A method, device, medium and product for generating a balance wheel sorting scheme

Abstract

The application provides a generation method, device, medium and product of a balance wheel sorting scheme. The method comprises: obtaining a sorting target of a balance wheel sorting scheme to be generated in a target balance wheel sorting system, the sorting target being a target expected to be achieved in a sorting process; generating at least one candidate balance wheel sorting scheme according to the sorting target; simulating the at least one candidate balance wheel sorting scheme through a digital twin model corresponding to the target balance wheel sorting system to obtain a simulation result corresponding to each candidate balance wheel sorting scheme; and outputting a balance wheel sorting scheme of the target balance wheel sorting system based on the simulation result. The generated balance wheel sorting scheme can be fully and reasonably used in the balance wheel sorting system, thereby improving the sorting efficiency.

Description

Technical Field

[0001] This application relates to the field of logistics processing, and in particular to a method, equipment, medium and product for generating a balance wheel sorting scheme. Background Technology

[0002] With the rapid development of e-commerce and modern logistics, logistics sorting systems are playing an increasingly important role in supply chain management. The efficient operation of sorting systems directly affects the operational efficiency of logistics centers, order processing speed, and customer satisfaction. Swing wheel sorting systems are a common type of automated logistics sorting equipment. Through the rotation and precise control of swing wheels, they sort items destined for different places into designated sorting lanes.

[0003] In related technologies, the sorting scheme of the balance wheel often relies on the experience of the operators.

[0004] However, this method of determining the balance wheel sorting scheme based on the operator's experience often results in problems such as low sorting efficiency and inability to fully and rationally utilize the balance wheel sorting system. Summary of the Invention

[0005] Based on the defects and shortcomings of the prior art, this application proposes a method, equipment, medium and product for generating a balance wheel sorting scheme, so that the formulated balance wheel sorting scheme can make full and reasonable use of the balance wheel sorting system, thereby improving sorting efficiency.

[0006] According to a first aspect of the present application, a method for generating a balance wheel sorting scheme is provided. The method includes: obtaining a sorting target for a balance wheel sorting scheme to be generated in a target balance wheel sorting system, wherein the sorting target refers to the target expected to be achieved during the sorting process; generating at least one candidate balance wheel sorting scheme based on the sorting target; simulating the at least one candidate balance wheel sorting scheme using a digital twin model corresponding to the target balance wheel sorting system to obtain a simulation result corresponding to each candidate balance wheel sorting scheme; and outputting the balance wheel sorting scheme of the target balance wheel sorting system based on the simulation results.

[0007] According to a second aspect of the embodiments of this application, an electronic device is provided, including: a memory and a processor; the memory is connected to the processor and is used to store a program; the processor is used to implement the method for generating the balance wheel sorting scheme as described above by running the program in the memory.

[0008] According to a third aspect of the embodiments of this application, a storage medium is provided, on which a computer program is stored, and when the computer program is run by a processor, it implements the method for generating the balance wheel sorting scheme as described above.

[0009] According to a fourth aspect of the embodiments of this application, a computer program product is provided, including computer program instructions, which, when executed by a processor, cause the processor to implement the method for generating the balance wheel sorting scheme as described above.

[0010] According to a fifth aspect of the embodiments of this application, a chip is provided, including a processor and a data interface. The processor reads and runs a program stored in a memory through the data interface to execute a method for generating a balance wheel sorting scheme as described in any one of the first aspects of the embodiments of this application.

[0011] This application provides a method, equipment, medium, and product for generating a balance wheel sorting scheme. The method involves obtaining the sorting target of the balance wheel sorting scheme to be generated in the target balance wheel sorting system, where the sorting target refers to the expected goal during the sorting process. Based on the sorting target, at least one candidate balance wheel sorting scheme is generated. The at least one candidate balance wheel sorting scheme is simulated using a digital twin model corresponding to the target balance wheel sorting system, obtaining simulation results for each candidate scheme. Based on the simulation results, the balance wheel sorting scheme for the target balance wheel sorting system is output. Because at least one candidate balance wheel sorting scheme is generated based on the sorting target of the scheme, and simulation is performed using a digital twin model to select the scheme applicable to the target balance wheel sorting system, the resulting balance wheel sorting scheme can fully and rationally utilize the balance wheel sorting system, thereby improving sorting efficiency. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0013] Figure 1 A flowchart illustrating the method for generating a balance wheel sorting scheme provided in an embodiment of this application;

[0014] Figure 2 A flowchart illustrating a method for establishing a digital twin model corresponding to a target balance wheel sorting scheme, provided in an embodiment of this application;

[0015] Figure 3 A schematic flowchart illustrating a target balance wheel sorting system based on simulation results output, provided for an embodiment of this application;

[0016] Figure 4 A flowchart illustrating an optimization method for an optimization algorithm provided in an embodiment of this application;

[0017] Figure 5 A schematic diagram of the structure of the device for generating the balance wheel sorting scheme provided in the embodiments of this application;

[0018] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] First, the technical terms involved in the embodiments of this application will be explained:

[0021] Digital Twin Technology is a simulation process that integrates multiple disciplines, multiple physical quantities, multiple scales, and multiple probabilities. It reflects the entire life cycle of the corresponding physical equipment by completing mapping in virtual space.

