Supplier recommendation method and apparatus, computer program product, electronic device

Abstract

The present disclosure relates to the technical field of data processing, and provides a supplier recommendation method and device, a computer program product and an electronic device. The method is applied to an offshore photovoltaic construction project. Different processes of the offshore photovoltaic construction project have different demand information for a same target raw material. The method comprises the following steps: determining a candidate supplier of the target raw material from candidate manufacturers based on distance; classifying the candidate supplier based on each evaluation index of the target raw material to obtain a classified result of the candidate supplier corresponding to each evaluation index; obtaining demand information of different processes of the offshore photovoltaic construction project for the target raw material, performing at least one level of matching between the demand information and the classified result, and determining a recommended supplier of the target raw material for each process according to a matching result; and respectively sending the recommended supplier of the recommended target raw material corresponding to each process unit of different processes. The present scheme can improve the accuracy of supplier recommendation.

Description

[0001] This application is a divisional application of the invention patent application with the application date of December 17, 2024, the application number of 202411861681.0, and the name of "Supplier recommendation method and device, computer program product, and electronic equipment". TECHNICAL FIELD

[0002] The present disclosure relates to the technical field of data processing, in particular to a supplier recommendation method applied to an offshore photovoltaic construction project, a supplier recommendation device applied to an offshore photovoltaic construction project, a computer program product, and an electronic device. BACKGROUND

[0003] Offshore photovoltaic refers to the construction and operation of solar photovoltaic power generation in marine environment, that is, installing photovoltaic panels in marine space to convert solar energy into electric energy.

[0004] The offshore photovoltaic construction project has many procedures and involves many suppliers. The related art lacks a method for intelligently managing and allocating suppliers in the offshore photovoltaic construction project, and cannot accurately recommend suppliers.

[0005] It should be noted that the information disclosed in the above background section is only used to strengthen the understanding of the background of the present disclosure, and therefore can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0006] The purpose of the present disclosure is to provide a supplier recommendation method and device applied to an offshore photovoltaic construction project, a computer program product, and an electronic device, so as to at least improve the accuracy of the supplier recommendation of the offshore photovoltaic project to some extent, and further improve the construction efficiency of the offshore photovoltaic project.

[0007] Other characteristics and advantages of the present disclosure will become apparent from the following detailed description, or will be learned by practice of the present disclosure.

[0008] According to a first aspect of the present disclosure, a supplier recommendation method applied to an offshore photovoltaic construction project is provided, different processes of the offshore photovoltaic construction project have different demand information for a same target raw material, and the method comprises the following steps: obtaining first position information corresponding to a production address of a candidate manufacturer of the target raw material and second position information corresponding to a construction address of the offshore photovoltaic construction project; determining a distance between the production address and the construction address according to the first position information and the second position information, and determining a candidate supplier of the target raw material from the candidate manufacturers based on the distance; classifying the candidate suppliers based on each evaluation index of the target raw material to obtain a classified result of the candidate suppliers corresponding to each evaluation index; obtaining demand information of different processes of the offshore photovoltaic construction project for the target raw material, performing at least one level of matching between the demand information and the classified result, and determining a recommended supplier of the target raw material for each process according to a matching result, wherein each process corresponds to a process unit, and process units of each process are different; and respectively recommending the recommended supplier of the target raw material to a process unit corresponding to each process.

[0009] According to a second aspect of the present disclosure, a supplier recommendation device applied to an offshore photovoltaic construction project is provided, different processes of the offshore photovoltaic construction project have different demand information for a same target raw material, and the device comprises the following modules: a position information obtaining module configured to obtain first position information corresponding to a production address of a candidate manufacturer of the target raw material and second position information corresponding to a construction address of the offshore photovoltaic construction project; a candidate supplier determining module configured to determine a distance between the production address and the construction address according to the first position information and the second position information, and determine a candidate supplier of the target raw material from the candidate manufacturers based on the distance; a classification module configured to classify the candidate suppliers based on each evaluation index of the target raw material to obtain a classified result of the candidate suppliers corresponding to each evaluation index; a matching module configured to obtain demand information of different processes of the offshore photovoltaic construction project for the target raw material, perform at least one level of matching between the demand information and the classified result, and determine a recommended supplier of the target raw material for each process according to a matching result, wherein each process corresponds to a process unit, and process units of each process are different; and a recommendation module configured to respectively recommend the recommended supplier of the target raw material to a process unit corresponding to each process.

[0010] According to a third aspect of the present disclosure, a computer program product containing instructions, when executed on a computer, causes the computer to perform the steps of the supplier recommendation method applied to the offshore photovoltaic construction project according to the first aspect.

[0011] According to a fourth aspect of the embodiments of the present disclosure, an electronic device is provided, comprising: a processor; and a storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the supplier recommendation method applied to the offshore photovoltaic construction project as described in the first aspect of the above embodiments.

[0012] From the above technical solutions, the supplier recommendation method applied to the offshore photovoltaic construction project, the supplier recommendation device applied to the offshore photovoltaic construction project, and the computer program product and the electronic device for implementing the supplier recommendation method applied to the offshore photovoltaic construction project in the exemplary embodiments of the present disclosure have at least the following advantages and positive effects:

[0013] In the technical solutions provided by some embodiments of the present disclosure, for any target raw material of the offshore photovoltaic project, first, candidate suppliers are determined from candidate manufacturers according to the distance between the production address of the candidate manufacturer and the construction address of the construction project, then the candidate suppliers are classified according to the evaluation indexes of the target raw material, and the classified results corresponding to different evaluation indexes are obtained, and then the recommended suppliers are determined for different processes according to the matching of the demand information of the target raw material and the classified results of different processes, and the recommended suppliers are determined for the process units corresponding to different processes. Compared with related technologies, the present disclosure can accurately recommend suppliers that meet the requirements of the process units for different processes of the offshore photovoltaic project for the same target raw material, thereby assisting in improving the construction efficiency of the offshore photovoltaic project, avoiding the situation that the construction progress of the offshore photovoltaic project is affected due to the wrong selection of suppliers, and reducing the potential risks of the offshore photovoltaic construction project.

[0014] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0015] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the present disclosure and, together with the specification, serve to explain the principles of the present disclosure. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0016] Figure 1 A schematic diagram of an exemplary system architecture to which the embodiments of the present disclosure can be applied is shown.

[0017] Figure 2A flowchart showing a method for recommending a supplier for an offshore photovoltaic construction project in an example embodiment of the present disclosure.

[0018] Figure 3 A flowchart showing a method for determining the capacity of a candidate supplier in an example embodiment of the present disclosure.

[0019] Figure 4 A flowchart showing a method for determining the recommended supplier for a target raw material for each process according to the matching result in an example embodiment of the present disclosure.

[0020] Figure 5 A flowchart showing another method for determining the recommended supplier for a target raw material for each process according to the matching result in an example embodiment of the present disclosure.

[0021] Figure 6 A flowchart showing still another method for determining the recommended supplier for a target raw material for each process according to the matching result in an example embodiment of the present disclosure.

