CN114742607B - Multi-user collaborative management system and method based on logistics supply chain - Google Patents

Multi-user collaborative management system and method based on logistics supply chain Download PDF

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CN114742607B
CN114742607B CN202210262073.2A CN202210262073A CN114742607B CN 114742607 B CN114742607 B CN 114742607B CN 202210262073 A CN202210262073 A CN 202210262073A CN 114742607 B CN114742607 B CN 114742607B
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孙冬丽
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Abstract

The invention discloses a multi-user collaborative management system and method based on a logistics supply chain, comprising the following steps: the order information acquisition module acquires the number of the product category of the customer order, the order quantity DL, the order specified time DT and the receiving place P2; the production information analysis module monitors production departments in the supply chain and acquires a relation curve of production rate and qualification rate of each product type in the production process; the storage loss data monitoring module acquires the natural damage rate of each product type in the storage process; the logistics distribution information analysis module is used for planning different distribution routes according to the relation between the position of the warehouse department and the order receiving place, obtaining road conditions in the different distribution routes and obtaining distribution time of the different distribution routes and product loss rate in the distribution process.

Description

Multi-user collaborative management system and method based on logistics supply chain
Technical Field
The invention relates to the technical field of logistics supply chains, in particular to a multi-user collaborative management system and method based on a logistics supply chain.
Background
Along with the rapid development of computer technology, people are increasingly widely used in the field of logistics supply chains, and people acquire data conditions in different links in the logistics supply chain through the computer technology, so that comprehensive analysis is performed on the data in each link, and effective management of each link in the logistics supply chain is further realized.
The existing multi-user collaborative management system based on the logistics supply chain only simply introduces the constitution mode of the management system (namely the link of the supply chain), but does not analyze specific operation flow and corresponding management method, and does not introduce the factors according to which the multi-user collaborative management is considered, so that the system has a great defect.
In view of the foregoing, there is a need for a system and method for multi-user collaborative management based on a logistics supply chain.
Disclosure of Invention
The invention aims to provide a multi-user collaborative management system and method based on a logistics supply chain, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a multi-user collaborative management system based on a logistics supply chain, comprising:
The order information acquisition module acquires the number of the product category of the customer order, the order quantity DL, the order specified time DT and the receiving place P2;
the production information analysis module monitors production departments in the supply chain and acquires a relation curve of production rate and qualification rate of each product type in the production process;
the storage loss data monitoring module acquires the natural damage rate of each product type in the storage process;
the logistics distribution information analysis module is used for planning different distribution routes according to the relation between the position of the warehouse department and the order receiving place, obtaining road conditions in the different distribution routes and obtaining distribution time of the different distribution routes and product loss rate in the distribution process;
the supply scheme generation module is used for acquiring a supply scheme corresponding to a customer order by combining information in the order information acquisition module, the production information analysis module, the storage loss data monitoring module and the logistics distribution information analysis module;
and the supply data adjustment module acquires the supply scheme corresponding to the customer order obtained by the supply scheme generation module and screens out the optimal supply scheme of the customer order.
In the process of multiuser collaborative management, each link in the supply chain is taken as a user needing collaborative management from each link of the stream supply chain, the client order data is analyzed and managed through the data relationship corresponding to a plurality of users (the data relationship corresponding to each link in the supply chain), and under the condition of ensuring that the client order is met, the income is maximized, namely the optimal supply scheme of the client order is realized (when the client order is met, the production department needs the least number of products produced, the production cost is lowest, and the enterprise income is highest).
Further, the method for obtaining the relation curve of the production rate and the qualification rate of each product category in the production process by the production information analysis module comprises the following steps:
s1.1, acquiring historical data corresponding to production departments in a supply chain, numbering product types, and collecting an i1 data set A in an i product type in the historical data i-i1 The said
Figure GDA0004056679080000021
wherein ,
Figure GDA0004056679080000022
representing the total number of productions in the history data to which the order of the 1 st data set in the i-th product category corresponds,
Figure GDA0004056679080000023
representing the number of products produced in unit time in the order production process of the ith 1 data set in the ith product category in the historical data,
Figure GDA0004056679080000024
Representing the number of qualified products in the history data corresponding to the order of the ith 1 data set in the ith product category,
the (1) th data set A in the (i) th product category in the historical data i-i1 The i 2-th element in (2) is denoted as
Figure GDA0004056679080000025
S1.2, summarizing the data sets with equal values corresponding to the third element in each data set corresponding to the ith product category in the history data into a blank set to obtain a data set summarizing set respectively corresponding to each production rate in the ith product category in the history data,
record the summary set of the j-th data set in the i-th product category in the historical data as B i-j ，
Summarizing the j-th data set in the ith product category in the historical data, and marking the 2-th element in the data set corresponding to the j-th 1 element as
Figure GDA0004056679080000031
Summarizing the j-th data set in the ith product category in the historical data, and marking the 4-th element in the data set corresponding to the j-th 1 element as
Figure GDA0004056679080000032
The production rate corresponding to the summary set of the j-th data set in the ith product category in the historical data is recorded as B3 i-j ；
S1.3, constructing a plane rectangular coordinate system by taking o as an origin, taking the production rate as an x axis and taking the qualification rate as a y axis;
s1.4, acquiring a coordinate fitting point (B3) corresponding to a j-th data set summary set in the i-th product category in the historical data i-j ，C i-j ) The C is i-j Representing the product qualification rate corresponding to the j-th data set summary set in the i-th product category in the historical data;
s1.5, marking coordinate fitting points corresponding to all data set summarization sets in the ith product category in the historical data obtained in the S1.4 in a plane rectangular coordinate system, and performing linear fitting on the marked coordinate fitting points through a linear fitting model prefabricated in a database to obtain a relation curve of the production rate and the qualification rate of the ith product category in the historical data in the production process, wherein the relation curve is marked as Fi (x);
s1.6, obtaining a relation curve of the production rate and the qualification rate of each product type in the historical data in the production process.
