A method, device, equipment and storage medium for selecting a site for an automobile after-sales service outlet

Abstract

The present invention discloses a method, device, equipment and storage medium for selecting a site for an automobile after-sales service outlet, and relates to the field of data processing. First, based on underlying parameters and target outlet constraint parameters, an ideal service outlet that satisfies the target outlet constraint conditions corresponding to the target outlet constraint parameters, and a real service outlet that satisfies the target outlet constraint conditions and the site selection constraint conditions are determined. The customer coverage of the ideal service outlet and the real service outlet is determined respectively, and when determining the customer coverage, the weights of automobile customers of different customer types are different, so that automobile customers of different customer types have different influences on the site selection of automobile after-sales service outlets. Finally, the service outlet with the largest customer coverage is used as the automobile after-sales service outlet, so as to achieve the maximum coverage of automobile after-sales service outlets to automobile customers, and the site selection of automobile after-sales service outlets can be completed more intelligently and accurately, and the site selection cost is reduced, and the site selection efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, device, equipment and storage medium for selecting a site for an automobile after-sales service network. Background Art

[0002] With the vigorous development of the automobile industry, the optimized layout of the automobile after-sales service network has become a core element to improve user satisfaction and brand competitiveness. At present, the site selection of automobile after-sales service outlets mostly relies on manual offline inspections, which has the problems of high site selection costs, long time consumption, low efficiency, and difficulty in accurately predicting market changes and competitive situations. Therefore, a more scientific and effective method is needed to complete the site selection of automobile after-sales outlets. Summary of the invention

[0003] The purpose of the present invention is to provide a method, device, equipment and storage medium for selecting a site for an automobile after-sales service outlet, which can more intelligently and accurately determine automobile after-sales service outlets, reduce site selection costs and improve site selection efficiency.

[0004] In order to solve the above technical problems, the present invention provides a method for selecting a site for an automobile after-sales service outlet, comprising:

[0005] Based on the obtained underlying parameters and target network point constraint parameters, determine an ideal service network point that satisfies the target network point constraint conditions corresponding to the target network point constraint parameters, and an actual service network point that satisfies the target network point constraint conditions and satisfies the location constraint conditions with the existing service network points;

[0006] Determine the customer coverage of the ideal service outlet according to the automobile customers covered by the ideal service outlet, the customer types corresponding to the automobile customers, and the corresponding relationship between the customer types and the customer weights;

[0007] Determining the customer coverage of the actual service outlet according to the automobile customers covered by the actual service outlet, the customer types corresponding to the automobile customers, and the corresponding relationship between the customer types and customer weights;

[0008] Wherein, the customer types include passenger cars and commercial vehicles, and the customer weight corresponding to the passenger car is different from the customer weight corresponding to the commercial vehicle;

[0009] The service outlet with the largest customer coverage among the ideal service outlet and the actual service outlet is used as the automobile after-sales service outlet.

[0010] Optionally, the target network point constraint parameters include a service radius of the service network point, a network point distance between the service network point and any other service network point, and a site selection planning area;

[0011] The target network point constraint condition includes that the actual network point distance between the service network point and any other service network point is greater than the network point distance specified by the target network point constraint parameter, and the service network point is located in the site selection planning area, and the actual service radius of the service network point is the service radius specified by the target network point constraint parameter.

[0012] Optionally, determining an ideal service network point that satisfies a target network point constraint condition corresponding to the target network point constraint parameter includes:

[0013] Clustering the automobile customers in the site planning area according to the genetic algorithm and the clustering algorithm to obtain cluster points;

[0014] The cluster points whose actual network point spacing between each cluster point and any other cluster point is greater than the network point spacing specified by the target network point constraint parameter and are located in the site selection planning area are taken as the ideal service network point, and the service radius of the ideal service network point is the service radius specified by the target network point constraint parameter.

[0015] Optionally, the determining of an actual service outlet that satisfies the target outlet constraint and satisfies the location constraint with the existing service outlets includes:

[0016] Clustering the automobile customers in the site planning area according to the genetic algorithm and the clustering algorithm to obtain cluster points;

[0017] The cluster points among the cluster points whose actual network point spacing with any other cluster points is greater than the network point spacing specified by the target network point constraint parameters, and which are located in the site selection planning area and whose distance with any existing service network point is greater than a preset threshold are taken as the actual service network points, and the service radius of the actual service network points is the service radius specified by the target network point constraint parameters.

[0018] Optionally, before obtaining the target grid point constraint parameters, the following steps are also included:

[0019] According to the business nature of the automobiles served by the automobile after-sales service outlets to be selected, determining the outlet spacing in the target outlet constraint parameters, wherein the outlet spacing is the distance between any two service outlets;

[0020] Among them, the business nature includes passenger cars and commercial vehicles, and the network point spacing corresponding to the passenger cars is smaller than the network point spacing corresponding to the commercial vehicles.

