Goods allocation method and system in industrial area

Abstract

The invention belongs to the technical field of logistics allocation, and provides a cargo allocation method and system for an industrial area. The number of goods is obtained in real time; performing big data analysis according to the cargo quantity to obtain a cargo supply stable time period; after a logistics center receives an order, warehouses are screened according to the stable supply time period of goods corresponding to the order by each warehouse, alternative warehouses are dynamically optimized and adjusted in real time according to analysis of a transportation path and resource allocation, excessive dependence on a single shortest path is avoided by selecting the warehouses in the alternative warehouses for delivery, the bottleneck effect is reduced, and the delivery efficiency is improved. The chain type influence caused by shortest path selection can be effectively relieved, the stability and reliability of a supply chain are ensured, and therefore the problem of intermittent supply interruption in a range is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of logistics allocation, and in particular relates to a method and system for allocating goods in an industrial area. Background Art

[0002] In industrial areas such as machinery, assembly, and manufacturing, since modern industry generally uses assembly lines and industrial robots for rapid production, the required raw materials and output of goods are very large. In many cases, the production workshop of the previous process is not located in the same area as the production workshop of the next process, and the production speed and production efficiency of the previous process and the next process are different due to the technical difficulty, degree of automation, and production scale of the process. For example, in the first case, the production speed of the previous process is very fast, and the production speed of the next process is slow; in the second case, the production speed of the previous process is slow, and the production speed of the next process is fast; in the first case, the production speed difference between the two production workshops will lead to a large backlog of goods produced by the previous process production workshop, while in the second case, the next process will stagnate; this situation is particularly prominent when the two workshops are not in the same industrial area, and the transportation of goods between them needs to be carried out through logistics deployment. The goods produced by the first workshop need to be stored in the warehouse, and the stagnant state of logistics has caused supply chain problems in the industrial area.

[0003] To solve the above problems, for example, a Chinese invention patent with publication number CN111080171A discloses a logistics allocation method based on a logistics allocation algorithm. By setting a central resource allocation point that can increase the amount of goods, the shortest path from each resource allocation point to each regional distribution center is determined, and then the total time consumed for delivering goods at each resource allocation point is used to adjust the amount of goods allocated to each resource allocation point, thereby ensuring the amount of goods at the resource allocation point and the optimal path, and improving logistics efficiency. However, in the peak season with a large number of orders, when the resource allocation point supplies multiple different industrial areas at the same time, the selection of the shortest path will affect the supply of goods in other industrial areas, thereby generating a chain effect, resulting in a range of intermittent supply interruptions. For example, a logistics center or distribution center that a shortest path passes through may be overloaded because it undertakes a large number of cargo transportation tasks. At the same time, the resources of the logistics centers and distribution centers on other paths may be idle or underutilized. This unbalanced resource allocation will lead to a decline in the supply capacity of some areas, thereby causing fluctuations in the supply chain. Summary of the invention

[0004] The purpose of the present invention is to propose a method and system for allocating goods in an industrial area to solve one or more technical problems existing in the prior art and at least provide a beneficial option or create conditions.

[0005] To achieve the above object, according to one aspect of the present invention, there is provided a method for allocating goods in an industrial area, and the method for allocating goods in an industrial area includes the following steps: S100, constructing a logistics allocation network; the logistics allocation network includes a logistics center, a distribution center and a warehouse; S200, obtaining the quantity of goods in the logistics center, distribution center and warehouse in the logistics allocation network in real time; S300, analyzing big data according to the quantity of goods to obtain a stable supply period; S400, after the logistics center receives an order, screening warehouses according to the stable supply period of the corresponding goods in each warehouse for the order.

[0006] Further, in S100, the location of the logistics center in the logistics allocation network is in the middle reaches of the logistics, which is the intermediate link between the warehouse and the distribution center; the distribution center distributes goods in each industrial area; after the logistics center obtains the orders from customers in the industrial area, it contacts the corresponding warehouse to deliver goods according to the quantity of goods required on the order. After the warehouse delivers the goods, the goods are transported to the logistics center through the logistics transportation path, and then the logistics center transports the goods to the distribution centers corresponding to each industrial area, and then the distribution center distributes the goods to the corresponding addresses on the order.

