An intelligent warehouse scheduling method based on dynamic library position weight allocation

Abstract

The application discloses an intelligent warehouse scheduling method based on dynamic library weight distribution, comprising: obtaining the volume parameter and weight parameter of the warehousing goods, calculating the volume occupation degree and weight occupation degree respectively, and distributing the warehousing weight value of the goods according to the value, which is positively correlated with the expected moving difficulty of the goods when the goods are discharged; obtaining the layout information of the warehouse area and the idle state of each library, if the weight value is higher than the set grading value, the idle library position of the bottom layer and adjacent peripheral channel is determined as the target library position area, otherwise, the idle library position of the non-bottom layer or far from the peripheral channel is determined as the target library position area; the idle library position in the target library position area is distributed as the warehousing storage library position, and the identification information is output. The application distributes the library position according to the volume and weight of the goods, so that the heavy goods are concentrated in the bottom layer and the light goods are stored in the internal, the layout of the warehouse area is optimized in the warehousing stage, the round distance of the handling equipment when the goods are discharged is reduced, and the warehousing operation efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent storage scheduling technology, and in particular to an intelligent storage scheduling method based on dynamic storage location weight allocation. Background Technology

[0002] Intelligent warehousing systems are the core hub of modern logistics operations, and the quality of warehouse scheduling methods directly determines the overall efficiency of goods turnover and operating costs. In large-scale intelligent warehousing scenarios, warehouse scheduling typically requires collaborative operation with lifting equipment (such as overhead cranes, stacker cranes, AGVs, and other handling equipment). Lifting equipment undertakes the critical handling functions of goods entering and leaving the warehouse. The rationality of the warehouse scheduling method directly affects the operating path length, empty-run rate, and overall energy consumption of the lifting equipment, playing an irreplaceable and crucial role in supply chain management.

[0003] Currently, some existing technologies have proposed methods for allocating storage locations based on cargo attributes to address the problem of warehouse space allocation. For example, some solutions calculate space allocation coefficients based on the type, volume, and weight of goods, dividing the warehouse into different storage units and sub-storage areas, so that goods are allocated to corresponding storage areas according to their physical characteristics. Other solutions construct multi-objective optimization functions that consider both the frequency of goods leaving the warehouse and the weight of goods to obtain the optimal storage location allocation result. These technical solutions have improved the utilization efficiency of warehouse space to some extent, lowered the center of gravity of the shelves, or reduced the handling distance of some goods.

[0004] However, the aforementioned existing technologies share a common cognitive flaw when addressing the warehouse location allocation problem: they all treat location allocation as an isolated, static optimization problem, focusing only on where the goods should be placed at present, without incorporating the impact of this allocation on future outbound operation efficiency into a unified consideration framework. Specifically, when large and heavy goods are allocated to higher levels or deeper into the warehouse, although the goods may not exhibit obvious irrationality during the inbound phase, during the subsequent outbound phase, when the lifting equipment needs to move from its current location to the location of the goods for retrieval, it will inevitably encounter physical obstacles along the way due to space occupied by other stored goods. This forces the lifting equipment to frequently detour, slow down, or change its planned route. This disconnect between inbound and outbound scheduling logic results in the actual travel distance of the lifting equipment when performing outbound tasks being far greater than the theoretical minimum distance, leading to a high empty-run rate, significantly increased energy consumption and time costs, and severely restricting the overall throughput efficiency of the warehousing system. Summary of the Invention

[0005] Therefore, the technical problem to be solved by this invention is to overcome the shortcomings of existing technologies, such as the disconnect between inbound and outbound operations, and the failure to incorporate the impact of the physical properties of goods on the difficulty of future outbound movement into unified scheduling considerations. This results in heavy goods being randomly scattered and stored in different areas of the warehouse, and the lifting equipment having to frequently detour around the spatial obstacles created by the heavy goods during outbound operations, leading to increased ineffective travel distances, high equipment idle rates, and low overall warehousing efficiency. The invention provides an intelligent warehouse scheduling method based on dynamic storage location weight allocation. By dynamically allocating storage locations according to the volume and weight of goods, heavy goods are concentrated on the outer perimeter of the bottom layer, while light goods are stored inside. This optimizes the spatial layout of the warehouse area in advance during the inbound stage, reduces the detour distance of handling equipment during outbound operations, and improves warehousing efficiency.

[0006] To address the aforementioned technical problems, this invention provides an intelligent storage scheduling method based on dynamic storage location weight allocation, comprising the following steps: Obtain the volume and weight parameters of the goods entering the warehouse; Based on volume and weight parameters, calculate the volume occupancy of goods on the storage space and the weight occupancy of goods on the storage space's load-bearing capacity, respectively. Based on volume and weight occupancy, inbound weight values ​​are assigned to goods. Inbound weight values ​​are used to characterize the placement priority of goods in the warehouse area. The placement priority is positively correlated with the expected difficulty of moving goods when they are moved out of the warehouse. Obtain the current storage location layout information of the current storage area and the current availability status of each storage location; Based on the inbound weight value, the corresponding target storage location area is matched for the goods in the storage location layout information, where: If the inbound weight value is higher than the set grading value, then the vacant storage space located at the bottom layer and adjacent to the outer passage will be identified as the target storage space area. If the weight value of the warehouse entry is not higher than the set grade value, then the vacant warehouse locations that are not at the bottom layer or far from the outer passage will be identified as the target warehouse location area. The available storage locations in the target storage area are matched and assigned as storage locations for goods entering the warehouse, and the storage location identification information of the storage locations is output.

[0007] In one embodiment of the present invention, the volume occupancy of goods on the storage space is calculated as follows: obtain the standard volume value V0 of a single storage space in the storage area, and calculate the volume occupancy R according to the following formula. V :R V =V / V0, where V is the volume parameter; the weight occupancy rate of goods affecting the storage location's load-bearing capacity is calculated as follows: obtain the rated load-bearing value W0 of a single storage location in the storage area, and calculate the weight occupancy rate R according to the following formula. W :R W =M / W0, where M is the weight parameter.