[0021] Optionally, after determining the actual service outlets that satisfy the target outlet constraint and satisfy the location constraint with the existing service outlets, the method further includes:

[0022] Determine the scoring results of each automobile repair shop within the preset range of the actual service outlet according to the preset scoring standard;

[0023] The auto repair shops with the highest scores will be selected as partners for auto after-sales services.

[0024] Optionally, after selecting the service outlet with the largest customer coverage among the ideal service outlet and the actual service outlet as the automobile after-sales service outlet, the method further includes:

[0025] The automobile customers, existing service outlets, the automobile after-sales service outlets, the service radius of the automobile after-sales service outlets, the outlet distance between the automobile after-sales service outlets and the existing service outlets, and the prohibited site selection area within the site selection planning area are displayed on the same map.

[0026] In order to solve the above technical problems, the present invention also provides a device for selecting a site for an automobile after-sales service network, the device comprising:

[0027] An ideal and actual service outlet determination module, for determining, based on the obtained underlying parameters and target outlet constraint parameters, an ideal service outlet that satisfies the target outlet constraint conditions corresponding to the target outlet constraint parameters, and an actual service outlet that satisfies the target outlet constraint conditions and satisfies the location constraint conditions with the existing service outlets;

[0028] An ideal customer coverage determination module, used to determine the customer coverage of the ideal service outlet according to the automobile customers covered by the ideal service outlet, the customer types corresponding to the automobile customers, and the corresponding relationship between the customer types and the customer weights;

[0029] A real customer coverage determination module, used to determine the customer coverage of the real service outlet according to the automobile customers covered by the real service outlet, the customer types corresponding to the automobile customers, and the corresponding relationship between the customer types and customer weights;

[0030] Wherein, the customer types include passenger cars and commercial vehicles, and the customer weight corresponding to the passenger car is different from the customer weight corresponding to the commercial vehicle;

[0031] The automobile after-sales service network point determination module is used to select the service network point with the largest customer coverage among the ideal service network point and the actual service network point as the automobile after-sales service network point.

[0032] In order to solve the above technical problems, the present invention also provides a device for selecting a site for an automobile after-sales service outlet, comprising:

[0033] Memory for storing computer programs;

[0034] A processor is used to implement the steps of any of the above-mentioned methods for selecting a location for an automobile after-sales service outlet when executing the computer program.

[0035] In order to solve the above technical problems, the present invention also provides a storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned methods for selecting a location for an automobile after-sales service outlet are implemented.

[0036] The beneficial effects of the present invention are to provide a method, device, equipment and storage medium for selecting the site of an automobile after-sales service outlet. First, based on the underlying parameters and the target outlet constraint parameters, an ideal service outlet that satisfies the target outlet constraint conditions corresponding to the target outlet constraint parameters, and an actual service outlet that satisfies the target outlet constraint conditions and the site selection constraint conditions are determined. The customer coverage of the ideal service outlet and the actual service outlet is determined respectively, and when determining the customer coverage, the weights of automobile customers of different customer types are different, so that automobile customers of different customer types have different influences on the site selection of automobile after-sales service outlets. Finally, the service outlet with the largest customer coverage is used as the automobile after-sales service outlet to achieve the maximum coverage of automobile customers by the automobile after-sales service outlet, which can complete the site selection of automobile after-sales service outlets more intelligently and accurately, reduce the site selection cost, and improve the site selection efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the prior art and the drawings required for use in the embodiments 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.

[0038] Figure 1 A first flow chart of the method for selecting a site for an automobile after-sales service outlet provided by the present invention;

[0039] Figure 2 A processing flow chart of the underlying parameters of the site selection model provided by the present invention;

[0040] Figure 3 A second flow chart of the method for selecting a site for an automobile after-sales service outlet provided by the present invention;

[0041] Figure 4 A schematic diagram of an automobile after-sales service outlet provided by the present invention;

[0042] Figure 5 A schematic diagram of the structure of the device for selecting a site for an automobile after-sales service outlet provided by the present invention;

[0043] Figure 6 This is a structural schematic diagram of the automobile after-sales service network site selection device provided by the present invention. DETAILED DESCRIPTION

[0044] The core of the present invention is to provide a method, device, equipment and storage medium for site selection of automobile after-sales service outlets, which can more intelligently and accurately determine automobile after-sales service outlets, reduce site selection costs and improve site selection efficiency.

[0045] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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 creative work are within the scope of protection of the present invention.

