Stacked storage material arrangement task hierarchical scheduling method based on structural conflict identification

Abstract

The application provides a kind of based on structure conflict identification's stacking storage material arrangement task grading scheduling method.Application in intelligent warehousing technical field, the method includes obtaining the stacking state data of each storage unit in stacking storage area;Based on stacking state data traverses each storage unit, determine whether there is the inverse order state of bottom layer material plan time earlier than upper layer covering material, if there is, it is determined that the storage unit exists structure conflict, and based on the time difference value of inverse order material and hierarchical difference value calculate blocking urgency coefficient;The material displacement operation of removing conflict is set as candidate arrangement task, according to the comparison result of blocking urgency coefficient and grading threshold value determines task level;Generate task scheduling queue with execution sequence, to maximize the goal of eliminating high blocking urgency coefficient, control execution mechanism to material grading scheduling arrangement.

Description

Technical Field

[0001] This invention relates to the field of intelligent warehousing technology, and in particular to a hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification. Background Technology

[0002] Due to its core advantages of high space utilization and low warehouse deployment cost, dense stacked storage is widely used in various warehousing scenarios such as flat warehouses and automated storage and retrieval systems, and has become one of the mainstream storage modes for high-density warehousing operations.

[0003] In stacked storage scenarios, the vertical stacking structure of materials directly affects the smoothness and efficiency of outbound operations, necessitating pre-emptive sorting task scheduling to eliminate potential outbound congestion. Existing stacked storage material sorting scheduling solutions often rely solely on the planned outbound times of materials, failing to adequately consider the structural constraints imposed by the vertical hierarchy of materials in stacked storage. This makes it impossible to accurately identify reverse-order conflicts where the planned outbound time of bottom-layer materials precedes that of upper-layer materials, nor can it quantify the impact of such conflicts on subsequent outbound operations. Furthermore, existing solutions lack scientific hierarchical management of sorting tasks, leading to issues such as low-priority tasks consuming core operational resources and high-urgency conflicts remaining unresolved in a timely manner. This results in ineffective relocation and repeated stacking during the outbound process, increasing operational time and equipment wear, ultimately leading to low efficiency in hierarchical scheduling of stacked storage material sorting tasks. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides a hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification.

[0005] According to a first aspect of the present invention, a hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification is provided. The method includes: Obtain the stacking status data of each storage unit in the current stacked storage area. The stacking status data includes at least the vertical hierarchical position of the material, the unique identifier of the material, and the associated planned outbound time. Based on the stacking state data, each storage unit is traversed to determine whether there is a reverse state where the planned outbound time of the bottom material is earlier than the planned outbound time of the material covering it. If so, it is determined that there is a structural conflict in the storage unit, and the obstruction urgency coefficient of the structural conflict is calculated based on the time difference and the hierarchical difference between the bottom material and the material covering it that caused the reverse state. The material relocation operation required to resolve the structural conflict is defined as a candidate sorting task, and the task level of the candidate sorting task is determined based on the comparison result between the obstruction urgency coefficient and the preset grading threshold. Based on the task level of the candidate sorting tasks, a task scheduling queue containing the execution order is generated, and with the goal of maximizing the elimination of high obstruction and urgency coefficients, the execution mechanism is controlled to perform graded scheduling and sorting of materials.

[0006] Furthermore, the calculation of the urgency factor of the structural conflict includes: The bottom material in the reverse order state is identified as the obstructed object, and all the covering materials above it are identified as the stagnant object. Calculate the difference between the planned departure time of the blocked object and the current system time to obtain the remaining operation time window; If the remaining operation time window is less than the preset critical operation cycle, the structural conflict is determined to be in a critical risk state, and the obstruction urgency coefficient is set to the maximum extreme value. If the remaining operation time window is greater than or equal to the critical operation cycle, the urgency coefficient of the obstruction is calculated based on the weighted sum of the hierarchical differences between the obstructed object and each blocked object, combined with the reciprocal of the remaining operation time window.

[0007] Further, determining the task level of the candidate sorting task includes: The preset grading thresholds include a first grading threshold and a second grading threshold, wherein the first grading threshold is greater than the second grading threshold. Determine whether the urgency coefficient corresponding to the candidate sorting task is greater than the first classification threshold. If the obstruction urgency coefficient is greater than the first classification threshold, the candidate sorting task is determined as a first type of hard sorting task. The first type of hard sorting task is used to resolve structural conflicts that directly block recent outbound demand. If the urgency coefficient of the obstruction is between the first grading threshold and the second grading threshold, then the candidate sorting task is determined as a second type of flexible sorting task, which is used to optimize the deep order of the stacked structure.

