Express optimal frequency optimization method and device, equipment and storage medium

Abstract

The invention relates to the technical field of information processing, in particular to an optimal express frequency optimization method and device, equipment and a storage medium, and the method comprises the steps: predicting the change trend data of order quantity through employing a time series analysis algorithm based on seasonal and daily fluctuation information, and determining frequency adjustment information according to the change trend data, performing local optimal frequency optimization on the plurality of logistics links according to the frequency adjustment information, generating a plurality of initial frequency combination schemes combined by different local frequency optimization information based on the constraint condition information, and evaluating the quality of each initial frequency combination scheme by using a preset scheme quality evaluation model, the optimal frequency combination scheme is determined according to the advantage and disadvantage sorting information of the frequency combination scheme, and the overall efficiency and benefit of express delivery can be more comprehensively improved by comprehensively considering the local optimal frequency of each link and then performing global optimal optimization, so that the site operation is more orderly and efficient, the labor cost is reduced, the overall delivery speed is improved, and the efficiency of express delivery is improved. And the satisfaction of customers is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of information processing, and particularly to an optimal frequency optimization method, device, equipment and storage medium for express delivery. Background Art

[0002] At present, with the booming rise of e-commerce, the volume of express delivery business has increased explosively. When the traditional express delivery operation mode deals with a huge number of orders, the frequency planning of each link lacks systematicness, often leading to problems such as delivery delays and high costs. For example, in the package sorting link, if the sorting frequency does not match the departure frequency of the transport vehicle, it may cause package backlogs; in the delivery link, if the delivery frequency of the delivery staff is unreasonable, it will reduce the delivery efficiency and affect the customer experience. Although there are certain logistics management means in the prior art, it fails to fully integrate data, algorithms and intelligent logistics technologies to achieve frequency optimization of the whole process, reducing the service quality and the competitiveness of express delivery companies. Summary of the Invention

[0003] In order to overcome the deficiencies of the prior art, the purpose of the present invention is to provide an optimal frequency optimization method, device, equipment and storage medium for express delivery, which can improve the overall delivery speed, optimize the frequencies of each link, make the site operations more orderly and efficient, reduce the waiting and idle time during the operation process, improve the operation efficiency of the site, reduce the labor cost, enhance the customer's usage experience, and increase the customer's satisfaction.

[0004] The first aspect of the present invention provides an optimal frequency optimization method for express delivery, including: collecting historical order data, and analyzing the seasonal and daily fluctuation information of orders according to the historical order data; based on the seasonal and daily fluctuation information, using a time series analysis algorithm to predict the change trend data of the order volume, and determining frequency adjustment information according to the change trend data; respectively performing local optimal frequency optimization on multiple logistics links according to the frequency adjustment information to obtain multiple local frequency optimization information, defining the constraints between the frequencies of each link to obtain constraint condition information; based on the constraint condition information, generating multiple initial frequency combination schemes composed of different combinations of the local frequency optimization information, evaluating the advantages and disadvantages of each initial frequency combination scheme using a preset scheme quality evaluation model to obtain frequency combination scheme quality ranking information; determining the optimal frequency combination scheme according to the frequency combination scheme quality ranking information, and sending the optimal frequency combination scheme to the management terminal.

[0005] Optionally, in the first implementation manner of the first aspect of the present invention, the collecting of historical order data and the analysis of the seasonal and daily fluctuation information of orders based on the historical order data include: collecting historical order data; performing data cleaning on the historical order data to obtain cleaned historical order data, filling in missing values in the cleaned historical order data to obtain filled historical order data; performing format conversion on the filled historical order data based on a preset target standard format to obtain standard historical order data; and analyzing the seasonal and daily fluctuation information of orders based on the standard historical order data.

[0006] Optionally, in the second implementation manner of the first aspect of the present invention, the predicting of the change trend data of the order volume using a time series analysis algorithm based on the seasonal and daily fluctuation information and the determination of frequency adjustment information based on the change trend data include: predicting the change trend data of the order volume using a time series analysis algorithm based on the seasonal and daily fluctuation information; collecting operation data of each express delivery station, various cost data related to express delivery, and feedback data of customers on express delivery services, where the operation data includes operation frequency, operation time, and operation volume, the various cost data includes transportation cost, labor cost, and site rent, and the feedback data includes satisfaction surveys and complaint records; and comprehensively analyzing the change trend data, the operation data, the various cost data, and the feedback data to obtain frequency adjustment information.

[0007] Optionally, in the third implementation manner of the first aspect of the present invention, locally optimizing the frequencies of multiple logistics links respectively according to the frequency adjustment information to obtain multiple locally optimized frequency information, and defining the constraints between the frequencies of each link to obtain constraint condition information, including: classifying the frequencies of multiple logistics links to obtain the pick-up frequency of the origin network point, the trunk shuttle frequency, the end distribution and delivery frequency, and the delivery frequency of the destination network point; locally optimizing the pick-up frequency of the origin network point according to the frequency adjustment information and in combination with the linear programming algorithm to obtain the first optimized frequency information; locally optimizing the trunk shuttle frequency according to the frequency adjustment information and in combination with the genetic algorithm to obtain the second optimized frequency information; locally optimizing the end distribution and delivery frequency according to the frequency adjustment information and in combination with the LSTM algorithm to obtain the third optimized frequency information; locally optimizing the delivery frequency of the destination network point according to the frequency adjustment information and in combination with the path planning algorithm to obtain the fourth optimized frequency information, and the first optimized frequency information, the second optimized frequency information, the third optimized frequency information, and the fourth optimized frequency information are all locally optimized frequency information; defining the constraints between the first optimized frequency information, the second optimized frequency information, the third optimized frequency information, and the fourth optimized frequency information to obtain constraint condition information, and the constraint condition information includes cost constraint, time window constraint, and resource constraint.

[0008] Optionally, in the fourth implementation manner of the first aspect of the present invention, generating multiple initial frequency combination schemes composed of different local frequency optimization information based on the constraint condition information, and evaluating the pros and cons of each initial frequency combination scheme to obtain frequency combination scheme pros and cons ranking information, including: defining a comprehensive objective function composed of a distribution efficiency dimension, a cost-benefit dimension, and a customer satisfaction dimension; generating multiple initial frequency combination schemes composed of different local frequency optimization information based on the constraint condition information and the comprehensive objective function; evaluating the pros and cons of each initial frequency combination scheme to obtain frequency combination scheme evaluation information; sorting the multiple frequency combination scheme evaluation information to obtain frequency combination scheme pros and cons ranking information.