[0022] Figure 7 A block diagram showing a composition of a supplier recommendation device for an offshore photovoltaic construction project in an example embodiment of the present disclosure.

[0023] Figure 8 A block diagram showing the structure of an electronic device in an example embodiment of the present disclosure. DETAILED DESCRIPTION

[0024] Example implementations will now be described more fully with reference to the accompanying drawings. Example implementations may, however, be implemented in many different forms and should not be construed as limited to the examples set forth herein; rather, these implementations are provided so that this disclosure will be thorough and complete, and will fully convey the scope of example implementations to those skilled in the art. The described features, structures, or characteristics can be combined in one or more implementations. In the following description, numerous specific details are provided to give a thorough understanding of example implementations. One skilled in relevant art will recognize, however, that the implementations can be practiced without one or more of the specific details, or with other methods, components, materials, and so forth. In other instances, well-known structures have not been described in detail to avoid obscuring the aspects of the disclosure. Accordingly, the

[0025] The terms "one", "a", "an", and "the" are used to mean one or more elements, components, etc.; the terms "includes" and "including" mean, and are used to mean, an open-ended transition that covers both the recited elements / situations and additional, unrecited elements / situations; the term "first" and "second" are used to denote a first and a second of an arbitrary number of elements, components, etc., and are not used to denote a limitation on the number of elements, components, etc.

[0026] In addition, the accompanying drawings are merely schematic and are not necessarily drawn to scale. Identical reference numerals denote the same or similar parts throughout the several views of the drawings and a repeated description is omitted. Some of the block diagrams shown in the drawings are functional entities that do not necessarily have to correspond to physically or logically independent entities. These functional entities can be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0027] In recent years, as the inland land resources are increasingly scarce, the photovoltaic projects with a wide occupation have gradually expanded the application scenarios to vast oceans. Offshore photovoltaic can build and operate solar photovoltaic power generation in the marine environment, so the offshore photovoltaic has a broad prospect.

[0028] However, the offshore photovoltaic construction project has many procedures and involves many suppliers, and the related technology lacks a method for intelligently managing and recommending the suppliers of offshore photovoltaic, resulting in low construction efficiency of offshore photovoltaic projects and affecting the construction progress.

[0029] To solve the above problems, the present disclosure provides a supplier recommendation method and device applied to an offshore photovoltaic construction project, which can be applied to Figure 1 the system architecture of the exemplary application environment shown.

[0030] As Figure 1 shown, the system architecture 100 can include a terminal device 110 and a server 120. The terminal device 110 can be a smart phone, a tablet computer, a desktop computer, a notebook computer, a smart wearable device, etc. The server 120 generally refers to a background system that provides related services of the supplier recommendation method applied to the offshore photovoltaic construction project in the present exemplary embodiment, and can be a server or a cluster formed by multiple servers. The terminal device 110 and the server 120 can be connected through a wired or wireless communication link to perform data interaction.

[0031] In an exemplary embodiment, the above-mentioned supplier recommendation method applied to the offshore photovoltaic construction project can be executed by the server 120. Correspondingly, a supplier recommendation device applied to the offshore photovoltaic construction project can be arranged in the server 120 to realize the corresponding module functions. For example, the server 120 can acquire first location information corresponding to a production address of a candidate manufacturer of a target raw material and second location information corresponding to a construction address of the offshore photovoltaic construction project, determine a distance between the production address and the construction address according to the first location information and the second location information, determine a candidate supplier of the target raw material from the candidate manufacturers based on the distance, classify the candidate suppliers based on each evaluation index of the target raw material, obtain classified results of the candidate suppliers corresponding to each evaluation index, and store the classified results in a database of the server 120. Then, the terminal device 110 can send demand information of the target raw material of a process unit of a different process of the offshore photovoltaic project to the server 120. Then, after the server 120 receives the demand information, the server 120 can perform at least one level of matching between the demand information and the classified results stored in the database, so as to determine a recommended supplier of the target raw material for each process according to a matching result, and thus recommend the recommended supplier of the target raw material to the process unit corresponding to the different process.

[0032] It should be understood that Figure 1 The number of terminal devices and servers in the system is only illustrative. According to the implementation needs, there can be any number of terminal devices and servers. For example, the server 120 can be a stand-alone physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs, and basic cloud computing services such as big data and artificial intelligence platforms.

[0033] Next, Figure 2 A flowchart of a supplier recommendation method applied to an offshore photovoltaic construction project in an exemplary embodiment of the present disclosure is shown, wherein demand information of different processes of the offshore photovoltaic construction project for the same target raw material is different. Referring to Figure 2 The method comprises:

[0034] In step S210, first location information corresponding to a production address of a candidate manufacturer of a target raw material and second location information corresponding to a construction address of the offshore photovoltaic construction project are acquired.

[0035] Step S220: Based on the first location information and the second location information, determine the distance between the production address and the construction address, and determine the candidate supplier of the target raw material from the candidate manufacturers based on the distance;

[0036] Step S230: Classify the candidate suppliers based on each evaluation index of the target raw material to obtain the classification results of the candidate suppliers corresponding to each evaluation index;

[0037] Step S240: Obtain the demand information of the target raw materials for different processes of the offshore photovoltaic construction project, perform at least one level matching between the demand information and the classified results, and determine the recommended supplier of the target raw materials for each process based on the matching results. Each process corresponds to a process unit, and the process unit of each process is different.

[0038] Step S250: Recommend the target raw material supplier to the process unit corresponding to each process.

[0039] exist Figure 2 In the technical solution provided by the illustrated embodiment, for any target raw material in an offshore photovoltaic project, firstly, candidate suppliers are determined from the candidate manufacturers based on the distance between the production address of the candidate raw material and the construction address of the construction project. Then, the candidate suppliers are classified according to the evaluation indicators of the target raw material, obtaining the classified results corresponding to different evaluation indicators. Next, based on the matching information of the target raw material requirements of different processes and the classified results, recommended suppliers are determined for different processes, and the determined recommended suppliers are recommended to the corresponding process units of different processes. Compared with related technologies, this disclosure can accurately recommend suppliers that meet the requirements of different process units in an offshore photovoltaic project for the same target raw material, thereby helping to improve the construction efficiency of offshore photovoltaic projects, avoiding situations where the construction progress of offshore photovoltaic projects is affected by incorrect supplier selection, and reducing the potential risks of offshore photovoltaic construction projects.

[0040] The following are Figure 2 The specific implementation methods of each step in the illustrated embodiment are described in detail below:

[0041] In step S210, the first location information corresponding to the production address of the candidate manufacturer of the target raw material and the second location information corresponding to the construction address of the offshore photovoltaic construction project are obtained.

[0042] In one exemplary embodiment, the target raw materials may include any construction materials in an offshore photovoltaic construction project, such as concrete, steel bars, etc., and this exemplary embodiment does not impose any special limitations on them.

[0043] In an exemplary application scenario, the same target raw material is required in different processes of a marine photovoltaic construction project, but the different processes have different demand information for the target raw material.