[0008] Furthermore, the generation of the task scheduling queue containing the execution order includes: All the first type of hard scheduling tasks are sorted in descending order of their respective urgency coefficients to construct the main scheduling sequence. Calculate the estimated resource consumption required to execute the second type of flexible reorganization task, and obtain the current amount of idle resources in the system; If the amount of idle resources is greater than the expected resource usage, then the second type of flexible reorganization task will be inserted into the idle time window of the main scheduling sequence. If the amount of idle resources is less than or equal to the expected resource usage, then only the main scheduling sequence is retained, and the addition of the second type of flexible reorganization task is postponed to ensure that high-priority conflicts are resolved first.

[0009] Further, inserting the second type of flexible reorganization task into the idle time window of the main scheduling sequence includes: Calculate the expected orderliness gain of the target storage unit after the execution of the second type of flexible sorting task; If the expected order gain is less than the preset minimum benefit threshold, the task is determined to be an invalid optimization and is removed from the task set. If the expected order gain is greater than or equal to the preset minimum benefit threshold, it is determined whether executing the task will cause new structural conflicts in neighboring storage units; if it is determined that no chain of negative conflicts will be triggered, the second type of flexible sorting task is finally added to the scheduling queue.

[0010] Furthermore, after the control actuator performs hierarchical scheduling and organization of materials, it also includes: At the end of each execution cycle, the changed stack state data is retrieved again; Determine if a new external inbound task causes the original non-conflicting structure to change into a new reverse state. If so, a new round of structural conflict identification will be conducted, and the newly generated urgency coefficient will be calculated. The newly generated delay urgency coefficient is compared with the coefficient of the unexecuted tasks in the current task scheduling queue. If the newly generated delay urgency coefficient is higher than the delay urgency coefficient of the first task in the queue, the task scheduling queue is preemptively rearranged.

[0011] Furthermore, the traversal of each storage unit includes: When it is determined that a certain storage unit does not have the reverse order state and its stacking dispersion index exceeds a preset dispersion threshold, it is determined that the storage unit has potential efficiency loss; wherein, the stacking dispersion index is used to characterize the degree of dispersion of materials in the same outbound batch in the vertical direction. A pre-sorting task is generated to address the potential efficiency loss, and the urgency coefficient of the pre-sorting task is set to a normalized value calculated based on the stacking dispersion index, so as to incorporate it into a unified task classification judgment.

[0012] Furthermore, the control actuator performs hierarchical scheduling and organization of materials, including: Obtain the current physical location coordinates of the actuator; Calculate the path cost of moving the execution mechanism from its current physical location to the storage unit location corresponding to the candidate sorting task; The task execution efficiency ratio is calculated based on the ratio of the obstruction urgency coefficient to the path cost. Within the same task level, prioritize the sorting task with the highest execution efficiency to maximize the elimination of structural conflicts within a unit of time.

[0013] According to a second aspect of the present invention, an electronic device is provided. The electronic device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the program to implement the method.

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

[0015] This invention acquires stacking status data such as the vertical hierarchical position, unique identifier, and planned outbound time of materials in each storage unit within the stacked storage area. This enables a full traversal judgment of the material outbound sequence and the reverse order of the stacked hierarchy, identifying structural conflicts and improving the efficiency and accuracy of pre-processing risk identification. By calculating the urgency coefficient of structural conflicts based on the time difference and hierarchy difference between the bottom and upper layers of materials in reverse order, and combining this with a preset grading threshold to determine the level of candidate processing tasks, this invention achieves quantitative and precise grading of processing task priorities, improving the rationality of scheduling resource allocation and the efficiency of task grading control. By aiming to maximize the elimination of high urgency coefficients, this invention generates task scheduling queues with execution order according to task level, controls the execution mechanism to complete grading scheduling and processing, minimizes invalid material transfer operations, and pre-emptively resolves outbound obstruction risks, thereby improving the scheduling execution efficiency and overall outbound flow efficiency of the entire stacked material processing process.

[0016] It should be understood that the description in the Summary of the Invention is not intended to limit the key or essential features of the embodiments of the present invention, nor is it intended to restrict the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0017] The above and other features, advantages, and aspects of the various embodiments of the present invention will become more apparent from the accompanying drawings and the following detailed description. The drawings are provided for a better understanding of the invention and are not intended to limit the scope of the invention. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein: Figure 1 A flowchart illustrating a hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification according to an embodiment of the present invention is shown. Figure 2A detailed flowchart illustrating the calculation of the obstruction urgency coefficient of a stacked storage material sorting task hierarchical scheduling method based on structural conflict identification according to an embodiment of the present invention is shown. Figure 3 A detailed flowchart illustrating the generation of a task scheduling queue containing the execution order in a hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification according to an embodiment of the present invention is shown. Figure 4 A detailed flowchart illustrating the hierarchical scheduling of materials in a stacked storage material sorting task based on structural conflict identification, according to an embodiment of the present invention, is shown. Figure 5 A block diagram of an exemplary electronic device capable of implementing embodiments of the present invention is shown. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0020] Figure 1 A flowchart of a hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification according to an embodiment of the present invention is shown. The method includes: S101, Obtain the stacking status data of each storage unit in the current stacked storage area. The stacking status data includes at least the vertical hierarchical position of the material, the unique identifier of the material, and the associated planned outbound time. In some embodiments, the stacked storage area is a three-dimensional warehouse area that uses vertical stacking to store materials, and the storage unit is an independent storage location in the warehouse area for storing a single set of stacked materials. The vertical hierarchy position is determined by sequentially increasing the number from bottom to top, with the supporting bottom surface of the storage unit as the reference surface.