[0009] Optionally, in the fifth implementation manner of the first aspect of the present invention, determining the best frequency combination scheme according to the frequency combination scheme pros and cons ranking information, and sending the best frequency combination scheme to the management terminal, including: determining the best frequency combination scheme according to the frequency combination scheme pros and cons ranking information; calling a preset visualization scheme template according to the best frequency combination scheme; filling the best frequency combination scheme into the visualization scheme template to obtain a frequency combination scheme report; sending the frequency combination scheme report to the management terminal so that the management terminal generates and displays a frequency combination scheme page based on the frequency combination scheme report.

[0010] Optionally, in the sixth implementation manner of the first aspect of the present invention, after determining the optimal frequency combination plan according to the frequency combination plan quality ranking information and sending the optimal frequency combination plan to the management terminal, the method further includes: receiving plan implementation result information; analyzing the plan implementation effect of the plan implementation result information to obtain plan implementation effect information, where the plan implementation effect information includes the improvement degree of distribution efficiency, the cost saving degree, and customer satisfaction; extracting the data characteristics of the plan implementation effect information, generating a model training sample according to the data characteristics; and adjusting the parameters of the plan quality evaluation model by using the model training sample.

[0011] The second aspect of the present invention provides an express delivery optimal frequency optimization device, including: a collection and analysis module, configured to collect historical order data and analyze the seasonal and daily fluctuation information of the order according to the historical order data; a prediction and determination module, configured to predict the change trend data of the order volume by using a time series analysis algorithm based on the seasonal and daily fluctuation information, and determine frequency adjustment information according to the change trend data; an optimization and definition module, configured to perform local optimal frequency optimization on multiple logistics links respectively according to the frequency adjustment information to obtain multiple local frequency optimization information, and define the constraints between the frequencies of each link to obtain constraint condition information; a generation and evaluation module, configured to generate multiple initial frequency combination plans composed of different local frequency optimization information based on the constraint condition information, evaluate the quality of each initial frequency combination plan to obtain frequency combination plan quality ranking information; and a determination and sending module, configured to determine the optimal frequency combination plan according to the frequency combination plan quality ranking information and send the optimal frequency combination plan to the management terminal.

[0012] Optionally, in the first implementation manner of the second aspect of the present invention, the collection and analysis module includes: a first collection unit, configured to collect historical order data; a cleaning and filling unit, configured to perform data cleaning on the historical order data to obtain historical order cleaning data, and perform missing value filling on the historical order cleaning data to obtain historical order filling data; a conversion unit, configured to perform format conversion on the historical order filling data based on a preset target standard format to obtain historical order standard data; and a first analysis unit, configured to analyze the seasonal and daily fluctuation information of the order according to the historical order standard data.

[0013] Optionally, in the second implementation manner of the second aspect of the present invention, the prediction and determination module includes: a prediction unit, configured to predict the change trend data of the order volume based on the seasonal and daily fluctuation information by using a time series analysis algorithm; a second collection unit, configured to collect the operation data of each express delivery station, various cost data related to express delivery, and feedback data of customers on express delivery services, where the operation data includes operation frequency, operation time, and operation volume, the various cost data includes transportation cost, labor cost, and site rent, and the feedback data includes satisfaction surveys and complaint records; a second analysis unit, configured to perform comprehensive analysis based on the change trend data, the operation data, the various cost data, and the feedback data to obtain frequency adjustment information.

[0014] Optionally, in the third implementation manner of the second aspect of the present invention, the optimization and definition module includes: a classification unit, configured to classify the frequencies of multiple logistics links to obtain the pick-up frequency of the origin network point, the trunk shuttle frequency, the end distribution and distribution frequency, and the delivery frequency of the destination network point; a first optimization unit, configured to perform local optimal frequency optimization on the pick-up frequency of the origin network point according to the frequency adjustment information and in combination with a linear programming algorithm to obtain first frequency optimization information; a second optimization unit, configured to perform local optimal frequency optimization on the trunk shuttle frequency according to the frequency adjustment information and in combination with a genetic algorithm to obtain second frequency optimization information; a third optimization unit, configured to perform local optimal frequency optimization on the end distribution and distribution frequency according to the frequency adjustment information and in combination with an LSTM algorithm to obtain third frequency optimization information; a fourth optimization unit, configured to perform local optimal frequency optimization on the delivery frequency of the destination network point according to the frequency adjustment information and in combination with a path planning algorithm to obtain fourth frequency optimization information, where the first frequency optimization information, the second frequency optimization information, the third frequency optimization information, and the fourth frequency optimization information are all local frequency optimization information; a first definition unit, configured to define the constraints between the first frequency optimization information, the second frequency optimization information, the third frequency optimization information, and the fourth frequency optimization information to obtain constraint condition information, where the constraint condition information includes cost constraints, time window constraints, and resource constraints.

[0015] Optionally, in the fourth implementation manner of the second aspect of the present invention, the generation and evaluation module includes: a second definition unit, configured to define a comprehensive objective function composed of a distribution efficiency dimension, a cost-benefit dimension, and a customer satisfaction dimension; a generation unit, configured to generate multiple initial frequency combination schemes composed of different combinations of the local frequency optimization information based on the constraint condition information and the comprehensive objective function; an evaluation unit, configured to evaluate the advantages and disadvantages of each initial frequency combination scheme to obtain frequency combination scheme evaluation information; a sorting unit, configured to sort the multiple frequency combination scheme evaluation information to obtain frequency combination scheme pros and cons sorting information.

[0016] Optionally, in the fifth implementation manner of the second aspect of the present invention, the determining and sending module includes: a determining unit, configured to determine the optimal frequency combination scheme according to the frequency combination scheme superiority and inferiority sorting information; a calling unit, configured to call a preset visualization scheme template according to the optimal frequency combination scheme; a filling unit, configured to fill the optimal frequency combination scheme into the visualization scheme template to obtain a frequency combination scheme report; and a sending unit, configured to send the frequency combination scheme report to a management terminal, so that the management terminal generates and displays a frequency combination scheme page based on the frequency combination scheme report.