[0007] There are multiple paths for the logistics transportation of goods between each warehouse and the distribution center, between the logistics center and the distribution center, and between the distribution center and the industrial area. Among them, the goods are raw materials, mechanical parts, electrical components, mechanical equipment, lubricating oil, cleaning agents, etc. in the industrial area.

[0008] Preferably, the logistics center, the distribution center and the warehouse respectively correspond to the transfer and distribution station, the regional distribution center and the urban logistics warehouse in a Chinese invention patent with the publication number of CN111080171A, a logistics allocation method based on a logistics allocation algorithm.

[0009] Preferably, the path can be a navigation path between the warehouse and the distribution center, and between the logistics center and the distribution center generated by calling the Baidu Map or Gaode Map API.

[0010] Specifically: for the starting latitude, starting longitude between the warehouse and the distribution center, and the ending latitude, ending longitude between the logistics center and the distribution center, call the path planning interface of the Baidu Map or Gaode Map API through an HTTP request, then the path planning interface of the Baidu Map returns a JSON format response file, and perform JSON parsing on the JSON format response file to obtain the detailed information of the path. The detailed information of the path includes the route, distance, and estimated time (travel time).

[0011] Further, in S200, the method for obtaining the quantity of goods in the logistics center, distribution center, and warehouse in the logistics deployment network in real time is as follows: In the logistics center, distribution center, and warehouse, the information of the goods is read through a barcode scanner to obtain the quantity of goods in the current inventory; among them, the barcode scanner is a smartphone, a QR code scanner, or a barcode scanner.

[0012] Preferably, the quantity of goods in the current inventory collected in the logistics center, distribution center, and warehouse is uploaded to the cloud server through the network respectively. Specifically: The operator scans the barcode of each good, and the barcode scanner sends the goods information data corresponding to the barcode to the data upload module. The data upload module formats the data into JSON format and uploads it to the API interface of the cloud server through an HTTPS POST request. The cloud server receives the data and stores it in the database, and at the same time generates an inventory report.

[0013] In the logistics center, distribution center, and warehouse, the traditional shortest path selection between different regions and links may lead to an increase in the transportation priority of goods in some industrial regions, while the transportation of goods in other industrial regions is postponed or reduced. This poor coordination may lead to a decrease in the efficiency of the entire supply chain. Especially in the case of large demand fluctuations, the problem of intermittent out-of-stock will be more prominent. And transportation delays and insufficient inventory in the warehouse will further amplify the problem of intermittent out-of-stock, making it easier to have a widespread intermittent out-of-stock during peak demand periods or emergencies. To solve this problem, the present application provides the following solution to analyze the stable supply period based on the quantity of goods through big data: Further, in S300, the method for analyzing the stable supply period based on the quantity of goods through big data is as follows: According to the time sequence of obtaining the quantity of goods, the quantity of goods in the logistics center is formed into a sequence, denoted as the central logistics sequence HubL; According to the time sequence of obtaining the quantity of goods, the quantity of goods in each warehouse storing this good is formed into a sequence respectively, denoted as the warehousing logistics sequence, represented by ReL(i) for the i-th warehousing logistics sequence; where i is the serial number of the warehousing logistics sequence; Within the range of i values, analyze the stable supply period of each warehousing logistics sequence ReL(i) for the central logistics sequence HubL specifically as follows: Record the time of the most recent increase in the quantity of this good in the warehousing logistics sequence ReL(i) as the most recent replenishment in-stock time ReT(i); Calculate the stable supply ratio StabRat of the warehouse corresponding to ReL(i) to the logistics center from ReT(i) to the current time; Analyze the consumption acceleration period ConT(HubL) of the warehousing logistics sequence ReL(i) for the logistics center; The product of the supply stability ratio StabRat and the consumption acceleration period ConT(HubL) is used as the supply stability period.

