Life cycle evaluation method, device and equipment for logistics network

Abstract

The invention discloses a life cycle evaluation method, device and equipment for a logistics network, the method is applied to the technical field of logistics, and the method comprises the steps: obtaining the operation data of the logistics network in the operation process of the logistics network; analyzing and processing the operation data by adopting an intelligent scheduling algorithm, and optimizing the delivery route of the logistics order in the logistics network; regularly performing compliance evaluation on the logistics network to obtain a first evaluation result of the logistics network; according to the operation condition of the logistics network and the market change information, whether the logistics network continues to operate is evaluated, and a second evaluation result is obtained; and determining the operation cycle of the logistics network according to the first evaluation result and the second evaluation result. According to the method, the compliance and the risk management capability are improved, the customer experience and the service quality are optimized, and the equipment management and maintenance efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method, device and equipment for evaluating the life cycle of a logistics network. Background Art

[0002] With the rapid development of e-commerce, the express delivery industry has ushered in unprecedented growth opportunities. However, the effective management of express delivery outlets has become a key factor restricting their service quality and operational efficiency. Existing management systems mostly focus on monitoring a single link and lack systematic and intelligent management of the entire life cycle of outlets. Therefore, there is an urgent need for a comprehensive management system that can fully cover all aspects of outlet planning, operation, optimization, and evaluation. At present, the operational data, customer information, vehicle scheduling and other information of express delivery outlets are often scattered in different systems and departments, resulting in serious information islands and difficulty in achieving centralized management and efficient use of data. This increases management costs, reduces operational efficiency, and makes it difficult to conduct global analysis and decision-making. In the daily operation of express delivery outlets, many links (such as order processing, sorting, delivery, etc.) are still highly dependent on manual operations, which not only increases labor costs, but also is prone to human errors. As a result, it is difficult to steadily improve service quality and efficiency, and it also increases the difficulty of management. Existing management tools may lack intelligent functions and cannot automatically predict, optimize and schedule based on real-time data and historical trends; this limits the further improvement of outlet operation efficiency and service quality. Due to the lack of comprehensive data collection and analysis capabilities, express delivery outlets often lack scientific basis in formulating operation strategies and adjusting resource allocation. This leads to subjectivity and blindness in the decision-making process, making it difficult to adapt to market changes and customer needs. With the rapid development of the express delivery industry, compliance and risk management have become increasingly important issues. However, the existing management system may not be able to fully cover compliance requirements and risk points, increasing the legal and financial risks of outlet operations. Summary of the invention

[0003] The present invention provides a life cycle assessment method, device and equipment for logistics outlets, which can enhance compliance and risk management capabilities, optimize customer experience and service quality, and improve equipment management and maintenance efficiency.

[0004] In one aspect, the present invention provides a method for life cycle assessment of a logistics network, the method comprising: During the operation of the logistics network, the operation data of the logistics network is obtained; the operation data includes the delivery area, the delivery volume, the collection volume and the receipt rate; An intelligent scheduling algorithm is used to analyze and process the operational data, and to optimize the delivery routes of logistics orders in logistics outlets; Regularly conduct compliance assessment on the logistics outlets to obtain first assessment results of the logistics outlets; According to the operation status of the logistics network point and the market change information, evaluating whether the logistics network point continues to operate, and obtaining a second evaluation result; The operation cycle of the logistics network is determined according to the first evaluation result and the second evaluation result.

[0005] In an exemplary embodiment, during the operation of the logistics network point, before obtaining the operation data of the logistics network point, the method further includes: Obtaining the network attribute information, management personnel information and registration information of the logistics network; the registration information includes registered capital and business license information; Automatically generate a site selection suggestion and an initial operation plan for the logistics network point based on the network point attribute information and the management personnel information; The registration information of the logistics network point is verified to obtain a verification result of the logistics network point.

[0006] In an exemplary embodiment, the method further comprises: Determine the business structure adjustment strategy and personnel allocation optimization strategy of the logistics network based on the operation data; Use a business volume forecasting model to predict business volume changes at the logistics outlets in future periods; According to the business volume change result, resources are allocated to the logistics network points; Conduct in-depth analysis of the operational data to identify operational bottlenecks and potential growth points of the logistics network; The operation strategy of the logistics network is adjusted according to the operation bottlenecks and potential growth points of the logistics network.

[0007] In an exemplary embodiment, the method further comprises: Acquire the business volume data of the logistics network point, and determine the production volume category area corresponding to the logistics network point according to the business volume data; Obtaining the individual order statistics of the logistics outlets; Calculate the target value completion rate of the logistics network point according to the real-time completion volume and target completion volume of the orders in the logistics network point; The first operation status of the logistics network point is determined according to the production category, individual order statistical information and target value completion rate of the logistics network point.

[0008] In an exemplary embodiment, the method further comprises: Obtaining the total number of customers and potential customers of the logistics outlets, and calculating the number of potential customer conversions and the potential customer conversion rate to obtain potential customer conversion information; Obtain the third-party collection ratio and the total number of third-party cooperation stations of the logistics outlets to obtain third-party information; Obtain the total amount of prepayments, credit limits, and shipment status of prepayment orders of the logistics outlet within a preset period of time, and obtain the prepayment information of the logistics outlet; Obtain the financial income and expenditure, total revenue, service quality parameters and safety test results of the logistics network to obtain the service safety data of the logistics network; The second operation status of the logistics network is determined based on the potential customer conversion information, third-party information, prepayment information and service security data of the logistics network.

[0009] In an exemplary embodiment, the method further comprises: Obtain all logistics outlets in the preset area and identify sub-healthy outlets and abnormal outlets, and obtain the operating status type of each logistics outlet; Determine the scale type of each logistics network point, and generate a network point summary table based on the operation status type and scale type of each logistics network point; Analyze the network point summary table according to the summary report analysis fields to obtain the network point analysis results; In response to a data viewing instruction for a logistics network point, viewing the network point analysis result; In response to the instruction triggered on the cloud monitoring platform, the real-time operation information of the logistics network point is viewed.