[0017] Optionally, in the sixth implementation manner of the second aspect of the present invention, it further includes: a receiving module, configured to receive scheme implementation result information; an analyzing module, configured to analyze the scheme implementation effect of the scheme implementation result information to obtain scheme implementation effect information, where the scheme implementation effect information includes the improvement degree of delivery efficiency, the cost saving degree, and the customer satisfaction; an extracting and generating module, configured to extract data features of the scheme implementation effect information and generate a model training sample according to the data features; and an adjusting module, configured to adjust parameters of the scheme superiority and inferiority evaluation model by using the model training sample.

[0018] The third aspect of the present invention provides an express delivery optimal frequency optimization device, where the express delivery optimal frequency optimization device includes: a memory and at least one processor, and instructions are stored in the memory; at least one of the processors calls the instructions in the memory, so that the express delivery optimal frequency optimization device executes each step of the express delivery optimal frequency optimization method described in any one of the above.

[0019] The fourth aspect of the present invention provides a computer-readable storage medium, where instructions are stored on the computer-readable storage medium, and when the instructions are executed by a processor, each step of the express delivery optimal frequency optimization method described in any one of the above is implemented.

[0020] In the technical solution of the present invention, a time series analysis algorithm is used to predict the change trend data of the order volume based on seasonal and daily fluctuation information. The frequency adjustment information is determined according to the change trend data. Local optimal frequency optimization is performed on multiple logistics links respectively according to the frequency adjustment information to obtain multiple local frequency optimization information. Based on the constraint condition information, multiple initial frequency combination schemes composed of different local frequency optimization information are generated. The preset scheme quality evaluation model is used to evaluate the quality of each initial frequency combination scheme to obtain the frequency combination scheme quality ranking information. According to the frequency combination scheme quality ranking information, the best frequency combination scheme is determined. By comprehensively considering the local optimal frequencies of each link and then performing global optimal optimization, the overall efficiency and benefit of express delivery can be improved more comprehensively, making the site operation more orderly and efficient, increasing the overall delivery speed, reducing the waiting and idle time during the operation process, improving the operation efficiency of the site, reducing the labor cost, enhancing the user experience of customers, and increasing the customer satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is the first flowchart of the express best frequency optimization method provided by the embodiment of the present invention;

[0022] Figure 2 It is the second flowchart of the express best frequency optimization method provided by the embodiment of the present invention;

[0023] Figure 3 It is the third flowchart of the express best frequency optimization method provided by the embodiment of the present invention;

[0024] Figure 4 It is the fourth flowchart of the express best frequency optimization method provided by the embodiment of the present invention;

[0025] Figure 5 It is a schematic structural diagram of an express best frequency optimization device provided by the embodiment of the present invention;

[0026] Figure 6 It is another schematic structural diagram of an express best frequency optimization device provided by the embodiment of the present invention;

[0027] Figure 7 It is a schematic structural diagram of an express best frequency optimization device provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] The present invention provides an express best frequency optimization method, device, equipment and storage medium, which improves the overall delivery speed, optimizes the frequencies of each link, makes the site operation more orderly and efficient, reduces the waiting and idle time during the operation process, improves the operation efficiency of the site, reduces the labor cost, enhances the user experience of customers, and increases the customer satisfaction.

[0029] In the description, claims and the above-mentioned drawings of the present invention, terms such as "first", "second", "third", "fourth", etc. (if any) are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances so that the embodiments described herein can be implemented in an order other than those illustrated or described herein. In addition, the term "comprising" or "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily limit to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0030] For ease of understanding, the specific process of the embodiments of the present invention will be described below. Please refer to Figure 1 , an embodiment of the optimal delivery frequency optimization method in the embodiments of the present invention includes:

[0031] 101. Collect historical order data, and analyze the seasonal and daily fluctuation information of orders based on the historical order data;

[0032] In this embodiment, obtain historical order data from the company's order management system. After data collection, it is necessary to preprocess the data, analyze the order fluctuations of each year, understand whether there are specific months with particularly high order volumes, analyze the impact of holidays, evaluate the changes in order volumes before and after holidays, analyze the changes in order volumes in different time periods by grouping orders by hour or minute, and use visualization means such as heat maps or line charts to display the order distribution in each period of a day. Combine seasonal fluctuations with daily fluctuations to obtain seasonal and daily fluctuation information.

[0033] 102. Based on the seasonal and daily fluctuation information, use a time series analysis algorithm to predict the change trend data of order volumes, and determine frequency adjustment information according to the change trend data;

[0034] In this embodiment, based on the seasonal and daily fluctuation information, use a time series analysis algorithm to predict the change trend data of order volumes, combine seasonal decomposition, identify short-term and long-term fluctuation trends of order volumes, determine the changes in order volumes in the next few months or weeks, identify the peak and trough periods of order volumes according to the predicted change trend of order volumes, and determine frequency adjustment information according to the change trend data. The frequency adjustment information includes specific adjustment strategies for peak and trough periods, clarifying when to increase or decrease the delivery frequency to ensure the efficient use of resources.

[0035] 103. Optimize the local optimal frequency for multiple logistics links respectively according to the frequency adjustment information to obtain multiple local frequency optimization information, define the constraints between the frequencies of each link, and obtain the constraint condition information;

[0036] In this embodiment, the logistics process is decomposed into multiple links, each link has an independent frequency adjustment requirement. Optimize the local optimal frequency for multiple logistics links respectively according to the frequency adjustment information to obtain multiple local frequency optimization information, and define the constraints between the frequencies of each link according to the connection and dependence relationships between different links to obtain the constraint condition information.

[0037] 104. Based on the constraint condition information, generate multiple initial frequency combination schemes composed of different local frequency optimization information, and use a preset scheme quality evaluation model to evaluate the quality of each initial frequency combination scheme to obtain the frequency combination scheme quality ranking information;

[0038] In this embodiment, generate multiple initial frequency combination schemes composed of different local frequency optimization information based on the constraint condition information. The constraint condition information includes the maximum and minimum limits for each frequency, the relationships between frequencies (for example, some frequencies must appear in the scheme at the same time, or some frequencies cannot appear at the same time), and other possible business rules or optimization objectives. The evaluation criteria include the feasibility of the scheme, the effect of the scheme, and the stability of the scheme. The ranking is based on the score. The scheme with a higher score is considered better.