[0008] In one embodiment of the present invention, the inbound weight value Q is calculated according to the following formula: Q=R V ·R W ·f; Where f is the historical outbound frequency coefficient of goods, and the historical outbound frequency coefficient f is determined as follows: Get the total number of times N goods left the warehouse within a preset historical time period, and get the average number of times N goods left the warehouse. a The historical outbound frequency coefficient f is calculated according to the following formula: f = 1 + N / N a .

[0009] In one embodiment of the present invention, the inbound weight value Q is calculated according to the following formula: Q=R V ·R W ·(1+C / C t ); Where C represents the number of currently congested passages in the area at the bottom level and adjacent to the outer passages. t The total number of passages in the area that is at the bottom level and adjacent to the outer passages.

[0010] In one embodiment of the present invention, the set grading value is determined in the following manner: Obtain the total number S of storage locations on the bottom floor of the warehouse area that are adjacent to the outer passageway, and obtain the proportion P of heavy goods arriving in the historical inbound records of the warehouse area. The volume occupancy of heavy goods is R. V and weight occupancy R W Goods with values ​​greater than 0.5; The set grade value Q0 is calculated using the following formula: ; Among them, R Vavg R is the average volume occupancy of all goods in historical inbound records. Wavg is the average weight occupancy of all goods in the historical inbound records, and N is the total quantity of heavy goods in the historical inbound records.

[0011] In one embodiment of the present invention, the reservoir layout information includes a three-dimensional spatial grid map of the reservoir, wherein each grid cell in the three-dimensional spatial grid map is labeled with floor height coordinates and passage distance coordinates. In a 3D spatial grid map, filter all grid cells whose layer height coordinates are equal to the minimum layer height coordinates to form the bottom layer cell set; In the bottom cell set, filter the grid cells whose channel distance coordinate value is less than the set channel distance coordinate value, and use them as the set of adjacent outer channel cells; In the set of cells adjacent to the outer channel, filter the grid cells whose storage location occupancy status is marked as free to form a candidate storage location cell set.

[0012] In one embodiment of the present invention, a detection sensor is provided at each storage location to determine whether there are goods in the storage location and generate a storage location occupancy status identifier.

[0013] In one embodiment of the present invention, when there are multiple vacant storage locations in the target storage location area, the planar coordinates of the current inlet are obtained in the three-dimensional spatial grid map, the planar coordinates of each vacant storage location in the target storage location area are obtained, the distance between each vacant storage location and the inlet is calculated, and the vacant storage location with the smallest distance is selected as the storage location for inlet storage.

[0014] In one embodiment of the present invention, when the inbound weight value is higher than the set grading value, and the number of all vacant storage locations in the storage area located at the bottom layer and adjacent to the outer passage is zero, the vacant storage locations located at the bottom layer and far from the outer passage in the storage area are determined as candidate target storage locations, and specific vacant storage locations in the candidate target storage locations are allocated as inbound storage locations.

[0015] In one embodiment of the present invention, the specific method for outputting the storage location identifier information of the inbound and outbound storage locations is as follows: Combine the storage location number and storage location coordinates into a storage location identifier data packet; The storage location identifier data packet is sent to the inbound task queue of the warehouse management system, serving as the destination address for the handling equipment to perform inbound handling tasks.

[0016] The technical solution of the present invention has the following advantages compared with the prior art: The intelligent warehouse scheduling method based on dynamic storage location weight allocation described in this invention dynamically evaluates the volume and weight of goods and considers their impact on the difficulty of future outbound movement, assigning goods with placement priority based on their inbound weight value. This method prioritizes goods with high inbound weight values ​​for placement in storage locations on the lower level and near external aisles, while allocating goods with lower weight values ​​to other areas. This effectively avoids placing bulky and heavy goods in the upper levels of the warehouse or deep within aisles, thereby reducing the need for cranes to detour, slow down, or change routes due to physical obstacles when performing outbound tasks. This reduces actual travel distance and empty-run rate, ultimately improving the overall throughput efficiency of the warehousing system and reducing operating energy consumption and time costs. Attached Figure Description

[0017] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings, wherein: Figure 1 This is a flowchart of the steps of the intelligent storage scheduling method based on dynamic storage location weight allocation of the present invention; Figure 2 This invention is a three-dimensional spatial grid. Figure 3 Flowchart of the steps for layer filtering rules; Figure 3 This is a flowchart of the steps in this invention to select the available storage location closest to the inlet. Figure 4 This is a flowchart of the steps in the degradation allocation rule when candidate storage slots are exhausted in this invention. Detailed Implementation

[0018] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0019] Reference Figure 1 As shown, this invention provides an intelligent warehouse scheduling method based on dynamic warehouse location weight allocation. First, the volume and weight parameters of the incoming goods are obtained, and then the volume occupancy and weight occupancy are calculated based on these two parameters. The volume occupancy reflects the degree to which the goods occupy the warehouse space, while the weight occupancy reflects the degree to which the goods affect the warehouse's carrying capacity.

[0020] Based on this, the present invention combines volume occupancy and weight occupancy to assign an warehousing weight value to each item of goods entering the warehouse. This warehousing weight value is not an abstract mathematical score; its physical meaning is explicitly assigned as being positively correlated with the expected difficulty of moving the goods when they are being handled out of the warehouse. In other words, the larger and heavier the goods are, the greater the handling resistance they need to overcome and the more difficult they are to move when leaving the warehouse, and therefore they are given a higher warehousing weight value.