In the process of obtaining the relation curve of the production rate and the qualification rate of each product category in the production process by the production information analysis module, the i1 data set A in the i product category in the historical data is obtained i-i1 Is to classify order information in history data and pass through the dataThe method ensures that the information format in the historical data is uniform, and the product types in the historical data are conveniently analyzed in the subsequent process, so that a relation curve of the production rate and the qualification rate of the ith product type in the historical data in the production process is obtained; the Fi (x) is obtained to comprehensively analyze the conditions in each link in the logistics supply chain in the subsequent steps, so as to provide data basis for obtaining the optimal supply scheme of the customer order.
Further, the method for obtaining the product qualification rate corresponding to the summary set of the j-th data set in the i-th product category in the historical data comprises the following steps:
s1.4.1, acquiring a j-th data set summary set in the i-th product category in the historical data;
s1.4.2 calculating the 4 th element in the data set corresponding to the 1 st element in the j-th data set summary set in the ith product category in the historical data
Figure GDA0004056679080000033
2 nd element in the dataset corresponding to the j1 st element +.>
Figure GDA0004056679080000034
Obtaining the qualification rate corresponding to the (j 1) th element in the j data set summary set in the (i) th product category in the historical data>
Figure GDA0004056679080000035
S1.4.3 obtaining the product qualification rate C corresponding to the j-th data set summary set in the i-th product category in the history data i-j ，
The said
Figure GDA0004056679080000041
Where nij represents the number of elements of the collection of the j-th dataset in the i-th product category in the history data.
Product qualification rate corresponding to the summary set of the j-th data set in the i-th product category in the historical dataIn the process of (1), obtaining the product percent of pass C corresponding to the summary set of the j-th data set in the i-th product category in the historical data i-j In the time-course of which the first and second contact surfaces,
Figure GDA0004056679080000042
representing the sum of the values of the 2 nd element in the corresponding data set of each element in the j-th data set summary set in the ith product category in the historical data; calculate- >
Figure GDA0004056679080000043
Is to obtain the 2 nd element value in the corresponding data set of the j1 st element in the j data set summary set in the ith product category in the history data>
Figure GDA0004056679080000044
Ratio of (2) to obtain->
Figure GDA0004056679080000045
Occupy C i-j Is a weight ratio of (2); obtaining the qualification rate C of each element in the j-th data set summary set in the i-th product category in the history data to the product by obtaining the qualification rate and the corresponding bias ratio of the j-th 1 element in the j-th data set summary set in the i-th product category in the history data i-j And further to the final product yield C i-j More accurate.
Further, the storage loss data monitoring module obtains the natural damage rate of each product category in the storage process, namely, the natural damage rate of each product category in the storage process of a storage department is obtained by obtaining the ratio of the number of damaged products stored in each batch in each category of products to the number of products stored in the corresponding batch in each category of products, the average value of the corresponding ratio of each batch in the same category of products is the natural damage rate of the corresponding product category in the storage process,
the natural damage rate of the ith product category during storage is noted as CSi.
Further, the method for obtaining the road conditions in different delivery routes by the logistics distribution information analysis module comprises the following steps:
S2.1, acquiring a position P1 of a warehouse department and an order receiving place P2;
s2.2, acquiring different corresponding distribution routes from P1 to P2 in the map, and acquiring the lengths corresponding to different types of roads in each distribution route;
s2.3, obtaining pavement damage degrees corresponding to each type of road in different distribution routes;
s2.4, forming a data pair by the length corresponding to each type of road in each distribution route and the corresponding road surface damage degree, wherein the first number of the data pair represents the length, the second number of the data pair represents the road surface damage degree,
adding data pairs corresponding to different types of roads in the same distribution route into the same blank set to obtain a distribution route road condition set;
the method for acquiring the pavement damage degree corresponding to each type of road in different distribution routes in S2.3 comprises the following steps:
s2.3.1 the length corresponding to the kth 1-type road in the kth delivery route is recorded as
Figure GDA0004056679080000051
S2.3.2, will
Figure GDA0004056679080000052
Dividing into intervals with the length of a first unit length, acquiring the number of single damaged areas of the pavement in each interval which are larger than or equal to the first unit area,
counting the number of single damaged areas of the road surface in the k2 th section of the k1 st type road in the k delivery route which is larger than or equal to the first unit area as
Figure GDA0004056679080000053
Acquisition of ∈10 by database query>
Figure GDA0004056679080000054
Corresponding intervalThe road surface breakage coefficient of (2) is expressed as +.>
Figure GDA0004056679080000055
S2.3.3 obtaining road surface breakage coefficients of each section of the kth 1-type road in the kth delivery route, and calculating the average value of the obtained road surface breakage coefficients of each section to obtain the breakage degree corresponding to the kth 1-type road in the kth delivery route
Figure GDA0004056679080000056
Wherein Nkk represents the number of sections corresponding to the kth 1 type road in the kth delivery route.