[0010] In an exemplary embodiment, determining the operation cycle of the logistics network point according to the first evaluation result and the second evaluation result includes: If the first evaluation result is that the outlet is compliant, and the second evaluation result is that the outlet continues to operate, it is determined that the logistics outlet continues to operate; If the first evaluation result is that the outlet is non-compliant, and the second evaluation result is that the outlet continues to operate, it is determined that the logistics outlet will stop operating at the target time; If the first evaluation result is a compliance result of the outlet, and the second evaluation result is a closure result of the outlet, it is determined that the logistics outlet will stop operating at the target time; If the first evaluation result is that the outlet is non-compliant and the second evaluation result is that the outlet is closed, it is determined that the logistics outlet will cease operations at the target time.

[0011] On the other hand, a life cycle assessment device for a logistics network point is provided, the device comprising: An operation data acquisition module, used to acquire the operation data of the logistics network point during the operation of the logistics network point; the operation data includes the delivery area, the delivery volume, the collection volume and the signing rate; A route optimization module, which is used to analyze and process the operation data using an intelligent scheduling algorithm to optimize the delivery routes of logistics orders in logistics outlets; A first evaluation module, used to regularly perform compliance evaluation on the logistics network point to obtain a first evaluation result of the logistics network point; A second evaluation module is used to evaluate whether the logistics network point continues to operate according to the operation status of the logistics network point and market change information, and obtain a second evaluation result; An operation cycle determination module is used to determine the operation cycle of the logistics network point based on the first evaluation result and the second evaluation result.

[0012] In an exemplary embodiment, the apparatus further comprises: An information acquisition module, used to acquire the network attribute information, management personnel information and registration information of the logistics network; the registration information includes registered capital and business license information; A plan generation module, used to automatically generate a location suggestion and an initial operation plan for the logistics network point based on the network point attribute information and the management personnel information; The verification result determination module is used to verify the registration information of the logistics network point and obtain the verification result of the logistics network point.

[0013] In an exemplary embodiment, the apparatus further comprises: A strategy determination module, used to determine the business structure adjustment strategy and personnel allocation optimization strategy of the logistics network point according to the operation data; A result prediction module is used to use a business volume prediction model to predict the business volume change results of the logistics network in the future period; A deployment module, used for deploying resources to the logistics network points according to the business volume change result; An identification module, used to conduct in-depth analysis of the operation data to identify the operation bottlenecks and potential growth points of the logistics network; The adjustment module is used to adjust the operation strategy of the logistics network according to the operation bottleneck and potential growth point of the logistics network.

[0014] In an exemplary embodiment, the apparatus further comprises: A business quantity acquisition module, used to acquire business volume data of the logistics network point, and determine the production volume category area corresponding to the logistics network point according to the business volume data; A statistical information acquisition module, used to obtain the individual order statistical information of the logistics network; A completion rate calculation module, used to calculate the target value completion rate of the logistics network point according to the real-time completion amount and the target completion amount of the orders in the logistics network point; The first state determination module is used to determine the first operation state of the logistics network point according to the production category, scattered order statistical information and target value completion rate of the logistics network point.

[0015] In an exemplary embodiment, the apparatus further comprises: A quantity acquisition module is used to obtain the total number of customers and the number of potential customers of the logistics outlets, and calculate the number of potential customer conversions and the potential customer conversion rate to obtain potential customer conversion information; A third-party information determination module is used to obtain the third-party collection ratio and the total number of third-party cooperation stations of the logistics outlets to obtain third-party information; A prepayment information determination module is used to obtain the total amount of prepayments, credit limits and shipment status of prepayment orders of the logistics outlet within a preset period of time, and obtain the prepayment information of the logistics outlet; A safety data acquisition module, used to acquire the financial revenue and expenditure, total revenue, service quality parameters and safety test results of the logistics network point, and obtain the service safety data of the logistics network point; The second status determination module is used to determine the second operating status of the logistics network point based on the potential customer conversion information, third-party information, prepayment information and service security data of the logistics network point.

[0016] In an exemplary embodiment, the apparatus further comprises: The operation status type acquisition module is used to acquire all logistics outlets in the preset area and identify sub-healthy outlets and abnormal outlets to obtain the operation status type of each logistics outlet; A summary table generation module is used to determine the scale type of each logistics network point and generate a network point summary table according to the operation status type and scale type of each logistics network point; A result analysis module, used to analyze the network point summary table according to the summary report analysis fields to obtain the network point analysis results; A result viewing module, used to view the analysis results of the logistics network points in response to the data viewing instruction of the logistics network points; The information viewing module is used to view the real-time operation information of the logistics network in response to the instructions triggered on the cloud monitoring platform.

[0017] In an exemplary embodiment, the operating cycle determination module includes: A first determination unit, configured to determine that the logistics outlet continues to operate if the first evaluation result is an outlet compliance result and the second evaluation result is an outlet continued operation result; A second determination unit is configured to determine that the logistics outlet will stop operating at a target time if the first evaluation result is that the outlet is non-compliant and the second evaluation result is that the outlet continues to operate; A third determining unit, configured to determine that the logistics outlet will stop operating at the target time if the first evaluation result is an outlet compliance result and the second evaluation result is an outlet closure result; The fourth determination unit is used to determine that the logistics network point will stop operating at the target time if the first evaluation result is a network point non-compliance result and the second evaluation result is a network point closure result.

[0018] On the other hand, an electronic device is provided, comprising a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded and executed by the processor to implement the life cycle assessment method of the logistics network as described above.

[0019] On the other hand, a computer storage medium is provided, which stores at least one instruction or at least one program, and the at least one instruction or at least one program is loaded and executed by a processor to implement the life cycle assessment method of the logistics network as described above.

[0020] On the other hand, a computer program product or a computer program is provided, the computer program product or the computer program includes computer instructions, the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes to implement the life cycle assessment method of the logistics network point as described above.