[0046] Please refer to Figure 1 , Figure 1 The first flow chart of the method for selecting a site for an automobile after-sales service network provided by the present invention comprises:

[0047] Step 101: Determine, based on the obtained underlying parameters and target network point constraint parameters, an ideal service network point that satisfies the target network point constraint conditions corresponding to the target network point constraint parameters, and an actual service network point that satisfies the target network point constraint conditions and satisfies the location constraint conditions with the existing service network points.

[0048] First, the present invention analyzes the location selection problem of automobile after-sales service outlets from two dimensions: reality and ideal. It can determine the ideal service outlets that need to be added under ideal conditions without being restricted by existing service outlets (that is, service outlets that have been built before the current automobile after-sales service outlet site selection); it can also determine the actual service outlets that need to be added based on the restrictions of existing service outlets, thereby optimizing the layout of automobile after-sales service outlets while saving construction costs. By comparing the differences between ideal service outlets and actual service outlets, more perspectives are provided for the subsequent selection of automobile after-sales service outlets.

[0049] It should be noted that the above-mentioned target network point constraint parameters are equivalent to the constraint conditions when selecting the site of the automobile after-sales service network point. Each time the site of the automobile after-sales service network point is selected, the target network point constraint parameters can be modified to obtain the automobile after-sales service network point that meets the site selection requirements. The above-mentioned underlying parameters are equivalent to other basic data required to determine the ideal service network point and the actual service network point, and can be updated according to a certain period. The above-mentioned underlying parameters, target network point constraint parameters, target network point constraint conditions and site selection constraint conditions will be introduced in detail in the subsequent embodiments, which will not be repeated here.

[0050] Specifically, when it is necessary to select a site for an automobile after-sales service outlet, the target outlet constraint parameters should be determined in advance so that the corresponding target outlet constraint conditions can be determined based on the obtained target outlet constraint parameters. The target outlet constraint conditions are used as constraint conditions when determining the ideal service outlets, and the ideal service outlets that are not restricted by existing service outlets and only meet the ideal expectations are screened out. On this basis, in order to save construction costs and avoid repeatedly establishing service outlets near existing service outlets, the present invention uses the target outlet constraint conditions and the site selection constraint conditions as constraint conditions when determining the actual service outlets, and screens out the actual service outlets that meet the ideal expectations and actual constraints.

[0051] Step 102: Determine the customer coverage of the ideal service outlet according to the automobile customers covered by the ideal service outlet, the customer types corresponding to the automobile customers, and the corresponding relationship between the customer types and the customer weights;

[0052] Step 103: Determine the customer coverage of the actual service outlets according to the automobile customers covered by the actual service outlets, the customer types corresponding to the automobile customers, and the corresponding relationship between the customer types and the customer weights;

[0053] Among them, customer types include passenger cars and commercial vehicles, and the customer weights corresponding to passenger cars are different from those corresponding to commercial vehicles.

[0054] The present invention has a deep understanding of all aspects of the operation of the automotive after-sales business, including business processes, key indicators, user behavior, and market demand, and clarifies that the location of automotive after-sales service outlets should be centered on automotive customers, and the maximum coverage of automotive customer groups can be achieved through accurate site selection. The present invention determines the coverage of service outlets to automotive customer groups by calculating the customer coverage of service outlets.

[0055] On this basis, the present invention introduces a customer weight allocation mechanism when evaluating the coverage of service outlets for automobile customer groups, and different customer types of automobile customers have different corresponding customer weights, so that different customer types of automobile customers have different influences on the site selection of automobile after-sales service outlets, thereby ensuring that the ultimately determined automobile after-sales service outlets can not only meet current business needs, but also flexibly adapt to market changes and achieve optimal allocation of resources.

[0056] Specifically, the present invention has pre-counted all automobile customers included in the site selection planning area and the customer types corresponding to each automobile customer, and recorded them in the underlying parameters. Therefore, automobile customers covered by the ideal service outlets (that is, automobile customers located within the service radius of the ideal service outlets, and the service radius can be specified by the target outlet constraint parameters), automobile customers covered by the actual service outlets (that is, automobile customers located within the service radius of the ideal service outlets, and the service radius can be specified by the target outlet constraint parameters), and the customer types corresponding to each automobile customer can all be determined by the underlying parameters. The present invention also pre-sets the corresponding relationship between customer types and customer weights in the underlying parameters. The above-mentioned customer types include passenger cars and commercial vehicles, and the customer weights corresponding to passenger cars are different from the customer weights corresponding to commercial vehicles.

[0057] Therefore, when determining the customer coverage of an ideal service outlet, the customer coverage of the ideal service outlet is determined based on the customer types corresponding to the automobile customers covered by the ideal service outlet, as well as the corresponding relationship between the customer type and the customer weight. Similarly, when determining the customer coverage of an actual service outlet, the customer coverage of an actual service outlet is determined based on the customer types of the automobile customers covered by the actual service outlet, as well as the corresponding relationship between the customer type and the customer weight.

