A warehouse layout generation method and apparatus

Abstract

The application discloses a kind of warehousing layout generation method and device, it is related to logistics and warehousing management technical field.The specific embodiment of the method includes: obtaining the demand data of warehousing layout, demand data includes natural language description information and structured drawing information;From natural language description information, structural design constraint is parsed, and space structure information is parsed from structured drawing information;Structural design constraint includes the equipment design constraint of each functional partition;According to structural design constraint and space structure information, generate warehousing partition scheme;According to the partition data of functional partition and equipment design constraint, the equipment layout of each functional partition is generated, and then the warehousing layout result corresponding to demand data is obtained.The embodiment realizes the end-to-end automation process from the demand data of multimodal to warehousing layout result, improves the design efficiency and intelligent level of warehousing layout, and the generated warehousing layout is more reasonable, meets complex and changeable warehousing demand.

Description

Technical Field

[0001] This invention relates to the field of logistics and warehousing management technology, and in particular to a method and apparatus for generating warehouse layouts. Background Technology

[0002] In the field of logistics and warehousing management, optimizing warehouse layout is a key step in improving warehousing efficiency and reducing costs. Related technologies include warehouse layout design methods such as Systematic Layout Planning (SLP), simulation and mathematical modeling, and Computer-Aided Design (CAD) / Building Information Modeling (BIM). SLP systematically plans warehouse layouts by analyzing logistics, information flow, and pedestrian flow. Simulation and mathematical modeling methods use simulation software to model warehouse layouts and evaluate the effectiveness of different layout schemes; mathematical modeling is used for space allocation and path optimization. CAD / BIM-aided design involves designers manually drawing warehouse layout diagrams using CAD / BIM tools.

[0003] However, the above-mentioned warehouse layout design methods mainly rely on human experience and manual operation, which makes it difficult to cope with large-scale, complex and ever-changing warehouse needs. In addition, the design cycle is long and easily affected by subjective human factors, making it difficult to ensure the consistency of the layout. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a warehouse layout generation method and apparatus, which realizes an end-to-end automated process from multimodal demand data to warehouse layout results, improves the design efficiency and intelligence level of warehouse layout, makes the generated warehouse layout more reasonable, can ensure the consistency and rationality of the layout, and can meet complex and ever-changing warehouse needs.

[0005] To achieve the above objectives, according to one aspect of the present invention, a warehouse layout generation method is provided, comprising: Obtain warehouse layout requirements data, including natural language description information and structured drawing information; Structural design constraints are parsed from the natural language description information, and spatial structure information is parsed from the structured drawing information; the structural design constraints include equipment design constraints for each functional area; A storage zoning scheme is generated based on the structural design constraints and the spatial structure information; the storage zoning scheme includes each functional zone and the zoning data of each functional zone; For each functional zone, the equipment layout of each functional zone is generated based on the partition data and equipment design constraints, so as to obtain the warehouse layout result corresponding to the demand data according to the warehouse partitioning scheme and the equipment layout of each functional zone.

[0006] Optionally, the structural design constraints indicate one or more optimization objectives for the warehouse layout, and a warehouse zoning scheme is generated based on the structural design constraints and the spatial structure information, including: The structural design constraints and the spatial structure information are fused to obtain the input data; The warehouse partitioning scheme is generated based on the input data, one or more optimization objectives, and a pre-trained partitioning generation model.

[0007] Optionally, the structural design constraints and the spatial structure information are fused to obtain input data, including: Extract each first entity and the constraint conditions of each first entity from the structural design constraints, and extract each second entity and the geometric information of each second entity from the spatial structure information; Each first entity is matched with each second entity, and the constraints of the successfully matched first entity and the geometric information of the second entity are fused to obtain the fusion information of each fused entity. The input data is obtained based on the fusion information of each fused entity.

[0008] Optionally, before generating the warehouse partitioning scheme based on the input data, the one or more optimization objectives, and the pre-trained partitioning generation model, the method further includes: retrieving the warehouse specifications corresponding to the input data from a preset warehouse knowledge base; and enhancing and completing the input data based on the warehouse specifications.

[0009] Optionally, the device layout for each functional partition is generated based on the partition data of the functional partitions and the device design constraints, including: One or more layout tasks corresponding to the functional partitions are constructed based on preset task types; For each layout task, the equipment layout corresponding to the layout task is generated based on the equipment design constraints of the functional partition and the partition data. The preset task type includes at least one of equipment selection, channel design or entrance / exit layout.