[0014] Among them, the calculation method of the supply stability ratio StabRat is as follows: The ratio of MinReL and MaxReL is used as the supply stability ratio StabRat of the corresponding warehouse of ReL(i) to the logistics center from ReT(i) to the current time; where, MinReL is the absolute value of the non-zero difference between the minimum value of each cargo quantity obtained from ReT(i) to the current time in ReL(i) in the warehousing logistics sequence and the minimum value of each cargo quantity obtained from ReT(i) to the current time in the sequence HubL; MaxReL is the absolute value of the non-zero difference between the maximum value of each cargo quantity obtained from ReT(i) to the current time in ReL(i) in the warehousing logistics sequence and the maximum value of each cargo quantity obtained from ReT(i) to the current time in the sequence HubL. Among them, the analysis method of the consumption acceleration period ConT(HubL) of the warehousing logistics sequence ReL(i) for the logistics center is as follows: Taking the cargo quantity at time ReT(i) in ReL(i) as the comparison quantity; taking the maximum value of the difference between the value of each cargo quantity obtained from time ReT(i) to the current time in the sequence HubL and the comparison quantity as APM; taking the acquisition time of the cargo quantity corresponding to APM in HubL as UnT; and recording the time period from ReT(i) to UnT as ConT(HubL).

[0015] The analyzed supply stability period is the analysis of the time data of the supply stability of demand forecasting and the supply chain, predicting in advance the potential supply chain stable time period, so that the subsequent cargo allocation can avoid the peak demand period or the time period when emergencies occur, thereby reducing the chain effect caused by insufficient cargo supply due to problems such as transportation delays and insufficient inventory, greatly avoiding the problem of intermittent warehouse out-of-stock in a wide range, and improving the reliability of the supply chain of logistics allocation.

[0016] Furthermore, in S400, after the logistics center receives an order, the method of screening warehouses according to the supply stability period of each warehouse for the goods corresponding to the order is as follows: Obtain the transportation duration required for each warehouse to reach the logistics center; screen out all the corresponding warehouses whose supply stability period duration of the goods corresponding to the order is greater than the transportation duration required as alternative warehouses.

[0017] By dynamically optimizing and real-time adjusting alternative warehouses based on the analysis of transportation routes and resource allocation through the above methods, selecting warehouses from alternative warehouses for delivery avoids over-reliance on a single shortest path, reduces the bottleneck effect, can effectively alleviate the chain effect brought by the shortest path selection, ensures the stability and reliability of the supply chain, and thus reduces the occurrence of intermittent out-of-stock problems within a certain range.

[0018] Preferably, select the warehouse with the largest duration value of the supply stability period of the goods corresponding to the order as the delivery warehouse for the goods corresponding to the order among the alternative warehouses.

[0019] Furthermore, according to the time sequence of the quantity of goods required for the order, the quantities of goods in each warehouse storing the goods are respectively formed into a sequence, which is denoted as the warehousing logistics sequence of the goods required for the order, and SReL(j) represents the warehousing logistics sequence of the goods required for the j-th order; where j is the serial number; record the time of the most recent increase in the quantity of the goods in SReL(j) as the most recent replenishment-in time SReT(j); Record the time of the most recent decrease in the quantity of goods between SReT(j) and the order placement time in the central logistics sequence HubL as the most recent shipment time OuT(j); When OuT(j) is after the supply stability period of the goods corresponding to the order, select the warehouse with the largest duration value of the supply stability period of the goods corresponding to the order as the delivery warehouse for the goods corresponding to the order among the alternative warehouses; When OuT(j) is within the supply stability period of the goods corresponding to the order, lock the warehouse with the largest duration value of the supply stability period of the corresponding goods among the alternative warehouses. Locking means marking that the warehouse stops delivering the goods corresponding to the order, and calculate the supply stability period of the corresponding goods in this warehouse in real time until OuT(j) is within the supply stability period of the goods corresponding to the order, and use this warehouse as the delivery warehouse for the goods corresponding to the order. (When OuT(j) is within the supply stability period of the goods corresponding to the order, it means that the logistics center has taken goods from the warehouse during the time within the supply stability period, which will cause supply pressure on the corresponding warehouse, and the predicted supply stability period may not be able to hold, so the delivery time of the corresponding warehouse may not be within the stable supply time period, so it is necessary to wait for the re-predicted supply stability period to meet the conditions).

[0020] Based on the impact of the shipment time of the central logistics sequence itself on transportation routes and resource allocation through the above methods, accurately identify whether the delivery of this order will cause pressure on the supply chain and result in intermittent out-of-stock problems. By delaying the delivery of one order, other alternative warehouses will not cause intermittent out-of-stock to other orders, avoiding intermittent out-of-stock within a certain range.

[0021] Further, the method for obtaining the transportation time required from each warehouse to the logistics center is as follows: the shortest travel time from each warehouse to the logistics center is obtained through the Baidu Map API or the Amap API as the transportation time required.

