Metering asset intelligent distribution method and system

Abstract

The invention relates to a metering asset intelligent distribution method and system, and belongs to the field of power metering asset supply chain management. Comprising the following steps: setting three grades of initial inventory limits according to the storage capacity of a three-stage warehouse-dividing intelligent turnover cabinet, updating the three grades of initial inventory limits through an exponential smoothing method, and comparing the updated alarm limits with the current inventory to obtain the scattered requirements of the metering assets; for a flat warehouse area, setting three grades of initial inventory limits according to a special task list, updating according to rules, comparing alarm limits with special task requirements of the current inventory, and adding the alarm limits and the special task requirements to obtain a total distribution requirement; demand pre-auditing is carried out by a second-level regional warehouse division administrator in combination with the inventory and a preset rule; after the verification is passed, the total delivery demand is converted into the number of standard turnover boxes, based on the delivery number, an optimal delivery route is generated through a TSP algorithm, an optimal loading scheme is planned in combination with a CVRP mileage saving method and vehicle specifications, an optimal delivery scheme is formed through integration, and a second-level regional sub-warehouse administrator confirms and adjusts the scheme; and the distribution task is issued after the distribution scheme information is confirmed. According to the invention, accurate measurement and calculation and intelligent distribution of measurement asset requirements are realized, the distribution efficiency is improved, and the inventory pressure and the labor cost are reduced.

Description

Technical Field

[0001] This invention relates to a method and system for intelligent distribution of metered assets, belonging to the field of power material supply chain management. Background Technology

[0002] The existing metering assets adopt a regional centralized distribution management model of "provincial first-level warehouse - second-level regional sub-warehouse - third-level sub-warehouse". Taking a power supply company as an example, its two second-level regional sub-warehouses need to directly supply 101 third-level sub-warehouses. At present, this model still relies on manual passive distribution. Demand submission, plan review and adjustment, distribution tasks and route planning are all completed manually, resulting in low distribution efficiency and difficulty in meeting the meter usage needs of the third-level sub-warehouses. Although some regions have established relatively complete second- and third-tier warehouse management systems and logistics distribution models, the management of metering assets and warehousing distribution lacks online digital and intelligent control methods, resulting in the following technical deficiencies: First, demand reporting relies on manual experience, lacking scientific data support and intelligent prediction models, making it unable to adapt to demand fluctuations, leading to excessive demand and distribution, high asset idle rates, low turnover rates, and resource waste; Second, the second-tier regional warehouses adopt a crude inventory management approach of "broad reserves but narrow usage," lacking intelligent inventory early warning and dynamic allocation mechanisms, making it difficult to accurately control the consumption of lower-level units, resulting in serious inventory backlog, occupying a large amount of capital and storage space, and materials are prone to expiration and obsolescence, making it difficult to achieve inventory optimization goals; Third, in the bulk installation of new meters, grassroots power supply station personnel need to complete multiple manual operations such as meter requisition and information entry, resulting in low automation, redundant processes, and a high workload and labor costs at the grassroots level.

[0003] There is an urgent need for an intelligent distribution method and system for measurable assets. Through scientific demand forecasting models, dynamic inventory limit control, and intelligent distribution plan planning, this system can solve technical problems such as inaccurate demand reporting, serious inventory backlog, and heavy workload at the grassroots level in the existing model. It can achieve scientific measurement of measurable asset demand, refined inventory management, and efficient distribution execution, reduce resource waste and labor costs, and ensure timely response to the needs of various warehouses. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention proposes a method and system for intelligent distribution of metered assets.

[0005] The technical solution of the present invention is as follows: On the one hand, this invention proposes a method for intelligent distribution of metered assets, comprising the following steps: For the intelligent turnover cabinets in the three-tiered warehouse system, three levels of turnover inventory limits—safety, early warning, and alarm—are set based on a preset upper limit for warehouse capacity. These limits are then updated using exponential smoothing based on historical data. The scattered demand for measurable assets is obtained by comparing the updated alarm limit with the current inventory. For the flat storage area in the three-tiered warehouse system, three levels of flat storage inventory limits—safety, early warning, and alarm—are set based on a preset special task list. These limits are updated according to preset update rules. The special task demand for measurable assets is obtained by comparing the updated alarm limit with the current inventory. The scattered demand for measurable assets and the special task demand for measurable assets are added together to obtain the total distribution demand for measurable assets in the three-tiered warehouse system. The secondary regional warehouse administrator conducts a preliminary review of the total distribution demand for metered assets based on the current inventory and preset rules of the secondary regional warehouse. After approval, the total delivery demand of the measured assets will be converted into the number of standard turnover boxes according to the turnover box adaptation rules. Based on the number of standard turnover boxes, the optimal delivery route plan will be generated using the TSP algorithm, and the loading plan will be planned using the CVRP mileage saving method combined with vehicle specifications to obtain the optimal delivery plan that integrates the optimal delivery route and loading rate. Based on the optimal delivery plan, confirm the delivery information and issue the delivery task for the measured assets.