[0021] After assigning weights, this invention obtains real-time warehouse location layout information and the vacancy status of each location in the current warehouse area, and performs differentiated location matching based on the weight value of the incoming goods. If the weight value is higher than the set threshold, it indicates that the goods are large-volume, heavy-duty goods, which are difficult to move when leaving the warehouse and require a lot of passage space. Therefore, they are allocated to vacant warehouse locations on the ground floor and near the outer passage. These warehouse locations have the physical advantages of not requiring lifting equipment, being close to the warehouse exit, and having wide and unobstructed passages, which can minimize the lifting stroke and detour distance of the lifting equipment when leaving the warehouse. Conversely, if the weight value is not higher than the set threshold, it indicates that the goods are small in size or light in weight, and are relatively easy to move when leaving the warehouse, without significantly obstructing the passage space. Therefore, they are allocated to internal warehouse locations that are not on the ground floor or far from the outer passage, reserving the high-quality warehouse location resources on the ground floor and outer perimeter for heavier goods that need them more.

[0022] In principle, the reason why the above-mentioned technical solution of this invention can solve the problem of the separation between warehousing and outbound operations lies in the establishment of a linkage mechanism that pre-plans warehousing allocation to facilitate outbound operations. Specifically, this invention does not treat warehousing allocation as an isolated decision, but rather predicts the difficulty of moving the goods when they are to be outbound at the moment of warehousing, and determines their storage location accordingly. Heavy goods are concentrated on the outer perimeter of the bottom floor, forming a regular spatial layout of heavier items on the outside and lighter items on the inside within the warehouse area. Under this layout, when any heavy goods need to be outbound, the lifting equipment does not need to go deep into the warehouse area, ascend to higher floors, or navigate through narrow passages; it can quickly complete the retrieval operation on the outer bottom floor. Even if small, lightweight ordinary goods are located inside or on higher floors, the driving force and space requirements for their handling are relatively low, and they do not pose a substantial constraint on the operating efficiency of the lifting equipment. More importantly, since heavy cargo is no longer scattered across different levels and areas within the warehouse, the internal passageways will not be obstructed by the presence of heavy cargo. This allows the lifting equipment to maintain unobstructed routes when performing outbound tasks, avoiding the extra travel distance and time lost due to detouring around heavy cargo.

[0023] Based on the above principles, this invention can improve outbound efficiency without relying on complex path optimization algorithms. Essentially, it proactively controls the inbound stage, altering the spatial distribution of goods within the warehouse area. This naturally imbues the warehouse layout with the physical characteristics of facilitating the removal of heavy items and storing lighter items, thereby reducing obstacles to outbound operations at the source. Accordingly, this invention achieves the following beneficial effects: First, by assigning clear physical meaning to the inbound weight value and incorporating the difficulty of outbound movement into the inbound decision-making process, the technical limitation of the separation between inbound allocation and outbound operations in the traditional scheme is broken, and the two are unified and linked. Secondly, by using a regular storage location distribution with heavier items on the outside and lighter items on the inside, the lifting and detour distances of the lifting equipment when heavy goods are taken out of the warehouse are effectively reduced, thus reducing the ineffective driving time and empty running rate of the equipment. Third, since heavy cargo no longer occupies the internal passageway space of the warehouse area, the internal passageway of the warehouse area remains unobstructed, the probability of the lifting equipment being obstructed by space when performing various outbound tasks is significantly reduced, and the overall smoothness of operation is improved. Fourth, this scheduling method only requires adding judgment on the volume and weight of goods and corresponding storage location allocation logic in the warehousing process, without modifying the existing warehousing equipment hardware, and has good compatibility and ease of implementation.

[0024] In this embodiment, the volume occupancy R of the goods on the storage space is calculated. VIn practice, it is necessary to obtain the standard volume value V0 of each storage location in the warehouse area in advance. This standard volume value V0 is usually determined based on the design specifications, dimensions, and maximum volume that the storage location can accommodate. For example, for a standard pallet location, V0 can be the product of its length, width, and height. The volume parameter V of the goods can be obtained in various ways, such as measuring the goods using 3D scanning equipment, consulting the specifications on the goods packaging, or manually inputting it before the goods enter the warehouse. Calculating the ratio between the actual volume parameter V of the goods and the standard volume value V0 of the storage location provides a direct and quantitative reflection of the actual occupancy of the storage location by the goods, ensuring the volume occupancy rate R. V The objectivity and comparability.

[0025] Similarly, when calculating the weight occupancy R of goods on the storage space's load-bearing capacity... W First, it's necessary to obtain the rated load-bearing capacity (W0) of each storage location within the warehouse area. The rated load-bearing capacity (W0) is the maximum weight the storage location's structure can withstand, designed to ensure its safety and stability and prevent accidents caused by overloading. W0 is typically provided by the warehouse designer or equipment supplier and stored in the storage location layout information of the warehouse management system. The weight parameter M of the goods can be obtained through real-time measurement with weighing equipment, consulting goods specification tables, or using system preset data. By calculating the ratio of the actual weight parameter M of the goods to the rated load-bearing capacity (W0) of the storage location, the extent to which the goods occupy the storage location's load-bearing capacity can be accurately assessed. This is crucial for avoiding storage location overloading, ensuring warehouse operational safety, and providing a reliable weight reference for subsequent storage location allocation.

[0026] In practical applications, evaluating the placement priority of goods solely based on their physical attributes may not fully reflect the frequency of goods leaving the warehouse and the dynamically changing operating environment in actual warehousing operations. This can lead to some frequently leaving goods being placed in hard-to-access locations or causing channel congestion, affecting overall operational efficiency and response speed. To address this, this invention provides two methods for calculating the inbound weight value Q. Before operation, the warehouse management system selects the appropriate weight calculation strategy based on the warehouse area's operating conditions.