[0022] Preferably, the method for obtaining the transportation time required from each warehouse to the logistics center is as follows: the transportation time required is a preset time.

[0023] Further, in S400, the order at least includes the order time (i.e., the time when the logistics center receives the order), the name of the goods, the quantity of the goods, the address and contact information of the goods demander.

[0024] The present invention also provides a goods allocation system for an industrial area, the system includes: a memory, a processor, and a computer program stored in the memory and operable on the processor, and the processor executes the computer program to run in the following units of the system: A goods quantity acquisition unit, configured to obtain the goods quantities of the logistics center, distribution centers, and warehouses in the logistics allocation network in real time; A supply data analysis unit, configured to perform big data analysis based on the goods quantities to obtain the stable supply periods; A supply warehouse screening unit, configured to screen warehouses according to the stable supply periods of each warehouse for the goods corresponding to the order after the logistics center receives the order.

[0025] The beneficial effects of the present invention are as follows: the present invention provides a goods allocation method and system for an industrial area, dynamically optimizes and adjusts alternative warehouses in real time according to the analysis of transportation routes and resource allocation, avoids over-reliance on a single shortest path by selecting warehouses from alternative warehouses for delivery, reduces the bottleneck effect, can effectively alleviate the chain effect brought by the shortest path selection, ensures the stability and reliability of the supply chain, and thus reduces the occurrence of widespread intermittent supply interruption problems. Description of the Drawings

[0026] By elaborating on the embodiments shown in conjunction with the drawings, the above and other features of the present invention will become more obvious. The same reference numerals in the drawings of the present invention represent the same or similar elements. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. In the drawings: Figure 1 Shows a flowchart of a goods allocation method for an industrial area; Figure 2 Shows a structural diagram of a goods allocation system for an industrial area. Detailed Embodiments

[0027] The concept, specific structure, and technical effects of the present invention will be clearly and completely described below in conjunction with the embodiments and the accompanying drawings to fully understand the purpose, solution, and effects of the present invention. It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other.

[0028] Embodiment 1 As Figure 1 shown is a flowchart of a method for goods allocation in an industrial area according to Embodiment 1. The following will be combined with Figure 1 to elaborate on a method for goods allocation in an industrial area according to Embodiment 1 of the present invention. The method includes the following steps: S100. Construct a logistics allocation network; the logistics allocation network includes a logistics center, a distribution center, and a warehouse; S200. Real-time obtain the quantity of goods in the logistics center, distribution center, and warehouse in the logistics allocation network; S300. Analyze the stable supply period through big data based on the quantity of goods; S400. After the logistics center receives an order, screen the warehouses according to the stable supply period of the corresponding goods in each warehouse for the order.

[0029] Furthermore, in S100, the location of the logistics center in the logistics allocation network is in the middle reaches of the logistics, which is the intermediate link between the warehouse and the distribution center; the distribution center distributes the goods in each industrial area; after the logistics center obtains the orders from customers in the industrial area, it contacts the corresponding warehouse to ship the goods according to the quantity of goods required on the order. After the warehouse ships the goods, the goods are transported to the logistics center through the logistics transportation path, and then the logistics center transports the goods to the distribution centers corresponding to each industrial area, and then the distribution center distributes the goods to the corresponding addresses on the order.

[0030] The goods are transported through multiple paths between each warehouse and the distribution center, between the logistics center and the distribution center, and between the distribution center and the industrial area. Among them, the goods are mechanical parts and mechanical equipment in the industrial area.

[0031] Preferably, the path can be the navigation path generated by calling the Baidu Map API between the warehouse and the distribution center, and between the logistics center and the distribution center.

[0032] Specifically: The starting latitude, starting longitude between the warehouse and the distribution center, and the ending latitude, ending longitude between the logistics center and the distribution center are used to call the path planning interface of the Baidu Map API through an HTTP request. Then, the path planning interface of the Baidu Map returns a JSON format response file, and the detailed information of the path is obtained by JSON parsing of the JSON format response file. The detailed information of the path includes the route, distance, and estimated travel time.

[0033] Further, in S200, the method for obtaining the quantity of goods in the logistics center, distribution center, and warehouse in the logistics distribution network in real time is as follows: Read the information of the goods through a barcode scanner in the logistics center, distribution center, and warehouse, so as to obtain the quantity of goods in the current inventory; among them, the barcode scanner is a smart phone, a two-dimensional code scanner, or a bar code scanner.