[0044] The different processes of the marine photovoltaic project include a booster station construction process, an onshore power collection line construction process, a cable laying construction process, etc. For example, the target raw material A is required in both the booster station construction process and the onshore power collection line construction process. The booster station construction process requires 5 tons of the target raw material A of a first standard, while the onshore power collection line construction process requires 3 tons of the target raw material A of a second standard, and the procurement budget of the target raw material for the onshore power collection line construction process is 10,000 yuan, etc.

[0045] In an exemplary embodiment, the candidate manufacturers can include manufacturers that can produce the target raw material meeting the construction standards of the marine photovoltaic project and are located in the administrative region to which the marine photovoltaic project belongs. The candidate manufacturers can also include manufacturers that can produce the target raw material and participate in bidding in the bidding stage, etc. The candidate manufacturers can be determined according to the demand, and the present exemplary embodiment does not make special limitations thereon.

[0046] In an exemplary embodiment, the production address of the candidate manufacturer can include the position coordinates of the factory address of the candidate manufacturer producing the target raw material. The construction address of the marine photovoltaic project can include the position coordinates of the construction material storage address of the marine photovoltaic project. In the present disclosure, the construction material storage address is located at the construction site, or the distance between the construction material storage address and the construction site is less than a first preset value.

[0047] In step S220, the distance between the production address and the construction address is determined according to the first position information and the second position information, and the candidate supplier of the target raw material is determined from the candidate manufacturers based on the distance.

[0048] For example, the distance between the production address and the construction address can include a straight-line distance, or can include a shortest transportation distance. The shortest transportation distance is determined according to the transportation route between the production address and the construction address.

[0049] For example, a specific embodiment of step S220 can include determining the candidate manufacturers whose distance to the construction address is less than or equal to a preset distance threshold as the candidate suppliers. That is, the recommended suppliers are within a predetermined geographic range of the construction site.

[0050] The determination method of the preset distance threshold can include that the number of candidate suppliers determined by the preset distance is greater than or equal to a preset number. That is, the preset distance cannot be set too small, otherwise the selection range of the suppliers will be too small.

[0051] In other words, the preset distance threshold is different for different target raw materials. For example, if the preset number is 10, for target raw material A, when the preset distance threshold is 10 kilometers, 11 candidate suppliers can be determined, and when the preset distance threshold is less than 10 kilometers, 8 candidate suppliers can be determined, so the preset distance threshold of target raw material A is 10 kilometers. For target raw material B, when the preset distance threshold is 5 kilometers, 12 candidate suppliers can be determined, and when the preset distance threshold is less than 5 kilometers, 5 candidate suppliers can be determined, so the preset distance threshold of target raw material B is 5 kilometers.

[0052] Of course, the preset distance threshold can also be determined according to other information, and the preset distance threshold can also be the same for different target raw materials, which is not specially limited in the present exemplary embodiment.

[0053] Next, with reference to Figure 2 In step S230, the candidate suppliers are classified based on each evaluation index of the target raw material, to obtain the classified results of the candidate suppliers corresponding to each evaluation index.

[0054] In an exemplary embodiment, the evaluation index of the target raw material includes the capacity index, the price index, and the quality index. Of course, the evaluation index of the target raw material can also include other evaluation indexes, such as whether it is environmentally friendly, etc., which is not specially limited in the present exemplary embodiment.

[0055] For example, a specific embodiment of step S230 can include: classifying the candidate suppliers according to the capacity of the candidate suppliers for the target raw material, to obtain a capacity classification table; classifying the candidate suppliers according to the price of the target raw material provided by the candidate suppliers, to obtain a price classification table; and classifying the candidate suppliers according to the quality of the target raw material provided by the candidate suppliers, to obtain a quality classification table.

[0056] For the capacity classification table, candidate suppliers belonging to the same capacity interval can be determined as the same capacity category according to different capacity intervals, so as to obtain the capacity classification table of the candidate suppliers. The range of the capacity interval can be customized according to the demand, which is not specially limited in the present exemplary embodiment. For example, a capacity greater than or equal to 1 ton and less than 3 tons is one category, a capacity greater than or equal to 3 tons and less than 6 tons is one category, and so on. However, the range of the capacity interval cannot be too large, otherwise, the capacity of the same category can be too different, resulting in inaccurate recommendation. The candidate suppliers can also be automatically clustered and classified according to the clustering algorithm based on the capacity information, so as to determine the candidate suppliers with similar capacity as the same category, thereby obtaining the capacity classification table of the candidate suppliers. Of course, the candidate suppliers can also be classified based on the capacity information in other ways, such as determining the candidate suppliers with the same capacity as the same category.

[0057] For the price classification table, candidate suppliers belonging to the same price interval can be determined as the same price category according to different price intervals, so as to obtain the price classification table of the candidate suppliers. The range of the price interval can also be customized according to the demand, which is not specially limited in the present exemplary embodiment. Similarly, the range of the price interval cannot be too large, otherwise, the price of the same category can be too different, resulting in inaccurate recommendation. The candidate suppliers can also be automatically clustered and classified according to the clustering algorithm based on the price information, so as to determine the candidate suppliers with similar price as the same category, thereby obtaining the price classification table of the candidate suppliers.

[0058] For the quality classification table, candidate suppliers belonging to the same quality standard can be determined as the same quality category according to different quality standards, so as to obtain the quality classification table of the candidate suppliers. The quality standards can also be graded, and candidate suppliers producing target raw materials meeting the same quality standard of the quality level can be determined as the same quality category, so as to obtain the quality classification table of the candidate suppliers. For example, quality standard A and quality standard B belong to the first quality level, quality standard C and quality standard D belong to the second quality level, and so on.

[0059] Exemplarily, Figure 3 A flowchart of a method for determining the capacity of a candidate supplier to a target raw material in an exemplary embodiment of the present disclosure is shown. Referring to FIG. 4, Figure 3 The method can include steps S310 to S360. Wherein:

[0060] In step S310, the production information of the candidate supplier is obtained.

[0061] In an exemplary embodiment, the production information includes a device used time length of each production device, a device failure times, a device yield rate, a device failure time, a device output, a labor quantity, a working age of each labor, a historical working time length of each labor in a historical same period of a target raw material supply cycle of the offshore photovoltaic project.

[0062] For example, the production information of the candidate supplier can be directly provided by the candidate supplier or determined by the staff after investigating the production environment of the candidate supplier, and the present exemplary embodiment does not make special limitation thereto.

[0063] The target raw material supply cycle can be understood as a time period in which the target raw material needs to be supplied in the offshore photovoltaic construction project. For example, the target raw material needs to be provided within 30 days after the confirmation of supply, and the expected time of confirmation of supply is October 1, 2024, then the target raw material supply cycle is from October 2, 2024 to October 31, 2024. The historical same period can be understood as a historical time period of the same period in the past three years, such as from October 2, 2023 to October 31, 2023, from October 2, 2022 to October 31, 2022, and from October 2, 2021 to October 31, 2021.