[0021] S102, based on the stacking state data, traverse each storage unit to determine whether there is a reverse state where the planned outbound time of the bottom material is earlier than the planned outbound time of the material covering the upper layer; if there is, determine that there is a structural conflict in the storage unit, and calculate the obstruction urgency coefficient of the structural conflict based on the time difference and hierarchical difference between the bottom material and the material covering the upper layer that generated the reverse state. In some embodiments, the determination of the reverse order state is based on the vertically stacked materials within the same storage unit. The outbound time is compared for each pair of adjacent materials. When the planned outbound time of any lower-level material is earlier than that of the upper-level material, it is determined that there is a reverse order state.

[0022] In some embodiments, the time difference is the absolute difference between the planned outbound time of the bottom layer material and the planned outbound time of the top layer covering material, and the level difference is the difference in the level number of the bottom layer material and the top layer covering material in the vertical direction.

[0023] S103, the material relocation operation required to resolve the structural conflict is defined as a candidate sorting task, and the task level of the candidate sorting task is determined based on the comparison result between the obstruction urgency coefficient and the preset grading threshold. In some embodiments, the material relocation operation required to resolve structural conflicts refers to the transfer of all or part of the upper covering material that is blocking the bottom layer from leaving the warehouse to the target storage location, so that the blocked material can be left without hindrance before the planned time of leaving the warehouse.

[0024] S104, based on the task level of the candidate sorting tasks, generate a task scheduling queue containing the execution order, and control the execution mechanism to perform graded scheduling and sorting of materials with the goal of maximizing the elimination of high obstruction urgency coefficient.

[0025] In some embodiments, the actuator is an automated handling device configured in the stacked storage area that can perform vertical picking and placing and horizontal transfer of materials. The hierarchical scheduling and sorting refers to allocating the operating resources of the actuator to complete the corresponding sorting task in order of priority from high to low according to the task level.

[0026] In some embodiments, Figure 2This document illustrates a detailed flowchart of a hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification, according to an embodiment of the present invention. The method involves calculating the obstruction urgency coefficient of a structural conflict, including: identifying the bottom-layer material in a reverse-order state as the obstructed object, and all covering materials above it as obstruction objects; wherein the obstructed object is the bottom-layer material in the reverse-order state whose planned outbound time is earlier than the upper-layer material, and the obstruction object is all directly stacked materials directly above the obstructed object that would hinder its direct outbound movement; calculating the difference between the planned outbound time of the obstructed object and the current system time to obtain the remaining operation time window; wherein the current system time is the real-time system time used for structural conflict identification and obstruction urgency coefficient calculation, and the remaining operation time window is the longest available time for the obstructed object to complete the pre-outbound sorting operation; if the remaining... If the operation time window is less than the preset critical operation cycle, the structural conflict is determined to be in a critical risk state, and the obstruction urgency coefficient is set to its maximum value. The critical operation cycle is the preset longest standard operation time required to resolve a single structural conflict, and the maximum value is a fixed value exceeding the highest level threshold in the hierarchical threshold system, used to ensure that tasks in a critical risk state receive the highest execution priority. If the remaining operation time window is greater than or equal to the critical operation cycle, the obstruction urgency coefficient is calculated based on the weighted sum of the hierarchical differences between the obstructed object and each obstructed object, combined with the reciprocal of the remaining operation time window. The weighting of the hierarchical differences is positively correlated with the hierarchical differences; that is, the larger the hierarchical difference between the obstructed object and the obstructed object, the higher the corresponding weight, reflecting the higher operational difficulty and obstruction impact caused by multi-layered stacking obstruction. According to embodiments of the present invention, by clearly defining the obstructed object and the blocked object, the scope of conflict impact can be accurately locked, improving the pertinence of coefficient calculation; by calculating the remaining operation time window, the urgency of outbound delivery can be quantitatively represented, improving the sensitivity of risk identification; and by using scenario-specific coefficient calculation rules, critical risks can be prioritized and mitigated, improving the accuracy of urgency quantification.