[0006] Preferably, the method updates the three-level inventory turnover limits using exponential smoothing, specifically as follows: Collect historical meter usage data for the corresponding measurable assets of the three-tiered warehouse turnover cabinets, preset a smoothing coefficient, set the actual meter usage value of the first period as the initial forecast value, and use one or more exponential smoothing methods to iteratively calculate the forecast value of meter usage demand for the current period, expressed by the formula: ; In the formula, Indicates the first Forecast values ​​of meter usage for each cycle, Represents the smoothing coefficient. Indicates the first The actual table value used in each cycle, Indicates the first The forecast values ​​for each cycle are shown in the table. Based on the The demand forecast values ​​for each cycle are used to update the three-level inventory turnover limits, expressed by the formula: ; ; ; In the formula, Indicates the safety limit value. Indicates the warning limit value. Indicates the alarm limit value; If the updated three-level inventory limits exceed the preset storage capacity limit of the turnover cabinet, the storage capacity limit will be set according to the storage capacity limit, and the three-level turnover inventory limits will be recalculated and updated regularly every week.

[0007] Preferably, the method updates the three-tiered inventory limits according to preset rules, specifically as follows: Based on the imported special task list, extract the total task quantity, the quantity already delivered, and the start and end time of the task; if the total task quantity is less than 100 or the total task quantity is less than or equal to the quantity already delivered, set all three inventory limits to 0; if the total task quantity is greater than or equal to 100, allocate safety limits according to the task duration, with the warning limit = safety limit ÷ 2 and the alarm limit = safety limit ÷ 4, rounding up to the nearest integer in all three; if the safety limit + the quantity already delivered is greater than the total task quantity, adjust the safety limit = total task quantity - the quantity already delivered, and update the three inventory limits.

[0008] Preferably, the method obtains the scattered demand for measured assets and the specific task demand for measured assets by comparing the updated alarm limit with the current inventory, specifically as follows: For three-tiered distribution cabinets: if the current inventory is lower than the updated alarm limit, then the scattered demand for measurement assets = updated safety limit - current inventory; if the current inventory is greater than or equal to the updated alarm limit, then the scattered demand for measurement assets is 0. For the three-tiered warehouse leveling area: if its current inventory is lower than the updated alarm limit, then the special task requirement for measurement assets = updated safety limit - current inventory; if the current inventory is greater than or equal to the updated alarm limit, then the special task requirement for measurement assets is 0.

[0009] Preferably, the method uses the TSP algorithm to generate the optimal delivery route plan, specifically as follows: Using the preset map navigation function, the location information of secondary regional warehouses and each tertiary warehouse awaiting delivery is obtained, as well as the distance, time, and road cost weights between secondary regional warehouses and tertiary warehouses, and between tertiary warehouses; a path minimization objective function is established, expressed by the formula: ; In the formula, This represents any path arrangement of all three levels of sub-warehouses. Indicates path arrangement Total length, Indicates path arrangement After considering the total number of secondary and tertiary regional sub-warehouses, Indicates path arrangement The Middle indivual, Indicates path arrangement The Middle The location and the The distance between the locations Indicates path arrangement The first location and the first The distance between the locations; By iteratively calculating the sum of the weights of all path arrangements, the path with the smallest sum of weights is selected as the optimal delivery route.

