data flow associated enterprises of the (1) are used as early warning monitoring objects of the X-th authorized binding enterprises; calculating a comprehensive evaluation value of a logistics supply chain of a Y-th authorized binding enterprise, and selecting a data stream associated enterprise corresponding to the maximum comprehensive evaluation value of the logistics supply chain as an early warning monitoring object of the Y-th authorized binding enterprise; if the early warning monitoring object of the X-th authorized binding enterprise is the Y-th authorized binding enterprise and the early warning monitoring object of the Y-th authorized binding enterprise is the X-th authorized binding enterprise, a dynamic monitoring early warning binding relationship is formed between the X-th authorized binding enterprise and the Y-th authorized binding enterprise, and dynamic monitoring early warning information is output and sent to the X-th authorized binding enterprise and the Y-th authorized binding enterprise.
Referring to fig. 2 and 3, in the second embodiment: the utility model provides a logistics supply chain dynamic management method based on the Internet of things, which comprises the following steps:
identifying and marking all processing links in a logistics supply chain system, uniformly coding the processing links to generate a processing link code set which is marked as { I } 1 ，I 2 ，...，I U }, wherein I 1 ，I 2 ，...，I U Respectively representing the processing links of the U codes; acquiring record data in a logistics supply chain of each authorized binding enterprise, correspondingly identifying each processing link on the logistics supply chain based on the record data, marking the identification result and generating an enterprise processing link set to be marked as V X Wherein V is X Representing a set of processing links contained by an X-th authorized binding enterprise, and
acquiring a set of processing links contained in a Y-th authorized binding enterprise as V Y And (2) andif the relation exists between the set of processing links contained in the X-th authorized binding enterprise and the set of processing links contained in the Y-th authorized binding enterprise +.>X is not equal to Y, and the relationship between the X-th authorized binding enterprise and the Y-th authorized binding enterprise in the data stream is indicated; designating a set of all authorized-binding enterprise-generated data stream-associated enterprises associated with the X-th authorized-binding enterprise-presence data stream as V X ；
Extracting an intersection set V of a set of processing links contained in the X-th authorized binding enterprise and a set of processing links contained in the Y-th authorized binding enterprise XY Marking the set as a central processing link set; obtaining an isolated processing link set of an X-th authorized binding enterprise to be recorded as V XY1 And V is XY1 ＝V X -V XY Acquiring an isolated processing link set of a Y-th authorized binding enterprise as V XY2 And V is XY2 ＝V Y -V XY ；
Capturing data flow of processing links contained in each authorized binding enterprise, and processing link I a To processing link I b The transmitted record data is recorded as R, and the processing link I c To processing link I b The transmitted record data is recorded as r; if there is coincidence data between the record data R and the record data R, the processing link I is represented a Processing procedure I b And processing link I c Data flow cross operation exists between the two, centralized screening is carried out, and a processing link I is processed a Processing procedure I b And processing link I c Marking as a cross processing link; if there is no coincidence data between the record data R and the record data R, the processing link I is represented a Processing procedure I b And processing link I c No data flow cross operation exists between the two, boundary screening is carried out, and the link I is processed a Processing procedure I b And processing link I c Marking as non-cross processing links; wherein I is a 、I b 、I c ∈{I 1 ，I 2 ，...，I U A noteq.b noteq.c;
respectively carrying out centralized screening and borderline screening on a central processing link set corresponding to an X-th authorized binding enterprise, respectively carrying out centralized screening and borderline screening on an isolated processing link set corresponding to the X-th authorized binding enterprise, and respectively carrying out cross processing link extraction and non-cross processing link extraction on the central processing link set and the isolated processing link set corresponding to the X-th authorized binding enterprise;
binding the X-th authorization with a center processing link set V corresponding to an enterprise XY The cross processing links extracted through centralized screening generate a central cross processing link set which is marked as S 1 (X) generating a central non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the central non-cross processing link set as S 2 (X); binding the Y-th authorization with a center processing link set V corresponding to the enterprise XY The cross processing links extracted through centralized screening generate a central cross processing link set which is marked as S 1 (Y) generating a central non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the central non-cross processing link set as S 2 (Y); the relevance of the processing links of the center is calculated, and the specific calculation formula is as follows:
Wherein G is XY Representing the degree of association of central processing links, FS 1 (X)∪S 1 (Y)]Represent S 1 (X)∪S 1 (Y) the number of elements in the set, F [ S ] 2 (X)∪S 2 (Y)]Represent S 2 (X)∪S 2 (Y) the number of elements in the set, F [ S ] 1 (X)∩S 1 (Y)]Represent S 1 (X)∩S 1 (Y) the number of elements in the set, F [ S ] 1 (X)∩S 2 (Y)]Represent S 1 (X)∩S 2 (Y) the number of elements in the set, F [ S ] 2 (X)∩S 1 (Y)]Represent S 2 (X)∩S 1 (Y) the number of elements in the set, F [ S ] 2 (X)∩S 2 (Y)]Represent S 2 (X)∩S 2 (Y) the number of elements in the collection;
the X-th authorization is bound with an isolated processing link set V corresponding to an enterprise XY1 Generating an isolated cross processing link set through cross processing links extracted by centralized screeningIs marked as H 1 (X) generating an isolated non-cross processing link set by boundary screening and extracting non-cross processing links and marking the isolated non-cross processing link set as H 2 (X); binding the Y-th authorization with a center processing link set V corresponding to the enterprise XY2 Generating an isolated cross processing link set by the cross processing links extracted through centralized screening and marking the isolated cross processing link set as H 1 (Y) generating an isolated non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the isolated non-cross processing link set as H 2 (Y); calculating influence degree of the isolated processing link, wherein a specific calculation formula is as follows:
wherein Q is XY Representing the influence of isolated processing link, F [ H ] 1 (X)∪H 1 (Y)]Represents H 1 (X)∪H 1 (Y) the number of elements in the set, FH 2 (X)∪H 2 (Y)]Represents H 2 (X)∪H 2 (Y) the number of elements in the set, FH 1 (X)]Represents H 1 (X) the number of elements in the collection, FH 2 (X)]Represents H 2 (X) the number of elements in the collection;
calculating a comprehensive evaluation value L of the logistics supply chain based on the relevance of the central processing link and the influence of the isolated processing link XY ＝G XY *Q XY ；
Associating enterprise set V for data streams X Calculating a comprehensive evaluation value of a logistics supply chain by each data flow associated enterprise, and selecting the corresponding data flow associated enterprise when the comprehensive evaluation value of the logistics supply chain is maximum as an early warning monitoring object of an X-th authorized binding enterprise;
calculating a comprehensive evaluation value of a logistics supply chain of a Y-th authorized binding enterprise, and selecting a data stream associated enterprise corresponding to the maximum comprehensive evaluation value of the logistics supply chain as an early warning monitoring object of the Y-th authorized binding enterprise; if the early warning monitoring object of the X-th authorized binding enterprise is the Y-th authorized binding enterprise and the early warning monitoring object of the Y-th authorized binding enterprise is the X-th authorized binding enterprise, a dynamic monitoring early warning binding relationship is formed between the X-th authorized binding enterprise and the Y-th authorized binding enterprise, and dynamic monitoring early warning information is output and sent to the X-th authorized binding enterprise and the Y-th authorized binding enterprise;
for example, in fig. 3, where enterprise 1 and enterprise 2 are in a dynamic monitoring and early warning binding relationship, an early warning monitoring object of enterprise 2 is enterprise 3, and an early warning monitoring object of enterprise 3 is enterprise 1, then dynamic monitoring and early warning information is sent to enterprise 1 and enterprise 2; when the logistics supply system of the enterprise 1 has a problem, the problem can be overcome by the logistics supply system of the enterprise 2; when a problem occurs in the logistics supply system of the enterprise 2, the problem can be overcome by the logistics supply chain system of the enterprise 1 or the enterprise 3; when the logistics supply system of the enterprise 3 has a problem, the problem can be overcome by the logistics supply chain system of the enterprise 1 or indirectly by the logistics supply system of the enterprise 2; thereby providing an effective balance decision reference for the logistics supply chain system.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention and is not intended to limit the present invention, but although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the technical solutions described in the foregoing embodiments, or equivalents may be substituted for some of the technical features thereof. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. The logistics supply chain dynamic management method based on the Internet of things is characterized by comprising the following steps of:
step S100: acquiring record data in a logistics supply chain of each authorized binding enterprise, and identifying and marking all processing links on the logistics supply chain; based on each processing link on the logistics supply chain, carrying out data flow association on record data in the logistics supply chain of each authorized binding enterprise; the recorded data is based on data generated by transmission of the internet of things technology;
step S200: analyzing the associated data stream, dividing the processing links into a central processing link and an isolated processing link, carrying out centralized screening on each processing link with data stream crossing operation, and carrying out boundary screening on each processing link without data stream crossing operation;
step S300: calculating the relevance of the central processing link and the influence of the isolated processing link respectively based on the centralized screening result and the borderline screening result;
step S400: calculating a comprehensive evaluation value of the logistics supply chain based on the relevance of the central processing link and the influence of the isolated processing link; dynamically monitoring the logistics supply chain according to the comprehensive evaluation value of the logistics supply chain, and outputting dynamic monitoring and early warning information;
The specific implementation process of the step S100 includes:
step S101: identifying and marking all processing links in a logistics supply chain system, uniformly coding the processing links to generate a processing link code set which is marked as { I } 1 ，I 2 ，...，I U }, wherein I 1 ，I 2 ，...，I U Respectively representing the processing links of the U codes; acquiring record data in a logistics supply chain of each authorized binding enterprise, correspondingly identifying each processing link on the logistics supply chain based on the record data, marking the identification result and generating an enterprise processing link set to be marked as V X Wherein V is X Representing a set of processing links contained by an X-th authorized binding enterprise, and
step S102: acquiring a set of processing links contained in a Y-th authorized binding enterprise as V Y And (2) andI 2 ，...，I U if there is a relation between the set of processing links comprised by the X-th authorized binding enterprise and the set of processing links comprised by the Y-th authorized binding enterprise +.>Indicating that the X-th authorized-binding enterprise is associated with the Y-th authorized-binding enterprise presence data stream; designating a set of all authorized-binding enterprise-generated data stream-associated enterprises associated with the X-th authorized-binding enterprise-presence data stream as V X ；
The specific implementation process of the step S200 includes:
Step S201: extracting an intersection set V of a set of processing links contained in the X-th authorized binding enterprise and a set of processing links contained in the Y-th authorized binding enterprise XY Marking the set as a central processing link set; obtaining an isolated processing link set of an X-th authorized binding enterprise to be recorded as V XY1 And V is XY1 ＝V X -V XY Acquiring an isolated processing link set of a Y-th authorized binding enterprise as V XY2 And V is XY2 ＝V Y -V XY 。
2. The method for dynamically managing a logistics supply chain based on the internet of things according to claim 1, wherein the implementation process of step S200 further comprises:
step S202: capturing data flow of processing links contained in each authorized binding enterprise, and processing link I a To processing link I b The transmitted record data is recorded as R, and the processing link I c To processing link I b Transmission ofRecord data of (2) is denoted as r; if there is coincidence data between the record data R and the record data R, the processing link I is represented a Processing procedure I b And processing link I c Data flow cross operation exists between the two, centralized screening is carried out, and a processing link I is processed a Processing procedure I b And processing link I c Marking as a cross processing link; if there is no coincidence data between the record data R and the record data R, the processing link I is represented a Processing procedure I b And processing link I c No data flow cross operation exists between the two, boundary screening is carried out, and the link I is processed a Processing procedure I b And processing link I c Marking as non-cross processing links; wherein I is a 、I b 、I c ∈{I 1 ，I 2 ，...，I U A noteq.b noteq.c;
step S203: and respectively carrying out centralized screening and borderline screening on the center processing link set corresponding to the X-th authorized binding enterprise, respectively carrying out centralized screening and borderline screening on the isolated processing link set corresponding to the X-th authorized binding enterprise, and respectively carrying out cross processing link extraction and non-cross processing link extraction on the center processing link set and the isolated processing link set corresponding to the X-th authorized binding enterprise.