[0010] Optionally, the structural design constraints indicate one or more optimization objectives for the warehouse layout; generating the equipment layout corresponding to the layout task based on the equipment design constraints of the functional partitions and the partition data includes: The partition data and the device design constraints are input into the device layout model corresponding to the layout task; The equipment layout model is used to call a preset warehouse knowledge base to obtain the equipment information corresponding to the layout task; Based on the device information, the one or more optimization objectives, and the device layout model, the device layout corresponding to the layout task is obtained.

[0011] Optionally, after obtaining the warehouse layout result corresponding to the demand data based on the warehouse zoning scheme and the equipment layout of each functional zone, the method further includes: outputting the warehouse layout result in the form of structured data, drawings and / or natural language description.

[0012] According to another aspect of the present invention, a warehouse layout generation apparatus is provided, comprising: The acquisition module acquires warehouse layout requirement data, which includes natural language description information and structured drawing information. The parsing module parses the structural design constraints of the warehouse layout from the natural language description information and parses the spatial structure information from the structured drawing information; the structural design constraints include the equipment design constraints of each functional area; The partitioning generation module generates a warehouse partitioning scheme based on the structural design constraints and the spatial structure information; the warehouse partitioning scheme includes each functional partition and partitioning data for each functional partition; The layout generation module generates the equipment layout for each functional partition based on the partition data and equipment design constraints of the functional partition, so as to obtain the warehouse layout result corresponding to the demand data according to the warehouse partitioning scheme and the equipment layout of each functional partition.

[0013] According to another aspect of the present invention, an electronic device is provided, comprising: One or more processors; 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 warehouse layout generation method provided by the present invention.

[0014] According to another aspect of the present invention, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the warehouse layout generation method provided by the present invention.

[0015] One embodiment of the above invention has the following advantages or beneficial effects: The warehouse layout generation method of this invention first obtains and parses the warehouse layout demand data, obtains a warehouse zoning scheme based on the obtained structural design constraints and spatial result information, and then generates the equipment layout for each functional zone based on the warehouse zoning scheme, thereby obtaining the warehouse layout result. This method parses multimodal demand data, generates a warehouse zoning scheme based on the parsing results, and then generates the equipment layout based on the warehouse zoning scheme, thereby obtaining the warehouse layout result. This realizes an end-to-end automated process from multimodal demand data to warehouse layout result, improves the design efficiency and intelligence level of warehouse layout, makes the generated warehouse layout more reasonable, ensures the consistency and optimization of the layout, and can meet complex and ever-changing warehouse needs. It overcomes the problems of low efficiency, poor layout effect, and difficulty in meeting complex and ever-changing warehouse needs caused by the warehouse layout design method that relies on manual experience in the prior art.

[0016] The further effects of the aforementioned unconventional alternative methods will be explained below in conjunction with specific implementation methods. Attached Figure Description

[0017] The accompanying drawings are provided to better understand the invention and are not intended to unduly limit the scope of the invention. Wherein: Figure 1 This is a schematic diagram of the main process of a warehouse layout generation method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the main process of another warehouse layout generation method according to an embodiment of the present invention; Figure 3 This is a flowchart illustrating a warehouse layout generation method according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the main modules of the warehouse layout generation device according to an embodiment of the present invention; Figure 5 This is an exemplary system architecture diagram in which embodiments of the present invention can be applied; Figure 6 This is a schematic diagram of the structure of a computer system suitable for implementing terminal devices or servers of the present invention. Detailed Implementation

[0018] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention, including various details to aid understanding. These details should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0019] Figure 1 This is a schematic diagram of the main process of a warehouse layout generation method according to an embodiment of the present invention, as shown below. Figure 1 As shown, the warehouse layout generation method includes the following steps: Step S101: Obtain warehouse layout requirements data, which includes natural language description information and structured drawing information; Step S102: Extract structural design constraints from natural language description information and extract spatial structure information from structured drawing information; structural design constraints include equipment design constraints for each functional area; Step S103: Generate a warehouse zoning plan based on structural design constraints and spatial structure information; the warehouse zoning plan includes each functional zone and the zoning data of each functional zone; Step S104: For each functional zone, generate the equipment layout for each functional zone based on the partition data and equipment design constraints, so as to obtain the warehouse layout result corresponding to the demand data according to the warehouse partitioning scheme and the equipment layout of each functional zone.