[0034] Preferably, the quantity of goods in the current inventory collected in the logistics center, distribution center, and warehouse is uploaded to the cloud server through the network respectively. Specifically: The operator scans the barcodes of each good, and the barcode scanner sends the data of the goods information corresponding to the barcode to the data upload module. The data upload module formats the data into JSON format and uploads it to the API interface of the cloud server through an HTTPS POST request. The cloud server receives the data and stores it in the database, and generates an inventory report at the same time.

[0035] Further, in S300, the method for analyzing the stable supply period based on the quantity of goods through big data analysis is as follows: Record the sequence of the quantity of goods in the logistics center according to the time order of obtaining the quantity of goods as the central logistics sequence HubL; Record the sequences of the quantity of goods in each warehouse storing this good according to the time order of obtaining the quantity of goods as the warehousing logistics sequences, and represent the i-th warehousing logistics sequence as ReL(i); where i is the serial number of the warehousing logistics sequence; Analyze the stable supply period of each warehousing logistics sequence ReL(i) for the central logistics sequence HubL in turn within the range of i values. Specifically: Record the time when the quantity of this good increased last time in the warehousing logistics sequence ReL(i) as the recent replenishment inbound time ReT(i); Calculate the stable supply ratio StabRat of the warehouse corresponding to ReL(i) to the logistics center from ReT(i) to the current time; Analyze the consumption acceleration period ConT(HubL) of the warehousing logistics sequence ReL(i) for the logistics center; Take the product of the stable supply ratio StabRat and the consumption acceleration period ConT(HubL) as the stable supply period.

[0036] Among them, the calculation method of the supply stability ratio StabRat is as follows: taking the ratio of MinReL and MaxReL as the supply stability ratio StabRat of the corresponding warehouse of ReL(i) to the logistics center from ReT(i) to the current time; where MinReL is the absolute value of the non-zero difference between the minimum value of the quantities of each item obtained from ReL(i) from ReT(i) to the current time in the warehousing logistics sequence and the minimum value of the quantities of each item obtained from ReT(i) to the current time in the sequence HubL; MaxReL is the absolute value of the non-zero difference between the maximum value of the quantities of each item obtained from ReL(i) from ReT(i) to the current time in the warehousing logistics sequence and the maximum value of the quantities of each item obtained from ReT(i) to the current time in the sequence HubL. Among them, the analysis method of the consumption acceleration period ConT(HubL) of the warehousing logistics sequence ReL(i) for the logistics center is as follows: Taking the quantity of goods at time ReT(i) in ReL(i) as the comparison quantity; taking the maximum value of the difference between the values of the quantities of each item obtained from time ReT(i) to the current time in the sequence HubL and the comparison quantity as APM; taking the acquisition time of the corresponding quantity of goods of APM in HubL as UnT; and denoting the time period from ReT(i) to UnT as ConT(HubL).

[0037] Further, in S400, after the logistics center receives an order, the method for screening warehouses according to the supply stability periods of each warehouse for the goods corresponding to the order is as follows: obtaining the transportation time required for each warehouse to reach the logistics center; screening out all the corresponding warehouses whose supply stability period for the goods corresponding to the order is longer than the transportation time required as alternative warehouses.

[0038] Preferably, select the warehouse with the largest duration value of the supply stability period for the goods corresponding to the order among the alternative warehouses as the shipping warehouse for the goods corresponding to the order.

[0039] Further, the method for obtaining the transportation time required for each warehouse to reach the logistics center is as follows: obtaining the shortest travel time from each warehouse to the logistics center through the Baidu Map API as the transportation time required.

[0040] Preferably, the method for obtaining the transportation time required for each warehouse to reach the logistics center is as follows: the transportation time required is a preset time.

[0041] Further, in S400, the order includes at least the order time, the name of the goods, the quantity of the goods, the address and contact information of the goods demander.