[0021] The method, device and equipment for life cycle assessment of logistics network points provided by the present invention have the following technical effects: The present invention obtains the operation data of the logistics network point during the operation of the logistics network point; the operation data includes the delivery area, the delivery volume, the collection volume and the signing rate; the operation data is analyzed and processed by the intelligent scheduling algorithm, and the delivery routes of the logistics orders in the logistics network point are optimized; the compliance of the logistics network point is evaluated regularly to obtain the first evaluation result of the logistics network point; according to the operation status of the logistics network point and the market change information, whether the logistics network point continues to operate is evaluated to obtain the second evaluation result; according to the first evaluation result and the second evaluation result, the operation cycle of the logistics network point is determined. The present invention realizes the comprehensive integration of information, intelligent management, and data-driven decision-making; improves compliance and risk management capabilities, optimizes customer experience and service quality, and improves equipment management and maintenance efficiency, thereby promoting the further development and upgrading of the express delivery industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions and advantages of the embodiments of this specification or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 It is a schematic diagram of a life cycle assessment system for a logistics network provided in an embodiment of this specification; Figure 2 It is a flow chart of a life cycle assessment method for a logistics network provided in an embodiment of this specification; Figure 3 It is a flow chart of a method for adjusting the operation strategy of a logistics network provided in an embodiment of this specification; Figure 4 It is a flow chart of a method for determining a first operating state of a logistics network point provided in an embodiment of this specification; Figure 5 It is a flow chart of a method for determining a second operating state of a logistics network point provided in an embodiment of this specification; Figure 6 It is a structural schematic diagram of a life cycle assessment device for a logistics network point provided in an embodiment of this specification; Figure 7 It is a structural diagram of a server provided in an embodiment of this specification. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of this specification to clearly and completely describe the technical solutions in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0026] See also Figure 1 , Figure 1 is a schematic diagram of a life cycle assessment system for a logistics network provided in an embodiment of this specification, such as Figure 1 As shown, the life cycle assessment system of the logistics network may include at least a server 01 and a client 02 .

[0027] Specifically, in the embodiments of this specification, the server 01 may include an independently operated server, or a distributed server, or a server cluster composed of multiple servers, and may also be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. Server 01 may include a network communication unit, a processor, a memory, and the like. Specifically, the server 01 can be used to determine the operating cycle of a logistics outlet.

[0028] Specifically, in the embodiments of this specification, the client 02 may include physical devices such as smart phones, desktop computers, tablet computers, laptop computers, digital assistants, smart wearable devices, smart speakers, vehicle terminals, smart TVs, etc., and may also include software running in physical devices, such as web pages provided by some service providers to users, or applications provided by these service providers to users. Specifically, the client 02 may be used to query the operation cycle of logistics outlets online.

[0029] The following is an introduction to a life cycle assessment method for a logistics network of the present invention. Figure 2 It is a flowchart of a life cycle assessment method for a logistics network provided in an embodiment of this specification. This specification provides method operation steps as described in the embodiment or flowchart, but may include more or fewer operation steps based on conventional or non-creative labor. The order of steps listed in the embodiment is only one way of executing the steps among many orders, and does not represent the only order of execution. When the actual system or server product is executed, it can be executed in sequence or in parallel (for example, in a parallel processor or multi-threaded processing environment) according to the method shown in the embodiment or the accompanying drawings. Specifically, Figure 2 As shown, the method may include: S201: During the operation of the logistics network, the operation data of the logistics network is obtained; the operation data includes the delivery area, the delivery volume, the collection volume and the receipt rate. In the embodiments of this specification, the network planning module can automatically generate network site selection suggestions and initial operation plans based on market demand, regional characteristics and network manager information. Integrate registration information verification functions such as registered capital and business license to ensure network compliance. The operation management module can monitor network operation data in real time, including key indicators such as delivery area, delivery volume, collection volume, and receipt rate. Support the collaborative work of network operation managers, operation managers and other roles, improve operational efficiency through tasks allocation, progress tracking and other functions; introduce intelligent scheduling algorithms to optimize delivery routes and reduce operating costs.

[0030] S203: Analyze and process the operation data using an intelligent scheduling algorithm to optimize the delivery routes of logistics orders in logistics outlets.

[0031] In the embodiments of the present specification, sample operation data can be obtained, and the preset model corresponding to the intelligent scheduling algorithm can be trained using the sample operation data to obtain a delivery route optimization model; the operation data is input into the delivery route optimization model for analysis and processing, thereby optimizing the delivery routes of logistics orders in logistics outlets.

[0032] S205: Regularly conduct compliance assessment on the logistics network point to obtain a first assessment result of the logistics network point.

[0033] In the embodiments of the present specification, the compliance assessment and closure management module can be used to regularly conduct compliance assessments on outlets, including assessment targets such as judicial cases and administrative penalty records, so as to obtain a first assessment result.

[0034] S207: Based on the operation status of the logistics network and the market change information, assess whether the logistics network continues to operate, and obtain a second assessment result.

[0035] In the embodiment of this specification, the necessity of the outlet to continue operating can be evaluated according to the outlet operation situation and market changes, providing a basis for the closure decision. The closure process is set to ensure that asset liquidation, customer handover and other tasks are carried out in an orderly manner, thereby obtaining the second evaluation result.

[0036] S209: Determine the operation cycle of the logistics network according to the first evaluation result and the second evaluation result.

[0037] In the embodiment of this specification, during the operation of the logistics network point, before obtaining the operation data of the logistics network point, the method further includes: Obtaining the network attribute information, management personnel information and registration information of the logistics network; the registration information includes registered capital and business license information; Automatically generate a site selection suggestion and an initial operation plan for the logistics network point based on the network point attribute information and the management personnel information; The registration information of the logistics network point is verified to obtain a verification result of the logistics network point.

[0038] In the embodiments of the present specification, a network site selection suggestion and an initial operation plan may be automatically generated based on market demand, regional characteristics, and network point manager information.

[0039] In some embodiments, basic information of logistics outlets can be collected, including outlet codes, outlet names, etc. Expand to company categories, company sizes, and collect various types of management personnel as follows: 1. Operations Manager. Value: Administrative Workstation Management Office: Deputy Manager or above and the highest-ranking person. If none, set to 0. If multiple people, set the person with the latest creation date.

[0040] 2. Operation Manager. Value: Operation Department of the Administrative Workstation: The highest-ranking person above the Operation Supervisor. If there is none, then 0. If there are multiple people, then the person with the latest creation date is selected.

[0041] 3. Customer Service Manager. Value: Customer Service Department of the Administrative Workbench: The highest-ranking person above the Customer Service Supervisor. If there is none, then 0. If there are multiple people, then the person with the latest creation date is selected.

[0042] As well as judgment and analysis data such as the registered capital of the outlets, compliance judgment, and co-allocation judgment.