[0058] The present invention does not specifically limit the specific implementation method of calculating customer coverage. Taking the determination of the customer coverage of an ideal service outlet as an example, the customer types of all automobile customers covered by the ideal service outlet can be determined first, and then the customer weights of each automobile customer can be determined according to the corresponding relationship between the customer type and the customer weight, and finally the sum of the customer weights of all automobile customers covered by the ideal service outlet is used as the customer coverage of the ideal service outlet.

[0059] Step 104: The service outlet with the largest customer coverage among the ideal service outlet and the actual service outlet is selected as the automobile after-sales service outlet.

[0060] After determining the customer coverage of the ideal service outlets and the customer coverage of the actual service outlets, the service outlets with the largest customer coverage will be used as newly added automobile after-sales service outlets to maximize the coverage of the automobile customer group and optimize resource allocation.

[0061] It should also be noted that the executor of the automobile after-sales service outlet site selection method provided by the present invention can be a site selection model pre-trained in the processor. When the site selection of the automobile after-sales service outlet needs to be completed, the underlying parameters and target outlet constraint parameters are input into the site selection model, and the site selection model automatically executes the above steps.

[0062] In summary, the automobile after-sales service outlet site selection method provided by the present invention first determines the ideal service outlet that meets the target outlet constraint conditions corresponding to the target outlet constraint parameters based on the underlying parameters and the target outlet constraint parameters, as well as the actual service outlet that meets the target outlet constraint conditions and the site selection constraint conditions. The customer coverage of the ideal service outlet and the actual service outlet is determined respectively, and the weights of automobile customers of different customer types are different when determining the customer coverage, so that automobile customers of different customer types have different influences on the site selection of automobile after-sales service outlets. Finally, the service outlet with the largest customer coverage is used as the automobile after-sales service outlet to achieve the maximum coverage of automobile customers by the automobile after-sales service outlet, which can complete the site selection of automobile after-sales service outlets more intelligently and accurately, reduce the site selection cost, and improve the site selection efficiency.

[0063] Based on the above embodiments, the target grid point constraint parameters and their corresponding target grid point constraint conditions are described in detail below.

[0064] As an optional embodiment, the target network point constraint parameters include the service radius of the service network point, the network point distance between the service network point and any other service network point, and the site planning area;

[0065] The target network point constraint conditions include that the actual network point distance between the service network point and any other service network point is greater than the network point distance specified in the target network point constraint parameters, and the service network point is located within the site selection planning area, and the actual service radius of the service network point is the service radius specified by the target network point constraint parameters.

[0066] In this embodiment, by deeply analyzing various aspects of the operation of the automobile after-sales service business, including business processes, key indicators, user behavior, and market demand, the service radius of the service outlets, the distance between outlets, and the site planning area are used as restrictive conditions for determining ideal service outlets and actual service outlets.

[0067] The service radius of a service point refers to the geographical range within which the service point can cover and effectively provide automobile after-sales service. The value of the service radius in the above-mentioned target point constraint parameter can be set according to actual conditions, and this embodiment does not specifically limit this. For example, the service radius in the target point constraint parameter is set hierarchically according to the city where the automobile after-sales service point is located. Accordingly, the target point constraint condition includes that the actual service radius of the service point is the service radius specified in the target point constraint parameter, thereby ensuring that the final automobile after-sales service point can cover as many automobile customers as possible and provide after-sales service to more automobile customer groups.

[0068] The network spacing of a service network point refers to the straight-line distance between the service network point and any other service network point. The value of the network spacing in the above-mentioned target network point constraint parameter can be set according to the actual situation, and this embodiment does not specifically limit this. For example, the network spacing in the target network point constraint parameter is set hierarchically according to the city where the automobile after-sales service network point is located. Correspondingly, the target network point constraint condition includes that the actual network spacing between the service network point and any other service network point other than itself is greater than the network spacing in the target network point constraint parameter, which ensures that the automobile after-sales service network point provides after-sales services to more automobile customer groups while avoiding duplicate construction and saving construction costs.

[0069] The location planning area of ​​the service outlet refers to the area where the service outlet is expected to be located. When determining the location planning area in the target outlet constraint parameters, the prohibited location area should also be determined according to the city policy, and the location planning area should avoid including prohibited location areas to ensure that the final automobile after-sales service outlet can be built and used normally. Correspondingly, the target outlet constraint conditions include that the service outlet is located in the location planning area to ensure that the final automobile after-sales service outlet can provide automobile after-sales service normally.