[0064] In step S320, according to the device used time length, the device failure times and the device failure time, the device state of the device in the target raw material supply cycle of the offshore photovoltaic construction project is predicted.

[0065] In an exemplary embodiment, the device state includes a use state, a failure state and a stop state.

[0066] For example, a machine learning model can be trained according to sample data, so that the machine learning model can predict the next failure time of the device according to the device used time length, the device failure times and the device failure time, so as to predict the device state of the device in the target raw material supply cycle according to whether the next failure time of the device falls within the target raw material supply cycle. For example, if the predicted next failure time of the device is within the target raw material supply cycle, the device state of the device in the target raw material supply cycle is a failure state, otherwise it is a use state.

[0067] The training data can include sample data and sample labels, wherein the sample data can include device failure time, device failure times before the failure time, device used time length before the failure time, and label data is the next failure time of the device.

[0068] In step S330, for each device, a device capacity of the device for the target raw material in a target raw material supply period of the offshore photovoltaic construction project is determined according to the device state, the device yield rate and the device output.

[0069] For example, the usage state in the device state can be assigned a value of 1, and the failure state in the device state can be assigned a value of 0. Then, the device capacity of the device for the target raw material in the target raw material supply period is determined according to the product of the device state, the device yield rate and the device output.

[0070] In step S340, a predicted working time length of each labor force in the target raw material supply period is predicted according to a historical working time length of the labor force in a historical same period of the target raw material supply period.

[0071] For example, an average value of the working time length of each labor force in a plurality of historical same periods of the target raw material supply period can be calculated as the predicted working time length of the labor force in the target raw material supply period.

[0072] In step S350, a labor force capacity in the target raw material supply period of the offshore photovoltaic construction project is predicted according to the working seniority of each labor force, the number of labor forces and the predicted working time length.

[0073] For example, an average capacity efficiency of labor forces of different working seniorities can be statistically calculated in advance as a preset labor force capacity efficiency of the labor force corresponding to the working seniority. The average capacity efficiency can be understood as an output per hour. Then, for each labor force, the preset labor force capacity efficiency corresponding to the working seniority of the labor force is obtained, and the capacity of the labor force in the target raw material supply period is predicted according to the preset labor force capacity efficiency and the predicted working time length of the labor force in the target raw material supply period. The sum of the capacities of each labor force in the target raw material supply period is determined as the labor force capacity in the target raw material supply period of the offshore photovoltaic construction project.

[0074] In step S360, a capacity of the target raw material in the target raw material supply period of the offshore photovoltaic construction project is determined according to the device capacity and the labor force capacity.

[0075] For example, a total device capacity can be determined according to the sum of the capacities of each device, a total labor force capacity can be determined according to the sum of the capacities of each labor force, and then the sum of the total device capacity and the total labor force capacity is calculated to obtain the capacity of the target raw material in the target raw material supply period of the offshore photovoltaic construction project.

[0076] In the present disclosure, the capacity of the candidate supplier to supply the target raw material in the target supply period can be predicted by the above steps S310 to S360, so that the capacity and the supply period are combined, various factors affecting the capacity are comprehensively considered, the situation of the factors in the supply period is predicted, the accuracy of the capacity determination is improved, and the accuracy of the supplier recommendation is further improved. The risk that the recommended supplier cannot provide the target raw material in time due to various risk factors, resulting in the offshore photovoltaic construction project cannot be completed on schedule, is reduced.

[0077] With reference to the above Figure 2 In step S240, the demand information of the target raw material of different processes of the offshore photovoltaic construction project is obtained, the demand information and the classified results are matched at least one level, and the recommended supplier of the target raw material of each process is determined according to the matching result.

[0078] In an exemplary embodiment, each process corresponds to a process unit, and the process units of each process are different. For example, in the offshore photovoltaic construction project, different processes correspond to different process units, and different process units using the same target raw material have different demands for the target raw material. For example, a process unit needs target raw material with quality standard A, and a process unit needs target raw material with quality standard B.

[0079] In the present disclosure, the recommended supplier of the target raw material of each process can be determined according to the matching result of the demand information of the target raw material of different processes and the classified results obtained in the above step S230.

[0080] For example, the demand information includes any one of the demand amount, the budget price, and the quality standard. Based on this, Figure 4 A flowchart of a method for determining the recommended supplier of the target raw material of each process according to the matching result in an exemplary embodiment of the present disclosure is shown. With reference to the above Figure 4The method can include steps S410-S430. In step S410, for any process, when the demand information is the demand amount, the demand information is matched with the capacity in the capacity classification table to determine a candidate supplier in the capacity classification table whose capacity is greater than or equal to the demand amount indicated by the demand information as the recommended supplier of the target raw material for the process. In step S420, for any process, when the demand information is the budget price, the demand information is matched with the price in the price classification table to determine a candidate supplier in the price classification table whose price is less than or equal to the budget price indicated by the demand information as the recommended supplier of the target raw material for the process. In step S430, for any process, when the demand information is the quality standard, a first quality level to which the quality standard in the demand information belongs is determined, and the first quality level is matched with the quality level in the quality classification table to determine a candidate supplier corresponding to a second quality level higher than or equal to the first quality level in the quality classification table as the recommended supplier of the target raw material.

[0081] For example, one specific implementation of step S430 can include: different quality standards can be classified in advance, and quality standards belonging to the same quality level are classified into the same category, thereby establishing a mapping relationship table of quality standards and quality levels. Then the quality standard in the demand information is obtained, and the quality level corresponding to the quality standard in the mapping relationship table of quality standards and quality levels is queried, thereby obtaining the first quality level. Then the first quality level is matched with the quality level in the quality classification table, and a candidate supplier corresponding to a quality level indicated by a quality level in the quality classification table, whose quality standard is higher than the quality standard corresponding to the matched quality level, is determined as the recommended supplier.

[0082] Of course, when the quality classification table is classified and determined according to the same quality standard, the quality standard in the demand information can also be matched with the quality standard in the quality classification table. Then a candidate supplier corresponding to a matched quality standard is determined as the recommended supplier, which is not specially limited in this example implementation.

[0083] For example, the demand information can also include at least two of the demand amount, the budget price, and the quality standard. Based on this, Figure 5 Another flowchart of a method for determining the recommended supplier of the target raw material for each process according to the matching result in one example embodiment of the present disclosure is shown. Referring to FIG. 5, the method can include steps S510-S530. In step S510, for any process, when the demand information is the demand amount, the demand information is matched with the capacity in the capacity classification table to determine a candidate supplier in the capacity classification table whose capacity is greater than or equal to the demand amount indicated by the demand information as the recommended supplier of the target raw material for the process. In step S520, for any process, when the demand information is the budget price, the demand information is matched with the price in the price classification table to determine a candidate supplier in the price classification table whose price is less than or equal to the budget price indicated by the demand information as the recommended supplier of the target raw material for the process. In step S530, for any process, when the demand information is the quality standard, a first quality level to which the quality standard in the demand information belongs is determined, and the first quality level is matched with the quality level in the quality classification table to determine a candidate supplier corresponding to a second quality level higher than or equal to the first quality level in the quality classification table as the recommended supplier of the target raw material. Figure 5

[0084] ​In step S510, for each process, the demand information of the target raw material and the demand priority of the demand information are obtained.