[0010] Preferably, the method utilizes the CVRP (Cost Per mile) saving method combined with vehicle specification planning for installation schemes, specifically as follows: Based on the converted standard turnover box quantity, combined with the delivery vehicle specifications and optimal delivery route, the CVRP (Continuous Cost Reduction) mileage saving method is used for modeling: if the total turnover box demand is ≤140 boxes, all delivery requirements for the three-level distribution warehouses are combined and loaded into one vehicle; if the total demand is >140 boxes, full-load vehicles are prioritized, and the remaining capacity is planned according to the condition that each vehicle has no more than 2 delivery points and meets the 120-box departure condition; if a vehicle cannot depart due to a load capacity of less than 120 boxes, the number of delivery points for that vehicle is gradually increased and replanned until all delivery points are included in the plan; if it still cannot depart, the plan with the fewest vehicles and the highest loading rate is selected; finally, a loading plan that adapts to the route, meets the loading constraints, and has the optimal loading efficiency is generated.

[0011] On the other hand, the present invention also proposes a smart distribution system for metered assets, comprising the following modules: Delivery Demand Generation Module: This module establishes primary warehouses, secondary regional warehouses, and tertiary warehouses for measured assets. For the turnover cabinets in the tertiary warehouses, it sets three levels of turnover inventory limits—safety, early warning, and alarm—based on preset storage capacity limits. These limits are then updated using exponential smoothing based on historical data. The module compares the updated alarm limits with the current inventory to obtain scattered demand for measured assets. For the flat storage areas in the tertiary warehouses, it sets three levels of flat storage inventory limits—safety, early warning, and alarm—based on a preset special task list. These limits are updated according to preset update rules. The module compares the updated alarm limits with the current inventory to obtain specific task demand for measured assets. Finally, it adds the scattered demand and specific task demand to obtain the total delivery demand for measured assets across the tertiary warehouses. Audit module: The secondary regional warehouse administrator conducts a pre-audit of the total distribution demand for metered assets based on the current inventory of the secondary regional warehouse and preset rules; Optimal delivery plan generation module: After approval, the total delivery demand of the measured assets is converted into the number of standard turnover boxes according to the turnover box adaptation rules; based on the number of standard turnover boxes, the optimal delivery route plan is generated using the TSP algorithm, and the loading plan is planned using the CVRP mileage saving method combined with vehicle specifications to obtain the optimal delivery plan that integrates the optimal delivery route and loading rate. Delivery task assignment module: Based on the optimal delivery plan, confirm the delivery information and assign delivery tasks to the metered assets.

[0012] Metered Asset Monitoring Module: Used to monitor metered assets within a preset area, including monitoring the inventory information of metered assets in warehouses at all levels within the preset area, the information of metered assets in transit for delivery tasks, and the monitoring of aged metered assets and aged metered assets.

[0013] In another aspect, the present invention also proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method as described in any embodiment of the present invention.

[0014] In another aspect, the present invention also proposes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any embodiment of the present invention.

[0015] The present invention has the following beneficial effects: (1) This invention is a smart distribution method and system for measurable assets. It dynamically updates the three-level inventory limits of the turnover cabinet through the exponential smoothing method (to adapt to the historical fluctuation trend of scattered demand for measurable assets), updates the limit of the flat warehouse area in combination with the special task list rules (to match the phased demand of special renovation), and generates demand by comparing inventory with alarm limit. This technical feature makes the calculation of scattered demand for measurable assets and special task demand for measurable assets fit the actual use scenario, effectively avoids the risk of inventory backlog or shortage of measurable assets, and reduces the inventory holding cost of three-level warehouses.

[0016] (2) This invention is a method and system for intelligent distribution of metered assets. It integrates the optimal route planning capability of the TSP algorithm with the loading optimization logic of the CVRP mileage saving method based on the number of standard turnover boxes, and incorporates practical conditions such as vehicle loading constraints and delivery point number limitations to form an optimal solution. This technology overcomes the subjectivity and inefficiency of traditional manual planning, significantly shortens the total delivery mileage, increases vehicle load rate, reduces the number of transport trips and manpower input, and reduces time costs and fuel consumption during the delivery process.

[0017] (3) This invention is a method and system for intelligent distribution of measurable assets. Through a measurable asset monitoring module, it covers core information such as inventory in warehouses at all levels, status of assets in transit, and early warning of aging equipment in real time, forming a visualized management system. This technical feature solves the problems of opaque asset status and delayed risk warning in traditional distribution models. It can promptly detect hidden dangers such as abnormal inventory, delays in transit, and aging equipment, making it easier for administrators to respond and adjust quickly, and ensuring the storage security and delivery timeliness of measurable assets. Attached Figure Description

[0018] Figure 1 This is a flowchart of a smart distribution method for metered assets proposed in Embodiment 1 of the present invention; Figure 2 This is a table showing the number of turnover boxes proposed in Embodiment 1 of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] It should be understood that the step numbers used in the text are for ease of description only and are not intended to limit the order in which the steps are performed.