[0027] For example, setting the current system time to 08:00 on March 27, 2026, the stacked storage area is an e-commerce FMCG automated warehouse, the maximum vertical stacking level of a single storage unit is 8 layers, and the layer numbers are 1-8 from bottom to top of the supporting bottom surface. The preset critical operation cycle for resolving a single set of structural conflicts is 30 minutes, and the maximum extreme value of the obstruction urgency coefficient is fixed at 100; for storage unit A01-03, its stacking status data is as follows: Layer 1 (bottom layer) material unique identifier SKU0012, planned outbound time 08:20 on March 27, 2026; Layer 2 material SKU0045, planned outbound time 14:00 on March 27, 2026; Layer 3 material SKU0067, planned outbound time 08:20 on March 27, 2026. 16:00; Level 4 material SKU0089, planned outbound time 2026-03-27 18:00; It was determined that the storage unit is in a reverse order state, and the blocked object is identified as Level 1 material SKU0012, and the blocked objects are all materials in Levels 2, 3, and 4 directly above the blocked object; The remaining operation time window is calculated to be 08:20-08:00=20 minutes. 20 minutes < the preset critical operation cycle of 30 minutes, so the structural conflict is determined to be in a critical risk state, and its blocking urgency coefficient is set to the maximum extreme value of 100; For storage unit A02-05, its stacking status data is: Level 1 material SKU0101, planned outbound time 2026-03-27 At 09:30, the current system time is still 08:00, and the remaining operation time window is 90 minutes > 30 minutes. The obstructed object is SKU0101 of level 1. The blocked objects are materials of level 2 (level difference 1 with the obstructed object), level 3 (level difference 2 with the obstructed object), and level 4 (level difference 3 with the obstructed object) directly above. The weighted weight of the level difference is positively correlated with the level difference. The weight of level difference 1 is set to 1, level difference 2 to 1.5, and level difference 3 to 2. The weighted sum of the level differences is 1×1 + 2×1.5 + 3×2 = 10. The final calculated obstruction urgency coefficient is (10÷90)×100≈11.11.

[0028] In some embodiments, determining the task level of the candidate sorting task includes: the preset grading thresholds include a first grading threshold and a second grading threshold, wherein the first grading threshold is greater than the second grading threshold; wherein the first grading threshold and the second grading threshold are grading boundary values ​​pre-defined based on the frequency of outbound operations in the stacked storage area, the operating capacity of the actuator, and the material turnover characteristics of the storage area, used to classify sorting tasks of different urgency levels; determining whether the obstruction urgency coefficient corresponding to the candidate sorting task is greater than the first grading threshold; if the obstruction urgency coefficient is greater than the first grading threshold, then the candidate sorting task is determined as a first-class hard sorting task, which is used for... This invention addresses structural conflicts that directly hinder recent outbound demand. The first type of mandatory sorting task is a forced task that must be completed within the remaining time window of the blocked object, with a higher execution priority than all non-mandatory tasks and regular warehouse inbound / outbound operations. If the obstruction urgency coefficient is between the first and second grading thresholds, the candidate sorting task is classified as a second type of flexible sorting task. This second type of flexible sorting task optimizes the deep orderliness of the stacking structure. The second type of flexible sorting task is a non-mandatory, immediate-execution optimization task with a lower execution priority than the first type of mandatory sorting task, and is scheduled only without affecting the execution of mandatory tasks and regular inbound / outbound operations. According to this embodiment, the dual-threshold grading rule achieves precise grading of sorting tasks, improving the targeting of scheduling strategies; the definition of mandatory sorting tasks ensures priority protection for recent outbound conflicts, improving the timeliness of outbound operations; and the division of flexible sorting tasks achieves long-term optimization of the stacking structure, improving the overall efficiency of warehouse scheduling.

[0029] For example, the first tier threshold is preset to 80 and the second tier threshold is preset to 50. These two thresholds are pre-calibrated based on the warehouse's daily outbound operation frequency of 1200 orders, the stacker crane's operation capacity of 8 times per hour, and the average turnover characteristics of fast-moving consumer goods over 3 days. For the candidate sorting task corresponding to the aforementioned storage location A01-03, its urgency coefficient is 100, which is greater than the first tier threshold of 80. Therefore, this task is classified as a first-class hard sorting task. This task is a mandatory task that must be completed within the 20-minute remaining operation time window of SKU0012. Its execution priority is higher than all non-hard tasks and regular warehouse inbound and outbound operations. For the candidate sorting task corresponding to storage location B02-06, its urgency coefficient is 65. 65 is between the first tier threshold of 80 and the second tier threshold of 50. Therefore, this task is classified as a second-class flexible sorting task. This is a non-mandatory, immediate stacking structure optimization task. Its execution priority is lower than the first-class hard sorting task. It is only scheduled and executed on the premise of not affecting the execution of hard tasks and regular inbound and outbound operations.