[0070] Please refer to Figure 4 , Figure 4 A schematic diagram of an automobile after-sales service network provided by the present invention, Figure 4 Where L1 is the actual service radius of the automobile after-sales service outlet, which is also the service radius specified in the target outlet constraint parameters. L2 is the actual outlet distance between the automobile after-sales service outlet and the existing service outlets. L2 is greater than the outlet distance in the target outlet constraint parameters, and the automobile after-sales service outlet is located outside the prohibited site selection area.

[0071] Based on the above target network point constraint parameters and target network point constraint conditions, the process of determining the ideal service network point and the actual service network point is described below.

[0072] As an optional embodiment, determining an ideal service network point that satisfies the target network point constraint condition corresponding to the target network point constraint parameter includes:

[0073] According to the genetic algorithm and clustering algorithm, the automobile customers in the site selection planning area are clustered to obtain the cluster points;

[0074] The cluster points whose actual network point distance between each cluster point and any other cluster point is greater than the network point distance specified by the target network point constraint parameter and are located in the site selection planning area are regarded as ideal service network points, and the service radius of the ideal service network point is the service radius specified by the target network point constraint parameter.

[0075] As an optional embodiment, determining an actual service network point that satisfies the target network point constraint condition and satisfies the location constraint condition with the existing service network point includes:

[0076] According to the genetic algorithm and clustering algorithm, the automobile customers in the site selection planning area are clustered to obtain the cluster points;

[0077] The cluster points whose actual network point distance with any other cluster point is greater than the network point distance specified by the target network point constraint parameter, and are located in the site selection planning area, and whose distance with any existing service network point is greater than the preset threshold are taken as actual service network points. The service radius of the actual service network point is the service radius specified by the target network point constraint parameter.

[0078] In the above embodiment, when determining the ideal service outlets and the actual service outlets, the automobile customers in the site planning area are first clustered according to the genetic algorithm and the clustering algorithm (including but not limited to the K-means clustering algorithm) to obtain the clustering points. The genetic algorithm is used to globally search for the optimal solution. By simulating natural selection and genetic mechanisms, the site selection of automobile after-sales service outlets is continuously iterated and optimized, which can greatly reduce the amount of calculation. The clustering algorithm clusters automobile customers, that is, divides them into different groups, so as to better meet the needs of automobile customers and achieve maximum coverage of automobile customer groups.

[0079] On the basis of the above content, the cluster points in each cluster point that meet the target network point constraint conditions corresponding to the target network point constraint parameters are taken as ideal service network points. Please refer to the previous text for the target network point constraint conditions, which will not be described in detail in this embodiment. The cluster points in each cluster point that can meet both the target network point constraint conditions corresponding to the target network point constraint parameters and the site selection constraint conditions are taken as actual service network points. The site selection constraint condition is specifically that the distance between the cluster point and any existing service network point is greater than a preset threshold value, so as to avoid the problem of repeated site selection with existing service network points and avoid waste of construction costs. The preset threshold value can be set according to the actual situation, and this embodiment does not specifically limit this.

[0080] In summary, the above embodiments provide specific implementation methods for determining ideal service outlets and actual service outlets, integrating genetic algorithms and clustering algorithms to combine the global search and adaptability of genetic algorithms with the efficient clustering capabilities of clustering algorithms, and optimizing the data processing and analysis process in the site selection process of automobile after-sales service outlets. It provides better data processing and optimization capabilities for complex site selection problems, helps to accurately determine the automobile after-sales service outlets that need to be added, and promotes the site selection of automobile after-sales service outlets to move towards intelligence and refinement.

[0081] The following is a detailed description of the underlying parameters required to determine the automobile after-sales service outlets.

[0082] The underlying parameters include the automobile customers included in the site selection planning area, the customer type corresponding to each automobile customer, the correspondence between the customer type and the customer weight, the number of cars in the site selection planning area, the existing service outlets in the site selection planning area, the prohibited site selection areas in the site selection planning area, and the locations of automobile repair shops in the site selection planning area.

[0083] Among them, automobile customers in the site planning area refer to the service objects of automobile after-sales service outlets, including commercial vehicles, passenger vehicles, B-end customers and C-end customers, etc. The customer type corresponding to each automobile customer recorded in the underlying parameters, and the corresponding relationship between the customer type and the customer weight can assist in determining the coverage of the service outlets to the automobile customer group, which has been described in the previous article and will not be repeated here.

[0084] The number of cars in the site planning area refers to the number of cars owned, which can assist in analyzing the local market development potential. Existing service outlets are already built service outlets, so as to determine whether there are problems such as duplicate construction when determining new automobile after-sales service outlets in the future. Prohibited site selection areas can be determined based on local policy legal and regulatory restrictions, urban planning requirements, and environmental protection standard data. Auto repair shops have ready-made sites and maintenance personnel resources. By understanding the location of auto repair shops, the task of attracting investment for automobile after-sales service outlets can be better completed.