3. The method for dynamically managing a logistics supply chain based on the internet of things according to claim 2, wherein the specific implementation process of the step S300 comprises:
step S301: binding the X-th authorization with a center processing link set V corresponding to an enterprise XY The cross processing links extracted through centralized screening generate a central cross processing link set which is marked as S 1 (X) generating a central non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the central non-cross processing link set as S 2 (X); binding the Y-th authorization with a center processing link set V corresponding to the enterprise XY The cross processing links extracted through centralized screening generate a central cross processing link set which is marked as S 1 (Y) non-intersecting extraction by borderline screeningThe non-cross processing link set of the processing link generating center is marked as S 2 (Y); the relevance of the processing links of the center is calculated, and the specific calculation formula is as follows:
wherein G is XY Representing the degree of association of central processing links, FS 1 (X)∪S 1 (Y)]Represent S 1 (X)∪S 1 (Y) the number of elements in the set, F [ S ] 2 (X)∪S 2 (Y)]Represent S 2 (X)∪S 2 (Y) the number of elements in the set, F [ S ] 1 (X)∩S 1 (Y)]Represent S 1 (X)∩S 1 (Y) the number of elements in the set, F [ S ] 1 (X)∩S 2 (Y)]Represent S 1 (X)∩S 2 (Y) the number of elements in the set, F [ S ] 2 (X)∩S 1 (Y)]Represent S 2 (X)∩S 1 (Y) the number of elements in the set, F [ S ] 2 (X)∩S 2 (Y)]Represent S 2 (X)∩S 2 (Y) the number of elements in the collection;
step S302: the X-th authorization is bound with an isolated processing link set V corresponding to an enterprise XY1 Generating an isolated cross processing link set by the cross processing links extracted through centralized screening and marking the isolated cross processing link set as H 1 (X) generating an isolated non-cross processing link set by boundary screening and extracting non-cross processing links and marking the isolated non-cross processing link set as H 2 (X); binding the Y-th authorization with a center processing link set V corresponding to the enterprise XY2 Generating an isolated cross processing link set by the cross processing links extracted through centralized screening and marking the isolated cross processing link set as H 1 (Y) generating an isolated non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the isolated non-cross processing link set as H 2 (Y); calculating influence degree of the isolated processing link, wherein a specific calculation formula is as follows:
wherein Q is XY Representing an orphan processing ringDegree of influence of F [ H ] 1 (X)∪H 1 (Y)]Represents H 1 (X)∪H 1 (Y) the number of elements in the set, FH 2 (X)∪H 2 (Y)]Represents H 2 (X)∪H 2 (Y) the number of elements in the set, FH 1 (X)]Represents H 1 (X) the number of elements in the collection, FH 2 (X)]Represents H 2 (X) number of elements in the collection.
4. The method for dynamically managing a logistics supply chain based on the internet of things according to claim 3, wherein the specific implementation process of the step S400 comprises:
step S401: calculating a comprehensive evaluation value L of the logistics supply chain based on the relevance of the central processing link and the influence of the isolated processing link XY ＝G XY *Q XY ；
Step S402: associating enterprise set V for data streams X Calculating a comprehensive evaluation value of a logistics supply chain by each data flow associated enterprise, and selecting the corresponding data flow associated enterprise when the comprehensive evaluation value of the logistics supply chain is maximum as an early warning monitoring object of an X-th authorized binding enterprise;
step S403: calculating a comprehensive evaluation value of a logistics supply chain of a Y-th authorized binding enterprise, and selecting a data stream associated enterprise corresponding to the maximum comprehensive evaluation value of the logistics supply chain as an early warning monitoring object of the Y-th authorized binding enterprise; if the early warning monitoring object of the X-th authorized binding enterprise is the Y-th authorized binding enterprise and the early warning monitoring object of the Y-th authorized binding enterprise is the X-th authorized binding enterprise, a dynamic monitoring early warning binding relationship is formed between the X-th authorized binding enterprise and the Y-th authorized binding enterprise, and dynamic monitoring early warning information is output and sent to the X-th authorized binding enterprise and the Y-th authorized binding enterprise.