[0039] 105. Determine the best frequency combination scheme according to the frequency combination scheme quality ranking information, and send the best frequency combination scheme to the management terminal;

[0040] In this embodiment, select the scheme with the highest score from the frequency combination scheme quality ranking information as the best frequency combination scheme, and send the best frequency combination scheme to the management terminal through an appropriate communication protocol.

[0041] In the embodiments of the present invention, a time series analysis algorithm is used to predict the change trend data of the order volume based on seasonal and daily fluctuation information. The frequency adjustment information is determined according to the change trend data. The local optimal frequencies of multiple logistics links are optimized respectively according to the frequency adjustment information to obtain multiple local frequency optimization information. Based on the constraint condition information, multiple initial frequency combination schemes composed of different local frequency optimization information are generated. The preset scheme quality evaluation model is used to evaluate the quality of each initial frequency combination scheme to obtain the frequency combination scheme quality ranking information. The best frequency combination scheme is determined according to the frequency combination scheme quality ranking information. By comprehensively considering the local optimal frequencies of each link and then performing global optimal optimization, the overall efficiency and benefit of express delivery can be improved more comprehensively, making the site operation more orderly and efficient, improving the overall delivery speed, reducing the waiting and idle time during the operation process, improving the operation efficiency of the site, reducing the labor cost, enhancing the user experience of customers, and increasing the customer satisfaction.

[0042] Please refer to Figure 2 , the second embodiment of the best frequency optimization method for express delivery in the embodiments of the present invention includes:

[0043] 201. Collect historical order data;

[0044] In this embodiment, the historical order data is directly obtained by querying the enterprise's database system, or the historical order data is regularly pulled by calling the provided API interface.

[0045] 202. Clean the historical order data to obtain the cleaned historical order data, and fill in the missing values of the cleaned historical order data to obtain the filled historical order data;

[0046] In this embodiment, duplicate records of the historical order data are identified and deleted by comparing key fields such as order ID, customer ID, and order time. Through data screening, values that are obviously unreasonable are identified and corrected or deleted, and unnecessary columns or fields are deleted, and only the core fields required for analysis are retained to obtain the cleaned historical order data. Check the missing situation of each field. For the missing numerical fields (such as order amount, number of goods, etc.), the mean value of the field is selected for filling. If the data is severely skewed, the median is selected for filling. In some cases, the missing values may be affected by adjacent data. For example, the delivery time field of the order may be filled according to the time of the previous order. For the missing categorical fields (such as customer type, order status, etc.), the most common value in the field is used for filling to obtain the filled historical order data.

[0047] 203. Based on the preset target standard format, convert the format of the filled historical order data to obtain the standard historical order data;

[0048] In this embodiment, through the field mapping relationship, the field names in the original data are converted into field names in the target standard format. According to the requirements of the target standard format, the data types of each field are uniformly converted, all date and time fields are unified in format, and according to the standard format requirements, the field values are mapped or converted to obtain the historical order standard data.

[0049] 204. Analyze the seasonal and daily fluctuation information of orders based on the historical order standard data;

[0050] In this embodiment, based on the historical order standard data, analyze the order fluctuations each year to understand whether there are specific months with particularly high order volumes. By analyzing the impact of holidays, evaluate the changes in order volumes before and after holidays. By grouping orders by hour or minute, analyze the changes in order volumes at different time periods, and use visualization means such as heat maps or line charts to display the order distribution within a day. Combine the seasonal fluctuations with the daily fluctuations to obtain the seasonal and daily fluctuation information.

[0051] 205. Based on the seasonal and daily fluctuation information, use time series analysis algorithms to predict the change trend data of order volumes;

[0052] In this embodiment, based on the seasonal and daily fluctuation information, use time series analysis algorithms to predict the change trend data of order volumes. Combine seasonal decomposition to identify the short-term and long-term fluctuation trends of order volumes, determine the changes in order volumes in the next few months or weeks, and based on the predicted change trend of order volumes, identify the peak and trough periods of order volumes.

[0053] 206. Collect the operation data of each express delivery station, various cost data related to express delivery, and customer feedback data on express delivery services. The operation data includes operation frequency, operation time, and operation volume. The various cost data includes transportation costs, labor costs, and site rents. The feedback data includes satisfaction surveys and complaint records;

[0054] In this embodiment, collect the operation data of each express delivery station, various cost data related to express delivery, and customer feedback data on express delivery services. The operation data is the basic data used to describe the operation efficiency and workload of the express delivery station, including operation frequency, operation time, and operation volume. The various cost data is used to evaluate the operation costs and efficiency of the express delivery station, including transportation costs, labor costs, and site rents. The customer feedback data is an important basis for evaluating service quality, including satisfaction surveys and complaint records.

[0055] 207. Conduct a comprehensive analysis based on the change trend data, operation data, various cost data, and feedback data to obtain frequency adjustment information;

[0056] In this embodiment, potential change patterns can be identified from the trend data, so as to predict future demand changes and cost changes, and guide frequency adjustment. The operation data can directly reflect the rationality of the current operation frequency and operation time. Each cost data reflects the capital expenditure in the site operation. The adjustment of the frequency directly affects cost control. It is necessary to analyze each cost data to find the impact of frequency adjustment on costs. The customer feedback data directly reflects whether the frequency adjustment can improve service quality. Analyze the customer feedback data under different frequencies to determine whether the frequency is proportional to customer satisfaction. Combine the above aspects of analysis to obtain frequency adjustment information.

[0057] In the embodiment of the present invention, data in multiple dimensions such as orders, operations, costs, and customer feedback are covered, ensuring that decisions are based on comprehensive information. Through data cleaning and filling missing values, the accuracy and integrity of the data are improved, providing a reliable basis for subsequent analysis. Through the analysis of seasonality and daily fluctuations, the change trend of the order volume can be accurately predicted to help optimize resource allocation. Combining operation data and cost data, inefficient links can be identified and adjusted, thereby reducing costs and improving service quality. By integrating customer satisfaction and complaint feedback into the analysis, it is ensured that the final optimization plan not only focuses on efficiency but also improves the customer experience.

[0058] Please refer to Figure 3 , the third embodiment of the optimal express delivery frequency method in the embodiment of the present invention includes:

[0059] 301. Classify the frequencies of multiple logistics links to obtain the pick-up frequency of the origin network point, the trunk shuttle frequency, the end distribution frequency, and the delivery frequency of the destination network point;

[0060] In this embodiment, the frequencies of multiple logistics links are classified to obtain multiple local frequency classification information, and each local frequency classification information is one of the pick-up frequency of the origin network point, the trunk shuttle frequency, the end distribution frequency, and the delivery frequency of the destination network point.