[0027] Firstly, if there are significant differences in the frequency distribution of goods leaving the warehouse (i.e., there are clearly defined high-frequency turnover goods and low-frequency storage goods), then the historical outbound frequency correction module will be activated, using Q=R. V ·R W • f Calculate the inbound weight value. This calculation method aims to comprehensively consider the physical characteristics of the goods (volume occupancy R). V Weight occupancy R WThe system incorporates dynamic operational characteristics (historical outbound frequency coefficient f) to more comprehensively characterize the placement priority of goods in the warehouse area. By introducing the historical outbound frequency coefficient f, the inbound weight value Q not only reflects the physical space occupation and carrying capacity requirements of goods in the warehouse, but also reflects the expected activity level of goods being moved out of the warehouse. When the f value is high, even if R... V and R W A relatively low Q value will correspondingly increase the Q value, prompting the system to allocate the goods to a more easily accessible location. The historical outbound frequency coefficient f is an indicator of the activity level of goods being moved out of the warehouse within a specific time period. The higher the coefficient, the more frequently the goods are moved out, and the more urgent their access needs in the warehouse area. Quantifying this dynamic attribute allows for more intelligent warehouse location scheduling strategies to adapt to changes in actual business needs. Obtaining the total number of outbound transactions N within a preset historical time period refers to the system querying historical outbound records stored in the Warehouse Management System (WMS) or related databases to count the actual number of outbound operations for a specific good over a past period (e.g., the most recent week, month, or quarter). This preset historical time period can be flexibly configured according to the warehouse's business characteristics and data update frequency to ensure that the acquired data effectively reflects the recent outbound trend of goods. Obtaining the average number of outbound transactions N for all goods in the warehouse area. a This refers to calculating the total number of outbound shipments of all different types of goods within a preset historical time period, which is the same as the total number of outbound shipments N. This average number is then divided by the total number of goods types or the total inventory level to obtain an average value. a As a benchmark, it is used to standardize the outbound frequency of individual goods, enabling effective comparison with other goods and avoiding deviations caused by excessively large differences in absolute outbound frequency. The calculation formula is f = 1 + N / N. a The total number of times a single item leaves the warehouse (N) is compared with the average number of times all items in the warehouse leave the warehouse (N). a Calculate the ratio and add 1 to it. Adding 1 ensures that the historical outbound frequency coefficient f is always greater than or equal to 1, preventing Q from becoming zero when N is zero, thus ensuring all goods receive a basic placement priority. When N is much greater than N0... a When N approaches N, the f-value will increase significantly, indicating that the goods are frequently shipped items; when N approaches N... a When N is much smaller than N0, the value of f is close to 2; when N is much smaller than N0, the value of f is close to 2. a When the value of f approaches 1, this calculation method can dynamically adjust the importance of goods, making them play a key role in the calculation of the inbound weight value Q.

[0028] Secondly, if the capacity of the storage area channels approaches saturation and AGV congestion occurs frequently, the real-time channel status correction module will be activated, using Q=R. V ·R W·(1+C / C t The inbound weight value Q is calculated by comprehensively considering the physical characteristics of the goods and the real-time operational status within the warehouse area. Volume occupancy R V This reflects the storage space requirements of the goods, specifically the weight occupancy rate R. W This reflects the demand of goods for the storage space's capacity. By multiplying these two figures, a preliminary assessment of the overall occupancy of storage space by goods can be obtained. Based on this, a congestion coefficient (1+C / C) is introduced. t This allows the inbound weight value Q to be dynamically adjusted to reflect the current operational pressure in the warehouse area, especially in high-priority areas. When congestion increases, the congestion coefficient increases, thereby increasing the inbound weight value Q, guiding the system to allocate such goods to other relatively uncongested areas, or to carry out more refined scheduling within congested areas.

[0029] Specifically, C represents the number of congested passageways within a specific area defined as the bottom level and adjacent to the outer passageways in the warehouse area. The congestion status can be determined based on various real-time data, such as the number of handling equipment within the passageway, their movement speed, the accumulation of goods within the passageway, or the queue length of tasks. For example, when the number of handling equipment in a passageway exceeds a preset threshold, or the average movement speed of the equipment falls below a preset threshold, that passageway can be determined to be congested. By collecting and analyzing this data in real time, the C value can be dynamically obtained, thus reflecting the actual operational pressure in a localized area of ​​the warehouse area. Simultaneously, C... t This represents the total number of all channels within a specific area defined as the bottom layer and adjacent to the outer channels in the storage area. This value is typically a relatively fixed parameter representing the channel capacity of that high-priority area. (The last sentence appears to be incomplete and possibly refers to a different concept.) t By comparing the two, we can obtain the current congestion ratio C / C for this area. t This ratio visually reflects the workload and availability of the area.

[0030] In some of the above embodiments, goods are assigned an inbound weight value, and the goods are allocated to different target storage areas based on the comparison between the weight value and a set grading value. However, if the set grading value fails to fully consider the actual operating conditions and historical data of the storage area, for example, when the actual demand and supply relationship of high-quality storage locations (storage locations on the ground floor and adjacent to the outer passageway) changes, a fixed grading value may lead to unreasonable allocation of high-quality storage location resources, thereby affecting the overall inbound efficiency and the smoothness of subsequent outbound operations. To address this, this application further proposes a method for determining the set grading value, specifically including: obtaining the total number S of storage locations on the ground floor and adjacent to the outer passageway in the storage area; obtaining the arrival ratio P of heavy goods in the historical inbound records of the storage area, where heavy goods are defined as volume occupancy R. V and weight occupancy R W Goods with values ​​greater than 0.5; then, calculate and set the grading value Q0 according to the following formula: ; Among them, R Vavg R is the average volume occupancy of all goods in historical inbound records. Wavg is the average weight occupancy of all goods in the historical inbound records, and N is the total quantity of heavy goods in the historical inbound records.

[0031] The set tier value Q0 is a key threshold used to differentiate the priority of goods entering the warehouse. When the weight value of goods entering the warehouse is higher than this tier value, they are usually assigned to a more favorable storage location area; otherwise, they are assigned to other areas. Its accuracy directly affects the optimal allocation of storage space resources and warehouse operation efficiency.

