CN116720802A - Logistics planning intelligent processing system based on artificial intelligence - Google Patents
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Abstract
The invention discloses an intelligent logistics planning processing system based on artificial intelligence, relates to the technical field of logistics planning, and solves the technical problem that in the prior art, targeted logistics planning cannot be performed under different demand matching strengths of stores and suppliers; after the logistics supply line in the planning center is detected normally, the data characteristic analysis platform performs data characteristic analysis on the regional end and the supply end, so that the regional end and the supply end are guaranteed to be qualified in corresponding logistics planning, planning of the supply end can be guaranteed to achieve early warning, planning change can be performed according to real-time data, meanwhile, the regional end is subjected to service demand analysis and logistics planning in cooperation with the supply end, accuracy of logistics planning adjustment is improved, logistics planning of the supply end is performed according to requirements of the regional end at different moments, and the supply efficiency of the supply end is maximized while the requirements of the regional end are met.
Description
Technical Field
The invention relates to the technical field of logistics planning, in particular to an artificial intelligence-based logistics planning intelligent processing system.
Background
In the prior art, in the logistics distribution process between a store and a supplier, the existing logistics route cannot be detected, logistics planning cannot be performed after detection, meanwhile, under the condition of different demand matching strengths of the store and the supplier, targeted logistics planning cannot be performed, so that logistics planning efficiency is reduced, in addition, real-time early warning cannot be performed after planning is completed, and timely adjustment cannot be performed when logistics planning deviates;
in view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to solve the problems, and provides an artificial intelligence-based logistics planning intelligent processing system.
The aim of the invention can be achieved by the following technical scheme: the logistics planning intelligent processing system based on the artificial intelligence comprises a regional end, a planning center and a supply end, wherein the regional end is in communication connection with a plurality of stores, the supply end is in communication connection with a plurality of suppliers, the regional end and the supply end perform signal transmission and logistics distribution under the data transmission of the planning center, and in the logistics distribution process, the planning center sends instructions to a data characteristic analysis platform and a planning intelligent early warning platform to perform planning analysis on logistics between the regional end and the supply end;
the regional end gathers demand instructions of stores and sends the demand instructions and corresponding stores to a planning center, after the planning center receives the demand instructions, the supply end sends the demand instructions to suppliers and sends feedback instructions and corresponding suppliers to the planning center after the suppliers make instruction feedback, the planning center establishes data communication between the stores and the suppliers, a communication closed loop is formed, logistics detection is carried out on the corresponding stores and the suppliers in the communication closed loop process, after a logistics supply line in the planning center passes the detection, a data feature analysis platform carries out data feature analysis on the regional end and the supply end, logistics planning is carried out through the data feature analysis, and after the planning center carries out logistics planning through the data feature analysis on the regional end and the supply end, a planning intelligent early warning platform carries out early warning on logistics distribution of the regional end and the supply end.
As a preferred embodiment of the present invention, the flow detection process is as follows:
marking a logistics route corresponding to a supplier and a store as a logistics supply line, setting a label i as a natural number larger than 1, and acquiring buffer time between the store demand time and the supplier supply time in the logistics supply line and the advance of the store actual receiving end time and the preset receiving end time; acquiring the ratio of the quantity of goods meeting the demands of a store in the real-time supply quantity of suppliers in a logistics supply line;
obtaining a detection coefficient Ci of a real-time logistics supply line in a planning center through analysis; and comparing the detection coefficient Ci of the real-time logistics supply line in the planning center with a detection coefficient threshold value.
As a preferred embodiment of the present invention, if the detection coefficient Ci of the real-time logistics supply line in the planning center exceeds the detection coefficient threshold, determining that the corresponding logistics supply line is abnormal in detection, and re-matching the store and the supplier of the corresponding logistics supply line by the planning center; if the detection coefficient Ci of the real-time logistics supply line in the planning center does not exceed the detection coefficient threshold value, the corresponding logistics supply line is judged to be detected normally.
As a preferred embodiment of the invention, after the logistics supply line in the planning center is detected to be normal, the data characteristic analysis platform analyzes the demand of the regional end, obtains the time difference between the maximum demand period and the minimum demand period of the goods covered by the store in the regional end and the maximum difference between the waiting time of the corresponding supply of the goods covered by the store, and compares the time difference.