[0030] In some embodiments, Figure 3 This document illustrates a detailed flowchart of a hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification, according to an embodiment of the present invention, for generating a task scheduling queue containing an execution order. The method includes: sorting all first-type hard sorting tasks in descending order of their respective urgency coefficients to construct a main scheduling sequence; calculating the estimated resource occupancy required to execute the second-type flexible sorting tasks, and obtaining the current idle resource quantity of the system; wherein the estimated resource occupancy is the execution time and equipment capacity quota required to complete a single group of second-type flexible sorting tasks, and the idle resource quantity is the remaining resource quantity after the system meets the requirements of the main scheduling sequence execution and regular inbound / outbound operations. The available execution time and capacity quota of the schedulable execution mechanism; if the idle resource amount > the expected resource occupancy, then the second type of flexible reorganization task is inserted into the idle time window of the main scheduling sequence; wherein, the idle time window is the schedulable time interval between two adjacent hard reorganization tasks in the main scheduling sequence, without other mandatory operation requirements; if the idle resource amount ≤ the expected resource occupancy, then only the main scheduling sequence is retained, and the addition of the second type of flexible reorganization task is postponed to ensure that high-priority conflicts are resolved first; wherein, the postponement refers to temporarily storing the second type of flexible reorganization task in the task pool to be executed, and re-matching resources and making admission judgments when the scheduling queue is updated next time. According to the embodiments of the present invention, by sorting hard tasks in descending order, priority scheduling of high-urgent conflicts is achieved, improving the efficiency of eliminating core risks; by comparing resource occupancy and idle amount, reasonable management of system resources is achieved, improving resource utilization; by flexibly inserting idle time windows, structural optimization is achieved under the premise that the main task is not disturbed, improving the stability of scheduling.

[0031] For example, the current system identifies three groups of Category I hard-response tasks, with corresponding urgency coefficients of 100, 92, and 85, respectively. Sorted in descending order of coefficient, the main scheduling sequence is: task with coefficient 100 → task with coefficient 92 → task with coefficient 85. The execution order of tasks within this main scheduling sequence cannot be preempted by other tasks with lower priority than Category I tasks. Calculations show that the estimated execution times for the three groups of tasks are 25 minutes, 20 minutes, and 22 minutes, respectively, with an 18-minute idle time window between adjacent tasks where there is no mandatory work requirement. For a single group of Category II flexible-response tasks, the required time to complete them is calculated... The estimated resource consumption is 15 minutes of stacker crane operation time and full capacity quota. After satisfying the main scheduling sequence and regular inbound and outbound operations, the system currently has 18 minutes of available idle resources for operation time and corresponding capacity quota. If 18 minutes > 15 minutes, the second type of flexible sorting task will be inserted into the 18-minute idle time window of the main scheduling sequence. If the current idle resources of the system are only 10 minutes of operation time and 10 minutes < 15 minutes, only the main scheduling sequence will be retained, and the second type of flexible sorting task will be temporarily stored in the task pool to be executed, and postponed until the next scheduling queue update to re-match resources and make admission judgments.

[0032] In some embodiments, inserting the second type of flexible sorting task into the idle time window of the main scheduling sequence includes: calculating the expected orderliness gain of the target storage unit after the execution of the second type of flexible sorting task; wherein, the expected orderliness gain is the increase in the percentage of materials in the target storage unit stacked in ascending order from bottom to top according to the planned outbound time after the execution of the flexible sorting task, compared to the percentage of materials stacked in ascending order before execution; if the expected orderliness gain is less than a preset minimum benefit threshold, then the task is determined to be an invalid optimization and removed from the task set; wherein, the minimum benefit threshold is a preset threshold. A minimum order enhancement margin is defined for a flexible sorting task to have execution value, used to filter redundant operations with no substantial optimization effect. If the expected order gain is greater than or equal to a preset minimum benefit threshold, it is determined whether executing the task will cause new structural conflicts in adjacent storage units. If it is determined that no chain of negative conflicts will occur, the second type of flexible sorting task is finally added to the scheduling queue. The adjacent storage unit is the storage unit to which the target storage location belongs in the material relocation operation of the flexible sorting task belongs, and the chain of negative conflicts refers to the situation where the material relocation operation causes a new reverse order state in the storage unit to which the target storage location belongs. According to the embodiments of the present invention, by calculating the expected order gain, the benefit prediction of flexible tasks is realized, avoiding resource consumption of ineffective operations; by screening with the minimum benefit threshold, low-value tasks are eliminated, improving the cost-effectiveness of optimization operations; by pre-judging chain conflicts, new risks are avoided in advance, improving the overall stability of the warehouse structure.

[0033] For example, the minimum benefit threshold for determining the execution value of a flexible sorting task is preset to 20%. For the second type of flexible sorting task to be inserted, the material forward stacking ratio of the target storage unit before execution is 40%. After executing the task, the expected forward stacking ratio of the target storage unit is 75%. The calculated expected order gain is 75% - 40% = 35% > 20%, so the task is determined to have execution value. Further verification shows that the target storage location for the material relocation task is storage unit B03-08. The planned outbound time of the current top layer material in this storage unit is 2026-03-27 20:00, and the planned outbound time of the material to be moved is 2026-03-27 17:00. After the material is moved, no new reverse order state will be generated, and there will be no chain negative conflicts. Finally, it is confirmed that the second type of flexible sorting task will be added to the scheduling queue. If the expected order gain of a task to be inserted is only 15% < 20%, it is determined to be an invalid optimization and is removed from the task set.