[0032] The total number, S, of storage locations located on the bottom floor and adjacent to the outer passageways in the warehouse area is obtained. This number S represents the total capacity of the most easily accessible and efficiently handled high-quality storage locations within the warehouse area. This parameter can be obtained by reading storage location layout data and attribute information from the warehouse management system, or by analyzing and statistically processing the 3D spatial grid map of the warehouse area. This parameter reflects the static supply capacity of high-quality storage locations in the current warehouse area.

[0033] The arrival percentage P of heavy goods in the historical inbound records of the warehouse area is obtained. This percentage P reflects the historical demand intensity for high-quality storage locations (typically used for storing heavy or high-turnover goods). By analyzing historical inbound data, the proportion of goods meeting the definition of heavy goods among all inbound goods within a specific time period can be statistically determined. This parameter provides a historical demand basis for dynamically adjusting the tiering values.

[0034] Heavy cargo is defined as volumetric occupancy R V and weight occupancy R WGoods with a volume occupancy rate greater than 0.5. Heavy goods are explicitly defined here as those requiring high storage space volume and load-bearing capacity. Volume occupancy rate R V and weight occupancy R W The calculation method has been described in the above embodiments, namely, it is obtained by the ratio of cargo volume to standard warehouse volume and the ratio of cargo weight to warehouse rated load-bearing capacity, respectively. This definition ensures the objectivity and operability of heavy cargo identification.

[0035] The above formula is used to calculate the set grade value Q0, providing a method for dynamically calculating the set grade value Q0. Wherein, RVavg R is the average volume occupancy of all goods in historical inbound records. Wavg This represents the average weight occupancy of all goods in historical inbound records. These two averages reflect the general occupancy characteristics of goods within the warehouse area, providing a basic reference for grading values. N represents the total quantity of heavy goods in historical inbound records. The term P·N / S serves as a dynamic adjustment factor, comprehensively considering the historical arrival ratio of heavy goods (P), the total quantity of historical heavy goods (N), and the total quantity of high-quality warehouse locations (S). This adjustment factor reflects the relative scarcity of high-quality warehouse location resources or the historical demand pressure of heavy goods on high-quality warehouse locations. When high-quality warehouse locations are relatively scarce (S is small) or the demand for heavy goods is strong (P·N is large, i.e., a large quantity of historical heavy goods with a high arrival ratio), this adjustment factor will increase, thereby raising the set grading value Q0. This ensures that only goods with higher inbound weight values ​​can be allocated to high-quality warehouse locations, preventing high-quality warehouse locations from being occupied by low-priority goods. Conversely, when high-quality warehouse locations are sufficient, the grading value Q0 will decrease accordingly, improving the utilization rate of high-quality warehouse locations.

[0036] Reference Figure 2 As shown, this application further proposes a three-dimensional spatial grid map of the storage area, which includes the storage area layout information. Each grid cell in the three-dimensional spatial grid map is labeled with a floor height coordinate value and aisle distance coordinate value. In the three-dimensional spatial grid map, all grid cells with floor height coordinate values ​​equal to the minimum floor height coordinate value are selected as the bottom layer cell set. In the bottom layer cell set, grid cells with aisle distance coordinate values ​​less than a set aisle distance coordinate value are selected as the adjacent outer aisle cell set. In the adjacent outer aisle cell set, grid cells with storage location occupancy status marked as idle are selected as the candidate storage location cell set.

[0037] Specifically, the reservoir layout information is constructed as a three-dimensional spatial grid map of the reservoir area. This three-dimensional spatial grid map is a data structure that discretizes and abstracts the physical reservoir space, dividing the entire reservoir area into a series of regular, minimum addressable grid cells. Each grid cell not only represents a specific spatial location within the reservoir area but is also precisely labeled with its floor height coordinates and aisle distance coordinates. The floor height coordinates indicate the vertical height level of the cell; for example, the lowest floor can be set to a floor height coordinate of 1, increasing sequentially upwards. The aisle distance coordinates quantify the proximity of the cell to the surrounding aisles of the reservoir area; for example, the Euclidean or Manhattan distance from the center point of the cell to the nearest surrounding aisle can be calculated, or the coordinates can be marked according to preset area division rules. These coordinate labels enable the system to accurately locate and describe the attributes of every micro-space within the reservoir area, providing a refined spatial data foundation for subsequent intelligent scheduling.

[0038] Based on this, to identify storage locations that meet specific criteria, the system first performs a filtering operation on the 3D spatial grid map. Specifically, it filters all grid cells whose floor height coordinates are equal to the minimum floor height coordinate value, and defines this set of cells as the bottom layer set. The minimum floor height coordinate value usually corresponds to the ground floor or the lowest storage layer of the storage area. These storage locations typically have better load-bearing capacity and more convenient handling conditions. Subsequently, in the determined bottom layer set, the system further filters grid cells whose aisle distance coordinates are less than a set aisle distance coordinate value, defining this set of cells as the adjacent outer aisle cell set. The set aisle distance coordinate value is a preset threshold used to define the range of adjacent outer aisles. This threshold can be flexibly configured according to the actual layout of the storage area, the working range of the handling equipment, and the requirements for handling efficiency. Through this filtering process, the system can accurately identify all storage locations in the storage area located on the bottom layer and close to the outer aisles. Finally, in the adjacent outer aisle cell set, the system further filters grid cells whose storage location occupancy status is marked as free, thus forming the final candidate storage location cell set. Storage location occupancy status indicators provide real-time information on whether a storage location is currently occupied. This information can be obtained, for example, through sensor detection at the storage location or data updates from the warehouse management system. Only storage locations with an occupancy status of "free" are included in the candidate set, ensuring that allocated storage locations are available.