[0021] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0022] The terms “comprising” and “including” indicate the presence of the described feature, whole, step, operation, element and / or component, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0023] The term “and / or” refers to any combination of one or more of the associated listed items, as well as all possible combinations, and includes these combinations.

[0024] Example 1: See Figure 1 This embodiment proposes a proactive intelligent delivery method for metered assets, including the following steps: S100. Obtain historical data from the three-tiered storage system for the measured assets. Based on the inventory capacity of the three-tiered storage system, set the initial values ​​for the three limit levels of the intelligent turnover cabinet, expressed by the formula: ; ; ; In the formula, Indicates the safety limit value. Indicates the warning limit value. Indicates the alarm limit value. This indicates the maximum capacity of the inventory. S101. The initial values ​​of the three limit switches are updated using the exponential smoothing algorithm, as expressed by the formula: ; In the formula, Indicates the first The forecast table for each cycle contains values. Represents the smoothing coefficient. Indicates the first The actual table value used in each cycle, Indicates the first The forecast values ​​for each cycle are shown in the table. It should be noted that, depending on the number of smoothing operations, exponential smoothing is divided into single exponential smoothing, double exponential smoothing, and triple exponential smoothing, etc. Different smoothing operations are suitable for different types of time series data. When starting the calculation, the predicted value of the first period is set as the actual table value of the first period. Furthermore, the smoothing coefficient value is chosen based on the data's recent change capability and its volatility. The smoothing coefficient ranges from 0.1 to 0.9. The smoothing constant determines the smoothing level and the response speed to the difference between the predicted and actual results. The closer the smoothing constant is to 1, the faster the influence of the distant actual value on the smoothed value of the current period decreases; the closer the smoothing constant is to 0, the slower the influence of the distant actual value on the smoothed value of the current period decreases. Therefore, when the time series is relatively stable, a smaller smoothing coefficient can be used; when the time series fluctuates greatly, a larger smoothing coefficient should be used so as not to ignore the influence of the distant actual value.

[0025] In this embodiment, the actual meter readings for the 19th week of 2025 and the predicted meter readings for the 20th week of 2024 of a town-level power supply station in a certain city are obtained, as shown in the table below: Table 1

[0026] The demand for Class A single-phase prepaid smart energy meters (module-remote-switch built-in, no module), 220V, 5(60)A, 2 time periods, and two tariff rates was predicted for the 20th week of 2025 at the town-level power supply station. A smoothing coefficient of 0.6 was used for the first smoothing calculation, resulting in: 0.6*44+0.4*19=34. Based on the value obtained from the first smoothing calculation, a second smoothing calculation was performed, resulting in: 0.2*34+0.8*52=48. That is, the demand for Class A single-phase prepaid smart energy meters (module-remote-switch built-in, no module), 220V, 5(60)A, 2 time periods, and two tariff rates at the town-level power supply station in the 20th week of 2025 was 48.

[0027] In this embodiment, based on the 48 electricity meter values ​​of Class A single-phase prepaid smart energy meters (module-remote-switch built-in, no module), 220V, 5(60)A, 2 time periods, and two rates set by the town-level power supply station in the 20th week of 2025, combined with the above-mentioned inventory limit rules of the smart turnover cabinet, the alarm limit = P1, the warning limit = P1*120%, and the safety limit = P1*150% are calculated.

[0028] It should be noted that the values ​​of the three inventory limits must not exceed the maximum storage capacity; otherwise, they should be set to the maximum storage capacity.

[0029] S103. Obtain the special task list for the secondary regional warehouses of the measurement assets. The special task list includes the annual renovation list of single-phase meters, current transformers, and data acquisition terminals, and fill in the task start time and task end time. Based on the imported special task list, calculate the annual tasks of each tertiary warehouse and automatically set the initial values ​​of the three-level inventory limits for each type of asset in the flat warehouse area. The threshold setting rules are as follows: (1) For tasks with a total number of less than 100, no limit is set, and all three limits are set to 0. (2) If the total number of tasks is less than or equal to the number of deliveries, the three limits are also set to 0; (3) If the total number of tasks is greater than or equal to 100, the safety limit shall be allocated according to the start and end time of the specific task. For example: if the number of tasks is 500 and the task start time is from 2025.02.01 to 2025.12.31, the safety limit = 500 / 10; the warning limit = safety limit / 2; the alarm limit = safety limit / 4; the decimals of the three limits shall be rounded up.