[0022] Swing wheel sorting system: This is an automated sorting equipment widely used in logistics, warehousing and manufacturing industries. It can automatically sort goods into designated sorting lanes based on different standards such as region, express company, and customer channel through the rotation and precise control of the swing wheel.

[0023] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only one component of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0024] Before introducing the solution proposed in this application, the relevant technologies will first be introduced:

[0025] With the rapid development of e-commerce and modern logistics, the importance of logistics sorting systems, as a key link in the supply chain, is becoming increasingly prominent. An efficient sorting system can significantly improve the operational efficiency of a logistics center, accelerate order processing, and enhance customer satisfaction.

[0026] Swing wheel sorting systems, as a common and widely used automated logistics sorting equipment, occupy an important position in the logistics industry. Through the rotation and precise control of the swing wheel, these systems sort goods destined for different locations into designated sorting lanes. Compared to traditional manual sorting, this automated sorting method greatly improves the accuracy and speed of sorting.

[0027] However, the formulation of balance wheel sorting schemes in related technologies has certain limitations. Specifically, current balance wheel sorting schemes often rely heavily on the experience of operators. That is, operators subjectively judge the sorting process, the characteristics of goods, and the operating rules of the balance wheel sorting system based on their long-term accumulated work experience, and then determine the balance wheel sorting scheme.

[0028] However, this method of developing a swing wheel sorting solution based on the operator's manual experience has two main drawbacks. Firstly, the varying experience levels of different operators lead to a lack of standardization and consistency in the sorting process, making it difficult to guarantee optimal results each time and resulting in low sorting efficiency. Secondly, operators, limited by their individual knowledge and experience, cannot fully and rationally utilize system resources, failing to leverage the advantages of the swing wheel sorting system and thus wasting equipment resources and increasing operating costs to some extent.

[0029] Based on this, embodiments of this application provide a new method, device, medium, and product for generating a balance wheel sorting scheme. The method involves obtaining the sorting target of the balance wheel sorting scheme to be generated in the target balance wheel sorting system, where the sorting target refers to the expected goal achieved during the sorting process. Based on the sorting target, at least one candidate balance wheel sorting scheme is generated. The at least one candidate balance wheel sorting scheme is simulated using a digital twin model corresponding to the target balance wheel sorting system, obtaining simulation results for each candidate scheme. Based on the simulation results, the balance wheel sorting scheme for the target balance wheel sorting system is output. Since at least one candidate balance wheel sorting scheme is generated based on the sorting target of the scheme, and simulation is performed using a digital twin model to select the scheme applicable to the target balance wheel sorting system, the resulting balance wheel sorting scheme can fully and rationally utilize the balance wheel sorting system, thereby improving sorting efficiency.

[0030] The method for generating the balance wheel sorting scheme provided in the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0031] Exemplary methods

[0032] Figure 1 This is a flowchart illustrating the method for generating the balance wheel sorting scheme provided in an embodiment of this application. Please refer to... Figure 1In an exemplary embodiment, the method for generating the provided balance wheel sorting scheme may include the following steps:

[0033] Step 100: Obtain the sorting target of the balance wheel sorting scheme to be generated in the target balance wheel sorting system. The sorting target refers to the expected goal to be achieved during the sorting process. Step 110: Generate at least one candidate balance wheel sorting scheme based on the sorting target. Step 120: Simulate the at least one candidate balance wheel sorting scheme using a digital twin model corresponding to the target balance wheel sorting system, obtaining simulation results for each candidate balance wheel sorting scheme. Step 130: Output the balance wheel sorting scheme of the target balance wheel sorting system based on the simulation results.

[0034] Among them, the balance wheel sorting scheme refers to a series of plans and arrangements designed to achieve a specific sorting goal. The candidate balance wheel sorting scheme refers to the balance wheel sorting scheme generated based on the sorting goal, which has not been simulated by the digital twin model corresponding to the target balance wheel sorting system. The output after simulation by the digital twin model is the final balance wheel sorting scheme of the target balance wheel sorting system.