[0034] In some embodiments, after the control actuator performs hierarchical scheduling and sorting of materials, the method further includes: at the end of each execution cycle, re-acquiring the changed stacking status data; wherein the execution cycle is a fixed-duration job scheduling cycle preset by the system, or a node cycle for the completion of a single sorting task, and the changed stacking status data is the updated material stacking information in the storage unit after the sorting operation or inbound / outbound operation is completed; determining whether there is a new external inbound task that causes the original non-conflict structure to change to a new reverse order state; wherein the new external inbound task refers to a new task added within the current scheduling cycle that needs to be stored in the corresponding storage unit. In the material receiving operation, the non-conflict structure refers to the original forward stacking structure without any reverse order. If so, a new round of structural conflict identification is performed, and the newly generated obstruction urgency coefficient is calculated. The newly generated obstruction urgency coefficient is compared with the obstruction urgency coefficient of the unexecuted tasks in the current task scheduling queue. If the newly generated obstruction urgency coefficient is higher than the obstruction urgency coefficient of the first task in the queue, the task scheduling queue is preemptively rearranged. The preemptive rearrangement refers to inserting the newly generated high-urgency task directly to the first position of the task scheduling queue, giving it priority in allocating execution resources, and shifting the unexecuted tasks in the original queue sequentially according to priority. According to the embodiments of the present invention, by updating the stacking state after the execution cycle, the real-time synchronization of the storage state is achieved, improving the timeliness of conflict identification; by determining the reverse order of new receiving tasks, new conflicts are captured in a timely manner, avoiding risk accumulation; and by preemptive queue rearrangement, higher-urgency tasks are prioritized for execution, improving the dynamic adaptability of the scheduling system.

[0035] For example, with a preset execution cycle of 15 minutes, at the end of the first execution cycle at 08:15 on 2026-03-27, the stacking status data after the change of the entire warehouse area is retrieved again. It is verified that the storage unit A04-02 originally had no reverse order status. At 08:10, a new external inbound task is completed, storing material SKU0210 with a planned outbound time of 09:00 on 2026-03-27 into storage location level 1. The planned outbound time of materials in storage location levels 1-3 were all after 12:00 on 2026-03-27. This inbound operation changes the original forward order structure to a new reverse order state. A new round of structural conflict identification is performed, and the obstruction urgency coefficient of the newly generated structural conflict is calculated to be 94. Compared with the obstruction urgency coefficient of 92 of the first unexecuted task in the current task scheduling queue, 94 > 92. Therefore, a preemptive rearrangement is performed on the task scheduling queue, and the newly generated high-urgency task is directly inserted into the first position of the task scheduling queue, and stacker crane execution resources are allocated with priority. Unexecuted tasks in the original queue are moved to the next position according to priority.

[0036] In some embodiments, traversing each storage unit includes: determining that a storage unit has potential efficiency loss when it is determined that the storage unit does not have the reverse order state and its stacking dispersion index exceeds a preset dispersion threshold; wherein, the stacking dispersion index is used to characterize the degree of dispersion of materials in the same outbound batch in the vertical direction; wherein, the same outbound batch is a set of materials whose planned outbound time is within the same preset outbound time interval, and the stacking dispersion index is calculated by the distribution variance of materials in the same outbound batch at the vertical level; generating a pre-sorting task for the potential efficiency loss, and setting the urgency coefficient of the pre-sorting task to a normalized value calculated based on the stacking dispersion index, so as to include it in a unified task classification judgment; wherein, the normalized value is a standardized value that maps the stacking dispersion index to the same numerical range as the urgency coefficient, so that the pre-sorting task can be prioritized using the same classification threshold system as other sorting tasks. According to embodiments of the present invention, by determining the stacking dispersion index, the potential efficiency loss in the state without reverse order can be identified, thus expanding the coverage of scheduling optimization; by generating pre-sorting tasks, the pre-optimization of the storage structure can be achieved, reducing the probability of subsequent conflicts; by setting the normalization coefficient, the pre-sorting tasks and the existing system can be uniformly managed, improving the consistency of scheduling management.

[0037] For example, the preset stacking dispersion threshold is 0.6. The same outbound batch is defined as the set of materials whose planned outbound time is between 14:00 and 16:00 on March 27, 2026. The stacking dispersion index is calculated by the variance of the distribution of materials in the same outbound batch at the vertical level. For storage unit C01-06, after traversal and determination, it is determined that there is no reverse order. The materials in this storage unit belonging to the 14:00-16:00 outbound batch are distributed at levels 1, 3, 5, and 7 respectively. The variance of the hierarchical distribution of this batch of materials is calculated to be 0.72. 0.72 > the preset dispersion threshold of 0.6, indicating that there is potential efficiency loss in this storage unit. A pre-processing task is generated for this potential efficiency loss. The stacking dispersion index of 0.72 is normalized to a value range of 0-100 consistent with the urgency coefficient through linear mapping, resulting in a corresponding urgency coefficient of 42.

