Method and device for multi-depth rational storage of automated stereoscopic warehouse, electronic equipment and medium

Abstract

The application discloses a kind of automated stereoscopic warehouse multi-depth warehouse sorting method and device, electronic equipment, medium, comprising: batch goods inventory is classified and deep position is classified according to inventory classification and deep position classification;According to the storage corresponding priority of inventory level and deep level of warehouse sorting rule configuration and the storage of warehouse sorting range, obtain the batch goods inventory that needs to be sorted;According to the batch goods inventory that needs to be sorted and idle deep position, sorting is aggregated, and the first deep position matching combination and the batch goods inventory that is not matched successfully are obtained;When deep position utilization rate reaches threshold value, from the batch goods inventory that is not matched successfully, filter out the batch goods inventory contained in the order to be shipped job, then deep position mixed storage aggregation is carried out, and the second deep position matching combination is obtained;Query the deep position of mixed batch goods inventory to be shipped, query the deep position with idle position and idle deep position, carry out the reverse storage operation to mixed deep position, and the mixed batch goods inventory is shifted to idle deep position or the outermost position of mixed deep position.

Description

Technical Field

[0001] This application relates to the field of automated storage and retrieval systems (AS / RS) technology, and in particular to a method, apparatus, electronic device, and medium for an automated storage and retrieval system with multiple depths. Background Technology

[0002] When warehouse staff find that there are insufficient empty storage locations in the automated warehouse, they manually query the storage location inventory data, manually select the storage locations that need to be managed, export the data table for analysis, and derive a management plan. In the management interface, they manually fill in the source and target storage locations and the appropriate quantities. In multi-deep storage scenarios, the workload is large, time-consuming, and labor-intensive, and when the data analysis is incomplete, the management result may not be optimal.

[0003] The current technology provides a manual inventory management interface where users can select goods, manually enter source and target storage locations, and choose the quantity of goods. It also restricts the mixing of goods and batches to ensure that the goods meet inventory management requirements after inventory management. Deep storage locations have strict access sequences, and mixing goods will negatively impact outbound processing efficiency.

[0004] In summary, the existing technology has the following shortcomings: 1. Inefficient manual selection: The existing process requires manual selection of source and target storage locations one by one, and manual input of the storage quantity. The operation steps are cumbersome, rely on a large amount of human judgment and input, and the overall efficiency is low.

[0005] 2. Numerous restrictions and high operational difficulty: Due to strict restrictions on the mixed storage of different goods and batches in different storage locations, the order of storage and retrieval within deep storage locations, and the multiple combinations of matching deep storage locations, operators need to repeatedly try to determine the compliant target storage location. This process incurs high trial-and-error costs and makes it difficult to quickly locate available storage locations, significantly increasing the operational difficulty.

[0006] 3. Lack of holistic thinking in localized inventory management: Current methods rely excessively on the personal experience of operators. Insufficient experience can easily lead to incorrect or missed inventory locations, hindering systematic optimization based on the overall inventory layout. Because inventory is not first categorized and planned globally, adjustments are often limited to localized areas, resulting in unsatisfactory final outcomes. Summary of the Invention

[0007] Therefore, the purpose of this application is to provide a method, apparatus, electronic device, and medium for automated three-dimensional warehouses with multiple depths, in order to address the shortcomings in related technologies.

[0008] According to a first aspect of the embodiments of this application, a method for automated multi-depth spatial storage of a three-dimensional warehouse is provided, comprising: Based on the inventory age, time since last shipment, and average shipment interval of the batch of goods, the inventory of the batch of goods is classified into different inventory levels; all available storage spaces are queried and classified into different storage spaces; the batch of goods inventory that needs to be managed is obtained according to the storage priority corresponding to the inventory level and storage space level configured in the management rules and the management storage space range. Based on the batch of goods inventory and available deep space required for inventory management, inventory management aggregation is performed to obtain the first deep space matching combination and the batch of goods inventory that failed to match. An inventory management task is generated based on the first deep space matching combination, and a four-way shuttle car is assigned to perform the inventory management operation. When the deep storage utilization rate reaches the threshold, the batch goods inventory included in the pending outbound operation order is filtered out from the unmatched batch goods inventory. Then, deep storage mixed placement aggregation is performed to obtain the second deep storage matching combination. Based on the second deep storage matching combination, a storage management task is generated and a four-way shuttle is assigned to perform the storage management operation. Based on the pending outbound order, the deep storage location of the mixed batch of goods in the warehouse is retrieved. If there is an available storage location, the mixed storage location is moved to an available storage location or the outermost storage location of the mixed storage location.