[0020] In this embodiment of the invention, the first step is to acquire the warehouse layout requirements data. This data includes natural language description information and structured drawing information. The natural language description information describes the warehouse layout requirements and may include the functional requirements of each functional area, constraints, and optimization goals of the warehouse layout. For example, the natural language description information could be: "A high-frequency picking area is needed near the shipping outlet, the cold chain area is needed away from heat sources, the office area is needed near the main entrance, and the AGV (Automatic Guided Vehicle) passage width is not less than 2.5 meters." The structured drawing information can be the structural civil engineering drawings of the warehouse layout, which may include structured information such as the length, width, and height of the warehouse, load-bearing walls, column grid, doors and windows, and fire exits.

[0021] After obtaining the warehouse layout requirements data, the natural language description information and structured drawing information are analyzed separately. A large model can be used to perform semantic understanding of the natural language description information, and structural design constraints can be extracted from it. Structural design constraints are constraints that have a structural limiting effect on the warehouse layout design. These constraints can include functional requirement constraints for each functional area, equipment design constraints, and general constraints. For example, the functional requirement constraints for each functional area refer to the restrictions on the spatial structure, size, and location of different warehouse operation areas. For example, the high-frequency sorting area should be close to the shipping outlet; the cold chain area should be far away from heat sources; and the office area should be close to the main entrance. Equipment design constraints can include equipment type, equipment parameters, and requirements for space dimensions and aisle width, such as automated sorting shelves and their spatial distribution; general constraints can include warehouse specifications (such as fire safety, cold chain temperature control, AGV aisle width, etc.); spatial structure information can be parsed from structured drawing information. If the structured drawing information is a dxf (Drawing Exchange Format, a two-dimensional vector graphics format) file, it can first be parsed into a JSON (a lightweight text data exchange format) file, and then the spatial structure information can be parsed from the JSON file using a large model. If the structured drawing information is a JSON file, the spatial structure information can be directly parsed. Spatial structure information includes spatial data such as dimensions, structure, and constraints.

[0022] Then, based on structural design constraints and spatial structure information, a warehouse zoning scheme is generated. This scheme can include various functional zones and their respective zoning data. Each functional zone can also include one or more sub-zones. For example, a cold chain zone could include multiple sub-zones such as frozen storage, refrigerated storage, and ultra-low temperature storage. The zoning data for each functional zone can include the zone type, spatial coordinates, etc. The warehouse zoning scheme can be obtained based on the structural design constraints, spatial structure information, and the pre-trained zoning generation model.

[0023] The pre-trained partition generation model can be obtained by fine-tuning a large model, such as Deepseek or GLM (General Language Model). Specifically, the pre-trained partition generation model is obtained through the following method: acquiring a training sample set, which includes multiple demand data samples and corresponding warehouse partitioning schemes for each demand data sample. Each demand data sample includes natural language description information and structured drawing information of the warehouse layout. The natural language description information is parsed to obtain structural design constraints, and the structured drawing information is parsed to obtain spatial structure information. The large model is then fine-tuned using the structural design constraints, spatial structure information, and corresponding warehouse partitioning schemes to obtain the pre-trained partition generation model.

[0024] In this embodiment of the invention, structural design constraints indicate one or more optimization objectives for the warehouse layout. Generating a warehouse zoning scheme based on structural design constraints and spatial structure information includes: fusing structural design constraints and spatial structure information to obtain input data; and generating a warehouse zoning scheme based on the input data, one or more optimization objectives, and a pre-trained zoning generation model.

[0025] In this embodiment of the invention, after parsing the structural design constraints and spatial structure information, the two are fused. This can be achieved by semantically aligning the structural design constraints and spatial structure information to obtain input data. This input data is then fed into a pre-trained partitioning generation model to obtain a warehouse partitioning scheme. Specifically, the structural design constraints may include one or more optimization objectives, such as space utilization or picking efficiency. These constraints may include functional requirements constraints, equipment design constraints, and general constraints for each functional partition. The spatial structure information may include spatial data such as dimensions, structure, and constraints. Input data is obtained by fusing the structural design constraints and spatial structure information. This input data, combined with one or more optimization objectives, is then fed into the pre-trained partitioning generation model. The pre-trained model performs multi-objective optimization, automatically weighing various indicators and automatically completing the spatial partitioning, area calculation, and preliminary layout of each functional partition, thereby obtaining the warehouse partitioning scheme. Multimodal fusion makes the input data more complete, and the optimization objectives achieve layout optimization, resulting in a more rational warehouse partitioning scheme.