[0085] For the above-mentioned underlying parameters, it is necessary to determine the source and acquisition method of the parameters, evaluate the reliability and accuracy of the parameters, and formulate a parameter collection plan (including the time, frequency and collection channels of parameter collection, etc.); the collected parameters also need to be preprocessed (including but not limited to data cleaning, removal of noise and abnormal parameters, unification of data format, etc.) to ensure the quality and accuracy of the underlying parameters obtained.

[0086] Specifically, in the acquisition stage of the underlying parameters, such as the car customers, car ownership, prohibited site selection areas, and car repair shop locations in the underlying parameters, they can be obtained in real time or regularly through technical means such as API (Application Programming Interface), data sharing platform, and web crawlers. The existing service outlets in the underlying parameters can be obtained by file import. At the same time, a data quality monitoring mechanism is established to regularly evaluate the accuracy and completeness of the underlying parameters obtained, and to process and correct them in a timely manner to ensure that the quality of the underlying parameters meets the analysis requirements.

[0087] In the preprocessing stage of the underlying parameters, for example, the customer addresses of potential B-end automotive customers obtained from corporate official websites, industry data, and map points of interest may contain errors, anomalies, or missing information. They need to be cleaned, their longitude and latitude supplemented, and the city names standardized. The underlying parameters from different sources need to be combined into a unified data set to solve problems such as data redundancy and inconsistency, and to identify the same entity in different data sources through matching algorithms.

[0088] Please refer to Figure 2 , Figure 2 The processing flow chart of the underlying parameters of the site selection model provided by the present invention. The underlying parameters are divided into internal data and external data according to different data sources. Internal data includes existing service outlets, automobile customers and outlet work orders; external data includes potential customers, outlet spacing, auto repair shops, service radius and social policies. Internal data is obtained by file import, and external data is obtained through technical means such as API, data sharing platform, web crawler, etc. The above data is evaluated, cleaned, converted and integrated, and finally archived in the form of Excel spreadsheets for input into the site selection model.

[0089] In addition, the above-mentioned underlying parameters can be updated according to a preset period, for example, once a month, to ensure the reliability and accuracy of the automobile after-sales service outlets determined by the site selection model based on the underlying parameters.

[0090] As an optional embodiment, before obtaining the target grid point constraint parameters, the method further includes:

[0091] According to the business nature of the automobiles served by the automobile after-sales service outlets to be selected, the outlet spacing in the target outlet constraint parameters is determined, and the outlet spacing is the distance between any two service outlets;

[0092] Among them, the nature of the business includes passenger cars and commercial vehicles, and the network spacing corresponding to passenger cars is smaller than that corresponding to commercial vehicles.

[0093] In this embodiment, differentiated automobile after-sales service outlet location planning is implemented for automobiles of different business natures. According to the different business natures of the automobiles served by the automobile after-sales service outlets to be selected, the corresponding target outlet constraint parameters are respectively specified so that the location selection model can adaptively determine the corresponding ideal service outlets and actual service outlets.

[0094] In this embodiment, the business nature of the car mainly affects the value of the network point spacing in the target network point constraint parameter. Specifically, this embodiment divides the business nature of the car into passenger cars (mainly used to transport passengers and their belongings) and commercial vehicles (to be used to transport goods or personnel), and the network point spacing corresponding to passenger cars is smaller than the network point spacing corresponding to commercial vehicles. The above strategy not only closely connects with the current core business group, namely B-end corporate customers, but also proactively considers the needs of C-end individual car owners in the future market to ensure the comprehensiveness and foresight of the service network.

[0095] As an optional embodiment, after determining the actual service outlets that meet the target outlet constraint and meet the location constraint with the existing service outlets, the method further includes:

[0096] According to the preset scoring standards, determine the scoring results of each automobile repair shop within the preset range of the actual service outlets;

[0097] The auto repair shops with the highest scores will be selected as partners for auto after-sales services.

[0098] Please refer to Figure 3 , Figure 3 The second flow chart of the method for selecting the site of the automobile after-sales service outlet provided by the present invention. In this embodiment, after selecting the actual service outlet, the automobile repair shops around the actual service outlet are comprehensively evaluated, and the above-mentioned automobile repair shops are scored based on the preset scoring criteria, and the automobile repair shops with the highest scoring results are selected as the above-mentioned automobile after-sales service cooperation partners. The preset scoring criteria include the site selection distance, years of operation, maintenance qualifications, taxpayer type, and financial capacity, etc., which are not particularly limited in this application.