[0009] According to a second aspect of the embodiments of this application, an apparatus for an automated storage and retrieval system with multiple depths is provided, comprising: The assessment and grading module is used to grade the inventory of batch goods based on the inventory age, the time since the last shipment, and the average shipment interval; query all available storage spaces and grade them according to their depth; and obtain the batch goods inventory that needs to be managed based on the storage priority and storage depth range of the inventory level and storage depth configured in the management rules. The inventory management strategy module is used to aggregate inventory management data based on the batch of goods inventory and available deep storage space required for inventory management, obtain a first deep storage space matching combination and unmatched batch of goods inventory, generate an inventory management task based on the first deep storage space matching combination, and assign a four-way shuttle car to perform inventory management operations. The mixed placement strategy module is used to filter out the batch goods inventory contained in the pending outbound operation order from the unmatched batch goods inventory when the deep position utilization rate reaches the threshold. Then, deep position mixed placement aggregation is performed to obtain a second deep position matching combination. Based on the second deep position matching combination, a warehouse management task is generated and a four-way shuttle car is assigned to perform the warehouse management operation. The intelligent shifting module is used to query the depth of mixed batches of goods inventory in the warehouse according to the order to be shipped out, and to perform a reverse shifting operation on the mixed batches of goods inventory to an empty depth or the outermost depth of the mixed depth.

[0010] According to a second aspect of the embodiments of this application, an electronic device is provided, comprising: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors perform the method as described in the first aspect.

[0011] According to a fourth aspect of the embodiments of this application, a computer-readable storage medium is provided that stores computer instructions thereon, which, when executed by a processor, implement the steps of the method as described in the first aspect.

[0012] The technical solutions provided by the embodiments of this application may include the following beneficial effects: 1. Tiered Strategy: Based on core factors such as inventory age, time since last shipment, and average shipment interval, a comprehensive score is used to tier the inventory.

[0013] 2. Inventory Management Strategy: Based on the warehouse space utilization rate, depth coordinates, depth fullness rate, and inventory information, select inventory items that can be managed and carry out inventory management operations.

[0014] 3. Mixed storage strategy: Allows for mixed storage of deep-position inventory based on inventory level, and also provides preventative measures against obstruction of deep-position mixed storage based on analysis of pending outbound orders.

[0015] This application integrates dynamic assessment and grading, inventory matching strategies, mixed placement strategies, and intelligent relocation technology. By analyzing real-time inventory age and outbound interval data, combined with preset rules, it performs tiered management of goods inventory and storage depth. A matching algorithm aggregates batches of goods requiring inventory management with available deep storage locations, generating optimal tasks and assigning them to a four-way shuttle for execution. When deep storage utilization exceeds a threshold, it automatically filters outbound orders and implements mixed placement aggregation to improve space utilization. Using a palletizing operation, mixed goods are moved to available or outer storage locations, reducing operational interference. This overcomes the low space utilization problem of traditional automated storage systems, especially in multi-deep storage scenarios where manual intervention costs are high. This device shortens goods storage and retrieval time and improves efficiency through inventory management strategies and intelligent relocation. The mixed placement strategy is automatically activated when deep storage is scarce, maximizing storage density, reducing idle areas, and enhancing space utilization. It reduces manual intervention, achieves automated inventory management, improves overall warehouse turnover, and lowers operating costs.

[0016] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] Figure 1 This is a flowchart illustrating an automated multi-depth spatial storage method for a three-dimensional library, according to an exemplary embodiment.

[0019] Figure 2 This is a block diagram illustrating an automated three-dimensional warehouse multi-depth storage device according to an exemplary embodiment.

[0020] Figure 3 This is a schematic diagram of the structure of an electronic device according to an exemplary embodiment. Detailed Implementation

[0021] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0022] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0023] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0024] Explanation of the name: Automated storage and retrieval system (AS / RS): An intelligent warehousing facility that uses high-rise racks as its core storage structure, combined with aisles, conveyor systems, and computer management systems, to achieve automated storage and retrieval of goods and efficient use of space.

[0025] Four-way shuttle: an unmanned handling device that moves in four directions (lateral, longitudinal, forward, and backward) along a pre-installed track, and completes the storage, retrieval, handling, and sorting of goods through an intelligent control system.

[0026] Depth: Each storage location can store multiple storage units at its depth.

[0027] Storage location: The specific physical location in a warehouse used to store goods; it is the smallest storage unit in warehouse management.

[0028] Full Load: An indicator for judging the storage status of goods in multiple storage locations. When all storage locations within a depth are filled with goods, the depth is considered full. When only some storage locations within a depth are filled with goods, the depth is considered incomplete.

[0029] Inventory: The general term for all kinds of goods that an enterprise reserves to meet the needs of production, sales or services.

[0030] Full pallet: An inventory unit formed by storing the same type of goods together on a standard pallet.

[0031] Warehouse management: Improve storage capacity and operational efficiency through reasonable layout and cargo classification.