As a preferred implementation manner of the invention, if the difference value of the time length between the maximum demand period and the minimum demand period of the goods covered by the store in the regional end exceeds the period time length difference threshold value, or the maximum difference value of the time length of the goods covered by the store corresponding to the supply waiting time length exceeds the time length maximum difference threshold value, the logistics demand intensity of the current regional covered store in the regional end is judged to be small, and the corresponding regional end covered area is marked as an easy-to-regulate region; if the difference value of the time length of the maximum demand period and the minimum demand period of the goods covered by the store in the regional end does not exceed the period time length difference value threshold value, and the maximum difference value of the time length of the goods covered by the store corresponding to the supply waiting time length does not exceed the time length maximum difference value threshold value, judging that the logistics demand intensity of the current regional covered store in the regional end is high, and marking the corresponding regional end covered region as a difficult-to-regulate region.
As a preferred embodiment of the invention, the number of the logistics routes intersected at the position of the regional end store and the vehicle traffic of the corresponding intersected logistics routes are obtained, the number of the logistics routes intersected at the position of the regional end store and the vehicle traffic of the corresponding intersected logistics routes are analyzed, and if any value of the number of the logistics routes intersected at the position of the regional end store and the vehicle traffic of the corresponding intersected logistics routes exceeds a corresponding threshold value, the current region of the corresponding regional end is marked as an easy-to-distribute region; and if any numerical value of the number of the stream routes intersected at the position of the regional end store and the vehicle traffic of the corresponding intersected stream route does not exceed the corresponding threshold value, marking the current region of the corresponding regional end as a difficult-to-distribute region.
As a preferred embodiment of the invention, the areas are divided into areas difficult to regulate and distribute, areas easy to regulate and distribute and areas easy to regulate and distribute according to the types of coverage areas at the end of the areas.
As a preferred embodiment of the invention, planning analysis is carried out on a supply end which is in logistics distribution with an area end, a difficult-to-regulate and difficult-to-regulate area and an easy-to-regulate and difficult-to-regulate area are uniformly marked as a planning reference area, and the difficult-to-regulate and easy-to-regulate area is uniformly marked as a non-planning reference area; and the instantaneous increase distribution quantity ratio difference of the planned reference area and the non-planned reference area at the same time and the distribution quantity continuous increase speed excess quantity of the planned reference area and the non-planned reference area at the same time in the real-time logistics distribution process are obtained, and the instantaneous increase distribution quantity ratio difference of the planned reference area and the non-planned reference area at the same time and the distribution quantity continuous increase speed excess quantity of the planned reference area and the non-planned reference area at the same time in the real-time logistics distribution process are analyzed.
As a preferred implementation manner of the invention, if the instantaneous increase delivery volume ratio difference of the planned reference area and the non-planned reference area exceeds the ratio difference threshold value and the delivery volume continuous increase speed of the planned reference area and the non-planned reference area exceeds the excess volume threshold value in the real-time logistics delivery process, the logistics plan of the current supply end is set to be a high-speed delivery plan;
if the instantaneous increasing distribution quantity ratio difference of the planning reference area and the non-planning reference area exceeds the ratio difference threshold value and the distribution quantity continuous increasing speed of the planning reference area and the non-planning reference area does not exceed the multi-output threshold value in the real-time logistics distribution process, the logistics plan of the current supply end is set to be a route intersection plan;
if the instantaneous increasing distribution quantity ratio difference of the planning reference area and the non-planning reference area does not exceed the ratio difference threshold value in the real-time logistics distribution process and the distribution quantity continuous increasing speed of the planning reference area and the non-planning reference area exceeds the excessive quantity threshold value, the logistics planning of the current supply end is set to be high-quality planning;
and if the instantaneous increasing distribution quantity ratio difference of the planned reference area and the non-planned reference area at the same time in the real-time logistics distribution process does not exceed the ratio difference threshold value and the distribution quantity continuous increasing speed of the planned reference area and the non-planned reference area does not exceed the multi-output quantity threshold value, setting the logistics plan of the current supply end as a cost-reducing plan.