5. A logistics supply chain dynamic management system based on the internet of things, the system comprising: the system comprises a dynamic sensing module, an associated data stream analysis module, a screening result processing module and a dynamic early warning module;
the dynamic sensing module is used for acquiring record data in a logistics supply chain of each authorized binding enterprise, and identifying and marking all processing links on the logistics supply chain; based on each processing link on the logistics supply chain, carrying out data flow association on record data in the logistics supply chain of each authorized binding enterprise; the recorded data is based on data generated by transmission of the internet of things technology;
the associated data flow analysis module is used for analyzing associated data flows, dividing processing links into a central processing link and an isolated processing link, carrying out centralized screening on each processing link with data flow crossing operation, and carrying out boundary screening on each processing link without data flow crossing operation;
the screening result processing module is used for respectively calculating the relevance of the central processing link and the influence of the isolated processing link based on the centralized screening result and the borderline screening result;
the dynamic early warning module calculates a comprehensive evaluation value of the logistics supply chain based on the relevance of the central processing link and the influence of the isolated processing link; dynamically monitoring the logistics supply chain according to the comprehensive evaluation value of the logistics supply chain, and outputting dynamic monitoring and early warning information;
The dynamic perception module also comprises a data identification unit and a data stream association relation judgment unit;
the data identification unit is used for identifying and marking all the processing links in the logistics supply chain system, uniformly coding the processing links, and generating a processing link code set which is recorded as { I } 1 ，I 2 ，...，I U }, wherein I 1 ，I 2 ，...，I U Respectively representing the processing links of the U codes; acquiring record data in a logistics supply chain of each authorized binding enterprise, correspondingly identifying each processing link on the logistics supply chain based on the record data, marking the identification result and generating an enterprise processing link set to be marked as V X Wherein V is X Representing a set of processing links contained by an X-th authorized binding enterprise, and
the data stream association relation judging unit is used for acquiring a set of processing links contained in the Y-th authorized binding enterprise and marking the set as V Y And (2) andif the relation exists between the set of processing links contained in the X-th authorized binding enterprise and the set of processing links contained in the Y-th authorized binding enterprise +.>Indicating that the X-th authorized-binding enterprise is associated with the Y-th authorized-binding enterprise presence data stream; designating a set of all authorized-binding enterprise-generated data stream-associated enterprises associated with the X-th authorized-binding enterprise-presence data stream as V X ；
The associated data stream analysis module comprises a processing link dividing unit, wherein the processing link dividing unit is used for extracting an intersection set V of a set of processing links contained in an X-th authorized binding enterprise and a set of processing links contained in a Y-th authorized binding enterprise XY Marking the set as a central processing link set; obtaining an isolated processing link set of an X-th authorized binding enterprise to be recorded as V XY1 And V is XY1 ＝V X -V XY Acquiring an isolated processing link set of a Y-th authorized binding enterprise as V XY2 And V is XY2 ＝V Y -V XY 。
6. The internet of things-based logistics supply chain dynamic management system of claim 5, wherein: the associated data stream analysis module further comprises a data stream cross operation capturing unit;
the data flow cross operation capturing unit is used for capturing data flow of the processing links contained in each authorized binding enterprise and capturing the processing link I a To processing link I b The transmitted record data is recorded as R, and the processing link I c To processing link I b Transmission ofRecord data of (2) is denoted as r; if there is coincidence data between the record data R and the record data R, the processing link I is represented a Processing procedure I b And processing link I c Data flow cross operation exists between the two, centralized screening is carried out, and a processing link I is processed a Processing procedure I b And processing link I c Marking as a cross processing link; if there is no coincidence data between the record data R and the record data R, the processing link I is represented a Processing procedure I b And processing link I c No data flow cross operation exists between the two, boundary screening is carried out, and the link I is processed a Processing procedure I b And processing link I c Marking as non-cross processing links; wherein I is a 、I b 、I c ∈{I 1 ，I 2 ，...，I U A noteq.b noteq.c; and respectively carrying out centralized screening and borderline screening on the center processing link set corresponding to the X-th authorized binding enterprise, respectively carrying out centralized screening and borderline screening on the isolated processing link set corresponding to the X-th authorized binding enterprise, and respectively carrying out cross processing link extraction and non-cross processing link extraction on the center processing link set and the isolated processing link set corresponding to the X-th authorized binding enterprise.