[0032] In automated storage and retrieval systems (AS / RS), goods are stored by depth, with each depth containing one or more storage locations. Each storage location is supported by pallets, and inventory in each depth is strictly managed using a last-in, first-out (LIFO) system. When goods are to be shipped out, a four-way shuttle transports the goods to the assigned storage location and then to the exit. Since the demand for outbound shipments is variable, it cannot be guaranteed that an entire depth can be emptied at once. Therefore, after multiple outbound shipments, some storage locations within a multi-depth system will have inventory while others will be empty. Furthermore, goods from the same batch may be scattered across multiple different depths, resulting in most multi-depth systems not being fully utilized and wasting warehouse space.

[0033] This invention provides a method for automated storage and retrieval systems with multiple depths, offering the ability to organize warehouse space based on inventory space, dynamic inventory levels, and order clustering data analysis.

[0034] Figure 1 This is a flowchart illustrating an automated multi-depth spatial storage method for automated three-dimensional warehouses, according to an exemplary embodiment, such as... Figure 1 As shown, the method may include the following steps: S1. Classify the batch of goods inventory according to the inventory age, the time since the last shipment, and the average shipment interval; query all available storage spaces and classify them according to their depth; obtain the batch of goods inventory that needs to be managed according to the storage priority and management depth range of the inventory level and storage depth configured in the management rules.

[0035] The inventory of batches of goods is classified into different levels based on the age of the goods in stock, the time since the last shipment, and the average time interval between shipments. A1: Statistically analyze the inventory age of each batch of goods, the time since the last shipment, and the average time interval between shipments, and then standardize the data. Specifically, the process involves querying the inbound date of a batch of goods inventory, calculating the inbound age using the formula: Inbound Age = Current Time - Inbound Date, and then standardizing the inbound age using Z-score to obtain a standardized value. Similarly, it involves querying the last outbound time of a batch of goods inventory, calculating the time since the last outbound using the formula: Time Since Last Outbound = Current Time - Last Outbound Time, and then standardizing the time since the last outbound using Z-score to obtain a standardized value. Finally, it involves querying the set T of all outbound times for the batch of goods inventory, subtracting the previous time from the next time within set T to calculate the interval between each outbound, obtaining a set of differences, averaging these differences to obtain the average outbound interval, and then standardizing the average outbound interval using Z-score to obtain a standardized value. This approach allows for the development of metrics closely aligned with the actual warehousing operations, while standardization processes data from different metrics, enabling fair comparisons between them.

[0036] A2: Calculate a comprehensive score for each batch of goods inventory, where Score = w1 × standardized value of inventory age + w2 × standardized value of average outbound interval + w3 × standardized value of distance from last outbound, and w1, w2, and w3 are user-defined weighting ratios. Specifically, the weighting ratios of each dimension are configured in the inventory management rules, using the formula: Score = w1 × standardized inventory age + w2 × standardized average outbound interval + w3 × standardized distance from last outbound, to calculate the comprehensive score for each batch of goods inventory. Using custom weighting ratios, the weighting ratios can be adjusted at any time according to the actual scenario, making the calculated comprehensive score closer to the actual scenario.

[0037] A3: Based on the comprehensive score, the batch of goods inventory is divided into multiple levels.

[0038] Specifically, the calculated comprehensive inventory score for each batch of goods is sorted in descending order. Based on the number and proportion of inventory levels configured in the inventory management rules, the comprehensive score is divided into multiple corresponding levels. By default, the inventory is classified into three levels: Level 1, Level 2, and Level 3. The batch of goods inventory is classified according to the configured proportions, and the number and proportions of levels can be adjusted at any time to make the classification more in line with the actual scenario.

[0039] This involves querying all free depth bits and classifying the depth bits into depth levels, including: Specifically, query all idle deep positions L3, mark in advance the position distances corresponding to the outbound ports of the deep positions, sort the deep positions in descending order according to the maintained position distances, and divide the deep positions into multiple deep position levels according to the number of deep position levels and level ratios configured by the inventory management rules. By default, the deep position levels are divided into fast, normal, and low speed. The inventory management rules maintain the corresponding relationship between the deep position levels and the inventory levels. The storage corresponding priorities of the inventory levels and the deep position levels are as follows: the first-level priority corresponds to the fast deep positions to the normal deep positions and then to the slow deep positions, the second-level priority corresponds to the normal deep positions to the slow deep positions, and the third-level priority corresponds to the slow deep positions to the normal deep positions. Different levels of inventory can be stored in different levels of deep positions. High-level inventory can be preferentially stored in the deep positions close to the outbound port, and low-level inventory can be preferentially stored in the deep positions far from the outbound port, thus improving the outbound efficiency.