In the process of acquiring the road conditions in different delivery routes, the logistics delivery information analysis module considers that the corresponding road types in different routes are different, and the lengths corresponding to the road types are also different; obtaining the pavement damage degree corresponding to each type of road in different distribution routes, wherein the influence degree on the distribution time of the product and the loss rate of the product in the logistics distribution process is different in consideration of the difference of pavement damage degree in the different types of roads; the method is used for ensuring the uniformity of the form of road information in the distribution route, and is convenient for calculating the distribution time of different distribution routes and the product loss rate in the distribution process in the subsequent process.
Further, the method for obtaining the distribution time of different distribution routes and the product loss rate in the distribution process by the logistics distribution information analysis module comprises the following steps:
s3.1, acquiring road condition sets of each distribution route obtained in the step S2.4;
s3.2, obtaining an influence value Gi (m) of average unit length per first unit length on the product loss rate of the ith category in a road with the breakage degree m in the historical data, wherein the first unit length is recorded as L0;
s3.3, when the product of the ith category passes through the kth delivery route, the product loss rate in the delivery process
Figure GDA0004056679080000061
Said->
Figure GDA0004056679080000062
Wherein Mk represents the number of types of the i-th kind of products passing through the road in the kth delivery route;
s3.4 obtaining the delivery time of the ith product type through the kth delivery route
Figure GDA0004056679080000063
The said
Figure GDA0004056679080000064
wherein ,
Figure GDA0004056679080000065
indicating the speed of the vehicle when the product of the ith category is delivered through the kth 1-type road in the kth delivery route, without being affected by the road breakage degree, < + >>
Figure GDA0004056679080000066
And obtaining through database query.
In the process that the logistics distribution information analysis module obtains distribution time of different distribution routes and product loss rate in the distribution process, gi (m) is obtained by considering that the corresponding damage degree of a road is different or the types of products distributed on the road are different, and the influence on the products is correspondingly changed; obtaining product loss rate in distribution process
Figure GDA0004056679080000067
In the process of (1), calculate->
Figure GDA0004056679080000068
Considering the influence value of the damage degree of the road corresponding to the kth 1 type road in the kth delivery route on the loss rate of the delivered ith type of product, wherein Gi (m) corresponds to a function, when the independent variable is m, the value of the dependent variable is Gi (m), and the function Gi (m) is acquired through a database;
calculation of
Figure GDA0004056679080000069
In order to obtain the damage degree of the road when the product of the ith category is delivered by the vehicle and passes through the kth 1 type road in the kth delivery route>
Figure GDA00040566790800000610
The corresponding speed after the influence is further influenced, so that the corresponding time of each supply scheme is conveniently calculated, and a data basis is provided for the follow-up screening of the supply schemes meeting the customer order condition.
Further, the method for obtaining the supply scheme corresponding to the customer order by the supply scheme generation module comprises the following steps:
s4.1, obtaining the serial number of the product category of the customer order, the order quantity DL, the order stipulation time DT and the receiving place P2;
s4.2, a relation curve Fi (x) of the production rate and the qualification rate of the ith product type in the historical data in the production process;
s4.3, acquiring the natural damage rate of the ith product type in the storage process and marking the natural damage rate as CSI;
s4.4, obtaining the product loss rate in the delivery process when the product of the ith category passes through the kth delivery route
Figure GDA00040566790800000611
Acquiring delivery time of the ith product category through the kth delivery route>
Figure GDA00040566790800000612
S4.5, calculating the total number Q1 of products required to be produced by completing the customer order, calculating the total time length T occupied by the corresponding scheme of Q1,
the said
Figure GDA0004056679080000071
Wherein i0 represents the number of the product category of the customer order, k3 represents the distribution route corresponding to P1 to P2 in the supply scheme corresponding to Q1, x0 represents the production rate of the product in the supply scheme corresponding to Q1, fi0 (x 0) represents the qualification rate in the production process of the product in the supply scheme corresponding to Q1,
the said
Figure GDA0004056679080000072
S4.6, Q1 and T corresponding to different supply schemes are obtained, Q1 and T corresponding to the same supply scheme are formed into a scheme data pair, the scheme data pair with T smaller than or equal to DT is screened out, and the supply schemes corresponding to the scheme data pairs in the screening result are all supply schemes corresponding to a customer order.
In the process of acquiring the supply scheme corresponding to the customer order by the supply scheme generation module, reference is made from two aspects of time corresponding to the supply scheme and total quantity of products required to be produced when the quantity of the products in the customer order is met; when calculating the time corresponding to the supply scheme, directly calculating
Figure GDA0004056679080000073
Is to obtain the total time spent by each link in the logistics supply chain, +. >
Figure GDA0004056679080000074
Corresponding to the production time of the customer order product, < >>
Figure GDA0004056679080000075
The distribution time of the products of the customer order is correspondingly calculated, the time consumed in the storage link is not calculated in the scheme, the fact that the products are produced and stored in the storage is considered in the process, when the products are produced, the time of the products in the storage department coincides with the time of the production department, and when the production department produces the productsThe products of the warehouse department are directly distributed, so that the influence of the time in the warehouse link on the total time of the supply scheme is directly defaulted to be 0; when the total number Q1 of products required to be produced by the customer order is calculated, the difference of the yield of the products produced at different production rates and the difference of the loss rate of the products in different types during storage are considered, the difference of the loss rate of the products in the distribution process due to different distribution routes and road damage in the corresponding distribution routes are comprehensively considered from the angles, and the products are quantitatively analyzed, so that the best supply scheme of the customer order can be conveniently screened out in the subsequent process.