[0043] Also includes risk information: 1. Number of contracted areas. Query the total number of subordinate branches and service departments based on the current first-level company.

[0044] 2. Registered capital. Query based on company code / business registration number. Data source: Qichacha.

[0045] 3. Compliance status. The company has not obtained a valid express business license. The data source is the actual submission of the business license application in the licensing system.

[0046] 4. Whether it is co-configured. The value is taken from the co-configuration report data in the network management manager.

[0047] Basic data collection of parking lot: 1. Total number of employees. The total number of employees in the first-level outlets whose employment status is full-time or on-probation (excluding special departments).

[0048] 2. Insurance coverage.

[0049] 3. Number of vehicles / rated load volume. Count the total number of vehicles entered into the first-level outlets.

[0050] 4. Number of venues. Count the total number of venues that have entered information in the first-level outlets.

[0051] 5. Warehouse number. It counts the total number of first-level outlets whose site type is "warehouse" in the site information.

[0052] 6. Registered equipment. Count the total number of equipment registered on the equipment registration platform in the first-level outlets. Types include but are not limited to sorting machines, Yunbiaoxia equipment, etc.

[0053] 7. Number of industrial mobile phones. Count the number of registered mobile phones. Three-segment code order information, etc. The rules are: 1. Two-segment code recognition rate / accuracy. The basic data basis for the automatic sorting of express parcels to outlets, data source: outlet order configuration system (formerly Zhipao system)-order intervention-order intelligent diagnosis. 2. Three-segment code recognition rate / accuracy. The basic data basis for the distribution of express parcels from outlets to salesmen, data source: outlet order configuration system (formerly Zhipao system)-order intervention-order intelligent diagnosis.

[0054] In the embodiments of this specification, Figure 3 As shown, Figure 3 The flowchart is a method for adjusting the operation strategy of a logistics network, and the method further includes: S301: Determine a business structure adjustment strategy and a staffing optimization strategy for the logistics network based on the operation data; S303: using a business volume prediction model to predict business volume changes of the logistics network in future periods; S305: Allocating resources for the logistics network points according to the business volume change result; S307: Performing in-depth analysis on the operation data to identify the operation bottlenecks and potential growth points of the logistics network; S309: Adjusting the operation strategy of the logistics network according to the operation bottleneck and potential growth points of the logistics network.

[0055] In the embodiments of the present specification, a business volume prediction model can be trained based on the historical operating data of the logistics network in the historical time period and the historical business volume change results, and the current operating data of the logistics network can be input into the business volume prediction model to predict the business volume change results of the logistics network in the future time period; thereby, the resources of the logistics network can be allocated according to the business volume change results; and the operating data can be deeply analyzed to identify the operating bottlenecks and potential growth points of the logistics network; thereby, the operating strategy of the logistics network can be adjusted to improve the operating efficiency of the logistics network.

[0056] In the embodiments of this specification, Figure 4 As shown, Figure 4 The present invention is a flow chart of a method for determining a first operating state of a logistics network point, wherein the method further comprises: S401: Acquire the business volume data of the logistics network point, and determine the production volume category corresponding to the logistics network point according to the business volume data; S403: Obtaining the scattered order statistics information of the logistics network; S405: Calculating the target value completion rate of the logistics network point according to the real-time completion amount and the target completion amount of the orders in the logistics network point; S407: Determine the first operation status of the logistics network point according to the production category, individual order statistics and target value completion rate of the logistics network point.

[0057] In an embodiment of the present specification, the target value completion rate of the logistics network can be calculated based on the real-time completion volume and target completion volume of orders in the logistics network; if at least one of the production category, individual order statistical information and target value completion rate of the logistics network is abnormal, the first operating state of the logistics network is determined to be an abnormal state; if the production category, individual order statistical information and target value completion rate of the logistics network are all normal, the first operating state of the logistics network is determined to be a normal state.

[0058] In the embodiments of this specification, the traffic information is statistically analyzed respectively: 1. Zoning: According to the nature of the outlets, there are production areas, balance areas, non-production areas, and others.

[0059] 2. Achieve 17% market share in the industry. Default is 17% 3. Current actual market share: Take the market share of T-1.

[0060] 4. Difference: Achieve 17% market share in the industry - current actual market share, which may be negative.

[0061] Data time: T-2 before 13:00, T-1 after 13:00.

[0062] The statistical analysis of market share information data is as follows: Statistical analysis of scattered order information: 1. The target of the outlets for scattered orders. According to the change range of the provincial target (approved) compared with the target (estimated), the target for each outlet to adjust in the same proportion is also the target requirement for the execution of the performance bond.

[0063] 2. The completion volume of the outlets. The completion volume of the outlets is the completion volume of the subordinate branches + the subordinate service departments without targets (estimates) + the completion volume of the outlets themselves.

[0064] 3. Target value achievement rate: Amount completed / target value.

[0065] 4. Data time: T-2 before 13:00, T-1 after 13:00.

[0066] Customer information statistics analysis and diagnosis: Customer stratification: 1.Data source: Provincial and regional business managers-Customer managers-Customer insights.

[0067] 2. Data time: T-2 before 13:00, T-1 after 13:00.

[0068] The calculation rules for customer insight data are as follows: 1. Total number of customers: Provincial Management Manager - Customer Insights - Existing Customers Tab - All Types Filter Conditions - [Total Number of Customers] 2. Number of potential customers: Provincial Management Manager - Customer Insights - Existing Customers Tab - All Types Filter Conditions - [Total Number of Potential Customers] 3. Number of potential customers converted: 4. Potential customer conversion rate: Provincial business manager - Customer insights - Potential customer tab - All types of screening conditions - [Potential customer conversion rate].

[0069] In the embodiments of this specification, Figure 5 As shown, Figure 5 The present invention is a flow chart of a method for determining a second operating state of a logistics network point, wherein the method further comprises: S501: Obtain the total number of customers and the number of potential customers of the logistics outlet, and calculate the number of potential customer conversions and the potential customer conversion rate to obtain potential customer conversion information; S503: Obtain the third-party collection ratio and the total number of third-party cooperation stations of the logistics network to obtain third-party information; S505: Obtain the total amount of prepayments, credit limits, and shipment status of prepayment orders of the logistics outlet within a preset period of time, and obtain prepayment information of the logistics outlet; S507: Obtain the financial income and expenditure, total revenue, service quality parameters and safety test results of the logistics network point to obtain the service safety data of the logistics network point; S509: Determine the second operation status of the logistics network point according to the potential customer conversion information, third-party information, prepayment information and service security data of the logistics network point.