[0040] Among them, according to the storage corresponding priorities of the inventory levels and the deep position levels configured by the inventory management rules and the inventory management deep position range, the inventory of the batch of goods that needs to be managed is obtained, including: B1: According to the inventory management rules, screen out the inventory set L1 of N2 types of deep position batch goods with a full storage rate <N1%; screen out the inventory set L2 of N3 types of small deep position batch goods with a full storage rate of 100%; N1, N2, and N3 are all configured and defined by the inventory management rules; Specifically, the deep position inventory that needs to be managed is divided into two types. The first type is to manage the deep position inventory with a full storage rate less than the threshold to idle deep positions or other unfilled deep positions. The second type is to merge and manage the small deep position inventory with a full storage rate of 100% into large deep positions. The full storage rate is calculated according to the formula: full storage rate = the number of storage positions occupied by the inventory / the total number of storage positions in the deep position, and the full storage rate of all current deep positions is calculated. According to the full storage rate threshold N1, the unfilled deep position range N2, and the full storage small deep position range N3 configured by the inventory management rules, filter out the inventory set L1 of the batch of goods in the deep positions N2 with a full storage rate less than the threshold N1, and then filter out the inventory set L2 of the batch of goods in the small deep positions N3 with a full storage rate of 100%. The first method is to increase the full storage rate of the deep positions and release more storage positions. The second method is to improve the utilization rate of the small deep positions and release more deep positions. Both methods are to increase the full storage rate of the deep positions and improve the storage capacity to release storage positions. At the same time, the configuration of the full storage rate threshold and the deep position range by the inventory management rules can be dynamically adjusted according to the actual situation to achieve the purpose of increasing the full storage rate of the deep positions and improving the storage capacity.

[0041] B2: Query the current outbound order, and mark the inventory level of the batch of goods required in the order as the first level.

[0042] Specifically, query the current orders awaiting shipment, obtain the order batch goods details, locate the required batch of goods inventory based on the goods details, and mark the inventory level of this batch of goods as the highest level. Because this batch of goods inventory is in a state of imminent shipment, marking it as the highest level can prevent it from being mixed into deep storage locations during inventory management, thus affecting shipment efficiency.

[0043] S2. Based on the batch of goods inventory and available storage space required for inventory management, perform inventory management aggregation to obtain a first storage space matching combination and the unmatched batch of goods inventory. Generate an inventory management task based on the first storage space matching combination and assign a four-way shuttle to perform the inventory management operation. This step is divided into the following sub-steps: S21. Combine L1 and L2, and then perform internal matching and aggregation to obtain a successfully matched combination L5 and an unmatched batch inventory set L6.

[0044] Specifically, L1 and L2 are combined to obtain L4. L4 is then grouped by depth to obtain a depth set SW1. Each depth location in SW1 with inventory is traversed to obtain a set of inventory locations SKW1. A greedy algorithm is used to simulate and calculate the re-storage of SKW1 into the depth set SW1, prioritizing the use of the fewest depth locations and secondarily minimizing the remaining capacity of the depth locations. When multiple identical depth locations are matched, depth locations at the same level are used first, and the correspondence between depth level and inventory level is maintained according to the aforementioned inventory management rules. Finally, the depth set SW2 that SKW1 can use is calculated. The locations SKW1 in SW1 and all locations SKW2 not in SW2 are traversed to obtain the complement of SKW1 and SKW2, namely, the location SKW3 that SKW1 is not in SKW2, and the location SKW4 that SKW2 is not in SKW1. SKW3 is recorded as the source location, and SKW4 is recorded as the target location, resulting in the matching combination L5 and the unmatched batch inventory set L6. First, matching and aggregating existing deep-space inventory can rationally organize existing deep-space inventory, improve the full utilization rate of used deep-space inventory, and increase warehouse capacity utilization.

[0045] S22. Match and aggregate the unmatched batch inventory set L6 with the idle deep position L3 to obtain the successfully matched combination L7 and the unmatched batch inventory set L8.

[0046] Specifically, L6 is grouped by depth to obtain a depth set SW3. The number of inventory locations in each depth within SW3 is traversed to obtain an inventory location set SKW5. A greedy algorithm is used to simulate and calculate the placement of SKW5 into the available depth location L5, prioritizing the use of the fewest available depth locations, followed by minimizing the remaining capacity of depth locations. When multiple identical depth locations are matched, depth locations at the same level are prioritized, and the correspondence between depth level and inventory level is maintained according to the aforementioned inventory management rules. Finally, the set of depth locations SW4 that SKW5 can use is calculated. SKW5 is designated as the source location, and the empty location SKW6 within SW4 is designated as the target location, resulting in a successfully matched combination L7 and an unmatched batch inventory set L8. The remaining inventory locations are then matched and combined with available depth locations to rationally utilize available depth locations. Incomplete or partially filled depth locations are moved to available depth locations, freeing up more depth locations and improving inventory utilization.

[0047] S23. Merge the successfully matched combinations L5 and L7 to obtain the first deep-bit matching combination L8, generate the database management task, and assign the four-way shuttle car to perform the database management operation.