Further, the method for obtaining the optimal supply scheme of the customer order by the supply data adjustment module comprises the following steps:
S5.1, obtaining a supply scheme corresponding to each scheme data pair in the screening result of S4.6;
s5.2, obtaining the optimal supply scheme of the customer order,
the optimal supply scheme for acquiring the customer order is the supply scheme with the minimum Q1 corresponding to the supply scheme acquired in the step S5.1.
A multi-user collaborative management method based on a logistics supply chain, the method comprising the steps of:
s1, acquiring the serial number of the product category of a customer order, the order quantity DL, the order specified time DT and the receiving place P2 through an order information acquisition module;
s2, monitoring production departments in a supply chain through a production information analysis module to obtain a relation curve of production rate and qualification rate of each product type in the production process;
s3, acquiring natural damage rate of each product type in the storage process through a storage loss data monitoring module;
s4, in the logistics distribution information analysis module, different distribution routes are planned according to the relation between the position of the warehouse department and the order receiving place, road conditions in the different distribution routes are obtained, and distribution time of the different distribution routes and product loss rate in the distribution process are obtained;
s5, a supply scheme generating module is combined with information in the order information acquisition module, the production information analysis module, the storage loss data monitoring module and the logistics distribution information analysis module to acquire a supply scheme corresponding to a customer order;
S6, obtaining the supply scheme corresponding to the customer order obtained by the supply scheme generating module through the supply data adjusting module, and screening out the optimal supply scheme of the customer order.
Compared with the prior art, the invention has the following beneficial effects: in the process of multiuser collaborative management, each link in the supply chain is taken as a user needing collaborative management from each link of the stream supply chain, the data of the customer orders are analyzed and managed through the data relationship corresponding to a plurality of users, a plurality of supply schemes meeting the customer orders are screened out, each supply scheme is quantized, and the optimal supply scheme of the customer orders is screened out, so that the effective management of the stream supply chain is realized.
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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 diagram of a multi-user collaborative management system based on a logistics supply chain;
FIG. 2 is a schematic flow chart of a method for obtaining a relation curve between the production rate and the qualification rate of each product type in the production process by a production information analysis module in a multi-user collaborative management system based on a logistics supply chain;
FIG. 3 is a flow chart of a method for a supply scheme generating module to obtain a supply scheme corresponding to a customer order in a multi-user collaborative management system based on a logistics supply chain according to the present invention;
fig. 4 is a flow chart of a multi-user collaborative management method based on a logistics supply chain.
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. 1-4, the present invention provides the following technical solutions: a multi-user collaborative management system based on a logistics supply chain, comprising:
the order information acquisition module acquires the number of the product category of the customer order, the order quantity DL, the order specified time DT and the receiving place P2;
the production information analysis module monitors production departments in the supply chain and acquires a relation curve of production rate and qualification rate of each product type in the production process;
The storage loss data monitoring module acquires the natural damage rate of each product type in the storage process;
the logistics distribution information analysis module is used for planning different distribution routes according to the relation between the position of the warehouse department and the order receiving place, obtaining road conditions in the different distribution routes and obtaining distribution time of the different distribution routes and product loss rate in the distribution process;
the supply scheme generation module is used for acquiring a supply scheme corresponding to a customer order by combining information in the order information acquisition module, the production information analysis module, the storage loss data monitoring module and the logistics distribution information analysis module;
and the supply data adjustment module acquires the supply scheme corresponding to the customer order obtained by the supply scheme generation module and screens out the optimal supply scheme of the customer order.