[0038] In some embodiments, Figure 4 This document illustrates a detailed flowchart of a hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification, according to an embodiment of the present invention. The method involves: acquiring the current physical location coordinates of the actuator; wherein the current physical location coordinates are the real-time location information of the actuator in the global coordinate system of the stacked storage area, the global coordinate system being established with a fixed reference point in the stacked storage area as its origin and covering the entire operating path range of all storage units and the actuator; calculating the path cost for the actuator to move from its current physical location to the storage unit location corresponding to the candidate sorting task; wherein the path cost is the shortest path required for the actuator to move from its current location to the target storage unit location. The weighted calculation of length, estimated movement time, and obstacle avoidance costs along the path is used to quantify the movement operation cost of performing the task. The task execution efficiency ratio is calculated based on the ratio of the obstruction urgency coefficient to the path cost. The task execution efficiency ratio quantifies the structural obstruction impact that can be eliminated per unit path cost; a higher ratio indicates a higher overall benefit from performing the task. Within the same task level, the task with the highest execution efficiency ratio is prioritized for execution to maximize the elimination of structural conflicts per unit time. The sorting adjustment within the same task level must not change the priority order between different task levels; that is, lower-level tasks, regardless of their efficiency ratio, must not preempt the execution resources of higher-level tasks. According to this embodiment of the invention, the quantification of task execution costs is achieved by calculating the location of the execution mechanism and the path cost, improving the economy of scheduling; the calculation of the task execution efficiency ratio achieves a comprehensive balance between urgency and execution cost, improving the conflict elimination efficiency per unit time; and the efficiency-priority scheduling within the same level achieves optimal resource allocation, improving the overall scheduling execution efficiency.

[0039] For example, a global rectangular coordinate system is established with the fixed reference point in the southwest corner of the storage area as the origin. The unit of the coordinate system is meters, covering all storage units and stacker crane operation paths in the entire storage area. The executing mechanism is an aisle-type stacker crane. When executing the scheduling of the first type of hard sorting task, the current physical position coordinates of the stacker crane are obtained as (12,5,2). There are currently 2 groups belonging to the first type of hard sorting task. Task 1 corresponds to a delay urgency coefficient of 92, and the target storage unit position coordinates are (20,5,3). Its path is calculated. The cost is 8 (shortest path length 8 meters, estimated movement time 12 seconds, no path obstacles, the weighted path cost is 8), and the task execution efficiency ratio is 92÷8=11.5; Task 2 has a corresponding obstruction urgency coefficient of 88, the target storage unit location coordinates are (45,5,3), and its path cost is calculated to be 35, and the task execution efficiency ratio is 88÷35≈2.51; within the same level of the first type of hard organization tasks, Task 1, which has a higher task execution efficiency ratio, is selected for execution first.

[0040] According to embodiments of the present invention, the present invention also provides an electronic device and a readable storage medium.

[0041] Figure 5 A schematic block diagram of an electronic device that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0042] The electronic device includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in ROM 502 or a computer program loaded into RAM 503 from storage unit 508. RAM 503 can also store various programs and data required for the operation of the electronic device. The computing unit 501, ROM 502, and RAM 503 are interconnected via bus 504. An I / O interface 505 is also connected to bus 504.

[0043] Multiple components in the electronic device are connected to the I / O interface 505, including: an input unit 506, such as a keyboard, mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a disk, optical disk, etc.; and a communication unit 509, such as a network interface card, modem, wireless transceiver, etc. The communication unit 509 allows the electronic device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0044] The computing unit 501 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 501 performs the various methods and processes described above, such as the hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification. For example, in some embodiments, the hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program can be loaded and / or installed on an electronic device via ROM 502 and / or communication unit 509. When the computer program is loaded into RAM 503 and executed by the computing unit 501, one or more steps of the hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification described above can be performed. Alternatively, in other embodiments, computing unit 501 may be configured by any other suitable means (e.g., by means of firmware) to perform a hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification.

[0045] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0046] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0047] In the context of this invention, a readable storage medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A readable storage medium can be a machine-readable signal medium or a machine-readable storage medium. A readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0048] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including voice input, speech input, or tactile input).

[0049] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0050] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0051] It should be understood that the various processes described above can be used to rearrange, add, or delete steps. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0052] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification, characterized in that, include: Obtain the stacking status data of each storage unit in the current stacked storage area. The stacking status data includes at least the vertical hierarchical position of the material, the unique identifier of the material, and the associated planned outbound time. Based on the stacking state data, each storage unit is traversed to determine whether there is a reverse state where the planned outbound time of the bottom material is earlier than the planned outbound time of the material covering it. If it exists, it is determined that there is a structural conflict in the storage unit, and the obstruction urgency coefficient of the structural conflict is calculated based on the time difference and hierarchical difference between the bottom material that generates the reverse state and the upper covering material. The material relocation operation required to resolve the structural conflict is defined as a candidate sorting task, and the task level of the candidate sorting task is determined based on the comparison result between the obstruction urgency coefficient and the preset grading threshold. Based on the task level of the candidate sorting tasks, a task scheduling queue containing the execution order is generated, and with the goal of maximizing the elimination of high obstruction and urgency coefficients, the execution mechanism is controlled to perform graded scheduling and sorting of materials.