[0048] Specifically, the successfully matched combinations L5 and L7 are merged to obtain a deep-position matching combination L8. The source and target storage locations in L8 are grouped according to their respective depth levels, into same-level and cross-level groups. After grouping, storage management tasks are generated for each group. Same-level storage management tasks are prioritized, followed by cross-level tasks, and then a four-way shuttle is assigned to perform the storage management operation. Grouping same-level and cross-level tasks and prioritizing same-level tasks before cross-level tasks effectively utilizes the four-way shuttle, avoiding frequent switching between same-level and cross-level operations, thus saving power resources and improving storage management efficiency.

[0049] S3: When the deep storage utilization rate reaches the threshold, filter out the batch inventory included in the pending outbound operation order from the unmatched batch inventory. Then, perform deep storage mixed placement aggregation to obtain a second deep storage matching combination. Generate a warehouse management task based on the second deep storage matching combination and assign a four-way shuttle to perform the warehouse management operation. This step includes the following sub-steps: S31. When the deep space utilization rate reaches the threshold, filter out the batch goods inventory contained in the pending outbound operation order from the unmatched batch goods inventory to obtain the inventory of the third-level goods. Specifically, according to the formula: Deep space utilization rate = Number of deep spaces with inventory / Total number of deep spaces, when the deep space utilization rate reaches the threshold N, the inventory set L8 containing unmatched batches of goods is filtered out, and the lowest-level set of unfilled deep space batches of goods inventory LL1 is obtained based on the corresponding inventory level. This design for deep space utilization ensures that deep inventory management is triggered only when there are insufficient deep spaces, releasing more deep spaces and improving warehouse capacity utilization. Simultaneously, inventory management is only performed on the lowest-level inventory, minimizing the impact on outbound efficiency.

[0050] S32. The inventory of the three-level goods is subjected to multiple deep-position mixing and aggregation without restriction on batches and goods to obtain a second deep-position combination; Specifically, for the batch inventory set LL1, the batch and product attributes are removed and matched and aggregated. First, matching and aggregation are performed within LL1, then the current free depth space L9 is queried, and finally, matching and aggregation are performed with the free depth space L9 to obtain the depth space combination LL2. There are no restrictions on batch and product depth space mixing and aggregation, which can free up more depth spaces and improve warehouse capacity utilization.

[0051] S4: Based on the pending outbound order, query the depth of the mixed batch of goods inventory in the warehouse, query for available storage locations, and perform a reverse loading operation on the mixed storage locations to move the mixed batch of goods inventory to an available storage location or the outermost storage location of the mixed storage locations. This step includes the following sub-steps: S41. Based on the pending outbound order data, query the depth K1 of mixed batches of goods in the warehouse, and locate the obstructing goods inventory G1 that needs to be moved in the depth K1 according to the depth location order. Specifically, the system queries the current pending outbound order data to obtain the order batch goods details. Based on the goods details, it locates the required batch goods inventory and finds the deep location K1 for mixed batch goods. The inventory within deep location K1 is sorted according to the last-in-first-out (LIFO) order to obtain the deep location inventory set KC1. The system then locates the required batch goods inventory KC within deep location K1. If KC is at the beginning of deep location inventory set KC1, no processing is performed. If KC is not at the beginning of deep location inventory set KC1, the inventory is extracted from the first position of KC1 up to the position containing KC, obtaining the blocking goods inventory G1 within deep location K1 that needs to be moved. Based on the pending outbound order data, the system quickly locates the batch goods inventory to be shipped and determines whether there are mixed batch goods blocking the inventory, providing a basis for further moving the batch goods inventory to be shipped to an empty storage location or the outermost deep location.

[0052] S42. Based on the absolute position of the deep position, the deep position K1 is matched with the free deep position in the same layer first, and then the free deep position across layers is matched. The blocked goods inventory G1 is matched to the free deep position in sequence to obtain the matching combination G2 of the blocked goods inventory and the free deep position. The relocation task is generated based on the obtained matching combination G2, and the four-way shuttle is assigned to perform the relocation operation. Specifically, the layer number of depth K1 is queried, all available depth positions KS are obtained, and the available depth positions KS are grouped into intra-layer available depth positions KS1 and cross-layer available depth positions KS2. Based on the number of storage locations of the blocked goods inventory G1, first, from the intra-layer available depth positions KS1, the number of available depth positions equal to the number of storage locations of G1 is obtained in priority -> the number of available depth positions greater than the number of storage locations of G1 is obtained -> the storage locations of G1 are matched with the storage locations of available depth positions in KS1, according to the last-in-first-out storage location order. After the intra-layer matching is completed, the remaining unmatched blocked goods inventory is matched with the storage locations of available depth positions in cross-layer KS2, finally obtaining the matching combination G2 of blocked goods inventory G1 and available depth positions. G1 is sorted in ascending order by storage location, and G2 is sorted in descending order by storage location. The source storage location is the storage location of G1 after sorting by storage location in ascending order, and the target storage location is the storage location of G2 after sorting by storage location in descending order. The source storage location corresponds to the target storage location, and a transfer task is generated. When there are sufficient empty storage spaces, move goods awaiting shipment from mixed batches to empty storage spaces in advance to improve shipment efficiency. Prioritize matching with storage spaces on the same floor; if storage spaces on the same floor are insufficient, match with storage spaces on different floors to improve inventory management efficiency.