[0039] In practical applications, this application further proposes installing detection sensors at each storage location to determine whether there are goods in the location and generate a storage location occupancy status indicator. Specifically, a detection sensor is a device capable of sensing physical quantities (e.g., the presence, distance, weight, etc. of an object) and converting them into processable electrical signals. In practical applications, detection sensors can take various forms. For example, photoelectric sensors can be used to determine whether there are goods in the storage location by detecting whether a light beam is blocked; ultrasonic sensors can be used to determine whether there are objects in the storage location by measuring the round-trip time of ultrasonic waves; or pressure sensors or weighing sensors can be used to determine whether there are goods by detecting changes in pressure or weight in the storage location. These sensors are strategically deployed at each storage location to ensure comprehensive coverage and real-time monitoring of the storage location status. When a detection sensor is triggered or its output signal changes, the system makes a judgment based on preset logic rules or thresholds. For example, if a photoelectric sensor detects that the light path is blocked, it determines that there are goods; if a pressure sensor detects that the weight in the storage location exceeds a preset empty threshold, it determines that there are goods. This judgment process is automated and requires no manual intervention, thus ensuring the objectivity and real-time nature of the judgment. After determining whether there are goods in a storage location, the system converts the result into a standardized storage location occupancy status identifier. For example, if goods are found, an occupancy identifier is generated; if no goods are found, an idle identifier is generated. These identifiers are typically stored as numbers (e.g., 1 for occupied, 0 for idle) or Boolean values ​​(e.g., True for occupied, False for idle), and are associated with the corresponding storage location number. This information is updated in real time to the storage area layout information for subsequent scheduling algorithms to use.

[0040] Reference Figure 3 As shown, when multiple vacant storage locations are available in the target storage area, this application further proposes an optimization strategy: selecting the optimal storage location by calculating the distance. Specifically, when multiple vacant storage locations exist in the target storage area, it means that after matching the target storage area in the storage layout information based on the goods' inbound weight value, there is not just one vacant storage location available in that area, but two or more vacant storage locations that meet the conditions. In this case, to avoid the inefficiency caused by random selection or manual intervention, a further strategy is needed to determine the final inbound storage location.

[0041] Therefore, the planar coordinates of the current entry point are first obtained in the 3D spatial grid map. The 3D spatial grid map is a digital representation of the warehouse layout information, where each grid cell represents a potential storage location or spatial area. The entry point is the physical entrance for goods into the warehouse area, and its planar coordinates (e.g., X and Y axis coordinates) are the starting point for distance calculation. These coordinates can be obtained through pre-configuration in the system, real-time positioning via sensors, or manual input, and are used to calculate the transport distance of goods from the entry point to each candidate storage location. Simultaneously, the planar coordinates of each available storage location in the target storage area are obtained. Each available storage location in the target storage area has a unique identifier and spatial location information in the 3D spatial grid map. Obtaining its planar coordinates is the basis for calculating its distance to the entry point. These coordinates are usually entered into the system during warehouse initialization and associated with storage location identification information for quick lookup during scheduling. Subsequently, the distance between each available storage location and the entry point is calculated. Distance calculation is based on planar coordinates and can use Euclidean distance, Manhattan distance, or other distance metrics that consider the actual transport path. The purpose of this step is to quantify the handling cost or time from the entry point to each candidate available storage location, providing a basis for subsequent optimization. Ultimately, the available storage location with the shortest distance is selected as the final storage location. After calculating the distances between all candidate available storage locations and the entry point, the system compares these distance values ​​and selects the available storage location with the shortest distance as the final storage location.

[0042] Reference Figure 4 As shown, when all preferred storage locations are occupied, this application further proposes that when the storage weight value is higher than the set grading value and the number of all vacant storage locations located at the bottom layer and adjacent to the outer passage in the storage area is zero, the vacant storage locations located at the bottom layer and far from the outer passage in the storage area are identified as candidate target storage locations, and specific vacant storage locations in the candidate target storage locations are allocated as storage locations for storage.

[0043] Specifically, when the system determines that the inbound weight value of currently incoming goods is higher than the preset tier value, the goods are considered high-priority goods and should be preferentially allocated to the optimal storage location area. At this time, the system will first check the number of vacant storage locations on the bottom floor of the storage area that are adjacent to the outer aisles. This condition determines whether there is a shortage of storage space resources when allocating storage locations for high-priority goods. When all these optimal storage locations are occupied, i.e., their number is zero, it indicates that the conventional optimization strategy cannot meet the current inbound demand of high-priority goods, and a backup strategy needs to be activated.

[0044] When preferred storage locations are exhausted, the system no longer adheres to the condition of proximity to outer aisles. Instead, it expands the search to include vacant storage locations on the lower levels of the storage area, away from outer aisles, and identifies these locations as candidate target storage areas. While these locations are slightly less efficient in outbound handling than those near outer aisles, they retain the important characteristic of being on the lower level, which helps maintain the stability of goods or facilitates the operation of certain types of handling equipment. This approach aims to provide suboptimal storage options for high-priority goods, avoiding scheduling disruptions due to a lack of preferred locations or the allocation of high-priority goods to less desirable, non-lower-level locations.

[0045] After identifying potential target storage areas, the system needs to select a specific vacant storage location within that area as the receiving storage location for the goods. This specific vacant storage location can be selected based on various strategies. For example, it can be chosen based on the distance between the storage entrance and the storage location to minimize handling paths; or based on the matching degree between the storage location size and the goods size to improve space utilization; or based on the matching degree between the storage location's load-bearing capacity and the goods weight. Through intelligent selection, it ensures that storage efficiency and subsequent operational convenience are optimized as much as possible, even within the candidate areas.

[0046] In practical applications, this application further proposes a specific method for outputting the storage location identification information of the storage location, including combining the storage location number and storage location coordinates of the storage location into a storage location identification data packet; and sending the storage location identification data packet to the storage task queue of the warehouse management system as the destination address for the handling equipment to perform storage handling tasks.

[0047] Specifically, the storage location number is a string or numeric code that uniquely identifies a specific storage location. For example, "A01-02-03" represents row 1, column 2, and floor 3 of area A. The storage location coordinates provide the precise physical location information of that storage location in three-dimensional space, such as (X, Y, Z) coordinate values, or more abstractly, floor height coordinate values ​​and aisle distance coordinate values. Combining these two types of information means associating logical identifiers with physical location information to form a structured data unit. This combination can be achieved in various ways, such as using the storage location number as the primary key and the storage location coordinates as its attribute, or encapsulating both in a JSON object, XML structure, or a specific data protocol to ensure the integrity and parsability of the information.