7. The internet of things-based logistics supply chain dynamic management system of claim 6, wherein: the screening result processing module further comprises a central processing link relevance calculating unit and an isolated processing link influence calculating unit;
the central processing link association degree calculating unit is used for binding the X-th authorization to a central processing link set V corresponding to the enterprise XY The cross processing links extracted through centralized screening generate a central cross processing link set which is marked as S 1 (X) generating a central non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the central non-cross processing link set as S 2 (X); binding the Y-th authorization with a center processing link set V corresponding to the enterprise XY Generating a central cross-processing link by the cross-processing links extracted by centralized screeningThe aggregate is denoted as S 1 (Y) generating a central non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the central non-cross processing link set as S 2 (Y); the relevance of the processing links of the center is calculated, and the specific calculation formula is as follows:
wherein G is XY Representing the degree of association of central processing links, FS 1 (X)∪S 1 (Y)]Represent S 1 (X)∪S 1 (Y) the number of elements in the set, F [ S ] 2 (X)∪S 2 (Y)]Represent S 2 (X)∪S 2 (Y) the number of elements in the set, F [ S ] 1 (X)∩S 1 (Y)]Represent S 1 (X)∩S 1 (Y) the number of elements in the set, F [ S ] 1 (X)∩S 2 (Y)]Represent S 1 (X)∩S 2 (Y) the number of elements in the set, F [ S ] 2 (X)∩S 1 (Y)]Represent S 2 (X)∩S 1 (Y) the number of elements in the set, F [ S ] 2 (X)∩S 2 (Y)]Represent S 2 (X)∩S 2 (Y) the number of elements in the collection;
the isolation processing link influence degree calculation unit is used for binding the X-th authorization with the isolation processing link set V corresponding to the enterprise XY1 Generating an isolated cross processing link set by the cross processing links extracted through centralized screening and marking the isolated cross processing link set as H 1 (X) generating an isolated non-cross processing link set by boundary screening and extracting non-cross processing links and marking the isolated non-cross processing link set as H 2 (X); binding the Y-th authorization with a center processing link set V corresponding to the enterprise XY2 Generating an isolated cross processing link set by the cross processing links extracted through centralized screening and marking the isolated cross processing link set as H 1 (Y) generating an isolated non-cross processing link set by boundary screening and extracting the non-cross processing links and marking the isolated non-cross processing link set as H 2 (Y); calculating influence degree of the isolated processing link, wherein a specific calculation formula is as follows:
wherein Q is XY Representing the influence of isolated processing link, F [ H ] 1 (X)∪H 1 (Y)]Represents H 1 (X)∪H 1 (Y) the number of elements in the set, FH 2 (X)∪H 2 (Y)]Represents H 2 (X)∪H 2 (Y) the number of elements in the set, FH 1 (X)]Represents H 1 (X) the number of elements in the collection, FH 2 (X)]Represents H 2 (X) number of elements in the collection.
8. The internet of things-based logistics supply chain dynamic management system of claim 7, wherein: the dynamic early warning module further comprises a logistics supply chain comprehensive evaluation value calculation unit and an early warning monitoring object selection unit;
the comprehensive evaluation value calculation unit of the logistics supply chain calculates the comprehensive evaluation value L of the logistics supply chain based on the relevance of the central processing link and the influence of the isolated processing link XY ＝G XY *Q XY ；
The early warning monitoring object selecting unit is used for associating the data flow with the enterprise set V X Calculating a comprehensive evaluation value of a logistics supply chain by each data flow associated enterprise, and selecting the corresponding data flow associated enterprise when the comprehensive evaluation value of the logistics supply chain is maximum as an early warning monitoring object of an X-th authorized binding enterprise; calculating a comprehensive evaluation value of a logistics supply chain of a Y-th authorized binding enterprise, and selecting a data stream associated enterprise corresponding to the maximum comprehensive evaluation value of the logistics supply chain as an early warning monitoring object of the Y-th authorized binding enterprise; if the early warning monitoring object of the X-th authorized binding enterprise is the Y-th authorized binding enterprise and the early warning monitoring object of the Y-th authorized binding enterprise is the X-th authorized binding enterprise, a dynamic monitoring early warning binding relationship is formed between the X-th authorized binding enterprise and the Y-th authorized binding enterprise, and dynamic monitoring early warning information is output and sent to the X-th authorized binding enterprise and the Y-th authorized binding enterprise.
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| KR20060019940A (en) * | 2004-08-30 | 2006-03-06 | 인천대학교 산학협력단 | Supply chain management system |
| CN105260871A (en) * | 2015-10-21 | 2016-01-20 | 高伟亮 | Supply chain and logistics transportation management system and method |
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| CN115271603A (en) * | 2022-08-05 | 2022-11-01 | 辽宁工程技术大学 | Supply chain data cooperation method based on block chain |
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| KR20060019940A (en) * | 2004-08-30 | 2006-03-06 | 인천대학교 산학협력단 | Supply chain management system |
| CN105260871A (en) * | 2015-10-21 | 2016-01-20 | 高伟亮 | Supply chain and logistics transportation management system and method |
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