[0035] The candidate balancing wheel sorting scheme is a different sorting scheme that is generated based on the sorting target of the target balancing wheel sorting system. Each candidate balancing wheel sorting scheme may include at least the material flow direction settings of each sorting lane and the operator settings of each sorting lane in the target balancing wheel sorting system.

[0036] The flow direction settings for each sorting lane are used to define the direction of goods movement in each lane. For example, whether the goods flow to the left or right exit, or some other specific direction, is crucial for planning the goods' path and ensuring correct sorting.

[0037] The staffing information for each sorting lane is used to clarify whether operators need to be assigned to each sorting lane, how many operators should be assigned, and the specific responsibilities of the operators, such as monitoring equipment and handling abnormal goods.

[0038] The sorting target can be a single-dimensional sorting target or a comprehensive sorting target composed of multiple sub-sorting targets. It can be understood that when the sorting target is a comprehensive sorting target composed of multiple sub-sorting targets, this comprehensive sorting target is obtained based on the multiple sub-sorting targets and pre-set weights corresponding to each of the multiple sub-sorting targets. The sorting target can be at least one of expected sorting efficiency, expected cost, and expected energy consumption. Specific sorting targets can be set according to actual business needs; this embodiment does not impose specific limitations on this.

[0039] A single-dimensional sorting objective refers to a sorting objective determined based on only one aspect. For example, if the objective is simply to improve sorting efficiency, then the focus is only on sorting more goods per unit of time, without considering other factors.

[0040] For example, suppose a small e-commerce warehouse experiences a sudden surge in orders. To process these orders as quickly as possible, the sorting goal is to improve sorting efficiency. Based on this goal, by optimizing the operating parameters of the target wheel sorting system, the resulting sorting solution focuses on sorting more goods per unit time, temporarily disregarding issues such as increased costs or energy consumption.

[0041] The sorting objectives of multiple dimensions are calculated to arrive at the final comprehensive sorting objective based on the pre-set weights of each sub-sorting objective. For example, in a real-world logistics sorting scenario, three sub-sorting objectives, namely sorting efficiency, cost, and energy consumption, may be considered simultaneously.

[0042] For example, suppose a logistics center, based on its business characteristics and development strategy, assigns a weight of 0.5 to the expected sorting efficiency, 0.3 to the expected cost, and 0.2 to the expected energy consumption. In actual operation, these three sub-objectives are balanced by continuously adjusting the operating mode, equipment configuration, and operator arrangements of the target wheel sorting system. For instance, using more efficient equipment can improve sorting efficiency but may increase costs and energy consumption. In this case, it is necessary to comprehensively consider the weights to find an optimal solution that achieves the best overall sorting target.

[0043] As can be seen, by setting sorting objectives in one or more dimensions, the priorities and specific indicators of each dimension can be flexibly adjusted, thereby achieving optimal resource allocation and maximizing operational efficiency. Furthermore, using digital twin models for simulation can help to better understand the interactions between sorting objectives in different dimensions, further optimizing the wheel sorting scheme.

[0044] After generating at least one candidate pendulum sorting scheme based on the sorting target, the at least one candidate pendulum sorting scheme is simulated using a pre-built digital twin model corresponding to the target pendulum sorting system. This simulates the operation of each candidate pendulum sorting scheme in the target pendulum sorting system. If problems occur during the simulation, the candidate pendulum sorting scheme can be adjusted accordingly to ensure that the candidate pendulum sorting scheme can efficiently and accurately complete the sorting target in actual application.

[0045] Among them, the digital twin model is a model built based on the target wheel sorting system to simulate the operation process of the target wheel sorting system and the operation process of personnel, so that the final output wheel sorting solution can make full and reasonable use of the wheel sorting system and improve sorting efficiency.

[0046] After outputting the target balance wheel sorting system's balance wheel sorting scheme, in this embodiment, the target balance wheel sorting system can also be controlled to execute the balance wheel sorting scheme to perform sorting operations.

[0047] According to the technical solution of this application embodiment, the sorting target of the pendulum sorting scheme to be generated in the target pendulum sorting system is obtained, where the sorting target refers to the expected target to be achieved during the sorting process; based on the sorting target, at least one candidate pendulum sorting scheme is generated; the at least one candidate pendulum sorting scheme is simulated using a digital twin model corresponding to the target pendulum sorting system to obtain the simulation result corresponding to each candidate pendulum sorting scheme; and the pendulum sorting scheme of the target pendulum sorting system is output based on the simulation result. Since at least one candidate pendulum sorting scheme is generated based on the sorting target of the pendulum sorting scheme, and the pendulum sorting scheme applied to the target pendulum sorting system is selected by simulating it in the digital twin model, the formulated pendulum sorting scheme can fully and reasonably utilize the pendulum sorting system, thereby improving sorting efficiency.