As a preferred embodiment of the present invention, the high-speed delivery plan is specifically implemented as: distributing the goods storage points of the suppliers and selecting addresses according to each store area; the route intersection planning is specifically performed as follows: intersection planning is carried out on the distribution route of the store corresponding to the regional end, and the quantity of stores in the planned reference region and the non-planned reference region in the distribution route is set in proportion; the high quality planning is specifically performed as: setting corresponding goods supply qualification rate of stores in the regional end, and ensuring the goods supply qualification rate when easy distribution is performed; the cost reduction planning is specifically implemented as follows: controlling the number of distributed warehouse points in the supply end and the current warehouse storage amount, and reducing the input cost of the supply end when the regional end service requirement is met; and carrying out logistics planning of the supply end according to the requirements of the regional end at different moments.
As a preferred implementation mode of the invention, after the regional end and the supply end carry out logistics planning through data feature analysis, the planning intelligent early warning platform acquires real-time logistics distribution time periods of the regional end and the supply end, carries out analysis early warning on the corresponding logistics distribution time periods, acquires the numerical deviation amount of the actual planning parameters and the preset planning parameters of the real-time logistics route corresponding to the planning reference region in the logistics distribution time periods and the shortening speed of the numerical deviation of the planning parameters in the using process of the real-time logistics route, and analyzes the numerical deviation amount.
As a preferred implementation manner of the invention, if the numerical deviation of the actual planning parameter and the preset planning parameter of the real-time logistics route corresponding to the planning reference area exceeds a numerical deviation threshold, or the shortening speed of the numerical deviation corresponding to the planning parameter exceeds a shortening speed threshold in the using process of the real-time logistics route, determining that the real-time logistics route in the planning center is normally planned; if the numerical deviation of the actual planning parameter and the preset planning parameter of the real-time logistics route corresponding to the planning reference area does not exceed the numerical deviation threshold, and the shortening speed of the planning parameter corresponding to the numerical deviation does not exceed the shortening speed threshold in the using process of the real-time logistics route, judging that the real-time logistics route in the planning center is abnormal, and carrying out data analysis and re-matching on the corresponding area end and the supply end.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, the planning center establishes data communication between the store and the supplier, forms a communication closed loop, and carries out logistics detection on the corresponding store and the supplier in the communication closed loop process, so that whether the logistics distribution of the corresponding store and the supplier is qualified or not is judged, the logistics efficiency is in an optimal state, and the high efficiency and timeliness of logistics planning are ensured.
2. According to the invention, after the logistics supply line in the planning center is detected normally, the data characteristic analysis platform performs data characteristic analysis on the regional end and the supply end, so that the regional end and the supply end are ensured to be qualified in corresponding logistics planning, the planning of the supply end can be ensured to achieve early warning, planning change can be performed according to real-time data, meanwhile, the regional end is subjected to service demand analysis, and logistics planning is performed by matching with the supply end, so that the accuracy of logistics planning adjustment is improved; and carrying out logistics planning of the supply end according to the requirements of the area end at different moments, and maximizing the supply efficiency of the supply end while meeting the requirements of the area end.
3. According to the logistics planning system and method, after the regional end and the supply end carry out logistics planning through the data feature analysis, the intelligent planning early warning platform carries out planning early warning on logistics distribution of the regional end and the supply end, real-time logistics distribution is guaranteed to be qualified, the situation that the logistics planning cannot be adjusted in time when deviation exists is avoided, and the qualification and the high efficiency of logistics planning are improved.
Drawings
The present invention is further described below with reference to the accompanying drawings for the convenience of understanding by those skilled in the art.