[0085] For example, the demand information of each process for the target raw material and the demand priority of the demand information can be input by the client, and the demand information and the demand priority are determined by each process unit according to the actual situation. For example, the demand information of a process unit includes the demand quantity and the budget price, and the priority of the budget price is higher than the priority of the demand quantity, that is, the candidate supplier satisfying the budget price is matched preferentially in subsequent matching.

[0086] In step S520, for the highest priority, the demand value indicated by the demand information of the highest priority and the classified result corresponding to the demand information are matched at the first level to obtain the matching result of the highest priority.

[0087] In an exemplary embodiment, the demand quantity in the demand information corresponds to the capacity classification table, the budget price in the demand information corresponds to the price classification table, and the quality standard in the demand information corresponds to the quality classification table.

[0088] For example, the demand value indicated by the demand information with the highest priority and the classified result corresponding to the demand information can be matched at the first level to obtain the matching result of the demand information with the highest priority. For example, the demand information includes the demand quantity, the budget price, and the quality standard, and the priority order is the quality standard, the budget price, and the demand quantity, that is, the priority of the quality standard is the highest, the priority of the budget price is the second, and the priority of the demand quantity is the lowest. The quality standard in the demand information and the quality classification table are matched at the first level to obtain the matching result of the demand information with the highest priority. The specific implementation of matching the quality standard in the demand information and the quality classification table at the first level can refer to the above step S430, which will not be described here.

[0089] In step S530, for other priorities, according to the priority order, the first category of the candidate supplier in the upper-level matching result corresponding to the upper-level priority is queried in the classified result corresponding to the demand information indicated by the current priority, the first category found is matched with the demand information indicated by the current priority, the matching result of the current priority is determined according to the candidate supplier in the upper-level matching result matched successfully according to the first category, and the process is repeated until the current priority is the last priority. According to the matching result of the last priority, the recommended supplier of the target raw material for the process is obtained.

[0090] In the case that the first category found in step S530 does not match the demand information indicated by the current priority, the candidate supplier included in the last matching result is determined as the recommended supplier of the process, and first prompt information is generated, the first prompt information being used to prompt the priority satisfied and the priority not satisfied by the current recommended supplier.

[0091] The specific implementation of matching the price category with the price category indicated by the budget price can refer to step S420 described above, and the specific implementation of matching the capacity category with the capacity category indicated by the demand quantity can refer to step S410 described above, which will not be described here again.

[0092] In an exemplary embodiment, in the case that the first category found in step S530 does not match the demand information indicated by the current priority, the candidate supplier included in the last matching result is determined as the recommended supplier of the process, and first prompt information is generated, the first prompt information being used to prompt the priority satisfied and the priority not satisfied by the current recommended supplier.

[0093] For example, after obtaining the matching result of the demand information with the priority first, when re-matching according to the matching result of the demand information with the priority first and the demand information with the next priority, there can be a case that none of the candidate suppliers in the matching result of the demand information with the priority first satisfies the demand value indicated by the demand information with the next priority, at this time, the candidate suppliers in the matching result of the demand information with the priority first can be directly determined as the recommended suppliers, and the first prompt information can be generated according to the related information of the demand information of each recommended supplier after the priority.

[0094] Continuing to take the demand information including demand quantity, budget price, quality standard, and the priority order of quality standard, budget price and demand quantity, i.e. the priority of quality standard is the highest, the priority of budget price is the second, and the priority of demand quantity is the lowest, as an example, after obtaining the matching result of budget price, if the production capacity of the candidate supplier in the matching result of budget price cannot meet the demand quantity, the candidate supplier in the matching result of budget price can be determined as the recommended supplier, and the first prompt information of “the current recommended supplier meets your quality demand and price demand, but the production capacity of the recommended supplier cannot meet your demand quantity, you can select and combine the recommended suppliers to meet your demand quantity” can be generated. Meanwhile, the production capacity information of each recommended supplier can also be provided in the first prompt information, so that the user can make a selection.

[0095] Exemplarily, in the case that the demand information includes at least two of demand quantity, budget price and quality standard, another specific implementation of step S240 can include: for each process, matching each demand information with the classified result corresponding to the demand information respectively to obtain the matching result of each demand information; and determining the recommended supplier of the target raw material for the process according to the candidate supplier existing in the matching result of each demand information.

[0096] For example, in the case that the demand information of a certain process includes multiple kinds, each kind of demand information can be separately matched with the classified result corresponding thereto to obtain the respective matching result, and then the intersection of the respective matching results is taken to determine the recommended supplier of the target raw material for the process according to the candidate supplier in the intersection.

[0097] In the present disclosure, the recommended supplier of the same target raw material in different production processes is realized for the case that the same target raw material is used in different processes of the same offshore photovoltaic construction project. There can be multiple suppliers that can simultaneously meet the demand of a certain production process in the recommended result, and the user can select one or more suppliers according to his / her preference or experience to cooperate.

[0098] Based on this, exemplarily, Figure 6 Another flowchart of a method of determining the recommended supplier of the target raw material for each process according to the matching result in an exemplary embodiment of the present disclosure is shown. Referring to FIG. 6, Figure 6 The method can include steps S610 to S650. Wherein:

[0099] In step S610, in response to the selection operation of any process unit on the recommended supplier, the recommended supplier indicated by the selection operation is determined as the target supplier of the target raw material for the process unit, and a first mark is added to the target supplier.

[0100] In an exemplary embodiment, the first mark is used to indicate the process unit supplied by the target supplier and the supply amount provided to the process unit.

[0101] For example, after a certain process unit performs a selection operation on the recommended supplier, the recommended supplier indicated by the selection operation can be determined as the target supplier of the target raw material for the process unit. The target supplier is the finally determined supplier, i.e., the target supplier is assigned to the process unit. After the target supplier is assigned to a certain process unit, a first mark can be added to the target supplier, which is used to indicate that the target supplier has been assigned, and the process unit assigned to the target supplier and the demand amount of the target raw material for the process unit.

[0102] In step S620, in the case where there is a candidate supplier with the first mark added in the matching result, the demand amount of the process, the capacity of the candidate supplier with the first mark added, and the supply amount indicated by the first mark are obtained.

[0103] In step S630, according to the capacity and the supply amount, the remaining capacity of the candidate supplier with the first mark added is determined.

[0104] In step S640, in the case where the remaining capacity is greater than the demand amount and the absolute value of the difference between the remaining capacity and the demand amount is greater than a first preset value, the candidate supplier with the first mark added is retained in the matching result, otherwise the candidate supplier with the first mark added is excluded from the matching result, so as to perform risk processing on the matching result.

[0105] In step S650, the candidate supplier remaining in the matching result after the risk processing is determined as the recommended supplier of the target raw material for the process.

