A processing method for arranging power material shelves

Abstract

The present application relates to the technical field of power material warehouse management, and particularly relates to a processing method for power material shelf arrangement, which converts the space clustering problem of similar shelves into a linear site selection problem of rectangular regions; including obtaining the length, width, quantity and inter-shelf gap, inter-row interval and other parameters of a certain type of shelf; then enumerating the surrounding regions formed under various centralized arrangement modes such as horizontal arrangement, length-width interchanging and 90-degree rotation, and calculating the length and width of each region; then normalizing and deduplicating all candidate regions to obtain a structured clustering layout scheme set; finally, taking the set as discrete candidate input, embedding a three-dimensional space layout optimization model, and realizing the integrated optimization of the overall allocation of similar shelves and the warehouse space. The present application converts the semantic rule of "similar centralized storage" into a computable geometric constraint, which significantly improves the automation level, space utilization rate and engineering feasibility of the power material warehouse layout.

Description

Technical Field

[0001] This invention relates to the field of power material storage management technology, and in particular to a method for arranging power material shelves. Background Technology

[0002] In power system warehouse management, to improve the efficiency of material storage and retrieval and the standardization of management, it is usually required that "similar materials be stored together". This requirement is essentially a spatial clustering problem. However, traditional clustering algorithms (such as K-Means, hierarchical clustering, etc.) output abstract point sets and lack clear geometric boundaries, making it difficult to directly embed them as constraints into subsequent warehouse layout optimization models (such as 3D packing models, mixed integer linear programming models).

[0003] On the other hand, while existing warehouse layout optimization models can efficiently handle the spatial arrangement of rectangular objects, their input objects must have defined dimensions. If each shelf is modeled separately, the business rule of "grouping similar items together" cannot be reflected; if clustering areas are manually defined, it relies on experience, is difficult to adapt to dynamic inventory changes, and cannot achieve end-to-end optimization.

[0004] Therefore, there is an urgent need for a technical solution that can structure the clustering results of similar shelves into a set of compact rectangular regions, so that the clustering process can be identified and optimized by mathematical models, thereby bridging the gap between "semantic clustering" and "geometric layout". Summary of the Invention

[0005] In view of this, the purpose of this invention is to propose a method for processing the layout of power material shelves, so as to solve the problem that the abstract grouping results output by traditional clustering algorithms cannot be directly embedded as geometric constraints into the three-dimensional warehouse layout optimization model.

[0006] To achieve the above objectives, this invention provides a method for processing the layout of power material shelving, which transforms the spatial clustering problem of similar shelving into a linear location problem of rectangular regions, comprising the following steps:

[0007] S1. Obtain shelf layout parameters, the parameters including the first... Single unit length of power supply rack ,width and total quantity and shelf gaps and row spacing ;

[0008] S2. Based on the above parameters, compare the number of rows of shelves traversed. To enumerate the multiple enclosed areas formed by this type of shelving under different centralized arrangement methods, where the length and width of each enclosed area are calculated by geometric accumulation;

[0009] S3. Perform integration and deduplication operations on the multiple enclosing regions to obtain a set of all feasible clustering layout schemes for this type of shelving.

[0010] S4. The clustering layout scheme set is used as discrete candidate input and embedded into a three-dimensional spatial layout optimization model to achieve integrated optimization of the overall allocation of similar shelves and storage space.

[0011] Preferably, in step S2, enumerating different centralized arrangement methods includes the following steps:

[0012] S2.1, Iterate through the number of shelves in each row. In order to obtain multiple feasible layout forms of this type of shelf in the horizontal arrangement mode;

[0013] S2.2, for each Calculate the size of the enclosed area formed by the horizontal arrangement of this type of shelving, thereby generating multiple candidate horizontal arrangement schemes;

[0014] Wherein, the length of the enclosing region is ;

[0015] The total number is Each row If there are 1, then the number of rows is: The number of remaining shelves is: ;

[0016] in, The length of a single shelf, The width of a single shelf. The installation clearance between adjacent shelves in the same row. This refers to the spacing between two rows of back-to-back shelves.