[0070] In an embodiment of the present specification, if at least one of the potential customer conversion information, third-party information, prepayment information and service security data of a logistics outlet is abnormal, the second operating state of the logistics outlet is determined to be an abnormal state.

[0071] In the embodiments of this specification, the terminal information diagnosis and evaluation includes: Receipt log analysis: 1. Third-party collection ratio: refers to the ratio of the collection volume of third-party cooperation stations, Zhipao, custom collection, etc. divided by the total volume of normal collection. Data source: Network Manager-Receipt Log Report-Field [Collection Ratio].

[0072] 2. Third-party cooperation station. The sum of the collection points. Data source: Network Manager - Receipt Log Report - Field [Number of Third-party Points].

[0073] 3. The number of points with more than 50 tickets. Network Manager - Receipt Log Report - Field [50 Tickets +] - [Total Number].

[0074] 4. Data time: T-8 before 13:00, T-1 after 13:00.

[0075] Analysis of data collection at terminal stores: 1. The number of stores to be built: terminal construction-target table-[terminal construction indicators].

[0076] 2. Number of stores built: terminal construction-target table-[total of supermarkets + post stations + honeypots + grid warehouses].

[0077] 3. Yunda Supermarket, Honeypot, and Co-construction Station. Terminal construction-warehousing quantity-site details-[Yunda Supermarket name].

[0078] 4. Owned items enter Yunda. Network Manager - Terminal Construction - Inventory Quantity - Field [Yunda enters Yunda - Yunda enters Yunda Supermarket].

[0079] Financial settlement analysis: Prepayment at outlets: 1. Total amount of prepayment. By default, the prepayment data of the branch in the last hour on day T is displayed. Data source: Prepayment system - Branch account balance query report - field [Balance]; 2. Credit limit. Data source: Prepayment system - Branch account management - Branch account balance inquiry report - field [Sending limit]; 3. Shipment status: Data source: Prepayment system - Branch account management - Branch account balance inquiry report - field [Shipping status]; Financial income and expenditure: 1. Single-ticket delivery fee received. Take the delivery fee received for a single ticket, the calculation formula is total amount / settlement ticket quantity, and the time is T-2. Data source: Express settlement system-paid management-delivery fee reconciliation details table-date segment summary layer-field [total amount] / settlement ticket quantity.

[0080] 2. Direct delivery of single-ticket dispatch fees. Single-ticket amount / number of direct delivery tickets. Data source: Timely collection and dispatch monitoring system - Headquarters direct delivery of dispatch fees - fields [Direct delivery amount] / [number of direct delivery tickets].

[0081] 3. Single-ticket assessment amount. Assessment fee forced settlement - single-ticket reward and punishment data. Time is T-2, data source: Express settlement system - assessment fee forced settlement - provincial department table - branch department table - field [assessment forced settlement item C - actual settlement - single-ticket amount].

[0082] 4. Rewards and penalties for single-ticket collection. Assessment fee settlement - single-ticket collection data. Time is T-2, data source: Express settlement system - assessment fee settlement - provincial department table - branch department table - field [assessment settlement item C - actual settlement - total amount] / collection volume.

[0083] 5. Rewards and penalties for single-ticket delivery. Assessment fee settlement - single-ticket delivery data. Time is T-2, data source: Express settlement system - assessment fee settlement - provincial department table - branch department table - field [assessment settlement item C - actual settlement - total amount] / delivery volume.

[0084] Price policy decision support A. Business volume assessment: Take the business volume assessment efficiency effective at the current outlet T-1.

[0085] 1. Industry 17%. The target volume is when the industry 17% is reached.

[0086] 2. Market share target value. The number of tickets is based on the market share target value specified by the industry.

[0087] 3. Business volume: The current business volume of the outlets.

[0088] 4. Rates.

[0089] 1. Assessment type. The types of rate assessment include pay upon receipt (no assessment), pay upon receipt (regular distribution rate), and pay upon receipt (business volume betting), etc. 2. Assessment cycle. It varies according to different policies, and can be daily or weekly. 3. Assessment rate. The rate value of the current policy; 4. Capped amount. The maximum amount of the dispatch subsidy cap; Income (Signature and Settlement) 1. Total revenue: the total revenue of the collection end + the dispatch end, the time is T-2, and the amount of the branch will be summarized to the first-level outlets; 2. Total revenue from parcel pickup: the revenue contribution of the parcel pickup outlets to the headquarters; 3. Total delivery revenue: the revenue contribution of the delivery outlets to the headquarters; Data source: Provincial and regional business managers-daily profit settlement-window negative contribution warning.

[0090] The service quality analysis is as follows: 1. KPI index. Data source: Network Manager-Homepage-Health Index-Network Table [Total Score]. Display time T-1.

[0091] 2. Provincial ranking. The overall ranking of the branch in the business province. The daily year-on-year comparison is the previous day.

[0092] 3. National ranking. The total ranking of this outlet among all outlets in the country. The daily year-on-year comparison is the previous day.

[0093] 4. Data time: T-2 before 13:00, T-1 after 13:00.

[0094] The safety production tests are as follows: Safety officer statistics, express market management method inspections, and inspections based on preset rules.

[0095] In the embodiment of this specification, determining the operation cycle of the logistics network point according to the first evaluation result and the second evaluation result includes: If the first evaluation result is that the outlet is compliant, and the second evaluation result is that the outlet continues to operate, it is determined that the logistics outlet continues to operate; If the first evaluation result is that the outlet is non-compliant, and the second evaluation result is that the outlet continues to operate, it is determined that the logistics outlet will stop operating at the target time; If the first evaluation result is a compliance result of the outlet, and the second evaluation result is a closure result of the outlet, it is determined that the logistics outlet will stop operating at the target time; If the first evaluation result is that the outlet is non-compliant and the second evaluation result is that the outlet is closed, it is determined that the logistics outlet will cease operations at the target time.