[0053] S43. When there are no available deep storage locations, first match the same-level deep storage locations with available storage locations according to priority, and then match the cross-level deep storage locations with available storage locations. Match the blocked goods inventory G1 to the deep storage locations with available storage locations according to the inventory order to obtain the matching combination G3 of the blocked goods inventory and the deep storage locations with available storage locations. Generate the first transfer task R1 based on the obtained matching combination G3. Then, swap the target storage location and the source storage location of the first transfer task R1, and arrange the target storage locations in reverse order to generate the second transfer task R2. First, assign the four-way shuttle car to perform the transfer operation of the first transfer task R1. After the transfer operation is completed, assign the four-way shuttle car to perform the transfer operation of the second transfer task R2 to achieve the transfer of mixed batch goods G1 to the outermost layer of the deep storage location.

[0054] Specifically, when S42 does not find any available deep storage locations, it queries deep storage locations with available locations and groups them into deep storage locations with available locations at the same level (KS3) and deep storage locations with available locations across levels (KS4). The blocked goods inventory G1 is matched with KS3 at the same level according to the last-in-first-out (LIFO) storage location order. After the same-level matching is completed, the remaining unmatched blocked goods inventory is matched with KS4 at the cross-level, resulting in a matching combination G3 of blocked goods inventory G1 and deep storage locations with available locations. G1 is sorted in ascending order by storage location, and G3 is sorted in descending order by storage location. The source storage location is the storage location after G1 is sorted in ascending order, and the target storage location is the storage location after G3 is sorted in descending order. The source storage location corresponds to the target storage location, generating the first shift task R1. Next, the target and source storage locations of the first relocation task R1 are swapped, and the target storage locations are arranged in reverse order to generate the second relocation task R2. The first relocation task R1 is first assigned to a four-way shuttle for the relocation operation. After the relocation operation is completed, the second relocation task R2 is assigned to a four-way shuttle for the relocation operation, thus moving the mixed batch goods G1 to the outermost layer of the deep storage location. In the absence of available deep storage locations, temporary vacant storage locations are fully utilized to move goods awaiting shipment from the deep storage location of the mixed batch goods to the outermost layer of the deep storage location in advance, thereby improving outbound efficiency.

[0055] As described in the above embodiments, this application integrates dynamic assessment and grading, inventory matching strategy, mixed placement strategy, and intelligent relocation technology. By analyzing real-time inventory age and outbound interval data, combined with preset rules, it performs tiered management of goods inventory and storage depth. A matching algorithm aggregates batches of goods requiring inventory management with available deep storage locations, generating optimal tasks and assigning them to a four-way shuttle for execution. When the utilization rate of deep storage locations exceeds a threshold, it automatically filters outbound orders and implements mixed placement aggregation to improve space utilization. Using a palletizing operation, mixed goods are moved to available or outer storage locations, reducing operational interference. This overcomes the problem of low space utilization in traditional automated storage systems, especially in multi-deep storage scenarios where manual intervention costs are high. This device shortens goods storage and retrieval time and improves efficiency through inventory management strategies and intelligent relocation. The mixed placement strategy is automatically activated when deep storage locations are scarce, maximizing storage density, reducing idle areas, and enhancing space utilization. It reduces manual intervention, achieves automated inventory management, improves overall warehouse turnover, and reduces operating costs.

[0056] Corresponding to the aforementioned embodiment of a method for arranging multiple depths in an automated storage and retrieval system, this application also provides an embodiment of an apparatus for arranging multiple depths in an automated storage and retrieval system.

[0057] Figure 2 This is a block diagram of an automated storage and retrieval system (AS / RS) with multiple depths, according to an exemplary embodiment. (Refer to...) Figure 2 The device includes: The assessment and grading module 1 is used to grade the inventory of batch goods based on the inventory age, the time since the last shipment, and the average time interval between shipments; query all available storage spaces and grade them according to their depth; and obtain the batch goods inventory that needs to be managed based on the storage priority and storage depth range of the inventory level and storage depth configured in the management rules. The inventory management strategy module 2 is used to aggregate inventory management based on the batch of goods inventory and available deep space required for inventory management, to obtain a first deep space matching combination and unmatched batch of goods inventory, to generate an inventory management task based on the first deep space matching combination, and to assign a four-way shuttle car to perform inventory management operation. The mixed placement strategy module 3 is used to filter out the batch goods inventory contained in the pending outbound operation order from the unmatched batch goods inventory when the deep position utilization rate reaches the threshold, and then perform deep position mixed placement aggregation to obtain a second deep position matching combination. Based on the second deep position matching combination, a warehouse management task is generated and a four-way shuttle car is assigned to perform the warehouse management operation. The intelligent shifting module 4 is used to query the depth of mixed batch goods inventory in the warehouse according to the order to be shipped out, query the depth of the mixed batch goods inventory, and perform a reverse operation on the mixed depth to move the mixed batch goods inventory to the empty depth or the outermost depth of the mixed depth.