[0099] As an optional embodiment, after the service outlet with the largest customer coverage among the ideal service outlet and the actual service outlet is used as the automobile after-sales service outlet, the method further includes:

[0100] The automobile customers, existing service outlets, automobile after-sales service outlets, the service radius of automobile after-sales service outlets, the distance between automobile after-sales service outlets and existing service outlets, and prohibited site selection areas within the site selection planning area are displayed on the same map.

[0101] In this embodiment, automobile customers, existing service outlets, automobile after-sales service outlets, service radius of automobile after-sales service outlets, outlet distances between automobile after-sales service outlets and existing service outlets, and prohibited site selection areas within the site selection planning area are displayed on the same map in a visual manner, so that users can intuitively verify the rationality and accuracy of the site selection of automobile after-sales service outlets and determine whether the automobile after-sales service outlets meet the constraints of the target outlet constraint parameters.

[0102] In addition, during the stage of developing and debugging the site selection model, the method provided in this embodiment can also be used to verify whether there are any problems or deviations in the automobile after-sales service outlets determined by the site selection model. If there are problems such as the location of the automobile after-sales service outlets being too concentrated or the service radius coverage being insufficient, the algorithm used in the site selection model can be adjusted and optimized as necessary, such as adjusting the parameters of the genetic algorithm, optimizing the automobile customer clustering strategy of the K-means clustering algorithm, etc., until the automobile after-sales service outlets determined by the site selection model meet the requirements.

[0103] Please refer to Figure 5 , Figure 5 The present invention provides a schematic diagram of the location selection device for automobile after-sales service outlets, which includes:

[0104] The ideal and actual service outlet determination module 501 is used to determine, based on the obtained underlying parameters and target outlet constraint parameters, an ideal service outlet that satisfies the target outlet constraint conditions corresponding to the target outlet constraint parameters, and an actual service outlet that satisfies the target outlet constraint conditions and satisfies the location constraint conditions with the existing service outlets;

[0105] An ideal customer coverage determination module 502 is used to determine the customer coverage of an ideal service outlet according to the automobile customers covered by the ideal service outlet, the customer types corresponding to the automobile customers, and the correspondence between the customer types and the customer weights;

[0106] The actual customer coverage determination module 503 is used to determine the customer coverage of the actual service outlets according to the automobile customers covered by the actual service outlets, the customer types corresponding to the automobile customers, and the corresponding relationship between the customer types and the customer weights; wherein the customer types include passenger cars and commercial vehicles, and the customer weights corresponding to passenger cars are different from those corresponding to commercial vehicles;

[0107] The automobile after-sales service network point determination module 504 is used to select the service network point with the largest customer coverage among the ideal service network point and the actual service network point as the automobile after-sales service network point.

[0108] For a detailed introduction to the automobile after-sales service network site selection device provided by the present invention, please refer to the above-mentioned embodiment of the automobile after-sales service network site selection method, and this application will not elaborate on it here.

[0109] Please refer to Figure 6 , 6 is a schematic diagram of the structure of the automobile after-sales service network site selection device provided by the present invention, and the automobile after-sales service network site selection device comprises:

[0110] Memory 601, used for storing computer programs;

[0111] The processor 602 is used to implement the steps of any of the above-mentioned methods for selecting a location for an automobile after-sales service outlet when executing a computer program.

[0112] For a detailed introduction to the automobile after-sales service network site selection device provided by the present invention, please refer to the above-mentioned embodiment of the automobile after-sales service network site selection method, and the present invention will not be elaborated here.

[0113] The present invention also provides a storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any of the above-mentioned methods for selecting a location for an automobile after-sales service outlet are implemented.

[0114] For a detailed introduction to the storage medium provided by the present invention, please refer to the above-mentioned embodiment of the method for selecting a location for an automobile after-sales service outlet, and the present invention will not be elaborated herein.

[0115] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. It should also be noted that in this specification, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, article or device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the presence of other identical elements in the process, article or device including the elements.

[0116] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for selecting a site for an automobile after-sales service outlet, characterized in that: include: Based on the obtained underlying parameters and target network point constraint parameters, determine an ideal service network point that satisfies the target network point constraint conditions corresponding to the target network point constraint parameters, and an actual service network point that satisfies the target network point constraint conditions and satisfies the location constraint conditions with the existing service network points; Determine the customer coverage of the ideal service outlet according to the automobile customers covered by the ideal service outlet, the customer types corresponding to the automobile customers, and the corresponding relationship between the customer types and the customer weights; Determining the customer coverage of the actual service outlet according to the automobile customers covered by the actual service outlet, the customer types corresponding to the automobile customers, and the corresponding relationship between the customer types and customer weights; Wherein, the customer types include passenger cars and commercial vehicles, and the customer weight corresponding to the passenger car is different from the customer weight corresponding to the commercial vehicle; The service outlet with the largest customer coverage among the ideal service outlet and the actual service outlet is used as the automobile after-sales service outlet.