FIG. 1 is a schematic block diagram of the present invention;
fig. 2 is a schematic flow chart of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, 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.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
Referring to fig. 1-2, an artificial intelligence-based logistics planning intelligent processing system comprises a regional end, a planning center and a supply end, wherein the regional end is in communication connection with a plurality of stores, the regional end is used as a signal transit point of the stores, the supply end is in communication connection with a plurality of suppliers, the supply end is used as a signal transit point of the suppliers, the regional end and the supply end perform signal transmission and logistics distribution under the data transmission of the planning center, and in the logistics distribution process, the planning center sends instructions to a data characteristic analysis platform and a planning intelligent early warning platform to perform planning analysis on logistics between the regional end and the supply end;
the regional end gathers the demand instruction of the store and sends the demand instruction and the corresponding store to the planning center, after the planning center receives the demand instruction, the supply end sends the demand instruction to the supplier, and after the supplier gives instruction feedback, the feedback instruction and the corresponding supplier are sent to the planning center, the planning center establishes data communication between the store and the supplier, a communication closed loop is formed, and the corresponding store and the supplier are subjected to logistics detection in the communication closed loop process, so that whether the corresponding store and the supplier are subjected to logistics distribution is judged to be qualified or not, the logistics efficiency is in an optimal state, and the high efficiency and timeliness of logistics planning are ensured;
marking a logistics route corresponding to a supplier and a store as a logistics supply line, setting a label i, wherein i is a natural number larger than 1, acquiring buffer time of a store demand time and a supplier supply time in the logistics supply line and advance of an actual receiving end time and a preset receiving end time of the store, and marking the buffer time of the store demand time and the supplier supply time in the logistics supply line and the advance of the actual receiving end time and the preset receiving end time of the store as HCSi and TQLi respectively; acquiring the ratio of the quantity of the store meeting the demand in the real-time supply quantity of the supplier in the logistics supply line, and marking the ratio of the quantity of the store meeting the demand in the real-time supply quantity of the supplier in the logistics supply line as HLZi;
by the formulaAcquiring a detection coefficient Ci of a real-time logistics supply line in a planning center, wherein y1, y2 and y3 are preset proportional coefficients, y1 is more than y2 and y3 is more than 0, beta is an error correction factor, and the value is 0.98;
comparing the detection coefficient Ci of the real-time logistics supply line in the planning center with a detection coefficient threshold value:
if the detection coefficient Ci of the real-time logistics supply line in the planning center exceeds the detection coefficient threshold, judging that the corresponding logistics supply line is abnormal in detection, and re-matching the store and the supplier of the corresponding logistics supply line by the planning center; if the detection coefficient Ci of the real-time logistics supply line in the planning center does not exceed the detection coefficient threshold value, judging that the corresponding logistics supply line is detected normally;
after the logistics supply line in the planning center is detected normally, the data characteristic analysis platform performs data characteristic analysis on the regional end and the supply end, so that the regional end and the supply end are ensured to be qualified in corresponding logistics planning, the planning of the supply end can be ensured to achieve early warning, planning change can be performed according to real-time data, meanwhile, the regional end is subjected to service demand analysis, and logistics planning is performed by matching with the supply end, so that the accuracy of logistics planning adjustment is improved;
the method comprises the steps of carrying out demand analysis on an area end, obtaining a time length difference value between a maximum demand period and a minimum demand period of goods covered by a store in the area end and a maximum difference value of a waiting time length of corresponding supply of goods covered by the store, and comparing the time length difference value between the maximum demand period and the minimum demand period of the goods covered by the store in the area end and the maximum difference value of the waiting time length of corresponding supply of goods covered by the store with a cycle time length difference value threshold value and a time length maximum difference value threshold value respectively:
if the difference value of the time length of the maximum demand period and the minimum demand period of the goods covered by the store in the regional end exceeds the period time length difference value threshold, or the maximum difference value of the time length of the goods covered by the store corresponding to the supply waiting time length exceeds the time length maximum difference value threshold, judging that the logistics demand intensity of the current regional covered store in the regional end is small, and marking the corresponding regional end coverage area as an easy-to-regulate region; if the difference value of the time length of the maximum demand period and the minimum demand period of the goods covered by the store in the regional end does not exceed the period time length difference value threshold value, and the maximum difference value of the time length of the goods covered by the store corresponding to the supply waiting time length does not exceed the time length maximum difference value threshold value, judging that the logistics demand intensity of the current regional covered store in the regional end is high, and marking the corresponding regional end covered region as a difficult-to-regulate region;