[0061] 302. According to the frequency adjustment information and in combination with the linear programming algorithm, perform local optimal frequency optimization on the pick-up frequency of the origin network point to obtain the first frequency optimization information;

[0062] In this embodiment, according to the frequency adjustment information, a linear programming model is constructed to optimize the pick-up frequency of the origin network point to obtain the first frequency optimization information.

[0063] 303. According to the frequency adjustment information and in combination with the genetic algorithm, perform local optimal frequency optimization on the trunk shuttle frequency to obtain the second frequency optimization information;

[0064] In this embodiment, according to the frequency adjustment information, a genetic algorithm model is constructed to optimize the trunk shuttle frequency, and the second frequency optimization information is obtained.

[0065] 304. According to the frequency adjustment information and combined with the LSTM algorithm, perform local optimal frequency optimization on the end distribution frequency to obtain the third frequency optimization information;

[0066] In this embodiment, according to the frequency adjustment information, an LSTM algorithm model is constructed to optimize the end distribution frequency, and the third frequency optimization information is obtained.

[0067] 305. According to the frequency adjustment information and combined with the path planning algorithm, perform local optimal frequency optimization on the delivery frequency of the destination network point to obtain the fourth frequency optimization information. The first frequency optimization information, the second frequency optimization information, the third frequency optimization information, and the fourth frequency optimization information are all local frequency optimization information;

[0068] In this embodiment, according to the frequency adjustment information, a path planning algorithm model is constructed to optimize the delivery frequency of the destination network point to obtain the fourth frequency optimization information. The first frequency optimization information, the second frequency optimization information, the third frequency optimization information, and the fourth frequency optimization information are all local frequency optimization information.

[0069] 306. Define the constraints between the first frequency optimization information, the second frequency optimization information, the third frequency optimization information, and the fourth frequency optimization information to obtain the constraint condition information. The constraint condition information includes cost constraint, time window constraint, and resource constraint;

[0070] In this embodiment, define the constraints between the first frequency optimization information, the second frequency optimization information, the third frequency optimization information, and the fourth frequency optimization information to obtain the constraint condition information. The constraint condition information includes cost constraint, time window constraint, and resource constraint. The optimization of each stage should ensure that it does not exceed the original cost range, and try to reduce the total cost through path optimization and frequency adjustment. The frequency optimization of each stage should follow the time window requirements set for each network point, and at the same time consider the impact of dynamic traffic, weather and other factors on the delivery timeliness. The optimization of each stage requires reasonable allocation of resources, such as the number of vehicles, the number of delivery personnel, the delivery path, etc., to ensure that the demand can be met and the efficiency can be improved.

[0071] 307. Define a comprehensive objective function composed of the dimensions of delivery efficiency, cost-benefit, and customer satisfaction;

[0072] In this embodiment, define a comprehensive objective function composed of the dimensions of delivery efficiency, cost-benefit, and customer satisfaction, and fuse the objectives of the delivery efficiency dimension, the cost-benefit dimension, and the customer satisfaction dimension together by means of weighted summation.

[0073] 308. Generate multiple initial frequency combination schemes composed of different combinations of local frequency optimization information based on constraint condition information and a comprehensive objective function;

[0074] In this embodiment, when generating multiple initial frequency combination schemes composed of different combinations of local frequency optimization information, after each initial frequency combination scheme is generated, it is necessary to evaluate its impact on the comprehensive objective function and ensure that the scheme meets the constraint condition information.

[0075] 309. Evaluate the advantages and disadvantages of each initial frequency combination scheme to obtain frequency combination scheme evaluation information;

[0076] In this embodiment, by assigning a weight to each evaluation dimension and then calculating the comprehensive score of the scheme based on the score of each dimension, and further evaluating the advantages and disadvantages of each initial frequency combination scheme according to the comprehensive score to obtain frequency combination scheme evaluation information.

[0077] 310. Sort the multiple frequency combination scheme evaluation information to obtain frequency combination scheme ranking information on advantages and disadvantages;

[0078] In this embodiment, sort the multiple frequency combination scheme evaluation information based on the high and low of the comprehensive score to obtain frequency combination scheme ranking information on advantages and disadvantages. The scheme with a higher score is considered to be better.

[0079] In the embodiment of the present invention, by classifying and locally optimizing the frequencies of multiple logistics links, the frequency of each link is optimally adjusted with the support of a specific algorithm, ensuring the efficient operation of each link. By using linear programming, genetic algorithms, LSTM algorithms, and path planning algorithms, the most suitable optimization tools are used for different links, improving the accuracy and effectiveness of optimization. By setting a comprehensive objective function (including distribution efficiency, cost-effectiveness, and customer satisfaction), it is ensured that the optimization not only focuses on a single dimension but also takes into account multiple objectives to improve the overall benefit. By clarifying the constraint conditions (such as cost, time window, resources) between each link, the optimization scheme is made more feasible in actual operation and over-idealization is avoided. By evaluating and ranking the frequency combination schemes, it is possible to understand the advantages and disadvantages of different schemes in real time and ensure that the finally selected scheme can maximize the interests in all aspects.

[0080] Please refer to Figure 4 , the fourth embodiment of the optimal frequency optimization method for express delivery in the embodiment of the present invention includes:

[0081] 401. Determine the best frequency combination scheme according to the frequency combination scheme ranking information on advantages and disadvantages;

[0082] In this embodiment, select the scheme with the highest score from the frequency combination scheme ranking information on advantages and disadvantages as the best frequency combination scheme.

[0083] 402. Call the preset visualization scheme template according to the optimal frequency combination scheme;

[0084] In this embodiment, select a suitable visualization scheme template according to the complexity and display type of the optimal frequency combination scheme.

[0085] 403. Fill the optimal frequency combination scheme into the visualization scheme template to obtain a frequency combination scheme report;

[0086] In this embodiment, after determining the appropriate visualization scheme template, extract the key data to be displayed from the optimal frequency combination scheme, and fill the key data into the visualization scheme template to obtain a frequency combination scheme report.