[0026] In this embodiment of the invention, the input data is obtained by fusing structural design constraints and spatial structural information, including: extracting each first entity and its constraint conditions from the structural design constraints; extracting each second entity and its geometric information from the spatial structural information; matching each first entity with each second entity; fusing the constraint conditions of the matched first entities and the geometric information of the matched second entities to obtain the fusion information of each fused entity; and obtaining the input data based on the fusion information of each fused entity.

[0027] In this embodiment of the invention, when fusing structural design constraints and spatial structure information, an entity recognition model can first be used to extract each first entity from the structural design constraints and each second entity from the spatial structure information. Each first entity and each second entity are then matched, and the successfully matched first or second entity is taken as the fused entity. A large model is used to fuse the constraints of the first entity and the geometric information of the second entity to obtain the fused information of the fused entity. For example, if the structural design constraints include a main channel width ≥ 2.5m and the spatial structure information includes a main channel width attribute of 2.2m, semantic alignment is performed to obtain the fused information: the structural design constraints are a main channel width ≥ 2.5m, and the spatial structure information is a main channel width of 2.2m. A width deviation in the main channel is also marked. This can then be further enhanced and completed based on the warehousing specifications in the warehousing knowledge base to obtain a main channel width ≥ 2.5m to meet the passage requirements of the AGV.

[0028] Then, the input data is obtained based on the fusion information of each fused entity, the constraints of the first entity that failed to match, and the geometric information of the second entity that failed to match. This ensures the integrity of the entity information, making the input data into the partition training model more complete and the resulting warehouse partitioning scheme more reasonable.

[0029] By parsing and multimodal fusion of natural language description information and structured drawing information, users can express their warehouse layout needs through natural language description information and achieve barrier-free human-computer interaction by combining structured civil engineering design drawings.

[0030] In this embodiment of the invention, before generating a warehouse partitioning scheme based on input data, one or more optimization objectives, and a pre-trained partitioning generation model, the method further includes: retrieving warehouse specifications corresponding to the input data from a preset warehouse knowledge base; and enhancing and completing the input data based on the warehouse specifications.

[0031] In this embodiment of the invention, the input data may contain specialized knowledge that needs to be supplemented. For example, the input data may include a cold chain area, but lack the warehousing specifications for that area, which would affect the accuracy of the generated warehouse layout results. Therefore, it is necessary to enhance and supplement the input data with knowledge. Various entities can be identified from the input data. For each entity, the corresponding warehousing specifications can be retrieved from a preset warehousing knowledge base. The retrieved warehousing specifications can then be used to enhance and supplement the entity. For example, based on the preset warehousing knowledge base, specialized knowledge such as the warehousing specifications for the cold chain area, AGV aisle width, and fire safety can be enhanced and supplemented. For instance, if the minimum passage width of an AGV is 2.5m, the main aisle width attribute of 2.2m in the input data can be corrected to 2.5m.

[0032] By automatically retrieving a pre-set warehouse knowledge base, professional knowledge can be supplemented, improving the accuracy and professionalism of the generated warehouse layout results. This pre-set knowledge base can be dynamically adjusted based on industry standards, equipment updates, etc. Specifically, the pre-set knowledge base can be a Retrieval-Augmented Generation (RAG), which can include warehouse specifications, equipment parameters, historical cases, etc. Retrieving the pre-set knowledge base can also obtain the corresponding equipment parameters for the input data, supplementing the input data with these parameters and thus providing support for equipment layout. This embodiment of the invention uses a pre-set warehouse knowledge base to enhance and supplement input data with professional domain knowledge, imposing rule constraints on the warehouse layout, resulting in a more reasonable and standardized generated warehouse layout.

[0033] In this embodiment of the invention, generating the equipment layout for each functional partition based on the partition data and equipment design constraints of the functional partition includes: constructing one or more layout tasks corresponding to the functional partition based on a preset task type; for each layout task, generating the equipment layout corresponding to the layout task based on the equipment design constraints and partition data of the functional partition, wherein the preset task type includes at least one of equipment selection, channel design, or entrance / exit layout.