acquiring the number of the logistics routes intersected at the positions of the regional end stores and the vehicle traffic corresponding to the intersected logistics routes, analyzing the number of the logistics routes intersected at the positions of the regional end stores and the vehicle traffic corresponding to the intersected logistics routes, and marking the current region corresponding to the regional end as an easy-to-distribute region if any value of the number of the logistics routes intersected at the positions of the regional end stores and the vehicle traffic corresponding to the intersected logistics routes exceeds a corresponding threshold value; if any numerical value of the number of the stream routes intersected at the position of the regional end store and the vehicle traffic of the corresponding intersected stream route does not exceed the corresponding threshold value, marking the current region of the corresponding regional end as a difficult-to-distribute region;
the method comprises the steps of dividing the area end coverage area into an area difficult to regulate and control, an area easy to regulate and control and easy to distribute according to the type of the area end coverage area;
planning and analyzing a supply end which is in logistics distribution with a regional end, uniformly marking a difficult-to-regulate and difficult-to-distribute region and an easy-to-regulate and difficult-to-distribute region as planning reference regions, and uniformly marking the difficult-to-regulate and easy-to-distribute region as non-planning reference regions; the method comprises the steps of obtaining the instantaneous increase distribution quantity ratio difference of a planned reference area and a non-planned reference area at the same time in the real-time logistics distribution process and the distribution quantity continuous increase speed excess quantity of the planned reference area and the non-planned reference area, and analyzing the instantaneous increase distribution quantity ratio difference of the planned reference area and the non-planned reference area at the same time and the distribution quantity continuous increase speed excess quantity of the planned reference area and the non-planned reference area in the real-time logistics distribution process;
if the instantaneous increasing distribution amount ratio difference of the planned reference area and the non-planned reference area exceeds the ratio difference threshold value and the distribution amount continuously increasing speed of the planned reference area and the non-planned reference area exceeds the excess amount threshold value in the real-time logistics distribution process, the logistics plan of the current supply end is set to be a high-speed distribution plan, and it can be understood that the regional end service requirement is high-efficiency distribution under the current data analysis result, so that the high-speed distribution plan fits the current regional requirement, wherein the high-speed distribution plan is specifically implemented as follows: distributing the goods storage points of the suppliers and selecting addresses according to each store area, so that the demands of stores are met while the concentrated storage pressure is reduced;
if the instantaneous increasing distribution amount ratio difference of the planned reference area and the non-planned reference area exceeds the ratio difference threshold value and the distribution amount continuous increasing speed and the excessive amount of the planned reference area and the non-planned reference area do not exceed the excessive amount threshold value in the real-time logistics distribution process, the logistics plan of the current supply end is set as the route intersection plan, and it can be understood that the requirement of the current area end at the same time is large, but the area regulation is convenient, namely the route intersection plan is specifically implemented as follows: intersection planning is carried out on the distribution routes of the stores corresponding to the regional ends, the quantity of stores in the planned reference area and the non-planned reference area in the distribution routes is set in proportion, and stores in the planned reference area and the non-planned reference area in the same distribution route are required to be screened according to the actual distance and distribution cost of the stores;
if the instantaneous increasing distribution quantity duty ratio difference of the planned reference area and the non-planned reference area does not exceed the duty ratio difference threshold value at the same time in the real-time logistics distribution process and the distribution quantity continuous increasing speed of the planned reference area and the non-planned reference area exceeds the excessive quantity threshold value, the logistics planning of the current supply end is set to be high-quality planning, namely the high-quality planning is specifically executed as follows: setting corresponding goods supply qualification rate of stores in the regional end, ensuring the goods supply qualification rate when easy distribution is performed, and avoiding the increase of cost of secondary distribution;
if the instantaneous increasing distribution quantity duty ratio difference of the planning reference area and the non-planning reference area does not exceed the duty ratio difference threshold value at the same time in the real-time logistics distribution process and the distribution quantity continuous increasing speed of the planning reference area and the non-planning reference area does not exceed the multi-output threshold value, the logistics planning of the current supply end is set as the cost-reducing planning, namely the cost-reducing planning is specifically implemented as follows: controlling the number of distributed warehouse points in the supply end and the current warehouse storage amount, and reducing the input cost of the supply end when the regional end service requirement is met;