The method for acquiring the relation curve of the production rate and the qualification rate of each product type in the production process by the production information analysis module comprises the following steps:
s1.1, acquiring historical data corresponding to production departments in a supply chain, numbering product types, and collecting an i1 data set A in an i product type in the historical data i-i1 The said
Figure GDA0004056679080000091
wherein ,
Figure GDA0004056679080000092
representing the total number of productions in the history data to which the order of the 1 st data set in the i-th product category corresponds,
Figure GDA0004056679080000093
representing the number of products produced in unit time in the order production process of the ith 1 data set in the ith product category in the historical data,
Figure GDA0004056679080000094
representing the number of qualified products in the history data corresponding to the order of the ith 1 data set in the ith product category,
the (1) th data set A in the (i) th product category in the historical data i-i1 The i 2-th element in (2) is denoted as
Figure GDA0004056679080000101
S1.2, summarizing the data sets with equal values corresponding to the third element in each data set corresponding to the ith product category in the history data into a blank set to obtain a data set summarizing set respectively corresponding to each production rate in the ith product category in the history data,
record the summary set of the j-th data set in the i-th product category in the historical data as B i-j ，
Summarizing the j-th data set in the ith product category in the historical data, wherein the j-th 1-th element corresponds to the data setThe 2 nd element in the list is recorded as
Figure GDA0004056679080000102
Summarizing the j-th data set in the ith product category in the historical data, and marking the 4-th element in the data set corresponding to the j-th 1 element as
Figure GDA0004056679080000103
The production rate corresponding to the summary set of the j-th data set in the ith product category in the historical data is recorded as B3 i-j ；
S1.3, constructing a plane rectangular coordinate system by taking o as an origin, taking the production rate as an x axis and taking the qualification rate as a y axis;
s1.4, acquiring a coordinate fitting point (B3) corresponding to a j-th data set summary set in the i-th product category in the historical data i-j ，C i-j ) The C is i-j Representing the product qualification rate corresponding to the j-th data set summary set in the i-th product category in the historical data;
s1.5, marking coordinate fitting points corresponding to all data set summarization sets in the ith product category in the historical data obtained in the S1.4 in a plane rectangular coordinate system, and performing linear fitting on the marked coordinate fitting points through a linear fitting model prefabricated in a database to obtain a relation curve of the production rate and the qualification rate of the ith product category in the historical data in the production process, wherein the relation curve is marked as Fi (x);
s1.6, obtaining a relation curve of the production rate and the qualification rate of each product type in the historical data in the production process.
The method for summarizing the product qualification rate corresponding to the jth data set in the ith product category in the historical data comprises the following steps:
s1.4.1, acquiring a j-th data set summary set in the i-th product category in the historical data;
S1.4.2 calculating the 4 th element in the data set corresponding to the 1 st element in the j-th data set summary set in the ith product category in the historical data
Figure GDA0004056679080000104
2 nd element in the dataset corresponding to the j1 st element +.>
Figure GDA0004056679080000105
Obtaining the qualification rate corresponding to the (j 1) th element in the j data set summary set in the (i) th product category in the historical data>
Figure GDA0004056679080000106
S1.4.3 obtaining the product qualification rate C corresponding to the j-th data set summary set in the i-th product category in the history data i-j ，
The said
Figure GDA0004056679080000111
Where nij represents the number of elements of the collection of the j-th dataset in the i-th product category in the history data.
In this example, if the 002 th dataset collection in the product category numbered 01 in the history data is { {01, 2000, 50, 1960}, {01,1500,50, 1440},
the qualification rate corresponding to the 1 st element in the 002 data set summary set in the 01 st product category in the historical data is
Figure GDA0004056679080000112
The 002 data set in the 01 st product category in the historical data is summarized, and the qualification rate corresponding to the 2 nd element is that
Figure GDA0004056679080000113
The product qualification rate corresponding to the 002 data set summary set in the 01 st product category in the historical data is
Figure GDA0004056679080000114
The storage loss data monitoring module obtains the natural damage rate of each product category in the storage process, namely, the natural damage rate of each product category in the storage process of a storage department in the history data is obtained by obtaining the ratio of the number of damaged products stored in each batch to the number of products stored in the corresponding batch in each category of products, the average value of the corresponding ratio of each batch in the same category of products is the natural damage rate of the corresponding product category in the storage process,
The natural damage rate of the ith product category during storage is noted as CSi.
The method for acquiring the road conditions in different delivery routes by the logistics delivery information analysis module comprises the following steps:
s2.1, acquiring a position P1 of a warehouse department and an order receiving place P2;
s2.2, acquiring different corresponding distribution routes from P1 to P2 in the map, and acquiring the lengths corresponding to different types of roads in each distribution route;
s2.3, obtaining pavement damage degrees corresponding to each type of road in different distribution routes;
s2.4, forming a data pair by the length corresponding to each type of road in each distribution route and the corresponding road surface damage degree, wherein the first number of the data pair represents the length, the second number of the data pair represents the road surface damage degree,
adding data pairs corresponding to different types of roads in the same distribution route into the same blank set to obtain a distribution route road condition set;
the method for acquiring the pavement damage degree corresponding to each type of road in different distribution routes in S2.3 comprises the following steps:
s2.3.1 the length corresponding to the kth 1-type road in the kth delivery route is recorded as
Figure GDA0004056679080000121
S2.3.2, will
Figure GDA0004056679080000122
Dividing into intervals with the length of a first unit length, acquiring the number of single damaged areas of the pavement in each interval which are larger than or equal to the first unit area,
counting the number of single damaged areas of the road surface in the k2 th section of the k1 st type road in the k delivery route which is larger than or equal to the first unit area as
Figure GDA0004056679080000123
Acquisition of ∈10 by database query>
Figure GDA0004056679080000124
Road surface breakage coefficient of corresponding zone is denoted +.>
Figure GDA0004056679080000125
S2.3.3 obtaining road surface breakage coefficients of each section of the kth 1-type road in the kth delivery route, and calculating the average value of the obtained road surface breakage coefficients of each section to obtain the breakage degree corresponding to the kth 1-type road in the kth delivery route
Figure GDA0004056679080000126
Wherein Nkk represents the number of sections corresponding to the kth 1 type road in the kth delivery route.