[0017] Preferably, in step S2.2:

[0018] like and If the number is even, then all shelves can be arranged back-to-back, and the width of the enclosed area is:

[0019] ;

[0020] Otherwise, if there are unpaired single-row shelves, the width of the enclosing rectangle is:

[0021] .

[0022] Preferably, in step S2, the enumeration of different centralized arrangement methods further includes:

[0023] Based on the horizontal arrangement, more enclosing regions are generated by changing the direction, specifically including the following operations:

[0024] S2.3 Perform a horizontal arrangement calculation based on the original dimensions of the shelf to obtain a set of candidate horizontal arrangement schemes;

[0025] S2.4 After swapping the length and width of the individual shelving units, perform a horizontal arrangement calculation to obtain a set of vertical arrangement candidate schemes;

[0026] S2.5. For each enclosed region in the horizontally arranged candidate scheme and the vertically arranged candidate scheme, generate its 90-degree rotation form respectively.

[0027] Preferably, step S3 includes the following steps:

[0028] S3.1. Merge the original schemes with their rotated forms to form an initial set of candidate schemes;

[0029] S3.2. For each enclosing region in the initial candidate scheme set, uniformly represent it in a form where its length is not less than its width, and remove duplicates to obtain the final clustering layout scheme.

[0030] Preferably, in step S4, the three-dimensional spatial layout optimization model is a mixed integer linear programming model or a three-dimensional packing model with channel constraints, wherein each similar shelf group must be assigned as a whole to a certain enclosing area in the clustering layout scheme, thereby transforming the clustering semantic constraints into geometric layout constraints.

[0031] Preferably, the shelf gap The row spacing is used to meet installation tolerances, maintenance space, or collision avoidance requirements between adjacent shelves. The width of the back-to-back passageway required to meet the needs of equipment operation, personnel passage or heat dissipation.

[0032] The beneficial effects of this invention are as follows:

[0033] I. Achieving a structured representation of clustering results: Transforming the abstract grouping output by traditional clustering algorithms into a series of compact enclosing regions with clear geometric dimensions (length and width), enabling the business rule of "storing similar clusters together" to have a quantifiable spatial form, and bridging the semantic gap between semantic information and geometric layout.

[0034] 2. Seamless integration of support and optimization models: The generated clustering layout scheme can be directly embedded as discrete candidate variables or hard constraints into mainstream warehouse optimization frameworks such as mixed integer linear programming (MILP) models and three-dimensional packing models with channel constraints, realizing end-to-end automated decision-making from "clustering" to "layout" and avoiding suboptimal solutions caused by manual intervention.

[0035] III. Feasible layout method for comprehensive coverage project: by traversing the number of shelves in each row. It distinguishes between "full pairing back-to-back" and "including single row" scenarios, accurately modeling the compact arrangement logic in actual warehousing; at the same time, it introduces the interchangeability of shelf length and width and 90-degree rotation expansion, exhaustively listing all feasible layouts under orthogonal directions, significantly improving the diversity and practicality of the solutions.

[0036] IV. Explicitly Incorporating Physical Installation Constraints: Explicitly include rack clearances in the calculation of the enclosed area dimensions. (For collision avoidance and maintenance) and row spacing (For operation and heat dissipation) Ensure that each generated candidate solution meets the safety requirements for engineering installation and operation, and avoid layouts that are theoretically feasible but not practically feasible.

[0037] V. Improve warehouse space utilization efficiency and management standardization: By strictly limiting similar materials to a single compact rectangular area, not only is the management chaos caused by material dispersion reduced, but it also facilitates forklift path planning and aisle design, thereby maximizing warehouse space utilization and operational efficiency while ensuring operational safety. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a schematic diagram of the main steps of the present invention;

[0040] Figure 2 For the present invention Figure 1 A flowchart illustrating the sub-steps. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0042] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this invention should have the ordinary meaning understood by those skilled in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0043] like Figure 1 , Figure 2 As shown, a method for arranging power material shelving is used to transform the spatial clustering problem of similar shelving into a linear location problem of rectangular regions, including the following steps:

[0044] S1. Obtain shelf layout parameters, the parameters including the first... Single unit length of power supply rack ,width and total quantity and shelf gaps and row spacing ;

[0045] This step aims to collect all physical and operational parameters that affect the layout of the shelving, providing basic data for subsequent calculations.