carrying out logistics planning of the supply end according to the requirements of the area end at different moments, and maximizing the supply efficiency of the supply end while meeting the requirements of the area end;
after the regional end and the supply end carry out logistics planning through data feature analysis, the planning intelligent early warning platform carries out planning early warning on logistics distribution of the regional end and the supply end, so that real-time logistics distribution is qualified, the situation that the logistics planning cannot be adjusted in time when deviation exists is avoided, and the qualification and the high efficiency of logistics planning are improved;
acquiring real-time logistics distribution time periods of an area end and a supply end, analyzing and pre-warning the corresponding logistics distribution time periods, acquiring the numerical deviation amount of the actual planning parameters and the preset planning parameters of the real-time logistics route corresponding to the planning reference area and the shortening speed of the numerical deviation of the planning parameters in the use process of the real-time logistics route in the logistics distribution time periods, and analyzing the numerical deviation amount of the actual planning parameters and the preset planning parameters of the real-time logistics route corresponding to the planning reference area and the shortening speed of the numerical deviation of the planning parameters in the use process of the real-time logistics route; the planning parameter is represented as a parameter aimed by planning, such as cost reduction planning, and the planning parameter is cost; the corresponding planning parameter of the high-speed delivery plan is speed, and the corresponding planning parameter of the route intersection plan is the proportion of delivered goods; the corresponding planning parameter of the high-quality planning is the distribution qualification rate;
if the numerical deviation value of the actual planning parameter and the preset planning parameter of the real-time logistics route corresponding to the planning reference area exceeds a numerical deviation value threshold, or the shortening speed of the planning parameter corresponding to the numerical deviation exceeds a shortening speed threshold in the using process of the real-time logistics route, judging that the real-time logistics route in the planning center is normally planned; if the numerical deviation of the actual planning parameter and the preset planning parameter of the real-time logistics route corresponding to the planning reference area does not exceed the numerical deviation threshold, and the shortening speed of the planning parameter corresponding to the numerical deviation does not exceed the shortening speed threshold in the using process of the real-time logistics route, judging that the real-time logistics route in the planning center is abnormal, and carrying out data analysis and re-matching on the corresponding area end and the supply end.
When the intelligent early warning system is used, the regional end gathers demand instructions of shops and sends the demand instructions and corresponding shops to the planning center, after the planning center receives the demand instructions, the supply end sends the demand instructions to the suppliers, after the suppliers make instruction feedback, the feedback instructions and the corresponding suppliers are sent to the planning center, the planning center establishes data communication between the shops and the suppliers, a communication closed loop is formed, the corresponding shops and the suppliers are subjected to logistics detection in the communication closed loop process, after a logistics supply line in the planning center passes detection, the data feature analysis platform performs data feature analysis on the regional end and the supply end, logistics planning is performed through the data feature analysis, and after the planning center performs logistics planning through the data feature analysis, the intelligent early warning platform performs planning early warning on logistics distribution of the regional end and the supply end.
The formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to a true value, and coefficients in the formulas are set by a person skilled in the art according to actual conditions; the preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (12)
1. The logistics planning intelligent processing system based on the artificial intelligence is characterized by comprising an area end, a planning center and a supply end, wherein the area end is in communication connection with a plurality of stores, the supply end is in communication connection with a plurality of suppliers, the area end and the supply end perform signal transmission and logistics distribution under the data transmission of the planning center, and in the logistics distribution process, the planning center sends instructions to a data characteristic analysis platform and a planning intelligent early warning platform to perform planning analysis on logistics between the area end and the supply end;
the regional end gathers demand instructions of stores and sends the demand instructions and corresponding stores to a planning center, after the planning center receives the demand instructions, the supply end sends the demand instructions to suppliers and sends feedback instructions and corresponding suppliers to the planning center after the suppliers make instruction feedback, the planning center establishes data communication between the stores and the suppliers, a communication closed loop is formed, logistics detection is carried out on the corresponding stores and the suppliers in the communication closed loop process, after a logistics supply line in the planning center passes the detection, a data feature analysis platform carries out data feature analysis on the regional end and the supply end, logistics planning is carried out through the data feature analysis, and after the planning center carries out logistics planning through the data feature analysis on the regional end and the supply end, a planning intelligent early warning platform carries out early warning on logistics distribution of the regional end and the supply end.