[0042] Embodiment 2 This Embodiment 2 replaces the method for selecting the shipping warehouse on the basis of Embodiment 1, specifically: Furthermore, according to the chronological order of the quantity of goods required for the order, the quantity of goods in each warehouse storing the goods is respectively formed into a sequence, which is recorded as the warehousing logistics sequence of the goods required for the order, and SReL(j) is used to represent the warehousing logistics sequence of the goods required for the j-th order; where j is the serial number; the time of the most recent increase in the quantity of the goods in SReL(j) is recorded as the most recent replenishment inbound time SReT(j). The time of the most recent decrease in the quantity of the goods between SReT(j) and the order placement time in the central logistics sequence HubL is recorded as the most recent shipment time OuT(j). When OuT(j) is after the supply stability period of the goods corresponding to the order, the warehouse with the largest duration value of the supply stability period of the goods corresponding to the order is selected from the alternative warehouses as the shipping warehouse for the goods corresponding to the order. When OuT(j) is within the supply stability period of the goods corresponding to the order, the warehouse with the largest duration value of the supply stability period of the corresponding goods in the alternative warehouses is locked. Locking means marking that the warehouse stops shipping the goods corresponding to the order, and the supply stability period of the goods corresponding to the warehouse is calculated in real time until OuT(j) is within the supply stability period of the goods corresponding to the order, and this warehouse is used as the shipping warehouse for the goods corresponding to the order.

[0043] In addition, the present invention also provides an embodiment of a goods allocation system for an industrial area, as Figure 2 shown in the structure diagram of a goods allocation system for an industrial area of the present invention. An embodiment of a goods allocation system for an industrial area includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the above embodiment of the goods allocation system for an industrial area are implemented.

[0044] The system includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it runs in the following units of the system: A goods quantity collection unit for obtaining in real time the quantity of goods in the logistics center, distribution center, and warehouse in the logistics allocation network; A supply data analysis unit for analyzing the supply stability period through big data based on the quantity of goods; A supply warehouse screening unit for screening warehouses according to the supply stability period of the goods corresponding to the order in each warehouse after the logistics center receives the order.

[0045] The described goods allocation system for an industrial area can run on computing devices such as desktop computers, laptops, PDAs, and cloud servers. The described goods allocation system for an industrial area, the operable system may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above examples are only examples of a goods allocation system for an industrial area and do not constitute a limitation on the goods allocation system for an industrial area. It may include more or fewer components than the examples, or combine certain components, or different components. For example, the goods allocation system for an industrial area may also include input / output devices, network access devices, buses, etc.

[0046] The so-called processor may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor is the control center of the operating system of the goods allocation system for an industrial area, and connects various parts of the operable system of the entire goods allocation system for an industrial area through various interfaces and lines.

[0047] The memory can be used to store the computer programs and / or modules. The processor realizes various functions of the goods allocation system for an industrial area by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory. The memory may mainly include a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.); the data storage area can store data created according to the use of the mobile phone (such as audio data, phone book, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one magnetic disk storage device, flash device, or other volatile solid-state storage devices.

[0048] Although the description of the present invention has been quite detailed and particularly describes several of the described embodiments, it is not intended to be limited to any of these details or embodiments or any particular embodiment, but rather to effectively cover the intended scope of the present invention. Additionally, the present invention is described above in terms of embodiments foreseeable by the inventors for the purpose of providing a useful description, and non-substantive changes to the present invention that are not currently foreseeable may still represent equivalent changes to the present invention.

Claims

1. A method for allocating goods in an industrial area, characterized in that: The method comprises the following steps: S100, build a logistics distribution network; the logistics distribution network includes logistics centers, distribution centers and warehouses; S200, real-time acquisition of the quantity of goods in logistics centers, distribution centers and warehouses in the logistics dispatch network; S300, analyzes the big data based on the quantity of goods to determine the stable supply period; S400, after receiving the order, the logistics center selects warehouses according to the stable supply period of the goods corresponding to the order; The method of analyzing the stable supply period based on the quantity of goods through big data is as follows: According to the time sequence of obtaining the quantity of goods, the quantity sequence of the goods in the logistics center is recorded as the center logistics sequence HubL; According to the time sequence of the acquisition of the quantity of goods, the quantity of goods in each warehouse storing the goods is sequenced and recorded as a storage logistics sequence, and ReL(i) represents the i-th storage logistics sequence; where i is the sequence number; Within the range of i values, the stable supply period of each warehouse logistics sequence ReL(i) to the central logistics sequence HubL is analyzed in turn.