[0087] 404. Send the frequency combination scheme report to the management terminal so that the management terminal generates and displays a frequency combination scheme page based on the frequency combination scheme report;

[0088] In this embodiment, send the frequency combination scheme report to the management terminal through email or API interface. After receiving the frequency combination scheme report, the management terminal will automatically parse it so that the management terminal generates and displays a frequency combination scheme page based on the frequency combination scheme report.

[0089] 405. Receive the information on the implementation result of the scheme;

[0090] In this embodiment, after the implementation of the scheme is completed, the information on the implementation result of the scheme is entered into the management terminal, a listener is created, and the listener is used to monitor the information on the implementation result of the scheme. When the listener monitors that the information on the implementation result of the scheme is entered into the management terminal, obtain the current information on the implementation result of the scheme.

[0091] 406. Analyze the implementation effect of the information on the implementation result of the scheme to obtain the information on the implementation effect of the scheme. The information on the implementation effect of the scheme includes the improvement degree of distribution efficiency, the degree of cost savings, and customer satisfaction;

[0092] In this embodiment, analyze the implementation effect of the information on the implementation result of the scheme to obtain the information on the implementation effect of the scheme. The information on the implementation effect of the scheme includes the improvement degree of distribution efficiency, the degree of cost savings, and customer satisfaction. Through the comprehensive analysis of distribution efficiency, cost savings, and customer satisfaction, the implementation effect of the scheme can be comprehensively evaluated.

[0093] 407. Extract the data features of the information on the implementation effect of the scheme, and generate model training samples according to the data features;

[0094] In this embodiment, relevant data features of distribution efficiency, cost savings, and customer satisfaction in the implementation effect information of the extraction solution are extracted. Once the relevant data features are extracted, the next step is to convert these data features into training samples for the machine learning model.

[0095] 408. Adjust the parameters of the solution quality evaluation model using the model training samples;

[0096] In this embodiment, understand the hyperparameters of the solution quality evaluation model, and based on the model training samples, use grid search, random search, or Bayesian optimization to adjust the hyperparameters of the solution quality evaluation model, and apply the optimized solution quality evaluation model to solution evaluation.

[0097] In the embodiment of the present invention, through comprehensive evaluation, implementation, and effect analysis, a closed-loop optimization is formed to continuously improve the decision-making quality. Through the automatic generation and display of templates and reports, the operation process is simplified, the efficiency and operability are improved. Based on the data feedback of the implementation effect, the model is used to adjust and optimize the solution evaluation, improving the accuracy of future decisions. Through model training and parameter adjustment, the frequency combination solution can be continuously optimized according to historical data, ensuring continuous improvement of distribution efficiency, cost control, and customer satisfaction.

[0098] The above describes the express best frequency optimization method in the embodiment of the present invention. Next, the express best frequency optimization device in the embodiment of the present invention will be described. Please refer to Figure 5 , an embodiment of the express best frequency optimization device in the embodiment of the present invention includes:

[0099] A collection and analysis module 501, configured to collect historical order data and analyze the seasonal and daily fluctuation information of the orders according to the historical order data;

[0100] A prediction and determination module 502, configured to predict the change trend data of the order volume using a time series analysis algorithm based on the seasonal and daily fluctuation information, and determine the frequency adjustment information according to the change trend data;

[0101] An optimization definition module 503, configured to perform local optimal frequency optimization on multiple logistics links respectively according to the frequency adjustment information to obtain multiple local frequency optimization information, and define the constraints between the frequencies of each link to obtain constraint condition information;

[0102] A generation and evaluation module 504, configured to generate multiple initial frequency combination solutions composed of different local frequency optimization information based on the constraint condition information, evaluate the pros and cons of each initial frequency combination solution, and obtain frequency combination solution pros and cons ranking information;

[0103] A determination and sending module 505, configured to determine the best frequency combination solution according to the frequency combination solution pros and cons ranking information, and send the best frequency combination solution to the management terminal.

[0104] In this embodiment, a time series analysis algorithm is used to predict the changing trend data of the order volume based on seasonal and daily fluctuation information. The frequency adjustment information is determined according to the changing trend data. Local optimal frequency optimization is performed on multiple logistics links respectively according to the frequency adjustment information to obtain multiple local frequency optimization information. Based on the constraint condition information, multiple initial frequency combination schemes composed of different local frequency optimization information are generated. The preset scheme quality evaluation model is used to evaluate the quality of each initial frequency combination scheme to obtain the frequency combination scheme quality ranking information. By comprehensively considering the local optimal frequencies of each link and then performing global optimal optimization, the overall efficiency and benefit of express delivery can be improved more comprehensively, making the site operation more orderly and efficient, increasing the overall delivery speed, reducing the waiting and idle time during the operation process, improving the operation efficiency of the site, reducing labor costs, enhancing the user experience of customers, and increasing customer satisfaction.

[0105] Please refer to Figure 6 , another embodiment of the express best frequency optimization device in the embodiment of the present invention includes:

[0106] A collection and analysis module 501, configured to collect historical order data and analyze the seasonal and daily fluctuation information of the orders according to the historical order data;

[0107] A prediction and determination module 502, configured to predict the changing trend data of the order volume using a time series analysis algorithm based on the seasonal and daily fluctuation information, and determine the frequency adjustment information according to the changing trend data;

[0108] An optimization and definition module 503, configured to perform local optimal frequency optimization on multiple logistics links respectively according to the frequency adjustment information to obtain multiple local frequency optimization information, and define the constraints between the frequencies of each link to obtain the constraint condition information;

[0109] A generation and evaluation module 504, configured to generate multiple initial frequency combination schemes composed of different local frequency optimization information based on the constraint condition information, evaluate the quality of each initial frequency combination scheme, and obtain the frequency combination scheme quality ranking information;

[0110] A determination and sending module 505, configured to determine the best frequency combination scheme according to the frequency combination scheme quality ranking information and send the best frequency combination scheme to the management terminal;

[0111] In this embodiment, the collection and analysis module 501 includes: a first collection unit 5011 for collecting historical order data; a cleaning and filling unit 5012 for cleaning the historical order data to obtain cleaned historical order data, and filling missing values in the cleaned historical order data to obtain filled historical order data; a conversion unit 5013 for converting the format of the filled historical order data based on a preset target standard format to obtain standard historical order data; and a first analysis unit 5014 for analyzing the seasonal and daily fluctuation information of orders according to the standard historical order data.