[0058] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0059] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0060] Accordingly, this application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; and, when the one or more programs are executed by the one or more processors, causing the one or more processors to implement the method described above for an automated three-dimensional library with multiple depths. Figure 3 The diagram shown is a hardware structure diagram of any device with data processing capabilities, which is part of an automated three-dimensional warehouse multi-depth storage device provided in an embodiment of the present invention. Except for... Figure 3In addition to the processor, memory, DMA controller, disk, and non-volatile memory shown, any data processing device in the embodiment may also include other hardware depending on the actual function of the data processing device, which will not be described in detail here.

[0061] Accordingly, this application also provides a computer-readable storage medium storing computer instructions, which, when executed by a processor, implement the method for automating multi-depth spatial storage of an automated three-dimensional library as described above. The computer-readable storage medium can be an internal storage unit of any data-processing device as described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium can also be an external storage device, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc., equipped on the device. Furthermore, the computer-readable storage medium can include both internal storage units of any data-processing device and external storage devices. The computer-readable storage medium is used to store the computer program and other programs and data required by the data-processing device, and can also be used to temporarily store data that has been output or will be output.

[0062] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this application are indicated by the claims.

[0063] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for automated storage and retrieval of multi-depth locations in a three-dimensional warehouse, characterized in that, Including: Classify the inventory of batch goods according to the age of the inventory, the time since the last outbound, and the average outbound interval; query all idle deep positions and classify the deep positions; Obtain the inventory of batch goods that need to be sorted according to the storage corresponding priorities and sorting deep position ranges of the inventory levels and deep position levels configured according to the sorting rules; According to the inventory of batch goods that need to be sorted and the idle deep positions, perform sorting aggregation to obtain the first deep position matching combination and the inventory of batch goods that are not successfully matched. Generate a sorting task according to the first deep position matching combination and assign a four-way shuttle vehicle to perform sorting operations; When the deep position utilization rate reaches the threshold, filter out the inventory of batch goods included in the outbound operation orders to be processed from the inventory of batch goods that are not successfully matched, and then perform deep position mixed storage aggregation to obtain the second deep position matching combination. Generate a sorting task according to the second deep position matching combination and assign a four-way shuttle vehicle to perform sorting operations; According to the outbound operation order to be processed, query the deep positions of the mixed storage inventory of batch goods in the warehouse, query the deep positions with idle storage locations, perform a reverse pallet operation on the mixed deep positions, and shift the mixed storage inventory of batch goods to the idle deep positions or the outermost storage locations of the mixed deep positions.

2. The method for automated multi-depth spatial storage of a three-dimensional warehouse according to claim 1, characterized in that, Classify the inventory of batch goods according to the age of the inventory, the time since the last outbound, and the average outbound interval, including: Statistically calculate the age of the inventory of batch goods, the time since the last outbound, and the average outbound interval, and then perform standardization processing; Calculate the comprehensive score Score for each inventory of batch goods, where Score = w1×standardized value of inventory age + w2×standardized value of average outbound interval + w3×standardized value of time since the last outbound, and w1, w2, w3 are user-defined weight ratios; Classify the inventory of batch goods into multiple levels according to the comprehensive score.

3. The method for automated multi-depth spatial storage of a three-dimensional warehouse according to claim 1, characterized in that, Query all idle deep positions and classify the deep positions, including:

4. The method for automated multi-depth spatial storage of a three-dimensional warehouse according to claim 1, characterized in that, Query all idle deep positions L3, and classify the deep positions into multiple deep position levels according to the positions of the corresponding outbound ports of the deep positions.