[0030] (4) If the safety limit plus the quantity already delivered is greater than the total task, adjust the safety limit = total task - quantity already delivered.

[0031] S104. The system calculates the delivery demand of all three-level warehouses daily at 8:00 AM through a scheduled task. Delivery demand = scattered demand of measured assets + demand of optional tasks.

[0032] The demand for scattered measurement assets is as follows: If the current inventory of any equipment in the turnover cabinet is lower than the alarm limit of that equipment, the equipment inventory in the turnover cabinet of the institute is replenished to the safety stock. If all the equipment is higher than the alarm limit, the institute has no demand for scattered measurement assets.

[0033] For example: A power supply station currently has 12 Class A single-phase prepaid smart meters (module-remote-switch built-in, no module) in stock, with an alarm limit of 48 and a safety stock of 72; and 8 Class B three-phase prepaid smart meters (no module / remote / external switch) in stock, with an alarm limit of 8, a warning limit of 10, and a safety limit of 12. Calculations show that the Kangmei Town power supply station needs 60 Class A single-phase prepaid smart meters (module-remote-switch built-in, no module) and 4 Class B three-phase prepaid smart meters (no module / remote / external switch) for scattered use.

[0034] The specific task requirement for measurement assets is as follows: If the current inventory of any equipment in the flat storage area is lower than the alarm limit of that equipment, the equipment inventory in the flat storage area of ​​the institute shall be replenished to the safety stock. If all the equipment is higher than the alarm limit, the institute has no specific task requirement for measurement assets.

[0035] S200: Pre-approval of delivery requirements for three-tiered warehouses. During the pre-approval process, it supports adding or deleting the quantity of measurement assets for delivery.

[0036] In this embodiment, the delivery requirement of Power Supply Station A in a certain city is 48 Class A single-phase prepaid smart energy meters (module-remote-switch built-in, no module) and 3 Class B three-phase prepaid smart energy meters (no module / remote / switch built-in). When the administrator conducts the pre-approval, the specific quantity of the power supply station's delivery requirement can be adjusted according to the actual situation.

[0037] S300. Based on the pre-approved power supply station delivery requirements, establish a minimum path objective function, expressed as the formula: ; In the formula, This represents any path arrangement of all power supply stations. Indicates path arrangement Total length, Indicates path arrangement The total number of locations visited. Indicates path arrangement The Middle One location, Indicates path arrangement The Middle The location and the The distance between the locations Indicates path arrangement The first location and the first The distance between the locations; Further, definition This indicates distribution from secondary regional warehouses. Starting point, the set of paths taken Each of the three levels of sub-accounts is subdivided once, finally reaching the second-level sub-account area. The shortest path; For example, in the case of only one three-tier sub-account, using By iterating through the shortest path cases, six possible outcomes can be obtained: , , , , , When there are two tertiary sub-accounts, utilize By iterating through the shortest path cases, we can obtain thirty possible results: , And so on; based on the current number of three-tiered warehouses, we can iterate through them, and after obtaining the traversal results, we can use the minimum path objective function to arrange all possible paths. Find the objective function that minimizes the path. The optimal delivery route is obtained by taking the permutation with the minimum value.

[0038] S301. Obtain the equipment requirements for the three-tiered storage area. Based on the preset turnover box types, convert and calculate the required quantity of standard metering boxes. The requirements for metering boxes for miscellaneous use and special tasks are calculated separately. The specific conversion rules are shown in the table below: Table 2

[0039] In this embodiment, it is assumed that there are three tertiary warehouses (A, B, and C) under a given secondary regional warehouse that need to be delivered. The delivery demand is obtained, resulting in a delivery demand table, as shown in the table below: Table 3

[0040] See Figure 2 Based on the conversion rules for converting turnover box types into the required number of standard metering boxes, data on the number of single-phase meter standard turnover boxes, three-phase meter standard turnover boxes, data on the number of data acquisition terminal standard turnover boxes, data on the number of current transformer standard turnover boxes, and the total number of turnover boxes required for delivery to the three third-level warehouses (A, B, and C) are obtained.