[0048] Based on this, the storage location identification data packet is sent to the inbound task queue of the Warehouse Management System (WMS). The Warehouse Management System is the core software platform responsible for coordinating and managing all operations within the warehouse. The inbound task queue is a list of pending tasks maintained internally by the WMS, containing all inbound operation instructions that need to be executed. Sending the storage location identification data packet to this queue is typically achieved through the WMS's application programming interface (API), message queue service, or direct writing to the database. This step ensures that the inbound storage location information determined by the intelligent scheduling method can be seamlessly transmitted to the WMS, so that the WMS can generate or update specific inbound operation instructions based on this information.

[0049] Ultimately, this warehouse location identification data packet is used as the destination address for the handling equipment to perform inbound handling tasks. Handling equipment refers to automated or semi-automated machinery responsible for moving goods in a warehouse, such as automated guided vehicles (AGVs), stacker cranes, shuttles, or robots. The destination address is the final physical location that the handling equipment needs to reach when performing a task. Using the warehouse location identification data packet directly as the destination address means that the packet contains all the information needed for the handling equipment to understand and navigate. After receiving this data packet, the handling equipment can parse the warehouse location number and coordinates, and use its own navigation system and positioning technology to plan a route and accurately transport the goods to the designated inbound storage location.

[0050] To further illustrate the intelligent storage scheduling method of the present invention, a more specific example is provided below to explain the above technical solution in greater detail: In a large intelligent warehousing center, "Warehouse Area A", the system receives a batch of "Goods A" awaiting warehousing. The goods are an industrial component with a volume of 2 cubic meters and a weight of 500 kilograms.

[0051] First, the system calculates the impact of "Goods A" on the storage location's volume and load-bearing capacity based on its volume and weight parameters. It is known that the standard volume V0 of a single storage location in "Storage Area A" is 4 cubic meters, and the rated load-bearing capacity W0 of a single storage location is 1000 kilograms.

[0052] Based on the calculation method, the volume occupancy R V =2 / 4=0.5.

[0053] Weight occupancy R W =500 / 1000=0.5.

[0054] Next, the system calculates the volume occupancy R. V and weight occupancy R WThe system assigns an inbound weight value to "Goods A". To more accurately reflect the placement priority of goods in the warehouse area and the expected difficulty of moving them out of the warehouse, the system also introduces a historical outbound frequency coefficient for goods. Assume that the total number of outbound trips for "Goods A" within a preset historical time period is N = 20, and the average number of outbound trips for all goods in "Warehouse Area A" is N... a It is 10 times.

[0055] Historical outbound frequency coefficient f = 1 + N / N a =1+20 / 10=3.

[0056] Inbound weight value Q=R V ·R W ·f=0.5·0.5·3=0.75.

[0057] The inbound weight value Q represents the placement priority of "goods A" in the warehouse area. The higher the value, the greater the expected difficulty in moving the goods when they leave the warehouse, and they should be placed in a location that is easy to retrieve.

[0058] Simultaneously, the system acquires the storage location layout information of "Storage Area A" and the current vacancy status of each storage location. The storage location layout information is presented in the form of a three-dimensional spatial grid map, with each grid cell labeled with floor height coordinates and aisle distance coordinates. Detection sensors on the storage locations determine in real time whether there are goods in the storage location and generate a storage location occupancy status indicator.

[0059] Before matching a target storage location area for "Goods A", the system needs to determine a preset grading value Q0. This preset grading value Q0 is determined by the system in advance, taking into account factors such as the total number of storage locations on the bottom floor of the storage area and adjacent to the outer aisles, the proportion of heavy goods arriving in historical inbound records, and the average volume and weight occupancy of all goods. Assume the current preset grading value Q0 is 0.6.

[0060] Now, the system compares the inbound weight value Q (0.75) of "Goods A" with the set grading value Q0 (0.6). Since Q is higher than Q0, the system determines the target storage location area as "an vacant storage location located on the bottom floor and adjacent to the outer passage".

[0061] The specific matching process is as follows: 1. In a 3D spatial grid map, filter all grid cells whose layer height coordinates are equal to the minimum layer height coordinates to form the bottom layer cell set.

[0062] 2. In the bottom cell set, filter the grid cells whose channel distance coordinate value is less than the set channel distance coordinate value to form a set of adjacent outer channel cells.

[0063] 3. In the set of adjacent outer channel cells, filter the grid cells whose storage location occupancy status is marked as free, and use them as the candidate storage location cell set.

[0064] Compared with existing technologies, this solution can intelligently allocate "goods A", which are bulky, heavy and frequently outbound, to storage locations on the bottom floor and near the outer passage by comparing the inbound weight value Q with the set grading value Q0. This optimizes the outbound path in advance during the inbound stage and avoids the problem of the lifting equipment having to frequently detour, slow down or change the predetermined route due to the space occupied by the goods when leaving the warehouse in the future.

[0065] It is worth noting that if the number of available storage spaces in "Warehouse Area A" located on the bottom floor and adjacent to the outer aisles is zero, the system will not simply assign "Goods A" to other less desirable storage spaces. Instead, the system will identify available storage spaces on the bottom floor of "Warehouse Area A" that are far from the outer aisles as candidate target storage areas, and select a specific available storage space from this candidate area (e.g., the one closest to the entry point) as the storage storage space for "Goods A". This alternative mechanism ensures that even if optimal storage space resources are scarce, it will prioritize the selection of the next best, still relatively easy-to-access storage space, further improving the robustness of the scheduling strategy.