[0034] In this embodiment of the invention, after obtaining the warehouse zoning plan, an Agent (Autonomous Agent, an intelligent agent with a "planning-execution-feedback" closed loop) can be used to automatically decompose tasks and arrange equipment according to the warehouse zoning plan. Specifically, one or more layout tasks corresponding to functional zones can be constructed based on preset task types. For example, the Agent can automatically decompose the warehouse zoning plan into layout tasks such as equipment selection, channel design, and entrance / exit arrangement. These multiple layout tasks can be executed in a logical order. One or more layout tasks can be constructed for each functional zone. By executing these one or more layout tasks and combining the partition data of the functional zone with the equipment design constraints, the corresponding equipment layout can be obtained. For example, by executing each layout task, equipment selection results, channel design results, and entrance / exit arrangement results can be obtained, thus realizing a detailed equipment layout for the warehouse zoning plan.

[0035] In embodiments of the present invention, such as Figure 2 As shown, structural design constraints indicate one or more optimization objectives for the warehouse layout; the equipment layout corresponding to the layout task is generated based on the equipment design constraints of the functional zones and the zone data, including: Step S201: Input the partition data and device design constraints into the device layout model corresponding to the layout task; Step S202: Use the equipment layout model to call the preset warehouse knowledge base to obtain the equipment information corresponding to the layout task; Step S203: Based on the device information, one or more optimization objectives, and the device layout model, obtain the device layout corresponding to the layout task.

[0036] In this embodiment of the invention, an agent is used to automatically decompose the warehouse zoning scheme into one or more layout tasks. For any layout task of each functional zone, the zoning data and equipment design constraints of that functional zone are input into the equipment layout model corresponding to the layout task. The agent includes the equipment layout model, which can be obtained by fine-tuning a larger model. Then, the equipment layout model calls a preset warehouse knowledge base, automatically selects equipment information from the preset warehouse knowledge base, and generates the equipment layout corresponding to the layout task based on the equipment information, one or more optimization objectives, and the equipment layout model. For the equipment selection task, the equipment information can include the type of each piece of equipment, which can include shelves, AGVs, sorting equipment, fire protection facilities, etc. For the aisle design layout task, the equipment information includes the aisle width. For the entrance and exit layout task, the equipment information can include the number of entrances and exits, etc.

[0037] For complex scenarios involving multiple floors, multiple temperature zones, and multiple operating modes, multiple agents can be used to work together to achieve dynamic collaboration and adaptive adjustment.

[0038] The equipment layout model is trained using the following method: Multiple equipment design constraints and optimization objectives, along with the corresponding equipment layout for each constraint, are obtained. The larger model is then fine-tuned or trained using these constraints and objectives to obtain the equipment layout model. The larger model can be a large language model such as Deepseek or GLM (General Language Model).

[0039] This invention achieves end-to-end warehouse layout generation through a large model-driven approach, improving the design efficiency and effectiveness of warehouse layout and ensuring the consistency and rationality of the layout.

[0040] In this embodiment of the invention, after obtaining the warehouse layout result corresponding to the demand data based on the warehouse zoning scheme and the equipment layout of each functional zone, the method further includes: outputting the warehouse layout result in the form of structured data, drawings and / or natural language description.

[0041] Specifically, after outlining the warehouse zoning plan and the equipment layout for each functional zone, the various functional zones and their respective equipment layouts are integrated to obtain the warehouse layout result. This result can be visualized. The visualization can take the form of structured data, such as JSON or XML format, including data on each functional zone and its equipment layout, facilitating subsequent integration and secondary development. Alternatively, it can be visualized as drawings, outputting the warehouse layout as editable CAD drawings for a more intuitive presentation. Finally, it can be visualized as natural language descriptions, automatically outputting descriptive information for each functional zone and equipment layout for easier management. For example, the output natural language description could be "High-frequency picking area 120m²". 2 Located on the west side of the shipping outlet, it is equipped with 4 sets of automatic sorting racks and an AGV aisle width of 2.5 meters.