[0096] In the embodiment of this specification, the method further includes: Obtain all logistics outlets in the preset area and identify sub-healthy outlets and abnormal outlets, and obtain the operating status type of each logistics outlet; Determine the scale type of each logistics network point, and generate a network point summary table based on the operation status type and scale type of each logistics network point; Analyze the network point summary table according to the summary report analysis fields to obtain the network point analysis results; In response to a data viewing instruction for a logistics network point, viewing the network point analysis result; In response to the instruction triggered on the cloud monitoring platform, the real-time operation information of the logistics network point is viewed.

[0097] In the embodiments of this specification, analysis reports of various dimensions can be constructed: 1: Regional screening conditions: headquarters-region-business province-grid area; 2: Network condition screening: all networks, sub-health networks, abnormal networks; 3: SELECTED selection box for network scale: all, large scale, medium scale, small scale, and very small scale; 4: Statistical dimensions: “aggregation dimension”, “network dimension”; The summary report analysis fields include: Branch basic information, abnormal assessment information, customer information, branch basic summary, branch management personnel The analysis fields of the branch report include: Branch basic information, abnormal assessment information, customer information, branch basic summary, branch management personnel You can click the [Outlet Name] link on the page to drill down and analyze the data.

[0098] In the embodiment of this specification, you can click the name of the outlet in the network management app-outlet 360 analysis report to enter the outlet detection page. Click the [Details button] to enter the detailed analysis page of the outlet layer throughout the life cycle of the outlet.

[0099] The functional steps of the network management app-branch details page are as follows: 1. Analysis of basic information of outlets Click [Cloud Monitoring Platform] and enter the branch monitoring area to check whether the branch's real-time operation is standardized.

[0100] Click the manager's [Phone] icon to contact the relevant person in charge by phone and remotely guide the person in charge on how to solve the problems in his section.

[0101] Click the [Navigation] icon on the right side of the branch address to jump to the third-party navigation APP for navigation to the branch destination, which makes it convenient for area managers to reach the destination with one click.

[0102] Click on the risk information to conduct a big data analysis of the branch label of this branch and the screening and suspension information in the area.

[0103] Click on the order splitting information to jump to the three-segment code related data layer, which provides the basic data basis for automatically sorting express parcels to outlets, and can perform order splitting intervention - order splitting intelligent diagnosis.

[0104] 2. Analysis of business volume of outlets Click the business volume information navigation bar to obtain ordering, collection, dispatch, and signing analysis data, and analyze and test the business layer of the outlets. At the same time, the market share of the outlets and the collection of scattered orders are fed back to further determine whether the business data of the outlets is within the threshold period.

[0105] 3. Branch customer information analysis Click the customer information navigation bar to obtain customer stratification information of different numbers of votes for this branch, which is used to detect the customer volume level of the branch. Click the customer insight navigation to obtain potential customer data, which is used to guide the branch to obtain more high-quality customers.

[0106] 4. Data analysis at the end of outlets Click on the receipt log navigation to obtain the receipt data, including multi-level analysis data from various third parties, to assist outlets in guiding receipt actions.

[0107] 5. Analysis of branch financial data By clicking on financial analysis, you can obtain the branch's prepayment details, the branch's financial income and expenditure information, and the branch's price policy information, which can help the branch to better guide and make decisions at the operational level.

[0108] 6. Timeliness and quality analysis of outlets Click on the outlet timeliness quality analysis to obtain the outlet's quality analysis data and the outlet's timeliness achievement data, providing the outlet with comprehensive guidance on KPI and timeliness assessment plans.

[0109] 7. Safety production analysis of outlets Click the safety production navigation bar to provide the safety personnel information and phone number. Click the phone icon to contact the safety officer to communicate and guide safety-related issues. At the same time, it provides the inspection information of the express market and the information of the twenty detailed inspections, real-time monitoring and assisting outlets to eliminate existing safety hazards.

[0110] It can be seen from the technical solutions provided in the above embodiments of this specification that, during the operation of the logistics outlets, the embodiments of this specification obtain the operation data of the logistics outlets; the operation data include the delivery area, the delivery volume, the collection volume and the signing rate; the operation data is analyzed and processed by the intelligent scheduling algorithm to optimize the delivery routes of the logistics orders in the logistics outlets; the compliance of the logistics outlets is regularly evaluated to obtain the first evaluation result of the logistics outlets; according to the operation status of the logistics outlets and the market change information, the logistics outlets are evaluated whether to continue to operate to obtain the second evaluation result; according to the first evaluation result and the second evaluation result, the operation cycle of the logistics outlets is determined. The present invention realizes the comprehensive integration of information, intelligent management, and data-driven decision-making; improves compliance and risk management capabilities, optimizes customer experience and service quality, and improves equipment management and maintenance efficiency, thereby promoting the further development and upgrading of the express delivery industry.

[0111] The embodiment of this specification also provides a life cycle assessment device for a logistics network point, such as Figure 6 As shown, the device comprises: Operation data acquisition module 610, used to acquire operation data of the logistics network point during the operation of the logistics network point; the operation data includes delivery area, delivery volume, collection volume and receipt rate; The route optimization module 620 is used to analyze and process the operation data using an intelligent scheduling algorithm to optimize the delivery routes of logistics orders in logistics outlets; A first evaluation module 630, configured to periodically perform compliance evaluation on the logistics network point to obtain a first evaluation result of the logistics network point; The second evaluation module 640 is used to evaluate whether the logistics network point continues to operate according to the operation status of the logistics network point and the market change information, and obtain a second evaluation result; The operation cycle determination module 650 is used to determine the operation cycle of the logistics network point according to the first evaluation result and the second evaluation result.

[0112] In an exemplary embodiment, the apparatus further comprises: An information acquisition module, used to acquire the network attribute information, management personnel information and registration information of the logistics network; the registration information includes registered capital and business license information; A plan generation module, used to automatically generate a location suggestion and an initial operation plan for the logistics network point based on the network point attribute information and the management personnel information; The verification result determination module is used to verify the registration information of the logistics network point and obtain the verification result of the logistics network point.