[0112] In this embodiment, the prediction and determination module 502 includes: a prediction unit 5021 for predicting the change trend data of the order volume based on the seasonal and daily fluctuation information using a time series analysis algorithm; a second collection unit 5022 for collecting the operation data of each express delivery station, various cost data related to express delivery, and customer feedback data on express delivery services, where the operation data includes operation frequency, operation time, and operation volume, the various cost data includes transportation cost, labor cost, and site rent, and the feedback data includes satisfaction surveys and complaint records; and a second analysis unit 5023 for comprehensively analyzing the change trend data, operation data, various cost data, and feedback data to obtain frequency adjustment information.

[0113] In this embodiment, the optimization and definition module 503 includes: a classification unit 5031 for classifying the frequencies of multiple logistics links to obtain the pick-up frequencies at the origin network points, the frequencies of trunk buses, the frequencies of end distribution and delivery, and the delivery frequencies at the destination network points; a first optimization unit 5032 for locally optimizing the pick-up frequencies at the origin network points according to the frequency adjustment information and in combination with a linear programming algorithm to obtain first frequency optimization information; a second optimization unit 5033 for locally optimizing the frequencies of trunk buses according to the frequency adjustment information and in combination with a genetic algorithm to obtain second frequency optimization information; a third optimization unit 5034 for locally optimizing the frequencies of end distribution and delivery according to the frequency adjustment information and in combination with an LSTM algorithm to obtain third frequency optimization information; a fourth optimization unit 5035 for locally optimizing the delivery frequencies at the destination network points according to the frequency adjustment information and in combination with a path planning algorithm to obtain fourth frequency optimization information, where the first frequency optimization information, the second frequency optimization information, the third frequency optimization information, and the fourth frequency optimization information are all local frequency optimization information; and a first definition unit 5036 for defining the constraints between the first frequency optimization information, the second frequency optimization information, the third frequency optimization information, and the fourth frequency optimization information to obtain constraint condition information, where the constraint condition information includes cost constraints, time window constraints, and resource constraints.

[0114] In this embodiment, the generation and evaluation module 504 includes: a second definition unit 5041 for defining a comprehensive objective function composed of a delivery efficiency dimension, a cost-benefit dimension, and a customer satisfaction dimension; a generation unit 5042 for generating multiple initial frequency combination schemes with different combinations of local frequency optimization information based on the constraint condition information and the comprehensive objective function; an evaluation unit 5043 for evaluating the advantages and disadvantages of each initial frequency combination scheme to obtain frequency combination scheme evaluation information; and a sorting unit 5044 for sorting the multiple frequency combination scheme evaluation information to obtain frequency combination scheme ranking information on the advantages and disadvantages.

[0115] In this embodiment, the determination and sending module 505 includes: a determination unit 5051 for determining the optimal frequency combination scheme according to the frequency combination scheme ranking information on the advantages and disadvantages; a calling unit 5052 for calling a preset visualization scheme template according to the optimal frequency combination scheme; a filling unit 5053 for filling the optimal frequency combination scheme into the visualization scheme template to obtain a frequency combination scheme report; and a sending unit 5054 for sending the frequency combination scheme report to the management terminal so that the management terminal generates and displays a frequency combination scheme page based on the frequency combination scheme report.

[0116] In this embodiment, it further includes: a receiving module 506 for receiving the scheme implementation result information; an analysis module 507 for analyzing the scheme implementation effect of the scheme implementation result information to obtain scheme implementation effect information, where the scheme implementation effect information includes the improvement degree of delivery efficiency, the cost savings degree, and the customer satisfaction; an extraction and generation module 508 for extracting the data characteristics of the scheme implementation effect information and generating model training samples according to the data characteristics; and an adjustment module 509 for using the model training samples to adjust the parameters of the scheme evaluation model on the advantages and disadvantages.

[0117] Above Figure 5 And Figure 6 The best frequency optimization device for express delivery in the embodiment of the present invention has been described in detail from the perspective of modular functional entities. Next, the best frequency optimization device for express delivery in the embodiment of the present invention will be described in detail from the perspective of hardware processing.

[0118] Figure 7FIG. 0 is a schematic structural diagram of an express delivery optimal frequency optimization device provided by an embodiment of the present invention. The express delivery optimal frequency optimization device 600 may vary greatly due to different configurations or performances, and may include one or more processors (central processing units, CPUs) 610 (for example, one or more processors) and a memory 620, and one or more storage media 630 (for example, one or more mass storage devices) for storing application programs 633 or data 632. Among them, the memory 620 and the storage media 630 may be transient storage or persistent storage. The program stored in the storage media 630 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations on the express delivery optimal frequency optimization device 600. Further, the processor 610 may be configured to communicate with the storage media 630 and execute a series of instruction operations in the storage media 630 on the express delivery optimal frequency optimization device 600 to implement the steps of the express delivery optimal frequency optimization method provided by the above method embodiments.

[0119] The express delivery optimal frequency optimization device 600 may further include one or more power supplies 640, one or more wired or wireless network interfaces 650, one or more input / output interfaces 660, and / or one or more operating systems 631, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, and so on. Those skilled in the art can understand that Figure 7 the shown structure of the express delivery optimal frequency optimization device does not constitute a limitation on the express delivery optimal frequency optimization device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0120] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium, and when the instructions are run on a computer, the computer is made to execute the steps of the express delivery optimal frequency optimization method.

[0121] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, devices, or units can refer to the corresponding processes in the foregoing method embodiments, and will not be described herein again.

[0122] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0123] Finally, it should be noted that the above are only preferred examples of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for optimizing the optimal frequency of express delivery, characterized in that: include: Collect historical order data, and analyze seasonality and daily fluctuation information of orders based on the historical order data; Based on the seasonal and daily fluctuation information, a time series analysis algorithm is used to predict the change trend data of the order volume, and the frequency adjustment information is determined according to the change trend data; According to the frequency adjustment information, local optimal frequencies are optimized for multiple logistics links respectively to obtain multiple local frequency optimization information, and constraints between the frequencies of each link are defined to obtain constraint condition information; Based on the constraint information, a plurality of initial frequency combination schemes composed of different local frequency optimization information are generated, and the quality of each of the initial frequency combination schemes is evaluated using a preset scheme quality evaluation model to obtain quality ranking information of the frequency combination schemes; An optimal frequency combination scheme is determined according to the quality ranking information of the frequency combination schemes, and the optimal frequency combination scheme is sent to a management terminal.