[0042] Figure 3This is a flowchart illustrating a warehouse layout generation method according to an embodiment of the present invention. First, the warehouse layout requirements data, including natural language description information and structured drawing information, are obtained. Then, the natural language description information and structured drawing information are input to the parsing module, which parses the obtained structural design constraints and spatial structure information, and merges them to obtain the input data. The knowledge enhancement and retrieval module (RAG) is then invoked to enhance and complete the input data. Next, the enhanced and completed input data is input to the large model partitioning generation module to obtain a warehouse partitioning scheme. Then, an agent is used to decompose tasks and arrange equipment according to the warehouse partitioning scheme to obtain the warehouse layout result. Finally, the output and visualization module outputs the warehouse layout result in the form of structured data, CAD drawings, or natural language descriptions.

[0043] The warehouse layout generation method of this invention first acquires and parses the warehouse layout requirements data. Based on the parsed natural language description information and structured drawing information, a warehouse zoning scheme is obtained. Then, based on the warehouse zoning scheme, the equipment layout of each functional zone is generated, resulting in the warehouse layout. This method parses multimodal requirements data, generates a warehouse zoning scheme based on the parsing results, and then generates the equipment layout based on the warehouse zoning scheme, ultimately obtaining the warehouse layout result. This achieves an end-to-end automated process from multimodal requirements data to warehouse layout results, improving the design efficiency and intelligence level of warehouse layout. The generated warehouse layout is more reasonable, ensuring consistency and optimization, and can meet complex and ever-changing warehouse requirements. It overcomes the problems of low efficiency, poor layout effect, and inability to meet complex and ever-changing warehouse requirements caused by existing warehouse layout methods that rely on manual experience.

[0044] Furthermore, this method, through the parsing and multimodal fusion of natural language description information and structured drawing information, allows users to express their warehouse layout requirements using natural language description information, and achieves barrier-free human-computer interaction by combining structured civil engineering design drawings. Utilizing large models and RAG technology, it automatically generates warehouse zoning schemes and equipment layouts, improving the design efficiency and intelligence level of warehouse layouts. Through agent intelligence, it achieves task decomposition, planning, knowledge retrieval, and dynamic optimization, supporting multi-objective collaboration and adaptive adjustment in complex scenarios. This method provides a warehouse layout generation approach based on large models, realizing an end-to-end automated design process, forming a complete closed loop from requirement input, knowledge enhancement, zoning generation, equipment layout to drawing output.

[0045] According to another aspect of the present invention, a warehouse layout generation apparatus 400 is provided, comprising: Module 401 acquires the warehouse layout requirements data, which includes natural language description information and structured drawing information. The parsing module 402 parses the structural design constraints of the warehouse layout from the natural language description information and the spatial structure information from the structured drawing information; the structural design constraints include the equipment design constraints of each functional area; The partitioning generation module 403 generates a warehouse partitioning scheme based on structural design constraints and spatial structure information; the warehouse partitioning scheme includes each functional partition and the partitioning data of each functional partition; The layout generation module 404 generates the equipment layout for each functional partition based on the partition data and equipment design constraints, so as to obtain the warehouse layout result corresponding to the demand data according to the warehouse partitioning scheme and the equipment layout of each functional partition.

[0046] In this embodiment of the invention, structural design constraints indicate one or more optimization objectives for the warehouse layout. The partition generation module 403 is further used to: fuse the structural design constraints and spatial structure information to obtain input data; and generate a warehouse partitioning scheme based on the input data, one or more optimization objectives, and a pre-trained partition generation model.

[0047] In this embodiment of the invention, the partition generation module 403 is further configured to: extract each first entity and the constraint conditions of each first entity from the structural design constraints; extract each second entity and the geometric information of each second entity from the spatial structure information; match each first entity with each second entity; fuse the constraint conditions of the matched first entity and the geometric information of the second entity to obtain the fusion information of each fused entity; and obtain input data based on the fusion information of each fused entity.

[0048] In this embodiment of the invention, the partition generation module 403 is further configured to: before generating the warehouse partitioning scheme based on the input data, the one or more optimization objectives, and the pre-trained partition generation model, retrieve the warehouse specifications corresponding to the input data from a preset warehouse knowledge base; and enhance and complete the input data based on the warehouse specifications.

[0049] In this embodiment of the invention, the layout generation module 404 is further configured to: construct one or more layout tasks corresponding to functional partitions based on preset task types; for each layout task, generate the equipment layout corresponding to the layout task according to the equipment design constraints and partition data of the functional partition, wherein the preset task type includes at least one of equipment selection, channel design or entrance / exit layout.