[0041] Based on the pre-defined delivery scenario for metered assets, namely, delivery vehicles are 1.5T trucks, each truck can carry a maximum of 140 single-phase turnover boxes, and the minimum number of departures is 120 single-phase turnover boxes; using the Capacity-Based Vehicle Routing Problem (CVRP) algorithm, the constraints for the delivery plan are formulated as follows: Constraint 1: If the total demand is ≤140 (boxes), all power supply stations are in one vehicle; Constraint 2: If the total demand is >140, when planning the delivery plan, priority should be given to fully loaded vehicles (140 boxes). The remaining quantity should be loaded onto other vehicles. Delivery routes should be selected according to the route management configuration. When planning the delivery plan, each vehicle should not have more than 2 delivery points. Delivery can only be carried out if 120 boxes are delivered. Constraint 3: When planning delivery routes, prioritize the shortest overall path. Constraint 4: If a vehicle cannot be dispatched (the capacity of a vehicle is less than 120 boxes), the number of vehicle delivery locations in the original Constraint 2 can be increased by 1, and the plan can be re-planned. If the inability to dispatch still occurs, repeat this operation until all pending delivery locations are in the delivery plan, and the planned plan no longer needs to be changed. Constraint 5: If a vehicle cannot be dispatched under the above constraints, select the delivery plan with the fewest vehicles and the highest overall loading rate, and display the planned delivery plan for manual adjustment by the secondary regional warehouse administrator.

[0042] S302. Based on the above, the system inputs the delivery demand of each power supply station into the algorithm model. The model calculates and summarizes all the solutions, counts the total mileage of each solution, and outputs the solution with the shortest total mileage as the optimal solution. Then, based on the demand statistics, the system allocates the demand for scattered meter usage / special tasks of each power supply station on each vehicle.

[0043] S400 and secondary regional warehouse managers can view the delivery plans for each delivery route on the delivery plan confirmation page, and confirm and adjust the delivery license plate number, delivery time, delivery personnel, and accompanying personnel information for each vehicle; after confirming that everything is correct, they can issue a delivery task.

[0044] After the S500 delivery task is issued, the local measurement assets of the second- and third-level warehouses are monitored to achieve visualization of the measurement assets of warehouses at all levels. The monitoring content includes: Inventory information at all levels of warehouses: Real-time viewing of inventory information of metering assets such as single-phase meters, three-phase meters, current transformers, and data acquisition terminals in secondary and tertiary regional warehouses; quick viewing of metering assets for high-age warnings and lists of high-age metering assets throughout the city; Delivery in transit measurement asset information: Monitor inventory and delivery in transit measurement assets, and view delivery task status and delivery task details.

[0045] Example 2: This embodiment proposes a proactive intelligent delivery system for metered assets, including the following modules: Delivery Demand Generation Module: This module establishes primary warehouses, secondary regional warehouses, and tertiary warehouses for measured assets. For the turnover cabinets in the tertiary warehouses, it sets three levels of turnover inventory limits—safety, early warning, and alarm—based on preset storage capacity limits. These limits are then updated using exponential smoothing based on historical data. The module compares the updated alarm limits with the current inventory to obtain scattered demand for measured assets. For the flat storage areas in the tertiary warehouses, it sets three levels of flat storage inventory limits—safety, early warning, and alarm—based on a preset special task list. These limits are updated according to preset update rules. The module compares the updated alarm limits with the current inventory to obtain specific task demand for measured assets. Finally, it adds the scattered demand and specific task demand to obtain the total delivery demand for measured assets across the tertiary warehouses. Audit module: The secondary regional warehouse administrator conducts a pre-audit of the total distribution demand for metered assets based on the current inventory of the secondary regional warehouse and preset rules; Optimal delivery plan generation module: After approval, the total delivery demand of the measured assets is converted into the number of standard turnover boxes according to the turnover box adaptation rules; based on the number of standard turnover boxes, the optimal delivery route plan is generated using the TSP algorithm, and the loading plan is planned using the CVRP mileage saving method combined with vehicle specifications to obtain the optimal delivery plan that integrates the optimal delivery route and loading rate. Delivery task assignment module: Based on the optimal delivery plan, confirm the delivery information and assign delivery tasks to the metered assets; Metered Asset Monitoring Module: Used to monitor metered assets within a preset area, including monitoring the inventory information of metered assets in warehouses at all levels within the preset area, the information of metered assets in transit for delivery tasks, and the monitoring of aged metered assets and aged metered assets.