2. The intelligent logistics planning processing system of claim 1, wherein the logistics detection process comprises:
marking a logistics route corresponding to a supplier and a store as a logistics supply line, setting a label i as a natural number larger than 1, and acquiring buffer time between the store demand time and the supplier supply time in the logistics supply line and the advance of the store actual receiving end time and the preset receiving end time; acquiring the ratio of the quantity of goods meeting the demands of a store in the real-time supply quantity of suppliers in a logistics supply line;
obtaining a detection coefficient Ci of a real-time logistics supply line in a planning center through analysis; and comparing the detection coefficient Ci of the real-time logistics supply line in the planning center with a detection coefficient threshold value.
3. The intelligent logistics planning processing system based on artificial intelligence according to claim 2, wherein if the detection coefficient Ci of the real-time logistics supply line in the planning center exceeds the detection coefficient threshold, determining that the corresponding logistics supply line is abnormal in detection, and the planning center re-matches the store and the supplier of the corresponding logistics supply line; if the detection coefficient Ci of the real-time logistics supply line in the planning center does not exceed the detection coefficient threshold value, the corresponding logistics supply line is judged to be detected normally.
4. The intelligent logistics planning processing system based on artificial intelligence according to claim 3, wherein after the logistics supply line in the planning center is detected to be normal, the data feature analysis platform analyzes the demand of the regional end, obtains the time difference between the maximum demand period and the minimum demand period of the goods covered by the store in the regional end and the maximum difference between the waiting time of the goods covered by the store corresponding to the supply, and compares the time difference.
5. The intelligent logistics planning processing system based on artificial intelligence according to claim 4, wherein if a difference between a period of time of a maximum demand period and a period of time of a minimum demand period of goods covered by a store in an area exceeds a period time difference threshold, or a maximum difference between a period of time of a waiting time of corresponding supply of goods covered by the store exceeds a period time maximum difference threshold, it is determined that the logistics demand intensity of the current area of the area end covering the store is small, and the coverage area of the corresponding area end is marked as an easy-to-regulate area; if the difference value of the time length of the maximum demand period and the minimum demand period of the goods covered by the store in the regional end does not exceed the period time length difference value threshold value, and the maximum difference value of the time length of the goods covered by the store corresponding to the supply waiting time length does not exceed the time length maximum difference value threshold value, judging that the logistics demand intensity of the current regional covered store in the regional end is high, and marking the corresponding regional end covered region as a difficult-to-regulate region.
6. The intelligent logistics planning processing system based on artificial intelligence according to claim 5, wherein the number of the logistics routes intersected at the position of the regional end store and the vehicle traffic corresponding to the intersected logistics routes are obtained, the number of the logistics routes intersected at the position of the regional end store and the vehicle traffic corresponding to the intersected logistics routes are analyzed, and if any value of the number of the logistics routes intersected at the position of the regional end store and the vehicle traffic corresponding to the intersected logistics routes exceeds a corresponding threshold value, the current region corresponding to the regional end is marked as an easy-to-distribute region; and if any numerical value of the number of the stream routes intersected at the position of the regional end store and the vehicle traffic of the corresponding intersected stream route does not exceed the corresponding threshold value, marking the current region of the corresponding regional end as a difficult-to-distribute region.
7. The intelligent logistics planning system based on artificial intelligence of claim 6, wherein the areas are divided into difficult-to-control and difficult-to-dispatch areas, easy-to-control and difficult-to-dispatch areas and easy-to-control and easy-to-dispatch areas according to the type of the coverage area of the area end.
8. The intelligent logistics planning processing system based on artificial intelligence according to claim 7, wherein a supply end of logistics distribution with an area end is subjected to planning analysis, difficult-to-control and difficult-to-distribute areas and easy-to-control and difficult-to-distribute areas are uniformly marked as planning reference areas, and difficult-to-control and easy-to-distribute areas are uniformly marked as non-planning reference areas; and the instantaneous increase distribution quantity ratio difference of the planned reference area and the non-planned reference area at the same time and the distribution quantity continuous increase speed excess quantity of the planned reference area and the non-planned reference area at the same time in the real-time logistics distribution process are obtained, and the instantaneous increase distribution quantity ratio difference of the planned reference area and the non-planned reference area at the same time and the distribution quantity continuous increase speed excess quantity of the planned reference area and the non-planned reference area at the same time in the real-time logistics distribution process are analyzed.