The method for obtaining the distribution time of different distribution routes and the product loss rate in the distribution process by the logistics distribution information analysis module comprises the following steps:
s3.1, acquiring road condition sets of each distribution route obtained in the step S2.4;
s3.2, obtaining an influence value Gi (m) of average unit length per first unit length on the product loss rate of the ith category in a road with the breakage degree m in the historical data, wherein the first unit length is recorded as L0;
S3.3, when the product of the ith category passes through the kth delivery route, the product loss rate in the delivery process
Figure GDA0004056679080000127
Said->
Figure GDA0004056679080000128
Wherein Mk represents the number of types of the i-th kind of products passing through the road in the kth delivery route;
in this embodiment, if the road types of the delivery route include three types, when the product with the product category number 02 passes through the 1 st delivery route, the corresponding road condition set of the delivery route is { [36,0.11], [0,0], [42,0.15] },
wherein [36,0.11] represents that the length of the corresponding data pair of the type 1 road is 36, the breakage degree of the road surface is 0.11,
[0,0] means that the length of the type 2 road correspondence data pair is 0, the breakage degree of the road surface is 0,
[42,0.15] the length of the data pair corresponding to the 3 rd type road is 42, and the breakage degree of the road surface is 0.15;
if the first unit length is 1.5, G2 (x) =0.1 x2-0.001,
product loss rate during delivery of 02 th category of product through 1 st delivery route
Figure GDA0004056679080000131
S3.4 obtaining the delivery time of the ith product type through the kth delivery route
Figure GDA0004056679080000132
The said
Figure GDA0004056679080000133
wherein ,
Figure GDA0004056679080000134
indicating that the vehicle delivers the ith category of product through the kth 1-type road in the kth delivery route without being affected by road breakage Speed at sound, < >>
Figure GDA0004056679080000135
And obtaining through database query.
The method for obtaining the supply scheme corresponding to the customer order by the supply scheme generation module comprises the following steps:
s4.1, obtaining the serial number of the product category of the customer order, the order quantity DL, the order stipulation time DT and the receiving place P2;
s4.2, a relation curve Fi (x) of the production rate and the qualification rate of the ith product type in the historical data in the production process;
s4.3, acquiring the natural damage rate of the ith product type in the storage process and marking the natural damage rate as CSI;
s4.4, obtaining the product loss rate in the delivery process when the product of the ith category passes through the kth delivery route
Figure GDA0004056679080000136
Acquiring delivery time of the ith product category through the kth delivery route>
Figure GDA0004056679080000137
S4.5, calculating the total number Q1 of products required to be produced by completing the customer order, calculating the total time length T occupied by the corresponding scheme of Q1,
the said
Figure GDA0004056679080000138
Wherein i0 represents the number of the product category of the customer order, k3 represents the distribution route corresponding to P1 to P2 in the supply scheme corresponding to Q1, x0 represents the production rate of the product in the supply scheme corresponding to Q1, fi0 (x 0) represents the qualification rate in the production process of the product in the supply scheme corresponding to Q1,
the said
Figure GDA0004056679080000139
S4.6, Q1 and T corresponding to different supply schemes are obtained, Q1 and T corresponding to the same supply scheme are formed into a scheme data pair, the scheme data pair with T smaller than or equal to DT is screened out, and the supply schemes corresponding to the scheme data pairs in the screening result are all supply schemes corresponding to a customer order.
The method for obtaining the optimal supply scheme of the customer order by the supply data adjustment module comprises the following steps:
s5.1, obtaining a supply scheme corresponding to each scheme data pair in the screening result of S4.6;
s5.2, obtaining the optimal supply scheme of the customer order,
the optimal supply scheme for acquiring the customer order is the supply scheme with the minimum Q1 corresponding to the supply scheme acquired in the step S5.1.
A multi-user collaborative management method based on a logistics supply chain, the method comprising the steps of:
s1, acquiring the serial number of the product category of a customer order, the order quantity DL, the order specified time DT and the receiving place P2 through an order information acquisition module;
s2, monitoring production departments in a supply chain through a production information analysis module to obtain a relation curve of production rate and qualification rate of each product type in the production process;
s3, acquiring natural damage rate of each product type in the storage process through a storage loss data monitoring module;
s4, in the logistics distribution information analysis module, different distribution routes are planned according to the relation between the position of the warehouse department and the order receiving place, road conditions in the different distribution routes are obtained, and distribution time of the different distribution routes and product loss rate in the distribution process are obtained;
S5, a supply scheme generating module is combined with information in the order information acquisition module, the production information analysis module, the storage loss data monitoring module and the logistics distribution information analysis module to acquire a supply scheme corresponding to a customer order;
s6, obtaining the supply scheme corresponding to the customer order obtained by the supply scheme generating module through the supply data adjusting module, and screening out the optimal supply scheme of the customer order.