[0048] Specifically, in order to establish a digital twin model for simulating candidate balance wheel sorting schemes, this embodiment provides an optional embodiment that can establish a digital twin model corresponding to the target balance wheel sorting system. For example... Figure 2 As shown, its specific implementation is as follows, including steps 200 to 220:

[0049] Step 200: Obtain the modeling data of the target pendulum sorting system and the modeling data of the operators in the target pendulum sorting system, respectively. Also obtain the operational data of the target pendulum sorting system and the operational data of the operators. Step 210: Establish a target pendulum sorting system model based on the modeling data of the target pendulum sorting system, and establish an operator model within the target pendulum sorting system model based on the operator modeling data. Step 220: Simulate sorting operations using the target pendulum sorting system model based on the operational data, and simulate sorting operations using the operator model based on the operational data, thus obtaining a digital twin model.

[0050] The modeling data for the target wheel sorting system can include hardware configuration data, cargo characteristic data, system operating parameters, and control logic data. Hardware configuration data can include the number, size, and material of the wheel, the length, width, and speed of the conveyor belt, and the number and location of sorting lanes. Cargo characteristic data can include various attribute information of the cargo, such as its shape, size, weight, and packaging. System operating parameters refer to various set parameters and actual operating indicators during normal system operation, such as the rotation frequency of the wheel, the response time of sorting actions, and cargo flow at different times. Control logic data refers to the system's control strategies and logical relationships, such as the rules for cargo sorting, including logical algorithms for sorting by destination and cargo type, as well as the collaborative working logic between devices. For example, when cargo arrives at a sensor at a specific location, the destination is determined based on its RFID tag information, and then the corresponding wheel is controlled to sort the cargo to the designated lane.

[0051] The operator's operational data includes: the operator's package receiving operation data, which refers to the relevant data generated when the operator performs package receiving operations on packages in the corresponding flow direction of the sorting lane. Specifically, the operator's package receiving operation data is obtained through photoelectric sensors pre-installed at the sorting lane.

[0052] In the process of building the 3D model, the operating data of the target balance wheel sorting system is first collected using technologies such as sensors, cameras, and RFID. At the same time, historical data such as sorting task records, equipment maintenance logs, and fault reports can also be collected. Then, 3D modeling software such as SolidWorks and 3ds Max is used to create a corresponding virtual model based on the actual structure and size of the target balance wheel sorting system.

[0053] The collected data is mapped to a virtual model, enabling data mapping and model parameterization. For example, real-time balance wheel rotation speed data collected by sensors is correlated with the balance wheel rotation speed parameters in the 3D model, allowing the balance wheel in the virtual model to rotate accordingly based on the actual data. Information such as the size and weight of goods is mapped onto virtual goods objects in the model, allowing it to simulate the actual goods transport and sorting process in the virtual environment. In this way, the 3D virtual model can accurately reflect the operating status of the actual balance wheel sorting system, ultimately forming a digital twin model with practical application value.

[0054] After simulating at least one candidate pendulum sorting scheme generated based on the sorting target using a digital twin model, simulation results are obtained for each candidate pendulum sorting scheme. These simulation results include the performance indicators corresponding to the candidate pendulum sorting scheme.

[0055] When outputting the balance wheel sorting scheme of the target balance wheel sorting system based on simulation results, specifically, as follows: Figure 3 As shown, the steps 300 to 310 may be included as follows:

[0056] Step 300: Based on the simulation results and the sorting target, determine the target candidate balance wheel sorting scheme from the at least one candidate balance wheel sorting scheme. Step 310: Optimize the target candidate balance wheel sorting scheme using an optimization algorithm to obtain the balance wheel sorting scheme of the target balance wheel sorting system.

[0057] Specifically, when determining the target candidate balance wheel sorting scheme from at least one candidate balance wheel sorting scheme, the performance indicators corresponding to the candidate balance wheel sorting schemes in the simulation results can be compared with the sorting target to determine the target candidate balance wheel sorting scheme whose performance indicators are closest to the sorting target.