9. The intelligent logistics planning processing system based on artificial intelligence according to claim 8, wherein if the instantaneous increase distribution ratio difference of the planned reference area and the non-planned reference area exceeds the duty ratio difference threshold value at the same time in the real-time logistics distribution process, and the distribution amount of the planned reference area and the non-planned reference area continuously increases more than the excess amount threshold value, the logistics plan of the current supply end is set as a high-speed distribution plan;
if the instantaneous increasing distribution quantity ratio difference of the planning reference area and the non-planning reference area exceeds the ratio difference threshold value and the distribution quantity continuous increasing speed of the planning reference area and the non-planning reference area does not exceed the multi-output threshold value in the real-time logistics distribution process, the logistics plan of the current supply end is set to be a route intersection plan;
if the instantaneous increasing distribution quantity ratio difference of the planning reference area and the non-planning reference area does not exceed the ratio difference threshold value in the real-time logistics distribution process and the distribution quantity continuous increasing speed of the planning reference area and the non-planning reference area exceeds the excessive quantity threshold value, the logistics planning of the current supply end is set to be high-quality planning;
and if the instantaneous increasing distribution quantity ratio difference of the planned reference area and the non-planned reference area at the same time in the real-time logistics distribution process does not exceed the ratio difference threshold value and the distribution quantity continuous increasing speed of the planned reference area and the non-planned reference area does not exceed the multi-output quantity threshold value, setting the logistics plan of the current supply end as a cost-reducing plan.
10. The intelligent logistics planning system of claim 9, wherein the high-speed distribution planning is specifically implemented as: distributing the goods storage points of the suppliers and selecting addresses according to each store area; the route intersection planning is specifically performed as follows: intersection planning is carried out on the distribution route of the store corresponding to the regional end, and the quantity of stores in the planned reference region and the non-planned reference region in the distribution route is set in proportion; the high quality planning is specifically performed as: setting corresponding goods supply qualification rate of stores in the regional end, and ensuring the goods supply qualification rate when easy distribution is performed; the cost reduction planning is specifically implemented as follows: controlling the number of distributed warehouse points in the supply end and the current warehouse storage amount, and reducing the input cost of the supply end when the regional end service requirement is met; and carrying out logistics planning of the supply end according to the requirements of the regional end at different moments.
11. The intelligent logistics planning processing system based on artificial intelligence according to claim 10, wherein after the planning center performs logistics planning on the regional end and the supply end through data feature analysis, the intelligent planning early warning platform acquires real-time logistics distribution time periods of the regional end and the supply end, performs analysis early warning on the corresponding logistics distribution time periods, acquires numerical deviation amounts of actual planning parameters and preset planning parameters of a real-time logistics route corresponding to a planning reference region in the logistics distribution time periods, and shortens the numerical deviation speeds of the planning parameters corresponding to the numerical deviation in the use process of the real-time logistics route, and analyzes the numerical deviation amounts.
12. The intelligent logistics planning processing system based on artificial intelligence according to claim 11, wherein if the numerical deviation between the actual planning parameter and the preset planning parameter of the real-time logistics route corresponding to the planning reference area exceeds a numerical deviation threshold, or the shortening speed of the numerical deviation corresponding to the planning parameter exceeds a shortening speed threshold in the using process of the real-time logistics route, determining that the real-time logistics route planning in the planning center is normal; if the numerical deviation of the actual planning parameter and the preset planning parameter of the real-time logistics route corresponding to the planning reference area does not exceed the numerical deviation threshold, and the shortening speed of the planning parameter corresponding to the numerical deviation does not exceed the shortening speed threshold in the using process of the real-time logistics route, judging that the real-time logistics route in the planning center is abnormal, and carrying out data analysis and re-matching on the corresponding area end and the supply end.
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