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 the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. 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 (7)

1. A multi-user collaborative management system based on a logistics supply chain, comprising:
the order information acquisition module acquires the number of the product category of the customer order, the order quantity DL, the order specified time DT and the receiving place P2;
the production information analysis module monitors production departments in the supply chain and acquires a relation curve of production rate and qualification rate of each product type in the production process;
the storage loss data monitoring module acquires the natural damage rate of each product type in the storage process;
the logistics distribution information analysis module is used for planning different distribution routes according to the relation between the position of the warehouse department and the order receiving place, obtaining road conditions in the different distribution routes and obtaining distribution time of the different distribution routes and product loss rate in the distribution process;
the supply scheme generation module is used for acquiring a supply scheme corresponding to a customer order by combining information in the order information acquisition module, the production information analysis module, the storage loss data monitoring module and the logistics distribution information analysis module;
The supply data adjusting module acquires the supply scheme corresponding to the customer order obtained by the supply scheme generating module, and screens out the optimal supply scheme of the customer order;
the method for obtaining the supply scheme corresponding to the customer order by the supply scheme generation module comprises the following steps:
s4.1, obtaining the serial number of the product category of the customer order, the order quantity DL, the order stipulation time DT and the receiving place P2;
s4.2, a relation curve Fi (x) of the production rate and the qualification rate of the ith product type in the historical data in the production process;
s4.3, acquiring the natural damage rate of the ith product type in the storage process and marking the natural damage rate as CSI;
s4.4, obtaining the product loss rate in the delivery process when the product of the ith category passes through the kth delivery route
Figure FDA0004056679070000011
Acquiring delivery time of the ith product category through the kth delivery route>
Figure FDA0004056679070000012
S4.5, calculating the total number Q1 of products required to be produced by completing the customer order, calculating the total time length T occupied by the corresponding scheme of Q1,
the said
Figure FDA0004056679070000013
Wherein i0 represents the number of the product category of the customer order, k3 represents the distribution route corresponding to P1 to P2 in the supply scheme corresponding to Q1, x0 represents the production rate of the product in the supply scheme corresponding to Q1, fi0 (x 0) represents the qualification rate in the production process of the product in the supply scheme corresponding to Q1, P1 represents the position of the warehouse department,
The said
Figure FDA0004056679070000021
S4.6, Q1 and T corresponding to different supply schemes are obtained, Q1 and T corresponding to the same supply scheme are formed into a scheme data pair, scheme data pairs with T less than or equal to DT are screened out, and the supply schemes corresponding to the scheme data pairs in the screening result are all supply schemes corresponding to a customer order;
the method for obtaining the optimal supply scheme of the customer order by the supply data adjustment module comprises the following steps:
s5.1, obtaining a supply scheme corresponding to each scheme data pair in the screening result of S4.6;
s5.2, obtaining the optimal supply scheme of the customer order,
the optimal supply scheme for acquiring the customer order is the supply scheme with the minimum Q1 corresponding to the supply scheme acquired in the step S5.1.
2. The multi-user collaborative management system based on a logistics supply chain of claim 1, wherein: the method for acquiring the relation curve of the production rate and the qualification rate of each product type in the production process by the production information analysis module comprises the following steps:
s1.1, acquiring historical data corresponding to production departments in a supply chain, numbering product types, and collecting an i1 data set A in an i product type in the historical data i-i1 The said
Figure FDA0004056679070000022
wherein ,
Figure FDA0004056679070000023
representing the total number of productions in the history data to which the order of the 1 st data set in the i-th product category corresponds,
Figure FDA0004056679070000024
representing the number of products produced in unit time in the order production process of the ith 1 data set in the ith product category in the historical data,
Figure FDA0004056679070000025
representing the number of qualified products in the history data corresponding to the order of the ith 1 data set in the ith product category,
the (1) th data set A in the (i) th product category in the historical data i-i1 The i 2-th element in (2) is denoted as
Figure FDA0004056679070000026
S1.2, summarizing the data sets with equal values corresponding to the third element in each data set corresponding to the ith product category in the history data into a blank set to obtain a data set summarizing set respectively corresponding to each production rate in the ith product category in the history data,
record the summary set of the j-th data set in the i-th product category in the historical data as B i-j ，
Summarizing the j-th data set in the ith product category in the historical data, and marking the 2-th element in the data set corresponding to the j-th 1 element as
Figure FDA0004056679070000031
Summarizing the j-th data set in the ith product category in the historical data, and marking the 4-th element in the data set corresponding to the j-th 1 element as
Figure FDA0004056679070000032
The production rate corresponding to the summary set of the j-th data set in the ith product category in the historical data is recorded as B3 i-j ；
S1.3, constructing a plane rectangular coordinate system by taking o as an origin, taking the production rate as an x axis and taking the qualification rate as a y axis;
s1.4, acquiring a coordinate fitting point (B3) corresponding to a j-th data set summary set in the i-th product category in the historical data i-j ，C i-j ) The C is i-j Representing the product qualification rate corresponding to the j-th data set summary set in the i-th product category in the historical data;
s1.5, marking coordinate fitting points corresponding to all data set summarization sets in the ith product category in the historical data obtained in the S1.4 in a plane rectangular coordinate system, and performing linear fitting on the marked coordinate fitting points through a linear fitting model prefabricated in a database to obtain a relation curve of the production rate and the qualification rate of the ith product category in the historical data in the production process, wherein the relation curve is marked as Fi (x);
s1.6, obtaining a relation curve of the production rate and the qualification rate of each product type in the historical data in the production process.