[0106] For example, for the demand information of any process, in the case where there is a candidate supplier with the first mark added in the final matching result of the demand information, it is necessary to measure whether the capacity of the candidate supplier can meet the demand of multiple processes. When the capacity of the candidate supplier with the first mark added cannot continue to meet the demand amount of the current process, the candidate supplier is excluded from the final matching result, otherwise the candidate supplier is retained, so as to perform risk processing on the matching result, and the candidate supplier included in the matching result after the risk processing is determined as the recommended supplier of the target raw material for the process.

[0107] Through the steps S610 to S650, when the same target raw material is required by different processes, the supplier recommendation can be made according to the production capacity of the supplier, so as to avoid the situation that the target raw material is not supplied in time, and improve the accuracy of the supplier recommendation.

[0108] In step S250, the recommended supplier of the target raw material is recommended to each process unit corresponding to each process.

[0109] For example, each process unit can log in to its own account through the client, and then input the demand information of any target raw material in the client. The method in the present disclosure is used to recommend the recommended supplier of the target raw material for the process unit. After obtaining the recommended supplier of each process, the recommended supplier of the target raw material can be recommended to each process unit in the client. Alternatively, the process unit identifier and the demand information of the target raw material for each process can be input in one client, and the recommended supplier of the target raw material for each process unit can be output in one client.

[0110] In the supplier recommendation method applied to the offshore photovoltaic construction project, according to the characteristics of the offshore photovoltaic construction project, the allocation management of the supplier can be performed, the accuracy of the supplier recommendation is improved, and the timeliness of the raw material supply is ensured. Meanwhile, different suppliers are recommended for different process units, different suppliers can provide corresponding raw materials in corresponding construction stages, and the packaging information and the like of different suppliers for the same raw material are also different, so as to avoid the mutual interference between different processes during construction, and improve the construction efficiency.

[0111] In addition, it should be noted that the above-mentioned figures are only schematic representations of the processes included in the method according to the exemplary embodiments of the present application, and are not for limiting purposes. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be executed synchronously or asynchronously, for example, in multiple modules.

[0112] Further, the exemplary embodiments of the present disclosure also provide a supplier recommendation device 700 applied to an offshore photovoltaic construction project, different processes of the offshore photovoltaic construction project have different demand information for the same target raw material, and the supplier recommendation device 700 comprises Figure 7As shown, the supplier recommendation device applied to the offshore photovoltaic construction project comprises the following program modules: a position information acquisition module 710 configured to acquire first position information corresponding to a production address of a candidate manufacturer of a target raw material and second position information corresponding to a construction address of the offshore photovoltaic construction project; a candidate supplier determination module 720 configured to determine a distance between the production address and the construction address according to the first position information and the second position information, determine a candidate supplier of the target raw material from the candidate manufacturers based on the distance; a classification module 730 configured to classify the candidate suppliers based on each evaluation index of the target raw material to obtain a classified result of the candidate suppliers corresponding to each evaluation index; a matching module 740 configured to acquire demand information of different processes of the offshore photovoltaic construction project for the target raw material, perform at least one level of matching between the demand information and the classified result, and determine a recommended supplier of the target raw material for each process according to a matching result, wherein each process corresponds to a process unit, and the process units of each process are different; and a recommendation module 750 configured to recommend the recommended supplier of the target raw material to each process unit of each process respectively.

[0113] Optionally, the evaluation indexes include capacity indexes, price indexes, and quality indexes, and the classification of the candidate suppliers based on each evaluation index of the target raw material to obtain a classified result corresponding to each evaluation index comprises: classifying the candidate suppliers according to the capacity of the candidate suppliers for the target raw material to obtain a capacity classification table; classifying the candidate suppliers according to the price of the target raw material provided by the candidate suppliers to obtain a price classification table; and classifying the candidate suppliers according to the quality of the target raw material provided by the candidate suppliers to obtain a quality classification table.

[0114] Optionally, the production capacity of the candidate supplier for the target raw material is determined by: obtaining production information of the candidate supplier, the production information comprising device used time length, device failure times, device failure time, device yield rate, device output, labor quantity, working age of each labor, historical working time length of each labor in a historical same period of a target raw material supply period of the offshore photovoltaic project; predicting device state of the device in the target raw material supply period of the offshore photovoltaic construction project according to the device used time length, the device failure times and the device failure time, the device state comprising use state, failure state; for each device, determining device production capacity of the device for the target raw material in the target raw material supply period of the offshore photovoltaic construction project according to the device state, the device yield rate and the device output; predicting predicted working time length of the labor in the target raw material supply period according to the historical working time length of each labor in the historical same period of the target raw material supply period; predicting labor production capacity in the target raw material supply period of the offshore photovoltaic construction project according to the working age of each labor, the labor quantity and the predicted working time length; determining production capacity of the candidate supplier for the target raw material in the target raw material supply period of the offshore photovoltaic construction project according to the device production capacity and the labor production capacity.

[0115] Optionally, the demand information comprises any one of demand quantity, budget price, quality standard, the obtaining of the demand information of different processes of the offshore photovoltaic construction project for the target raw material, the at least one level matching of the demand information and the classified result, and the determination of the recommended supplier of each process for the target raw material according to the matching result comprises: for any process, in the case that the demand information is the demand quantity, matching the demand information and the production capacity in the production capacity classification table to determine the candidate supplier with production capacity greater than or equal to the demand quantity indicated by the demand information in the production capacity classification table as the recommended supplier of the target raw material for the process; for any process, in the case that the demand information is the budget price, matching the demand information and the price in the price classification table to determine the candidate supplier with price less than or equal to the budget price indicated by the demand information in the price classification table as the recommended supplier of the target raw material for the process; for any process, in the case that the demand information is the quality standard, determining the first quality level to which the quality standard in the demand information belongs, matching the first quality level and the quality level in the quality classification table to determine the candidate supplier corresponding to the second quality level higher than or equal to the first quality level in the quality classification table as the recommended supplier of the target raw material.

[0116] Optionally, the demand information includes at least two of a demand amount, a budget price, and a quality standard, the obtaining of the demand information of the target raw material by different working procedures of the offshore photovoltaic construction project, the at least one-level matching of the demand information and the classified results, and the determining of the recommended supplier of the target raw material by each working procedure include: for each working procedure, obtaining the demand information of the target raw material by the working procedure and a demand priority of the demand information; for the highest priority, performing a first-level matching of a demand value indicated by the demand information of the highest priority and the classified results corresponding to the demand information, to obtain a matching result of the highest priority; for other priorities, according to a priority order, querying a first category of candidate suppliers in a first-level matching result corresponding to a last-level priority of the priority from the classified results corresponding to the demand information indicated by the current priority, matching the found first category with the demand information indicated by the current priority, and determining a matching result of the current priority according to the candidate suppliers in the first-level matching result that match the first category successfully, and repeating the process until the current priority is the last priority, and obtaining the recommended supplier of the target raw material by the working procedure according to the matching result of the last priority.