5. The method for automated multi-depth spatial storage of a three-dimensional warehouse according to claim 1, characterized in that, The inventory levels are divided into first level, second level, and third level; the deep position levels are divided into fast, normal, and slow speed. The storage corresponding priorities of the inventory levels and deep position levels are: the first level priority corresponds to fast deep positions to normal deep positions and then to slow deep positions, the second level priority corresponds to normal deep positions to slow deep positions, and the third level priority corresponds to slow deep positions to normal deep positions. Obtain the inventory of batch goods that need to be sorted according to the storage corresponding priorities and sorting deep position ranges of the inventory levels and deep position levels configured according to the sorting rules, including: According to the sorting rules, screen out the set L1 of N2 types of deep position batch goods inventories with a full storage rate < N1%; screen out the set L2 of N3 types of small deep position batch goods inventories with a full storage rate of 100%; N1, N2, and N3 are all configured and defined according to the sorting rules; 6. The method for automated multi-depth spatial storage of a three-dimensional warehouse according to claim 1, characterized in that, Query the current outbound order to be processed and mark the inventory levels of the batch goods required in the order as the first level. According to the inventory of batch goods that need to be sorted and the idle deep positions, perform sorting aggregation to obtain the first deep position matching combination and the inventory of batch goods that are not successfully matched, including: For the batch of goods inventory that needs to be managed, and all available deep positions L3, priority is given to matching within the same layer and then cross-layer matching is performed to finally obtain the first deep position combination L5 and the set of deep position batch goods inventory L6 that failed to match. The batch inventory that needs to be managed includes a deep batch inventory set L1 and a small deep batch inventory set L2.

7. The method for automated multi-depth spatial storage of a three-dimensional warehouse according to claim 1, characterized in that, When the deep-position utilization rate reaches a threshold, the batch goods inventory included in the pending outbound operation orders is filtered out from the unmatched batch goods inventory. Then, deep-position mixed placement aggregation is performed to obtain a second deep-position matching combination, including: When the deep inventory utilization rate reaches the threshold, the batch inventory contained in the pending outbound operation order is filtered out from the unmatched batch inventory to obtain the inventory of the third-level goods. The inventory of the three-level goods is subjected to multiple deep-position mixing and aggregation without restriction on batches and goods to obtain a second deep-position combination.

8. The method for automated multi-depth spatial storage of a three-dimensional warehouse according to claim 1, characterized in that, Based on the pending outbound order, the depth of the mixed batch of goods inventory in the warehouse is retrieved. If there are available storage locations, a reverse transfer operation is performed on the mixed storage locations to move the mixed batch of goods inventory to an available storage location or the outermost storage location of the mixed storage locations. This includes: Based on the pending outbound order data, query the depth K1 of mixed batches of goods in the warehouse, and locate the obstructing goods inventory G1 that needs to be moved within the depth K1 according to the depth location order. Based on the absolute position of the depth position, depth position K1 is matched with the free depth position in the same layer first, and then the free depth position across layers is matched. The blocked goods inventory G1 is matched to the free depth position in sequence to obtain the matching combination G2 of blocked goods inventory and free depth position. The relocation task is generated based on the obtained matching combination G2, and the four-way shuttle is assigned to perform the relocation operation. When there are no available deep storage locations, priority is given to first matching deep storage locations on the same level with available locations, and then matching deep storage locations across levels with available locations. The blocked goods inventory G1 is matched to deep storage locations with available locations according to the inventory order, resulting in a matching combination G3 between the blocked goods inventory and deep storage locations with available locations. Based on the obtained matching combination G3, the first relocation task R1 is generated. Then, the target location and source location of the first relocation task R1 are swapped, and the target locations are arranged in reverse order to generate the second relocation task R2. The first relocation task R1 is first assigned to a four-way shuttle car for relocation operations. After the relocation operations are completed, the second relocation task R2 is assigned to a four-way shuttle car for relocation operations, thereby realizing the relocation of mixed batch goods G1 to the outermost layer of deep storage locations.

9. A device for an automated three-dimensional warehouse with multiple depths, characterized in that, include: The assessment and grading module is used to grade the inventory of a batch of goods based on the age of the inventory, the time since the last shipment, and the average time interval between shipments; it also queries all available storage spaces and grades them according to their depth. Based on the storage priority and storage depth range of the inventory level and depth configured in the inventory management rules, the inventory of the batch of goods that need to be managed is obtained. The inventory management strategy module is used to aggregate inventory management data based on the batch of goods inventory and available deep storage space required for inventory management, obtain a first deep storage space matching combination and unmatched batch of goods inventory, generate an inventory management task based on the first deep storage space matching combination, and assign a four-way shuttle car to perform inventory management operations. The mixed placement strategy module is used to filter out the batch goods inventory contained in the pending outbound operation order from the unmatched batch goods inventory when the deep position utilization rate reaches the threshold. Then, deep position mixed placement aggregation is performed to obtain a second deep position matching combination. Based on the second deep position matching combination, a warehouse management task is generated and a four-way shuttle car is assigned to perform the warehouse management operation. The intelligent shifting module is used to query the depth of mixed batches of goods inventory in the warehouse according to the order to be shipped out, and to perform a reverse shifting operation on the mixed batches of goods inventory to an empty depth or the outermost depth of the mixed depth.

10. An electronic device, characterized in that, include: One or more processors; Memory, used to store 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 1-8.

11. A computer-readable storage medium storing computer instructions thereon, characterized in that, When executed by the processor, this instruction implements the steps of the method as described in any one of claims 1-8.

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