[0050] In this embodiment of the invention, structural design constraints indicate one or more optimization objectives for the warehouse layout; the layout generation module 404 is further configured to: input partition data and equipment design constraints into the equipment layout model corresponding to the layout task; call a preset warehouse knowledge base through the equipment layout model to obtain equipment information corresponding to the layout task; and obtain the equipment layout corresponding to the layout task based on the equipment information, one or more optimization objectives, and the equipment layout model.

[0051] In this embodiment of the invention, the layout generation module 404 is further configured to: after obtaining the warehouse layout result corresponding to the demand data according to the warehouse zoning scheme and the equipment layout of each functional zone, output the warehouse layout result in the form of structured data, drawings and / or natural language description.

[0052] According to another aspect of the present invention, an electronic device is provided, comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the warehouse layout generation method of the present invention.

[0053] According to another aspect of the present invention, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the warehouse layout generation method of the present invention.

[0054] Figure 5 An exemplary system architecture 500 is shown that can be applied to the warehouse layout generation method or warehouse layout generation apparatus of the present invention.

[0055] like Figure 5 As shown, system architecture 500 may include terminal devices 501, 502, and 503, a network 504, and a server 505. Network 504 serves as the medium for providing communication links between terminal devices 501, 502, and 503 and server 505. Network 504 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0056] Users can use terminal devices 501, 502, and 503 to interact with server 505 via network 504 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 501, 502, and 503, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0057] Terminal devices 501, 502, and 503 can be various electronic devices with displays that support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0058] Server 505 can be a server that provides various services, such as a backend management server that supports shopping websites browsed by users using terminal devices 501, 502, and 503 (for example only). The backend management server can analyze and process data such as received product information query requests, and feed back the processing results (such as target push information and product information - for example only) to the terminal devices.

[0059] It should be noted that the warehouse layout generation method provided in this embodiment of the invention is generally executed by server 505, and correspondingly, the warehouse layout generation device is generally set in server 505.

[0060] It should be understood that Figure 5 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0061] The following is for reference. Figure 6 It shows a schematic diagram of the structure of a computer system 600 suitable for implementing a terminal device of the present invention. Figure 6 The terminal device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0062] like Figure 6 As shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 602 or programs loaded from storage section 608 into random access memory (RAM) 603. The RAM 603 also stores various programs and data required for the operation of the system 600. The CPU 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0063] The following components are connected to I / O interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to I / O interface 605 as needed. A removable medium 611, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 610 as needed so that computer programs read from it can be installed into storage section 608 as needed.

[0064] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 609, and / or installed from removable medium 611. When the computer program is executed by central processing unit (CPU) 601, it performs the functions defined above in the system of this invention.

[0065] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0066] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0067] The modules described in the embodiments of the present invention can be implemented in software or hardware. The described modules can also be housed in a processor; for example, a processor can be described as including an acquisition module, a parsing module, a partition generation module, and a layout generation module. The names of these modules do not necessarily limit the module itself; for example, the acquisition module can also be described as "a module for acquiring warehouse layout requirement data".

[0068] In another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or it may exist independently and not assembled into the device. The computer-readable medium carries one or more programs, which, when executed by the device, cause the device to include: acquiring warehouse layout requirement data, the requirement data including natural language description information and structured drawing information; parsing structural design constraints from the natural language description information and parsing spatial structure information from the structured drawing information; the structural design constraints including equipment design constraints for each functional area; generating a warehouse zoning scheme based on the structural design constraints and spatial structure information; the warehouse zoning scheme including each functional area and partition data for each functional area; and for each functional area, generating an equipment layout for each functional area based on the partition data and equipment design constraints, so as to obtain a warehouse layout result corresponding to the requirement data based on the warehouse zoning scheme and the equipment layout of each functional area.

[0069] According to the technical solution of the present invention, the warehouse layout generation method of the present invention first obtains and parses the warehouse layout requirement data, obtains a warehouse zoning scheme based on the parsed natural language description information and structured drawing information, and then generates the equipment layout of each functional zone based on the warehouse zoning scheme, thereby obtaining the warehouse layout result. This method parses multimodal requirement data, generates a warehouse zoning scheme based on the parsing results, and then generates the equipment layout based on the warehouse zoning scheme, thereby obtaining the warehouse layout result. This achieves an end-to-end automated process from multimodal requirement data to warehouse layout result, improving the design efficiency and intelligence level of warehouse layout, making the generated warehouse layout more reasonable, ensuring layout consistency and optimization, and meeting complex and ever-changing warehouse requirements. It overcomes the problems of low efficiency, poor layout effect, and difficulty in meeting complex and ever-changing warehouse requirements caused by existing warehouse layout methods that rely on manual experience.