[0066] Finally, the system combines the location number of "Location 101" (e.g., "A-01-01-101") and the location coordinates (e.g., "X:10, Y:5, Z:1") into a location identification data packet. This location identification data packet is then sent to the warehouse management system's inbound task queue as the destination address for handling equipment (such as AGVs or stacker cranes) to perform inbound handling tasks. Based on this information, the handling equipment accurately moves "Goods A" to "Location 101". In this way, this solution optimizes the entire process from goods inbound to future outbound, significantly improving the overall throughput efficiency of the warehousing system.

[0067] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A smart warehouse scheduling method based on dynamic warehouse location weight allocation, characterized in that, Includes the following steps: Obtain the volume and weight parameters of the goods entering the warehouse; Based on volume and weight parameters, calculate the volume occupancy of goods on the storage space and the weight occupancy of goods on the storage space's load-bearing capacity, respectively. Based on volume and weight occupancy, inbound weight values ​​are assigned to goods. Inbound weight values ​​are used to characterize the placement priority of goods in the warehouse area. The placement priority is positively correlated with the expected difficulty of moving goods when they are moved out of the warehouse. Obtain the current storage location layout information of the current storage area and the current availability status of each storage location; Based on the inbound weight value, the corresponding target storage location area is matched for the goods in the storage location layout information, where: If the inbound weight value is higher than the set grading value, then the vacant storage space located at the bottom layer and adjacent to the outer passage will be identified as the target storage space area. If the weight value of the warehouse entry is not higher than the set grade value, then the vacant warehouse locations that are not at the bottom layer or far from the outer passage will be identified as the target warehouse location area. The available storage locations in the target storage area are matched and assigned as storage locations for goods entering the warehouse, and the storage location identification information of the storage locations is output.

2. The intelligent storage scheduling method based on dynamic storage location weight allocation according to claim 1, characterized in that: The method for calculating the volume occupancy of goods on the storage space is as follows: Obtain the standard volume value V0 of a single storage space in the storage area, and calculate the volume occupancy R according to the following formula. V :R V =V / V0, where V is the volume parameter; The method for calculating the weight occupancy of goods on the load-bearing capacity of a storage location is as follows: Obtain the rated load-bearing value W0 of a single storage location in the storage area, and calculate the weight occupancy R according to the following formula. W :R W =M / W0, where M is the weight parameter.

3. The intelligent storage scheduling method based on dynamic storage location weight allocation according to claim 2, characterized in that: The inbound weight value Q is calculated according to the following formula: Q=R V ·R W ·f; Where f is the historical outbound frequency coefficient of goods, and the historical outbound frequency coefficient f is determined as follows: Get the total number of times N goods left the warehouse within a preset historical time period, and get the average number of times N goods left the warehouse. a The historical outbound frequency coefficient f is calculated according to the following formula: f=1+N / N a 。 4. The intelligent storage scheduling method based on dynamic storage location weight allocation according to claim 2, characterized in that: The inbound weight value Q is calculated according to the following formula: Q=R V ·R W ·(1+C / C t ); Where C represents the number of currently congested passages in the area at the bottom level and adjacent to the outer passages. t The total number of passages in the area that is at the bottom level and adjacent to the outer passages.

5. The intelligent storage scheduling method based on dynamic storage location weight allocation according to claim 1, characterized in that: The gradation values ​​are determined as follows: Obtain the total number S of storage locations on the bottom floor of the warehouse area that are adjacent to the outer passageway, and obtain the proportion P of heavy goods arriving in the historical inbound records of the warehouse area. The volume occupancy of heavy goods is R. V and weight occupancy R W Goods with values ​​greater than 0.5; The set grade value Q0 is calculated using the following formula: ； Among them, R Vavg R is the average volume occupancy of all goods in historical inbound records. Wavg is the average weight occupancy of all goods in the historical inbound records, and N is the total quantity of heavy goods in the historical inbound records.

6. The intelligent storage scheduling method based on dynamic storage location weight allocation according to claim 1, characterized in that: The reservoir layout information includes a three-dimensional spatial grid map of the reservoir area. Each grid cell in the three-dimensional spatial grid map is labeled with the floor height coordinates and the passage distance coordinates. In a 3D spatial grid map, filter all grid cells whose layer height coordinates are equal to the minimum layer height coordinates to form the bottom layer cell set; In the bottom cell set, filter the grid cells whose channel distance coordinate value is less than the set channel distance coordinate value, and use them as the set of adjacent outer channel cells; In the set of cells adjacent to the outer channel, filter the grid cells whose storage location occupancy status is marked as free to form a candidate storage location cell set.

7. The intelligent storage scheduling method based on dynamic storage location weight allocation according to claim 6, characterized in that: Each storage location is equipped with a detection sensor to determine whether there are goods in the location and generate a storage location occupancy status indicator.

8. The intelligent storage scheduling method based on dynamic storage location weight allocation according to claim 6, characterized in that: When there are multiple vacant storage locations in the target storage area, the planar coordinates of the current inlet are obtained in the three-dimensional spatial grid map, the planar coordinates of each vacant storage location in the target storage area are obtained, the distance between each vacant storage location and the inlet is calculated, and the vacant storage location with the smallest distance is selected as the storage location for inlet storage.

9. The intelligent storage scheduling method based on dynamic storage location weight allocation according to claim 1, characterized in that: When the inbound weight value is higher than the set grading value, and the number of all vacant storage locations in the storage area that are located at the bottom layer and adjacent to the outer passage is zero, the vacant storage locations located at the bottom layer and far from the outer passage in the storage area are identified as candidate target storage locations, and specific vacant storage locations in the candidate target storage locations are allocated as inbound storage locations.

10. The intelligent storage scheduling method based on dynamic storage location weight allocation according to claim 1, characterized in that: The specific method for outputting and storing the storage location identifier information is as follows: Combine the storage location number and storage location coordinates into a storage location identifier data packet; The storage location identifier data packet is sent to the inbound task queue of the warehouse management system, serving as the destination address for the handling equipment to perform inbound handling tasks.

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