[0113] In an exemplary embodiment, the apparatus further comprises: A strategy determination module, used to determine the business structure adjustment strategy and personnel allocation optimization strategy of the logistics network point according to the operation data; A result prediction module is used to use a business volume prediction model to predict the business volume change results of the logistics network in the future period; A deployment module, used for deploying resources to the logistics network points according to the business volume change result; An identification module, used to conduct in-depth analysis of the operation data to identify the operation bottlenecks and potential growth points of the logistics network; The adjustment module is used to adjust the operation strategy of the logistics network according to the operation bottleneck and potential growth point of the logistics network.

[0114] In an exemplary embodiment, the apparatus further comprises: A business quantity acquisition module, used to acquire business volume data of the logistics network point, and determine the production volume category area corresponding to the logistics network point according to the business volume data; A statistical information acquisition module, used to obtain the individual order statistical information of the logistics network; A completion rate calculation module, used to calculate the target value completion rate of the logistics network point according to the real-time completion amount and the target completion amount of the orders in the logistics network point; The first state determination module is used to determine the first operation state of the logistics network point according to the production category, scattered order statistical information and target value completion rate of the logistics network point.

[0115] In an exemplary embodiment, the apparatus further comprises: A quantity acquisition module is used to obtain the total number of customers and the number of potential customers of the logistics outlets, and calculate the number of potential customer conversions and the potential customer conversion rate to obtain potential customer conversion information; A third-party information determination module is used to obtain the third-party collection ratio and the total number of third-party cooperation stations of the logistics outlets to obtain third-party information; A prepayment information determination module is used to obtain the total amount of prepayments, credit limits and shipment status of prepayment orders of the logistics outlet within a preset period of time, and obtain the prepayment information of the logistics outlet; A safety data acquisition module, used to acquire the financial revenue and expenditure, total revenue, service quality parameters and safety test results of the logistics network point, and obtain the service safety data of the logistics network point; The second status determination module is used to determine the second operating status of the logistics network point based on the potential customer conversion information, third-party information, prepayment information and service security data of the logistics network point.

[0116] In an exemplary embodiment, the apparatus further comprises: The operation status type acquisition module is used to acquire all logistics outlets in the preset area and identify sub-healthy outlets and abnormal outlets to obtain the operation status type of each logistics outlet; A summary table generation module is used to determine the scale type of each logistics network point and generate a network point summary table according to the operation status type and scale type of each logistics network point; A result analysis module, used to analyze the network point summary table according to the summary report analysis fields to obtain the network point analysis results; A result viewing module, used to view the analysis results of the logistics network points in response to the data viewing instruction of the logistics network points; The information viewing module is used to view the real-time operation information of the logistics network in response to the instructions triggered on the cloud monitoring platform.

[0117] In an exemplary embodiment, the operating cycle determination module includes: A first determination unit, configured to determine that the logistics outlet continues to operate if the first evaluation result is an outlet compliance result and the second evaluation result is an outlet continued operation result; A second determination unit is configured to determine that the logistics outlet will stop operating at a target time if the first evaluation result is that the outlet is non-compliant and the second evaluation result is that the outlet continues to operate; A third determining unit, configured to determine that the logistics outlet will stop operating at the target time if the first evaluation result is an outlet compliance result and the second evaluation result is an outlet closure result; The fourth determination unit is used to determine that the logistics network point will stop operating at the target time if the first evaluation result is a network point non-compliance result and the second evaluation result is a network point closure result.

[0118] The device and method embodiments in the described device embodiments are based on the same inventive concept.

[0119] An embodiment of the present specification provides an electronic device, which includes a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or at least one program is loaded and executed by the processor to implement a life cycle assessment method for a logistics network point as provided in the above method embodiment.

[0120] An embodiment of the present invention also provides a computer storage medium, which can be set in a terminal to store at least one instruction or at least one program related to a life cycle assessment method for a logistics network in a method embodiment. The at least one instruction or at least one program is loaded and executed by the processor to implement the life cycle assessment method for a logistics network provided in the above method embodiment.

[0121] The embodiment of the present invention also provides a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes to implement the life cycle assessment method of the logistics network point provided by the above method embodiment.

[0122] Optionally, in the embodiments of this specification, the storage medium may be located in at least one of the multiple network servers of the computer network. Optionally, in this embodiment, the storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store program codes.

[0123] The memory described in the embodiments of this specification can be used to store software programs and modules, and the processor executes various functional applications and data processing by running the software programs and modules stored in the memory. The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, application programs required for functions, etc.; the data storage area may store data created according to the use of the device, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage device. Accordingly, the memory may also include a memory controller to provide the processor with access to the memory.

[0124] The life cycle assessment method embodiment of the logistics network provided in the embodiments of this specification can be executed in a mobile terminal, a computer terminal, a server or a similar computing device. Taking running on a server as an example, Figure 7This is a hardware structure block diagram of a server for a life cycle assessment method for a logistics network provided in an embodiment of this specification. Figure 7 As shown, the server 700 may have relatively large differences due to different configurations or performances, and may include one or more central processing units (CPU) 710 (the central processing unit 710 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 730 for storing data, and one or more storage media 720 (such as one or more mass storage devices) for storing application programs 723 or data 722. Among them, the memory 730 and the storage medium 720 can be short-term storage or permanent storage. The program stored in the storage medium 720 may include one or more modules, each of which may include a series of instruction operations on the server. Furthermore, the central processing unit 710 can be configured to communicate with the storage medium 720 and execute a series of instruction operations in the storage medium 720 on the server 700. The server 700 may also include one or more power supplies 760, one or more wired or wireless network interfaces 750, one or more input and output interfaces 740, and / or one or more operating systems 721, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, etc.

[0125] The input / output interface 740 may be used to receive or send data via a network. A specific example of the network may include a wireless network provided by a communication provider of the server 700. In one example, the input / output interface 740 includes a network adapter (Network Interface Controller, NIC), which may be connected to other network devices via a base station so as to communicate with the Internet. In one example, the input / output interface 740 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0126] It can be understood by those skilled in the art that Figure 7 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 7 More or fewer components as shown, or with Figure 7 Different configurations are shown.