[0070] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for generating warehouse layouts, characterized in that, include: Obtain warehouse layout requirements data, including natural language description information and structured drawing information; Structural design constraints are parsed from the natural language description information, and spatial structure information is parsed from the structured drawing information; The structural design constraints include the equipment design constraints for each functional zone; A warehouse zoning scheme is generated based on the structural design constraints and the spatial structure information; The warehouse zoning scheme includes various functional zones and the zoning data for each functional zone; For each functional zone, the equipment layout of each functional zone is generated based on the partition data and equipment design constraints, so as to obtain the warehouse layout result corresponding to the demand data according to the warehouse partitioning scheme and the equipment layout of each functional zone.

2. The method according to claim 1, characterized in that, The structural design constraints indicate one or more optimization objectives for the warehouse layout. A warehouse zoning scheme is generated based on the structural design constraints and the spatial structure information, including: The structural design constraints and the spatial structure information are fused to obtain the input data; The warehouse partitioning scheme is generated based on the input data, one or more optimization objectives, and a pre-trained partitioning generation model.

3. The method according to claim 2, characterized in that, The structural design constraints and the spatial structure information are fused to obtain input data, including: Extract each first entity and the constraint conditions of each first entity from the structural design constraints, and extract each second entity and the geometric information of each second entity from the spatial structure information; Each first entity is matched with each second entity, and the constraints of the successfully matched first entity and the geometric information of the second entity are fused to obtain the fusion information of each fused entity. The input data is obtained based on the fusion information of each fused entity.

4. The method according to claim 2, characterized in that, Before generating the warehouse partitioning scheme based on the input data, the one or more optimization objectives, and the pre-trained partitioning generation model, the method further includes: Retrieve the warehousing specifications corresponding to the input data from the preset warehousing knowledge base; The input data is enhanced and completed based on the aforementioned warehousing specifications.

5. The method according to claim 1, characterized in that, Based on the partition data of the functional partitions and the device design constraints, the device layout for each functional partition is generated, including: One or more layout tasks corresponding to the functional partitions are constructed based on preset task types; For each layout task, the equipment layout corresponding to the layout task is generated based on the equipment design constraints of the functional partition and the partition data. The preset task type includes at least one of equipment selection, channel design or entrance / exit layout.

6. The method according to claim 5, characterized in that, The structural design constraints indicate one or more optimization objectives for the warehouse layout; Generate the device layout corresponding to the layout task based on the device design constraints of the functional partitions and the partition data, including: The partition data and the device design constraints are input into the device layout model corresponding to the layout task; The equipment layout model is used to call a preset warehouse knowledge base to obtain the equipment information corresponding to the layout task; Based on the device information, the one or more optimization objectives, and the device layout model, the device layout corresponding to the layout task is obtained.

7. The method according to claim 1, characterized in that, After obtaining the warehouse layout result corresponding to the demand data based on the warehouse zoning scheme and the equipment layout of each functional zone, the method further includes: outputting the warehouse layout result in the form of structured data, drawings and / or natural language description.

8. A warehouse layout generation device, characterized in that, include: The acquisition module acquires warehouse layout requirement data, which includes natural language description information and structured drawing information. The parsing module parses the structural design constraints of the warehouse layout from the natural language description information and parses the spatial structure information from the structured drawing information; The structural design constraints include the equipment design constraints for each functional zone; The partitioning generation module generates a warehouse partitioning scheme based on the structural design constraints and the spatial structure information; the warehouse partitioning scheme includes each functional partition and partitioning data for each functional partition; The layout generation module generates the equipment layout for each functional partition based on the partition data and equipment design constraints of the functional partition, so as to obtain the warehouse layout result corresponding to the demand data according to the warehouse partitioning scheme and the equipment layout of each functional partition.

9. An electronic device, characterized in that, include: One or more processors; 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 method as described in any one of claims 1-7.

10. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-7.

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