[0046] Example 3: This embodiment proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the method described in any embodiment of the present invention.

[0047] Example 4: This embodiment proposes a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method described in any embodiment of the present invention.

[0048] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, A and B simultaneously, or B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0049] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments disclosed herein can be implemented using electronic hardware, computer software, or a combination of electronic hardware and software. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0050] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0051] In the several embodiments provided in this application, any function, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0052] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for intelligent distribution of metered assets, characterized in that, Includes the following steps: Establish a primary warehouse, a secondary regional warehouse, and a tertiary warehouse for the measurable assets. For the turnover cabinets in the tertiary warehouse, set three levels of turnover inventory limits: safety, early warning, and alarm, based on the preset warehouse capacity limit. Update the three levels of turnover inventory limits using exponential smoothing method in combination with historical data. Based on the comparison between the alarm limit in the updated three levels of turnover inventory limits and the current inventory, obtain the scattered demand for the measurable assets. For the flat storage area of ​​the three-level warehouse, three levels of flat storage inventory limits are set based on a preset special task list: safety, early warning, and alarm. The three levels of flat storage inventory limits are updated according to preset update rules. The special task requirements for metered assets are obtained by comparing the alarm limit in the updated three levels of flat storage inventory limits with the current inventory. The scattered requirements for metered assets and the special task requirements for metered assets are added together to obtain the total distribution requirements for metered assets in the three-level warehouse. The secondary regional warehouse administrator conducts a preliminary review of the total distribution demand for metered assets based on the current inventory and preset rules of the secondary regional warehouse. After approval, the total delivery demand of the measured assets will be converted into the number of standard turnover boxes according to the turnover box adaptation rules. Based on the number of standard turnover boxes, the optimal delivery route plan will be generated using the TSP algorithm, and the loading plan will be planned using the CVRP mileage saving method combined with vehicle specifications to obtain the optimal delivery plan that integrates the optimal delivery route and loading rate. Based on the optimal delivery plan, confirm the delivery information and issue the delivery task for the measured assets.

2. The intelligent distribution method for metered assets according to claim 1, characterized in that, The method updates the three-level inventory turnover limits using exponential smoothing, specifically as follows: Collect historical meter usage data for the corresponding measurable assets of the three-tiered warehouse turnover cabinets, preset a smoothing coefficient, set the actual meter usage value of the first period as the initial forecast value, and use one or more exponential smoothing methods to iteratively calculate the forecast value of meter usage demand for the current period, expressed by the formula: ； In the formula, Indicates the first Forecast values ​​of meter usage for each cycle, Represents the smoothing coefficient. Indicates the first The actual table value used in each cycle, Indicates the first The forecast values ​​for each cycle are shown in the table. Based on the The demand forecast values ​​for each cycle are used to update the three-level inventory turnover limits, expressed by the formula: ； ； ； In the formula, Indicates the safety limit value. Indicates the warning limit value. Indicates the alarm limit value; If the updated three-level inventory limits exceed the preset storage capacity limit of the turnover cabinet, the storage capacity limit will be set according to the storage capacity limit, and the three-level turnover inventory limits will be recalculated and updated regularly every week.

3. The intelligent distribution method for metered assets according to claim 1, characterized in that, The method updates the three-tiered inventory limits according to preset rules, specifically as follows: Based on the imported special task list, extract the total task quantity, the quantity already delivered, and the start and end time of the task; if the total task quantity is less than 100 or the total task quantity is less than or equal to the quantity already delivered, set all three inventory limits to 0; if the total task quantity is greater than or equal to 100, allocate safety limits according to the task duration, with the warning limit = safety limit ÷ 2 and the alarm limit = safety limit ÷ 4, rounding up to the nearest integer in all three; if the safety limit + the quantity already delivered is greater than the total task quantity, adjust the safety limit = total task quantity - the quantity already delivered, and update the three inventory limits.

4. The intelligent distribution method for metered assets according to claim 1, characterized in that, The method obtains the scattered demand for measurement assets and the specific task demand for measurement assets by comparing the updated alarm limit with the current inventory, specifically as follows: For three-tiered distribution cabinets: if the current inventory is lower than the updated alarm limit, then the scattered demand for measurement assets = updated safety limit - current inventory; if the current inventory is greater than or equal to the updated alarm limit, then the scattered demand for measurement assets is 0. For the three-tiered warehouse leveling area: if its current inventory is lower than the updated alarm limit, then the special task requirement for measurement assets = updated safety limit - current inventory; if the current inventory is greater than or equal to the updated alarm limit, then the special task requirement for measurement assets is 0.