[0046] Monomer length and width : refers to the External dimensions of power supply racks in standard installation condition (unit: meters);

[0047] Total quantity : The total number of this type of shelf in the current warehouse;

[0048] Shelf gap The minimum installation clearance between two adjacent shelves in the same row, used to meet installation tolerances, maintenance operations, or prevent collisions, typically 0.05-0.2 meters;

[0049] Row spacing When two rows of shelves are placed back to back, the width of the physical aisle between them is reserved for equipment passage, heat dissipation, or personnel operation, with a typical value of 0.2-0.5 meters.

[0050] S2. Based on the above parameters, enumerate the multiple enclosed areas formed by this type of shelving under different centralized arrangement methods. The length and width of each enclosed area are calculated by geometric accumulation, representing a feasible compact arrangement of similar shelving.

[0051] This step is the core innovation of the present invention. Its goal is to exhaustively list all engineering-feasible centralized arrangement forms of similar shelving units and represent each form as an axis-aligned rectangular area (i.e., the "enclosed area").

[0052] In step S2, enumerating different centralized arrangement methods includes the following steps:

[0053] S2.1, Iterate through the number of shelves in each row. Simulate each emission The arrangement patterns of each shelf are determined to obtain multiple feasible layout forms of this type of shelf in the horizontal arrangement mode.

[0054] S2.2, for each Calculate the size of the enclosed area formed by the horizontal arrangement of this type of shelving, thereby generating multiple candidate horizontal arrangement schemes;

[0055] length The formula is ;

[0056] Number of rows decomposition: Total number of rows is Each row If there are 1, then the complete number of rows is: The remaining number of shelves (remainder) is: ;

[0057] in, The length of a single shelf, The width of a single shelf. The installation clearance between adjacent shelves in the same row. This refers to the spacing between two rows of back-to-back shelves.

[0058] width Based on whether complete pairing is possible, there are two scenarios:

[0059] Case A (Full Pairing): If and If the number is even, it means that all shelves can be arranged in pairs back to back, with no single rows. Therefore, the width of the enclosed area is:

[0060] ;

[0061] Case B (including single row): If or If the number is odd, then there exists an unpaired single-row shelf with a bounding rectangle of the width:

[0062] .

[0063] To cover more feasible solutions, directional freedom is further introduced:

[0064] Based on the horizontal arrangement, more enclosing regions are generated by changing the direction, specifically including the following operations:

[0065] S2.3 Perform a horizontal arrangement calculation based on the original dimensions of the shelf to obtain a set of candidate horizontal arrangement schemes;

[0066] S2.4 Vertical Arrangement: Interchange the length and width of the individual shelving units (i.e., using...) For length, (where the width is 1), perform the above horizontal arrangement calculation again to obtain a set of vertical candidate schemes;

[0067] S2.5, 90-degree rotation form: For each enclosing region in the original horizontal and vertical candidate schemes. Generate its 90-degree rotation form This is to cover all possible layouts in all orthogonal directions.

[0068] S3. Integrate and deduplicate the multiple surrounding areas to obtain all feasible clustering layout schemes for this type of shelving;

[0069] Step S3 includes the following steps:

[0070] S3.1. Merge the original schemes with their rotated forms to form an initial set of candidate schemes;

[0071] S3.2. For each enclosing region in the initial candidate scheme set, uniformly represent it in a form where its length is not less than its width, and remove duplicates to obtain the final clustering layout scheme.

[0072] Since orientation transformations may produce repetitive or symmetrical rectangles (e.g., (4,3) and (3,4) are equivalent after rotation), standardization is required.

[0073] Merge: Merge all candidate enclosed regions, including the original scheme, rotation scheme, horizontal arrangement, and vertical arrangement, into an initial candidate scheme set;

[0074] Standardization: For each rectangle It is uniformly represented as having a length that is not less than its width, i.e., converted to ;

[0075] Deduplication: Remove rectangles with exactly the same size, keeping only the unique ones.

[0076] S4. The clustering layout scheme is used as a structural candidate input and fused with the three-dimensional spatial layout optimization model to achieve overall optimization of the power material storage space.