[0117] Optionally, the apparatus further includes a first prompt module, which can be configured to: in a case where the found first category does not match the demand information indicated by the current priority, determining the candidate suppliers included in the first-level matching result as the recommended supplier of the working procedure, and generating first prompt information, the first prompt information being used to prompt a priority satisfied by the current recommended supplier and a priority not satisfied.

[0118] Optionally, the determining the recommended supplier of the target raw material for each process according to the matching result comprises: in a case where there is a candidate supplier added with a first mark in the matching result, obtaining a demand quantity of the process, a production capacity of the candidate supplier added with the first mark, and a supply quantity indicated by the first mark; determining a remaining production capacity of the candidate supplier added with the first mark according to the production capacity and the supply quantity; in a case where the remaining production capacity is greater than the demand quantity and an absolute value of a difference between the remaining production capacity and the demand quantity is greater than a first preset value, retaining the candidate supplier added with the first mark in the matching result, otherwise, eliminating the candidate supplier added with the first mark in the matching result, so as to perform risk processing on the matching result; and determining the candidate supplier remaining in the matching result after the risk processing as the recommended supplier of the target raw material for the process; wherein the adding manner of the first mark comprises: in response to a selection operation of any process unit on the recommended supplier, determining a recommended supplier indicated by the selection operation as a target supplier of the process unit for the target raw material, adding a first mark to the target supplier, and the first mark is used to indicate a process unit supplied by the target supplier and a supply quantity provided for the process unit.

[0119] The specific details of the parts of the above device have been described in detail in the method part embodiments, and the undisclosed details can be referred to the content of the method part embodiments, and thus will not be described again.

[0120] It should be noted that although several modules or units of the device for action execution are mentioned in the above detailed description, such division is not mandatory. In fact, according to the example embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into several modules or units.

[0121] In addition, although the steps of the method in the present disclosure are described in a specific order in the above detailed description, this is not required or implied that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired result. Additionally or alternatively, some steps can be omitted, a plurality of steps can be combined into one step, and / or one step can be divided into a plurality of steps, etc.

[0122] The example embodiments of the present disclosure also provide a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the above-mentioned supplier recommendation method applied to a marine photovoltaic construction project.

[0123] In an embodiment, the computer program product can be a tangible product including the computer program, such as a computer-readable storage medium storing the computer program. The computer-readable storage medium can be a storage medium based on an electrical, magnetic, optical, electromagnetic, infrared, or any other type of signal, including but not limited to random access memory (RAM), read only memory (ROM), a tape, a floppy disk, flash memory (Flash), a mechanical hard disk (HDD), a solid state hard disk (SSD), and the like. For example, the computer program product can be implemented as a non-volatile storage medium storing the computer program, such as a read only memory (ROM), a Nand Flash, and the like.

[0124] In an embodiment, the computer program product can be an intangible product including the computer program. For example, the computer program product can be implemented as a virtual digital product, such as an executable file, an installation package, or the like digital file storing the computer program.

[0125] The code of the computer program can be written in one or more programming languages. Programming languages include, for example, C, Java, C++, Python, and the like. The program code can execute entirely on the user's computing device, or partly on the user's computing device and partly on a remote computing device, or entirely on a remote computing device or server. In the latter scenario, the remote computing device can be connected to the user's computing device through any kind of network, including a local area network (LAN), a wide area network (WAN), or the like, or the connection can be made to an external computing device, such as through the Internet using an Internet Service Provider (ISP).

[0126] The computer program can be carried or transmitted by an electric, magnetic, optical, electromagnetic, infrared, or other signals. The electronic device can convert the signal carrying the computer program into a digital signal, and then run the computer program. When the computer program is running on the electronic device, its code is used to make the electronic device perform (more specifically, can make the processor of the electronic device perform) the method steps of various exemplary embodiments of the present disclosure, such as the above-mentioned supplier recommendation method applied to the offshore photovoltaic construction project, the demand information of the same target raw material is different for different processes of the offshore photovoltaic construction project, which includes the following steps: obtaining the first position information corresponding to the production address of the candidate manufacturer of the target raw material and the second position information corresponding to the construction address of the offshore photovoltaic construction project; according to the first position information and the second position information, the distance between the production address and the construction address is determined, and based on the distance, the candidate supplier of the target raw material is determined from the candidate manufacturer; based on each evaluation index of the target raw material, the candidate supplier is classified to obtain the classified result of the candidate supplier corresponding to each evaluation index; obtaining the demand information of the target raw material for different processes of the offshore photovoltaic construction project, at least one level of matching is performed between the demand information and the classified result, and the recommended supplier of the target raw material for each process is determined according to the matching result, wherein each process corresponds to a process unit, and the process units of each process are different; respectively to each process unit corresponding to the recommended target raw material of the recommended supplier.

[0127] By executing the above-mentioned method steps by the computer program, for the same target raw material, the supplier meeting the demand of the process unit can be accurately recommended for the process unit corresponding to the different processes of the offshore photovoltaic project, thereby assisting to improve the construction efficiency of the offshore photovoltaic project, avoiding the situation that the construction progress of the offshore photovoltaic project is affected due to the wrong selection of the supplier, and reducing the potential risk of the offshore photovoltaic construction project.

[0128] The exemplary embodiments of the present disclosure also provide an electronic device, which can be the terminal device 110 or the server 120 described above. The electronic device can include a processor and a memory. The memory stores executable instructions of the processor, which can be a computer program. The processor executes the executable instructions to perform the method steps of various exemplary embodiments of the present disclosure. In addition, the electronic device can further include a display for displaying a graphical user interface.

[0129] The following will be described with reference to Figure 8 The electronic device is exemplarily illustrated in the form of a general computing device. It should be understood that Figure 8 The electronic device 800 shown is only an example and should not limit the function and use range of the embodiments of the present disclosure.

[0130] AsFigure 8 As shown, the electronic device 800 can include a processor 810, a memory 820, a bus 830, an I / O (input / output) interface 840, a network adapter 850, a display 860.

[0131] The memory 820 can include a volatile memory, such as a RAM 821, a cache unit 822, and can also include a non-volatile memory, such as a ROM 823. The memory 820 can also include one or more program modules 824, which include, but are not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination of which can include implementation of a network environment. For example, the program modules 824 can include the modules in the above-described apparatus.

[0132] The processor 810 can include one or more processing units, such as: an AP (Application Processor, application processor), a modem processor, a GPU (Graphics Processing Unit, graphics processing unit), an ISP (Image Signal Processor, image signal processor), a controller, an encoder, a decoder, a DSP (Digital Signal Processor, digital signal processor), a baseband processor, and / or an NPU (Neural-Network Processing Unit, neural network processor), etc.