5. The intelligent distribution method for metered assets according to claim 1, characterized in that, The method utilizes the TSP algorithm to generate the optimal delivery route plan, specifically as follows: Using the preset map navigation function, the location information of secondary regional warehouses and each tertiary warehouse awaiting delivery is obtained, as well as the distance, time, and road cost weights between secondary regional warehouses and tertiary warehouses, and between tertiary warehouses; a path minimization objective function is established, expressed by the formula: ； In the formula, This represents any path arrangement of all three levels of sub-warehouses. Indicates path arrangement Total length, Indicates path arrangement After considering the total number of secondary and tertiary regional sub-warehouses, Indicates path arrangement The Middle indivual, Indicates path arrangement The Middle The location and the The distance between the locations Indicates path arrangement The first location and the first The distance between the locations; By iteratively calculating the sum of the weights of all path arrangements, the path with the smallest sum of weights is selected as the optimal delivery route.

6. The intelligent distribution method for metered assets according to claim 1, characterized in that, The method utilizes the CVRP (Continuous Vehicle Performance Reduction) mileage saving method combined with vehicle specifications to plan the vehicle installation scheme, specifically as follows: Based on the converted standard turnover box quantity, combined with the delivery vehicle specifications and the optimal delivery route, the CVRP mileage saving method is used for modeling: if the total turnover box demand is ≤140 boxes, all the demand for delivery to the three-level warehouses is combined and loaded into one vehicle; if the total demand is >140 boxes, full-load vehicles are planned first, and the remaining capacity is planned according to the condition that each vehicle has no more than 2 delivery points and meets the condition of 120 boxes for departure. If a vehicle cannot depart due to a carrying capacity of less than 120 boxes, the number of delivery points for that vehicle will be gradually increased and the plan will be redesigned until all delivery points are included in the plan. If the vehicle still cannot depart, the plan with the fewest vehicles and the highest loading rate will be selected. Finally, a loading plan that adapts to the route, meets the loading constraints, and has the best loading efficiency will be generated.

7. A smart distribution system for metered assets, characterized in that, Includes the following modules: Delivery demand generation module: Establishes primary warehouses, secondary regional warehouses, and tertiary warehouses for the measured assets. For the turnover cabinets in the tertiary warehouses, sets three levels of turnover inventory limits—safe, early warning, and alarm—based on the preset warehouse capacity limit. The three levels of turnover inventory limits are updated using exponential smoothing method in combination with historical data. Based on the comparison between the alarm limit in the updated three levels of turnover inventory limits and the current inventory, the scattered demand for the measured assets is obtained. For the flat storage area of ​​the three-level warehouse, three levels of flat storage inventory limits are set based on a preset special task list: safety, early warning, and alarm. The three levels of flat storage inventory limits are updated according to preset update rules. The special task requirements for metered assets are obtained by comparing the alarm limit in the updated three levels of flat storage inventory limits with the current inventory. The scattered requirements for metered assets and the special task requirements for metered assets are added together to obtain the total distribution requirements for metered assets in the three-level warehouse. Audit module: The secondary regional warehouse administrator conducts a pre-audit of the total distribution demand for metered assets based on the current inventory of the secondary regional warehouse and preset rules; Optimal delivery plan generation module: After approval, the total delivery demand of the measured assets is converted into the number of standard turnover boxes according to the turnover box adaptation rules; based on the number of standard turnover boxes, the optimal delivery route plan is generated using the TSP algorithm, and the loading plan is planned using the CVRP mileage saving method combined with vehicle specifications to obtain the optimal delivery plan that integrates the optimal delivery route and loading rate. Delivery task assignment module: Based on the optimal delivery plan, confirm the delivery information and assign delivery tasks to the metered assets.

8. The intelligent distribution system for metered assets according to claim 7, characterized in that, The system also includes a metering asset monitoring module, specifically: Metered Asset Monitoring Module: Used to monitor metered assets within a preset area, including monitoring the inventory information of metered assets in warehouses at all levels within the preset area, the information of metered assets in transit for delivery tasks, and the monitoring of aged metered assets and aged metered assets.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 6.

Images