2. The method for optimizing the optimal frequency of express delivery according to claim 1, characterized in that: The collecting of historical order data and analyzing seasonality and daily fluctuation information of orders according to the historical order data include: Collect historical order data; Performing data cleaning on the historical order data to obtain historical order cleaned data, and performing missing value filling on the historical order cleaned data to obtain historical order filled data; Based on a preset target standard format, the historical order filling data is formatted to obtain historical order standard data; The seasonality and daily fluctuation information of the orders are analyzed based on the historical order standard data.

3. The method for optimizing the optimal frequency of express delivery according to claim 1, characterized in that: The method of using a time series analysis algorithm to predict the change trend data of the order volume based on the seasonal and daily fluctuation information, and determining the frequency adjustment information according to the change trend data, includes: Based on the seasonal and daily fluctuation information, use time series analysis algorithms to predict the changing trend data of order volume; Collecting the operation data of each express delivery station, various cost data related to express delivery, and customer feedback data on express delivery services. The operation data includes operation frequency, operation time and operation volume. The various cost data includes transportation cost, labor cost and site rental. The feedback data includes satisfaction surveys and complaint records. Frequency adjustment information is obtained by performing a comprehensive analysis based on the change trend data, the operation data, the various cost data and the feedback data.

4. The method for optimizing the optimal frequency of express delivery according to claim 1, characterized in that: The method of performing local optimal frequency optimization on multiple logistics links according to the frequency adjustment information to obtain multiple local frequency optimization information, defining constraints between the frequencies of each link, and obtaining constraint condition information includes: Classify the frequencies of multiple logistics links to obtain the frequency of pickup at the originating outlet, the frequency of trunk bus, the frequency of terminal distribution and delivery, and the frequency of delivery at the destination outlet; According to the frequency adjustment information and in combination with a linear programming algorithm, the frequency of picking up items at the originating outlet is optimized to a local optimal frequency, thereby obtaining first frequency optimization information; According to the frequency adjustment information and in combination with a genetic algorithm, local optimal frequency optimization is performed on the main line bus frequency to obtain second frequency optimization information; According to the frequency adjustment information and in combination with the LSTM algorithm, the terminal distribution frequency is optimized at a local optimal frequency to obtain third frequency optimization information; performing local optimal frequency optimization on the destination outlet delivery frequency according to the frequency adjustment information and in combination with a path planning algorithm to obtain fourth frequency optimization information, wherein the first frequency optimization information, the second frequency optimization information, the third frequency optimization information and the fourth frequency optimization information are all local frequency optimization information; Define constraints between the first frequency optimization information, the second frequency optimization information, the third frequency optimization information, and the fourth frequency optimization information to obtain constraint condition information, where the constraint condition information includes cost constraints, time window constraints, and resource constraints.

5. The method for optimizing the optimal frequency of express delivery according to claim 1, characterized in that: The step of generating a plurality of initial frequency combination schemes composed of different local frequency optimization information based on the constraint condition information, evaluating the quality of each of the initial frequency combination schemes, and obtaining quality ranking information of the frequency combination schemes includes: Define a comprehensive objective function consisting of the dimensions of delivery efficiency, cost effectiveness, and customer satisfaction; Based on the constraint information and the comprehensive objective function, generating a plurality of initial frequency combination schemes composed of different local frequency optimization information; Evaluate the advantages and disadvantages of each of the initial frequency combination schemes to obtain frequency combination scheme evaluation information; The evaluation information of the plurality of frequency combination schemes is sorted to obtain the quality sorting information of the frequency combination schemes.

6. The method for optimizing the optimal frequency of express delivery according to claim 1, characterized in that: The determining the best frequency combination scheme according to the quality ranking information of the frequency combination schemes, and sending the best frequency combination scheme to the management terminal includes: Determine the best frequency combination scheme according to the quality ranking information of the frequency combination schemes; Calling a preset visualization scheme template according to the optimal frequency combination scheme; Filling the optimal frequency combination scheme into the visualization scheme template to obtain a frequency combination scheme report; The frequency combination scheme report is sent to a management terminal, so that the management terminal generates and displays a frequency combination scheme page based on the frequency combination scheme report.

7. The method for optimizing the optimal frequency of express delivery according to claim 1, characterized in that: After determining the best frequency combination scheme according to the frequency combination scheme superiority and inferiority ranking information and sending the best frequency combination scheme to the management terminal, the method further includes: Receive information on program implementation results; Analyze the implementation effect of the plan implementation result information to obtain the plan implementation effect information, wherein the plan implementation effect information includes the degree of improvement in delivery efficiency, the degree of cost savings, and customer satisfaction; Extracting data features of the scheme implementation effect information, and generating model training samples according to the data features; The model training samples are used to adjust the parameters of the scheme pros and cons evaluation model.

8. A device for optimizing the optimal frequency of express delivery, characterized in that: include: A collection and analysis module, used to collect historical order data and analyze seasonal and daily fluctuation information of orders based on the historical order data; A prediction and determination module, configured to predict the change trend data of the order volume based on the seasonal and daily fluctuation information using a time series analysis algorithm, and determine the frequency adjustment information according to the change trend data; An optimization definition module, used to perform local optimal frequency optimization on multiple logistics links according to the frequency adjustment information, obtain multiple local frequency optimization information, define constraints between the frequencies of each link, and obtain constraint condition information; A generation evaluation module is used to generate a plurality of initial frequency combination schemes composed of different local frequency optimization information based on the constraint condition information, evaluate the quality of each of the initial frequency combination schemes, and obtain quality ranking information of the frequency combination schemes; The determination and sending module is used to determine the best frequency combination scheme according to the quality ranking information of the frequency combination schemes, and send the best frequency combination scheme to the management terminal.

9. A device for optimizing the optimal frequency of express delivery, characterized in that: The express delivery optimal frequency optimization device comprises: a memory and at least one processor, wherein instructions are stored in the memory; At least one of the processors calls the instructions in the memory so that the express delivery optimal frequency optimization device executes each step of the express delivery optimal frequency optimization method as described in any one of claims 1-7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the various steps of the express delivery optimal frequency optimization method as described in any one of claims 1-7 are implemented.

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