2. A method for allocating goods in an industrial area according to claim 1, characterized in that: In S200, the method for obtaining the quantity of goods in the logistics center, distribution center and warehouse in the logistics distribution network in real time is: reading the information of the goods by a scanner in the logistics center, distribution center and warehouse, so as to obtain the current inventory quantity of goods; wherein the scanner is a smart phone, a QR code scanner or a barcode scanner.

3. The method for allocating goods in an industrial area according to claim 1, characterized in that: The specific analysis method of the supply stability period is as follows: record the time when the quantity of the goods in the storage logistics sequence ReL(i) increased the most recently as the most recent replenishment time ReT(i); calculate the supply stability ratio StabRat of the warehouse corresponding to ReL(i) to the logistics center from ReT(i) to the current time; analyze the consumption acceleration period ConT(HubL) of the storage logistics sequence ReL(i) to the logistics center; The product of the supply stability ratio StabRat and the consumption acceleration period ConT(HubL) is taken as the supply stability period.

4. A method for allocating goods in an industrial area according to claim 3, characterized in that: in, The calculation method of the supply stability ratio StabRat is: the ratio of MinReL to MaxReL is the supply stability ratio StabRat of the warehouse corresponding to ReL(i) to the logistics center from ReT(i) to the current time; where MinReL is the absolute value of the non-zero difference between the minimum value of the quantity of each product obtained from ReL(i) to the current time in the warehouse logistics sequence and the minimum value of the quantity of each product obtained from ReT(i) to the current time in the sequence HubL; MaxReL is the absolute value of the non-zero difference between the maximum value of the quantity of each product obtained from ReL(i) to the current time in the warehouse logistics sequence and the maximum value of the quantity of each product obtained from ReT(i) to the current time in the sequence HubL.

5. The method for allocating goods in an industrial area according to claim 3, characterized in that: in, The analysis method of the warehouse logistics sequence ReL(i) on the consumption acceleration period ConT(HubL) of the logistics center is: The quantity of goods in ReL(i) at time ReT(i) is taken as the comparison quantity; the maximum value of the difference between the value of each quantity of goods obtained from time ReT(i) to the current time in sequence HubL and the comparison quantity is recorded as APM; The collection time of the corresponding cargo quantity of APM in HubL is UnT; the time period from ReT(i) to UnT is ConT(HubL).

6. The method for allocating goods in an industrial area according to claim 1, characterized in that: In S400, after the logistics center receives the order, the method for screening warehouses according to the stable supply period of each warehouse for the goods corresponding to the order is: obtaining the transportation time required for each warehouse to the logistics center; screening out all corresponding warehouses whose stable supply period of the goods corresponding to the order is longer than the transportation time as alternative warehouses.

7. The method for allocating goods in an industrial area according to claim 1, characterized in that: Also includes: Among the alternative warehouses, the warehouse with the longest stable supply period for the goods corresponding to the order is selected as the shipping warehouse for the goods corresponding to the order.

8. The method for allocating goods in an industrial area according to claim 1, characterized in that: The method further includes: according to the time sequence of obtaining the quantity of goods required for the order, the quantity of goods in each warehouse storing the goods is respectively sequenced as the storage logistics sequence of the goods required for the order, and SReL(j) is used to represent the storage logistics sequence of the goods required for the jth order; wherein j is the sequence number; and the time when the quantity of the goods of the goods in SReL(j) is increased the most recently is recorded as the most recent replenishment time SReT(j); The time when the quantity of goods of the most recent goods is reduced between SReT(j) and the order placement time in the central logistics sequence HubL is recorded as the most recent shipment time OuT(j); When OuT(j) is after the stable supply period of the goods corresponding to the order, the warehouse with the longest stable supply period of the goods corresponding to the order is selected from the candidate warehouses as the shipping warehouse for the goods corresponding to the order; When OuT(j) is within the stable supply period of the goods corresponding to the order, the warehouse with the largest duration of the stable supply period of the corresponding goods among the alternative warehouses will be locked. Locking means marking the warehouse to stop shipping the goods corresponding to the order, and the stable supply period of the goods corresponding to the warehouse will be calculated in real time until OuT(j) is within the stable supply period of the goods corresponding to the order, at which time the warehouse will be used as the shipping warehouse for the goods corresponding to the order.

9. A cargo distribution system for industrial areas, characterized in that: The cargo allocation system for an industrial area comprises: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the cargo allocation method for an industrial area described in any one of claims 1 to 8 are implemented.

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