2. The method for selecting a site for an automobile after-sales service network as claimed in claim 1, characterized in that: The target network point constraint parameters include the service radius of the service network point, the network point distance between the service network point and any other service network point, and the site planning area; The target network point constraint condition includes that the actual network point distance between the service network point and any other service network point is greater than the network point distance specified by the target network point constraint parameter, and the service network point is located in the site selection planning area, and the actual service radius of the service network point is the service radius specified by the target network point constraint parameter.

3. The method for selecting a site for an automobile after-sales service network as claimed in claim 2, characterized in that: The step of determining an ideal service network point that satisfies the target network point constraint condition corresponding to the target network point constraint parameter includes: Clustering the automobile customers in the site planning area according to the genetic algorithm and the clustering algorithm to obtain cluster points; The cluster points whose actual network point spacing between each cluster point and any other cluster point is greater than the network point spacing specified by the target network point constraint parameter and are located in the site selection planning area are taken as the ideal service network point, and the service radius of the ideal service network point is the service radius specified by the target network point constraint parameter.

4. The method for selecting a site for an automobile after-sales service network as claimed in claim 2, characterized in that: The determining of an actual service network point that satisfies the target network point constraint condition and satisfies the location constraint condition with the existing service network points includes: Clustering the automobile customers in the site planning area according to the genetic algorithm and the clustering algorithm to obtain cluster points; The cluster points among the cluster points whose actual network point spacing with any other cluster points is greater than the network point spacing specified by the target network point constraint parameters, and which are located in the site selection planning area and whose distance with any existing service network point is greater than a preset threshold are taken as the actual service network points, and the service radius of the actual service network points is the service radius specified by the target network point constraint parameters.

5. The method for selecting a site for an automobile after-sales service network as claimed in claim 1, characterized in that: Before obtaining the target grid point constraint parameters, it also includes: According to the business nature of the automobiles served by the automobile after-sales service outlets to be selected, determining the outlet spacing in the target outlet constraint parameters, wherein the outlet spacing is the distance between any two service outlets; Among them, the business nature includes passenger cars and commercial vehicles, and the network point spacing corresponding to the passenger cars is smaller than the network point spacing corresponding to the commercial vehicles.

6. The method for selecting a site for an automobile after-sales service network as claimed in claim 1, characterized in that: After determining the actual service outlets that meet the target outlet constraint conditions and that meet the location constraint conditions with the existing service outlets, the method further includes: Determine the scoring results of each automobile repair shop within the preset range of the actual service outlet according to the preset scoring standard; The auto repair shops with the highest scores will be selected as partners for auto after-sales services.

7. The method for selecting a site for an automobile after-sales service network as claimed in claim 1, characterized in that: After selecting the service outlet with the largest customer coverage among the ideal service outlet and the actual service outlet as the automobile after-sales service outlet, the method further includes: The automobile customers, existing service outlets, the automobile after-sales service outlets, the service radius of the automobile after-sales service outlets, the outlet distance between the automobile after-sales service outlets and the existing service outlets, and the prohibited site selection area within the site selection planning area are displayed on the same map.

8. A device for selecting a site for an automobile after-sales service outlet, characterized in that: include: An ideal and actual service outlet determination module, for determining, based on the obtained underlying parameters and target outlet constraint parameters, an ideal service outlet that satisfies the target outlet constraint conditions corresponding to the target outlet constraint parameters, and an actual service outlet that satisfies the target outlet constraint conditions and satisfies the location constraint conditions with the existing service outlets; An ideal customer coverage determination module, used to determine the customer coverage of the ideal service outlet according to the automobile customers covered by the ideal service outlet, the customer types corresponding to the automobile customers, and the corresponding relationship between the customer types and the customer weights; A real customer coverage determination module, used to determine the customer coverage of the real service outlet according to the automobile customers covered by the real service outlet, the customer types corresponding to the automobile customers, and the corresponding relationship between the customer types and customer weights; Wherein, the customer types include passenger cars and commercial vehicles, and the customer weight corresponding to the passenger car is different from the customer weight corresponding to the commercial vehicle; The automobile after-sales service network point determination module is used to select the service network point with the largest customer coverage among the ideal service network point and the actual service network point as the automobile after-sales service network point.

9. A device for selecting a site for an automobile after-sales service outlet, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the method for selecting a location for an automobile after-sales service outlet as described in any one of claims 1 to 7 when executing the computer program.

10. A storage medium, characterized in that: The storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for selecting a location for an automobile after-sales service outlet as claimed in any one of claims 1 to 7.

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