[0127] It can be seen from the embodiments of the life cycle assessment method, device, electronic device or storage medium of the logistics network provided by the present invention that the present invention obtains the operation data of the logistics network during the operation of the logistics network; the operation data includes the delivery area, the delivery volume, the collection volume and the signing rate; the operation data is analyzed and processed by the intelligent scheduling algorithm to optimize the delivery routes of the logistics orders in the logistics network; the compliance of the logistics network is evaluated regularly to obtain the first evaluation result of the logistics network; according to the operation status of the logistics network and the market change information, the logistics network is evaluated whether to continue to operate to obtain the second evaluation result; according to the first evaluation result and the second evaluation result, the operation cycle of the logistics network is determined. The present invention realizes the comprehensive integration of information, intelligent management, and data-driven decision-making; improves compliance and risk management capabilities, optimizes customer experience and service quality, and improves equipment management and maintenance efficiency, thereby promoting the further development and upgrading of the express delivery industry.

[0128] It should be noted that the above sequence of the embodiments of this specification is for description only and does not represent the advantages and disadvantages of the embodiments. The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0129] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0130] A person skilled in the art will appreciate that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer storage medium, and the storage medium mentioned above may be a read-only memory, a disk or an optical disk, etc.

[0131] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for evaluating the life cycle of a logistics network, characterized in that: The method comprises: During the operation of the logistics network, the operation data of the logistics network is obtained; the operation data includes the delivery area, the delivery volume, the collection volume and the receipt rate; Using intelligent scheduling algorithms to analyze and process the operational data, and optimize the delivery routes of logistics orders in logistics outlets; Regularly conduct compliance assessment on the logistics network point to obtain a first assessment result of the logistics network point; According to the operation status of the logistics network point and the market change information, evaluating whether the logistics network point continues to operate, and obtaining a second evaluation result; The operation cycle of the logistics network is determined according to the first evaluation result and the second evaluation result.

2. The method according to claim 1, characterized in that During the operation of the logistics network point, before obtaining the operation data of the logistics network point, the method further includes: Obtaining the network attribute information, management personnel information and registration information of the logistics network; the registration information includes registered capital and business license information; Automatically generate a site selection suggestion and an initial operation plan for the logistics network point based on the network point attribute information and the management personnel information; The registration information of the logistics network point is verified to obtain a verification result of the logistics network point.

3. The method according to claim 1, characterized in that The method further comprises: Determine the business structure adjustment strategy and personnel allocation optimization strategy of the logistics network based on the operation data; Use a business volume forecasting model to predict business volume changes at the logistics outlets in future periods; According to the business volume change result, resources are allocated to the logistics network points; Conduct in-depth analysis of the operational data to identify operational bottlenecks and potential growth points of the logistics network; The operation strategy of the logistics network is adjusted according to the operation bottlenecks and potential growth points of the logistics network.

4. The method according to claim 1, characterized in that: The method further comprises: Acquire the business volume data of the logistics network point, and determine the output category corresponding to the logistics network point according to the business volume data; Obtaining the individual order statistics of the logistics outlets; Calculate the target value completion rate of the logistics network point according to the real-time completion volume and target completion volume of the orders in the logistics network point; The first operation status of the logistics network point is determined according to the production category, individual order statistical information and target value completion rate of the logistics network point.

5. The method according to claim 1, characterized in that The method further comprises: Obtaining the total number of customers and potential customers of the logistics outlets, and calculating the number of potential customer conversions and the potential customer conversion rate to obtain potential customer conversion information; Obtain the third-party collection ratio and the total number of third-party cooperation stations of the logistics outlets to obtain third-party information; Obtain the total amount of prepayments, credit limits, and shipment status of prepayment orders of the logistics outlet within a preset period of time, and obtain the prepayment information of the logistics outlet; Obtain the financial income and expenditure, total revenue, service quality parameters and safety test results of the logistics network to obtain the service safety data of the logistics network; The second operation status of the logistics network is determined based on the potential customer conversion information, third-party information, prepayment information and service security data of the logistics network.

6. The method according to claim 1, characterized in that The method further comprises: Obtain all logistics outlets in the preset area and identify sub-healthy outlets and abnormal outlets, and obtain the operating status type of each logistics outlet; Determine the scale type of each logistics network point, and generate a network point summary table based on the operation status type and scale type of each logistics network point; Analyze the network point summary table according to the summary report analysis fields to obtain the network point analysis results; In response to a data viewing instruction for a logistics network point, viewing the network point analysis result; In response to the instruction triggered on the cloud monitoring platform, the real-time operation information of the logistics network point is viewed.

7. The method according to any one of claims 1 to 6, characterized in that: The determining the operation cycle of the logistics network point according to the first evaluation result and the second evaluation result includes: If the first evaluation result is that the outlet is compliant, and the second evaluation result is that the outlet continues to operate, it is determined that the logistics outlet continues to operate; If the first evaluation result is that the outlet is non-compliant, and the second evaluation result is that the outlet continues to operate, it is determined that the logistics outlet will stop operating at the target time; If the first evaluation result is a compliance result of the outlet, and the second evaluation result is a closure result of the outlet, it is determined that the logistics outlet will stop operating at the target time; If the first evaluation result is that the outlet is non-compliant and the second evaluation result is that the outlet is closed, it is determined that the logistics outlet will cease operations at the target time.

8. A life cycle assessment device for a logistics network, characterized in that: The device comprises: An operation data acquisition module, used to acquire the operation data of the logistics network point during the operation of the logistics network point; the operation data includes the delivery area, the delivery volume, the collection volume and the signing rate; A route optimization module, which is used to analyze and process the operation data using an intelligent scheduling algorithm to optimize the delivery routes of logistics orders in logistics outlets; A first evaluation module, used to regularly perform compliance evaluation on the logistics network point to obtain a first evaluation result of the logistics network point; A second evaluation module is used to evaluate whether the logistics network point continues to operate according to the operation status of the logistics network point and market change information, and obtain a second evaluation result; An operation cycle determination module is used to determine the operation cycle of the logistics network point according to the first evaluation result and the second evaluation result.

9. An electronic device, characterized in that: The device includes: a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or at least one program is loaded and executed by the processor to implement the life cycle assessment method of a logistics network point as described in any one of claims 1-7.

10. A computer storage medium, characterized in that: The computer storage medium stores at least one instruction or at least one program, and the at least one instruction or at least one program is loaded and executed by the processor to implement the life cycle assessment method of the logistics network as described in any one of claims 1-7.

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