2. The hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification according to claim 1, characterized in that, The calculation of the urgency factor of the structural conflict includes: The bottom material in the reverse order state is identified as the obstructed object, and all the covering materials above it are identified as the stagnant object. Calculate the difference between the planned departure time of the blocked object and the current system time to obtain the remaining operation time window; If the remaining operation time window is less than the preset critical operation cycle, the structural conflict is determined to be in a critical risk state, and the obstruction urgency coefficient is set to the maximum extreme value. If the remaining operation time window is greater than or equal to the critical operation cycle, the urgency coefficient of the obstruction is calculated based on the weighted sum of the hierarchical differences between the obstructed object and each blocked object, combined with the reciprocal of the remaining operation time window.

3. The hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification according to claim 2, characterized in that, The determination of the task level of the candidate sorting task includes: The preset grading thresholds include a first grading threshold and a second grading threshold, wherein the first grading threshold is greater than the second grading threshold. Determine whether the urgency coefficient corresponding to the candidate sorting task is greater than the first classification threshold. If the obstruction urgency coefficient is greater than the first classification threshold, the candidate sorting task is determined as a first type of hard sorting task. The first type of hard sorting task is used to resolve structural conflicts that directly block recent outbound demand. If the urgency coefficient of the obstruction is between the first grading threshold and the second grading threshold, then the candidate sorting task is determined as a second type of flexible sorting task, which is used to optimize the deep order of the stacked structure.

4. The hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification according to claim 3, characterized in that, The generation of the task scheduling queue containing the execution order includes: All the first type of hard scheduling tasks are sorted in descending order of their respective urgency coefficients to construct the main scheduling sequence. Calculate the estimated resource consumption required to execute the second type of flexible reorganization task, and obtain the current amount of idle resources in the system; If the amount of idle resources is greater than the expected resource usage, then the second type of flexible reorganization task will be inserted into the idle time window of the main scheduling sequence. If the amount of idle resources is less than or equal to the expected resource usage, then only the main scheduling sequence is retained, and the addition of the second type of flexible reorganization task is postponed to ensure that high-priority conflicts are resolved first.

5. The hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification according to claim 4, characterized in that, The step of inserting the second type of flexible sorting task into the idle time window of the main scheduling sequence includes: Calculate the expected orderliness gain of the target storage unit after the execution of the second type of flexible sorting task; If the expected order gain is less than the preset minimum benefit threshold, the task is determined to be an invalid optimization and is removed from the task set. If the expected order gain is greater than or equal to the preset minimum benefit threshold, it is determined whether executing the task will cause new structural conflicts in neighboring storage units; if it is determined that no chain of negative conflicts will be triggered, the second type of flexible sorting task is finally added to the scheduling queue.

6. The hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification according to claim 5, characterized in that, After the control actuator performs hierarchical scheduling and organization of materials, it also includes: At the end of each execution cycle, the changed stack state data is retrieved again; Determine if a new external inbound task causes the original non-conflicting structure to change into a new reverse state. If so, a new round of structural conflict identification will be conducted, and the newly generated urgency coefficient will be calculated. The newly generated delay urgency coefficient is compared with the coefficient of the unexecuted tasks in the current task scheduling queue. If the newly generated delay urgency coefficient is higher than the delay urgency coefficient of the first task in the queue, the task scheduling queue is preemptively rearranged.

7. The hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification according to claim 6, characterized in that, The traversal of each storage unit includes: When it is determined that a certain storage unit does not have the reverse order state and its stacking dispersion index exceeds a preset dispersion threshold, it is determined that the storage unit has potential efficiency loss; wherein, the stacking dispersion index is used to characterize the degree of dispersion of materials in the same outbound batch in the vertical direction. A pre-sorting task is generated to address the potential efficiency loss, and the urgency coefficient of the pre-sorting task is set to a normalized value calculated based on the stacking dispersion index, so as to incorporate it into a unified task classification judgment.

8. The hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification according to claim 7, characterized in that, The control actuator performs hierarchical scheduling and organization of materials, including: Obtain the current physical location coordinates of the actuator; Calculate the path cost of moving the execution mechanism from its current physical location to the storage unit location corresponding to the candidate sorting task; The task execution efficiency ratio is calculated based on the ratio of the obstruction urgency coefficient to the path cost. Within the same task level, prioritize the sorting task with the highest execution efficiency to maximize the elimination of structural conflicts within a unit of time.

9. An electronic device, characterized in that, include: At least one processor; A memory that is communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification as described in any one of claims 1-8.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to execute the hierarchical scheduling method for stacked storage material sorting tasks based on structural conflict identification as described in any one of claims 1-8.

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