[0133] The processor 810 can be used to execute executable instructions stored in the memory 820, such as the above-described supplier recommendation method applied to the offshore photovoltaic construction project, the different processes of the offshore photovoltaic construction project have different demand information for the same target raw material, which includes the following steps: obtaining first position information corresponding to the production address of the candidate manufacturer of the target raw material and second position information corresponding to the construction address of the offshore photovoltaic construction project; determining the distance between the production address and the construction address according to the first position information and the second position information, and determining the candidate supplier of the target raw material from the candidate manufacturer based on the distance; classifying the candidate supplier based on each evaluation index of the target raw material to obtain the classified result of the candidate supplier corresponding to each evaluation index; obtaining the demand information of the target raw material for different processes of the offshore photovoltaic construction project, performing at least one level of matching between the demand information and the classified result, and determining the recommended supplier of the target raw material for each process according to the matching result, wherein each process corresponds to a process unit, and the process units of each process are different; respectively to each process unit corresponding to the recommended supplier of the recommended target raw material of each process.

[0134] By implementing the above method through a computer program, for the same target raw material, a process unit corresponding to a different process of the offshore photovoltaic project can be accurately recommended a supplier meeting the demand of the process unit, thereby assisting in improving the construction efficiency of the offshore photovoltaic project, avoiding the situation that the construction progress of the offshore photovoltaic project is affected due to the wrong selection of the supplier, and reducing the potential risk of the offshore photovoltaic construction project.

[0135] The bus 830 is used to realize the connection between different components of the electronic device 800, and can include a data bus, an address bus and a control bus.

[0136] The electronic device 800 can communicate with one or more external devices 900 (such as a keyboard, a mouse, an external controller, etc.) through the I / O interface 840.

[0137] The electronic device 800 can communicate with one or more networks through the network adapter 850, for example, the network adapter 850 can provide a mobile communication solution such as 3G / 4G / 5G, or provide a wireless communication solution such as a wireless local area network, Bluetooth, near field communication, etc. The network adapter 850 can communicate with other modules of the electronic device 800 through the bus 830.

[0138] The electronic device 800 can display a graphical user interface such as a recommended result interface through the display 860.

[0139] Although Figure 8 Other hardware and / or software modules can also be provided in the electronic device 800, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0140] In addition, the above figures are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present disclosure, and are not for limiting purposes. It is easy to understand that the processes shown in the above figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be executed synchronously or asynchronously, for example, in multiple modules.

[0141] As can be seen from the above, the technical solutions of the present disclosure can be implemented as a method, an apparatus, a system, a computer program product, a storage medium, an electronic device, and the like. Those skilled in the art can understand that each aspect of the present disclosure can be specifically implemented as a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, such as a "circuit", a "module" or a "system".

[0142] It should be understood that the present disclosure is not limited to particular methods, steps, or structures described herein and in the drawings, as such methods, steps, and structures can vary. Other embodiments within the scope of the present disclosure will be recognized by those of ordinary skill in the art based on the following description. It is intended to cover any and all variations of the present disclosure with the scope of the claims depending from a true spirit and scope of the present disclosure, including all equivalents thereof and modifications made to the disclosure as permitted by the appended claims.

Claims

1. A supplier recommendation method applied to an offshore photovoltaic construction project, characterized by, The different processes of the offshore photovoltaic construction project have different demand information for the same target raw material, and the method comprises the following steps: Obtain first position information corresponding to a production address of a candidate manufacturer of the target raw material and second position information corresponding to a construction address of the offshore photovoltaic construction project; Determine the distance between the production address and the construction address according to the first position information and the second position information, and determine the candidate supplier of the target raw material from the candidate manufacturers based on the distance; Classify the candidate suppliers based on each evaluation index of the target raw material to obtain the classified results of the candidate suppliers corresponding to each evaluation index; For each process, obtain the demand information of the process for the target raw material and the demand priority of the demand information, for the highest priority, perform first-level matching on the demand value indicated by the demand information of the highest priority and the classified results corresponding to the demand information to obtain the matching result of the highest priority, for other priorities, according to the priority order, query the first category of the candidate suppliers in the upper-level matching result corresponding to the upper-level priority from the classified results corresponding to the demand information indicated by the current priority, match the found first category with the demand information indicated by the current priority, and determine the matching result of the current priority according to the candidate suppliers in the upper-level matching result that match the first category successfully, repeat the process until the current priority is the last priority, and obtain the recommended supplier of the target raw material for the process according to the matching result of the last priority, wherein the demand information comprises at least two of demand quantity, budget price and quality standard, each process corresponds to a process unit, and the process units of each process are different; Respectively recommend the recommended supplier of the target raw material to the process unit corresponding to each process.

2. The method of claim 1, wherein, The evaluation indexes include capacity index, price index and quality index, and the classification of the candidate suppliers based on each evaluation index of the target raw material to obtain the classified results corresponding to each evaluation index comprises the following steps: Classify the candidate suppliers according to the capacity of the candidate suppliers for the target raw material to obtain a capacity classification table; Classify the candidate suppliers according to the price of the target raw material provided by the candidate suppliers to obtain a price classification table; Classify the candidate suppliers according to the quality of the target raw material provided by the candidate suppliers to obtain a quality classification table.

3. The method of claim 1, wherein, The method further comprises the following steps: In the case that neither the found first category nor the demand information indicated by the current priority matches, the candidate suppliers included in the upper-level matching result are determined as the recommended supplier of the process, and first prompt information is generated, wherein the first prompt information is used to prompt the priority satisfied and the priority not satisfied by the current recommended supplier.

4. A supplier recommendation device applied to an offshore photovoltaic construction project, characterized by, The different processes of the offshore photovoltaic construction project have different demand information for the same target raw material, and the device comprises the following steps: The position information acquisition module is configured to acquire first position information corresponding to a production address of a candidate producer of a target raw material and second position information corresponding to a construction address of the offshore photovoltaic construction project; The candidate supplier determination module is configured to determine a distance between the production address and the construction address according to the first position information and the second position information, and determine a candidate supplier of the target raw material from the candidate producers based on the distance; The classification module is configured to classify the candidate suppliers based on each evaluation index of the target raw material to obtain a classified result of the candidate suppliers corresponding to each evaluation index; The matching module is configured to acquire, for each process, demand information of the process on the target raw material and a demand priority of the demand information, perform first-level matching on a demand value indicated by the demand information of a highest priority and the classified result corresponding to the demand information to obtain a matching result of the highest priority, and for other priorities, according to a priority order, query, in the classified result corresponding to demand information indicated by a current priority, a first category of candidate suppliers in a last-level matching result corresponding to a last-level priority of the priority, match the found first category with the demand information indicated by the current priority, and determine a matching result of the current priority according to candidate suppliers in the last-level matching result that match the first category successfully, repeat the process until the current priority is the last priority, and according to the matching result of the last priority, obtain a recommended supplier of the target raw material for the process, wherein the demand information includes at least two of a demand amount, a budget price, and a quality standard, each process corresponds to a process unit, and process units of each process are different; The recommendation module is configured to recommend the recommended supplier of the target raw material to each process unit of each process respectively.

5. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the method of any one of claims 1 to 3.

6. An electronic device, comprising: The computer program is executed by the processor to implement the method of any one of claims 1 to 3. The computer program is executed by the processor to implement the method of any one of claims 1 to 3. The computer program is executed by the processor to implement the method of any one of claims 1 to 3. The computer program is executed by the processor to implement the method of any one of claims 1 to 3.

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