[0077] In step S4, the three-dimensional spatial layout optimization model is a mixed integer linear programming model or a three-dimensional packing model with channel constraints, wherein each similar shelf group must be assigned as a whole to a certain enclosing area in the clustering layout scheme, thereby transforming the clustering semantic constraints into geometric layout constraints.

[0078] The final set of clustered layout schemes is used as a discrete candidate variable set and embedded into the high-level layout optimization model:

[0079] Each scheme represents a "clustering unit", and the model decides "which rectangle to select for this type of shelf".

[0080] Constraints include: non-overlapping areas, interconnected passageways, and warehouse boundary restrictions;

[0081] The objective function can be: minimizing warehouse space occupied, maximizing space utilization, minimizing transport distance, etc.

[0082] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention is limited to these examples; within the framework of the invention, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity.

[0083] The embodiments of this invention are intended to cover all such substitutions, modifications, and variations falling within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., 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 processing the layout of power material shelving, used to transform the spatial clustering problem of similar shelving into a linear location problem of rectangular regions, characterized in that, Includes the following steps: S1. Obtain shelf layout parameters, the parameters including the first... Single unit length of power supply rack ,width and total quantity and shelf gaps and row spacing ; S2. Based on the above parameters, compare the number of rows of shelves traversed. To enumerate the multiple enclosed areas formed by this type of shelving under different centralized arrangement methods, where the length and width of each enclosed area are calculated by geometric accumulation; In step S2, enumerating different centralized arrangement methods includes the following steps: S2.1, Iterate through the number of shelves in each row. In order to obtain multiple feasible layout forms of this type of shelf in the horizontal arrangement mode; S2.2, for each Calculate the size of the enclosed area formed by the horizontal arrangement of this type of shelving, thereby generating multiple candidate horizontal arrangement schemes; Wherein, the length of the enclosing region is ; The total number is Each row If there are 1, then the number of rows is: The number of remaining shelves is: ; in, The length of a single shelf, The width of a single shelf. The installation clearance between adjacent shelves in the same row. The spacing between two rows of back-to-back shelves; In step S2.2: like and If the number is even, then all shelves can be arranged back-to-back, and the width of the enclosed area is: ； Otherwise, if there are unpaired single-row shelves, the width of the enclosing rectangle is: ； In step S2, the enumeration of different centralized arrangement methods also includes: Based on the horizontal arrangement, more enclosing regions are generated by changing the direction, specifically including the following operations: S2.3 Perform a horizontal arrangement calculation based on the original dimensions of the shelf to obtain a set of candidate horizontal arrangement schemes; S2.4 After swapping the length and width of the individual shelving units, perform a horizontal arrangement calculation to obtain a set of vertical arrangement candidate schemes; S2.

5. For each enclosing region in the horizontally arranged candidate scheme and the vertically arranged candidate scheme, generate its 90-degree rotation form respectively; S3. Perform integration and deduplication operations on the multiple enclosing regions to obtain a set of all feasible clustering layout schemes for this type of shelving. S4. The clustering layout scheme set is used as discrete candidate input and embedded into a three-dimensional spatial layout optimization model to achieve integrated optimization of the overall allocation of similar shelves and storage space.

2. The method for arranging power material shelving according to claim 1, characterized in that, Step S3 includes the following steps: S3.

1. Merge the original schemes with their rotated forms to form an initial set of candidate schemes; S3.

2. For each enclosing region in the initial candidate scheme set, uniformly represent it in a form where its length is not less than its width, and remove duplicates to obtain the final clustering layout scheme.

3. The method for arranging power material shelving according to claim 1, characterized in that, In step S4, the three-dimensional spatial layout optimization model is a mixed integer linear programming model or a three-dimensional packing model with channel constraints, wherein each similar shelf group must be assigned as a whole to a certain enclosing area in the clustering layout scheme, thereby transforming the clustering semantic constraints into geometric layout constraints.

4. The method for arranging power material shelving according to claim 1, characterized in that, The shelf gap The row spacing is used to meet installation tolerances, maintenance space, or collision avoidance requirements between adjacent shelves. The width of the back-to-back passageway required to meet the needs of equipment operation, personnel passage or heat dissipation.

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