3. The multi-user collaborative management system based on a logistics supply chain of claim 2, wherein: the method for summarizing the product qualification rate corresponding to the jth data set in the ith product category in the historical data comprises the following steps:
S1.4.1, acquiring a j-th data set summary set in the i-th product category in the historical data;
s1.4.2 calculating the 4 th element in the data set corresponding to the 1 st element in the j-th data set summary set in the ith product category in the historical data
Figure FDA0004056679070000033
2 nd element in the dataset corresponding to the j1 st element +.>
Figure FDA0004056679070000034
Obtaining the qualification rate corresponding to the (j 1) th element in the j data set summary set in the (i) th product category in the historical data>
Figure FDA0004056679070000035
S1.4.3 obtaining the product qualification rate C corresponding to the j-th data set summary set in the i-th product category in the history data i-j ，
The said
Figure FDA0004056679070000036
Where nij represents the number of elements of the collection of the j-th dataset in the i-th product category in the history data.
4. A multi-user collaborative management system according to claim 3 and wherein: the storage loss data monitoring module obtains the natural damage rate of each product category in the storage process, namely, the natural damage rate of each product category in the storage process of a storage department in the history data is obtained by obtaining the ratio of the number of damaged products stored in each batch to the number of products stored in the corresponding batch in each category of products, the average value of the corresponding ratio of each batch in the same category of products is the natural damage rate of the corresponding product category in the storage process,
The natural damage rate of the ith product category during storage is noted as CSi.
5. The multi-user collaborative management system according to claim 4, wherein: the method for acquiring the road conditions in different delivery routes by the logistics delivery information analysis module comprises the following steps:
s2.1, acquiring a position P1 of a warehouse department and an order receiving place P2;
s2.2, acquiring different corresponding distribution routes from P1 to P2 in the map, and acquiring the lengths corresponding to different types of roads in each distribution route;
s2.3, obtaining pavement damage degrees corresponding to each type of road in different distribution routes;
s2.4, forming a data pair by the length corresponding to each type of road in each distribution route and the corresponding road surface damage degree, wherein the first number of the data pair represents the length, the second number of the data pair represents the road surface damage degree,
adding data pairs corresponding to different types of roads in the same distribution route into the same blank set to obtain a distribution route road condition set;
the method for acquiring the pavement damage degree corresponding to each type of road in different distribution routes in S2.3 comprises the following steps:
S2.3.1 the length corresponding to the kth 1-type road in the kth delivery route is recorded as
Figure FDA0004056679070000041
S2.3.2, will
Figure FDA0004056679070000042
Dividing into intervals with the length of a first unit length, acquiring the number of single damaged areas of the pavement in each interval which are larger than or equal to the first unit area,
counting the number of single damaged areas of the road surface in the k2 th section of the k1 st type road in the k delivery route which is larger than or equal to the first unit area as
Figure FDA0004056679070000043
Acquisition of ∈10 by database query>
Figure FDA0004056679070000044
Road surface breakage coefficient of corresponding zone is denoted +.>
Figure FDA0004056679070000045
S2.3.3 and acquisition ofCalculating the average value of the obtained road surface breakage coefficients of each section in the kth 1 type road in the kth distribution route to obtain the breakage degree corresponding to the kth 1 type road in the kth distribution route
Figure FDA0004056679070000046
Wherein Nkk represents the number of sections corresponding to the kth 1 type road in the kth delivery route.
6. The multi-user collaborative management system according to claim 5, wherein: the method for obtaining the distribution time of different distribution routes and the product loss rate in the distribution process by the logistics distribution information analysis module comprises the following steps:
S3.1, acquiring road condition sets of each distribution route obtained in the step S2.4;
s3.2, obtaining an influence value Gi (m) of average unit length per first unit length on the product loss rate of the ith category in a road with the breakage degree m in the historical data, wherein the first unit length is recorded as L0;
s3.3, when the product of the ith category passes through the kth delivery route, the product loss rate in the delivery process
Figure FDA0004056679070000051
Said->
Figure FDA0004056679070000052
Wherein Mk represents the number of types of the i-th kind of products passing through the road in the kth delivery route;
s3.4 obtaining the delivery time of the ith product type through the kth delivery route
Figure FDA0004056679070000053
The said
Figure FDA0004056679070000054
wherein ,
Figure FDA0004056679070000055
indicating the speed of the vehicle when the product of the ith category is delivered through the kth 1-type road in the kth delivery route, without being affected by the road breakage degree, < + >>
Figure FDA0004056679070000056
And obtaining through database query.
7. A multi-user collaborative management method based on a logistics supply chain using the multi-user collaborative management system based on a logistics supply chain according to any one of claims 1-6, characterized in that: the method comprises the following steps:
s1, acquiring the serial number of the product category of a customer order, the order quantity DL, the order specified time DT and the receiving place P2 through an order information acquisition module;
S2, monitoring production departments in a supply chain through a production information analysis module to obtain a relation curve of production rate and qualification rate of each product type in the production process;
s3, acquiring natural damage rate of each product type in the storage process through a storage loss data monitoring module;
s4, in the logistics distribution information analysis module, different distribution routes are planned according to the relation between the position of the warehouse department and the order receiving place, road conditions in the different distribution routes are obtained, and distribution time of the different distribution routes and product loss rate in the distribution process are obtained;
s5, a supply scheme generating module is combined with information in the order information acquisition module, the production information analysis module, the storage loss data monitoring module and the logistics distribution information analysis module to acquire a supply scheme corresponding to a customer order;
s6, obtaining the supply scheme corresponding to the customer order obtained by the supply scheme generating module through the supply data adjusting module, and screening out the optimal supply scheme of the customer order.
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