[0058] For example, if the sorting goals are set as follows: sorting efficiency of 1000 items per hour, cost control within 500 yuan per hour, and energy consumption not exceeding 200 kWh per hour, then the simulation results obtained after simulating three different candidate pendulum sorting schemes are as follows:

[0059] Simulation results for candidate pendulum sorting scheme one show that it can sort 900 items per hour, with an hourly cost of 450 yuan and an energy consumption of 180 kWh. Simulation results for candidate pendulum sorting scheme two show that it can sort 1050 items per hour, with an hourly cost of 600 yuan and an energy consumption of 220 kWh. Simulation results for candidate pendulum sorting scheme three show that it can sort 950 items per hour, with an hourly cost of 520 yuan and an energy consumption of 190 kWh.

[0060] After comparing the performance indicators of each candidate pendulum sorting scheme with the sorting target, it was found that: Candidate pendulum sorting scheme one's sorting efficiency did not reach the sorting target, but its cost and energy consumption were lower than the target. Candidate pendulum sorting scheme two's sorting efficiency exceeded the sorting target, but its cost and energy consumption both exceeded the target. Candidate pendulum sorting scheme three's sorting efficiency was close to the sorting target, its cost exceeded the target by 20 yuan, but its energy consumption was lower than the target.

[0061] Based on the above comparison results, it can be seen that the first candidate pendulum sorting scheme has a large gap in sorting efficiency compared to the sorting target. Although the second candidate pendulum sorting scheme has high sorting efficiency, its cost and energy consumption exceed the sorting target by a large margin. The third candidate pendulum sorting scheme has relatively small gaps in sorting efficiency, cost, and energy consumption compared to the sorting target. It is the candidate pendulum sorting scheme with the closest performance indicators to the sorting target. Therefore, the third candidate pendulum sorting scheme is determined as the target candidate pendulum sorting scheme.

[0062] Subsequently, the target candidate balance wheel sorting scheme was further optimized based on the optimization algorithm to obtain the final balance wheel sorting scheme of the target balance wheel sorting system.

[0063] According to the technical solution of this application embodiment, by comparing the performance index corresponding to each candidate pendulum wheel sorting scheme with the sorting target, the target candidate pendulum wheel sorting scheme with the performance index closest to the sorting target is determined, and the target candidate pendulum wheel sorting scheme is optimized based on the optimization algorithm to obtain the pendulum wheel sorting scheme of the target pendulum wheel sorting system, thereby finding the pendulum wheel sorting scheme that best meets the sorting target and improving sorting efficiency.

[0064] Furthermore, in order to optimize the optimization algorithm proposed in the embodiments of this application, and to further optimize the target candidate balance wheel sorting scheme, such as... Figure 4 As shown, the method provided in this embodiment may further include the following steps 400 to 420:

[0065] Step 400: Obtain the historical balance wheel sorting scheme of the target balance wheel sorting system at preset time intervals. Step 410: Optimize the optimization algorithm based on the historical balance wheel sorting scheme. Step 420: Optimize the target candidate balance wheel sorting scheme based on the optimized algorithm.

[0066] Specifically, when optimizing the optimization algorithm provided in this embodiment, the historical balance wheel sorting scheme of the target balance wheel sorting system can be used as a reference. The optimization algorithm can be optimized by analyzing the historical balance wheel sorting scheme. Based on the optimized optimization algorithm, the target candidate balance wheel sorting scheme can be optimized to finally generate a more efficient balance wheel sorting scheme.

[0067] The timing for obtaining the historical balance wheel sorting scheme of the target balance wheel sorting system is a preset time interval. This preset time interval can be set according to actual needs. For example, it can be set to obtain the historical balance wheel sorting scheme once every 24 hours, or once every 7 days, or once every 30 days. This embodiment does not limit the specific time interval set.

[0068] In this embodiment, historical balance wheel sorting schemes previously used by the target balance wheel sorting system are acquired at preset time intervals. These historical schemes include specific methods used in sorting goods under different cleaning rollers, such as logistics flow settings and operator arrangements. By analyzing these historical schemes, areas for improvement in the optimization algorithm are identified. Adjustments to the algorithm's parameters or logical structure make the algorithm more refined and better suited to actual sorting needs. Subsequently, the optimized algorithm is used to further optimize the target candidate balance wheel sorting scheme. Through calculation and adjustment of the optimized algorithm, the target candidate balance wheel sorting scheme performs better in all aspects, ultimately resulting in a more efficient balance wheel sorting scheme that better meets the actual sorting objectives.

[0069] Furthermore, to determine the accuracy of the digital twin model, the solution provided in this embodiment may further include: acquiring actual operating data and simulated operating data of the balance wheel sorting scheme; determining the difference between the actual operating data and the simulated operating data; and determining the accuracy of the digital twin model based on the difference.

[0070] The actual operating data refers to the data generated by the target wheel sorting system during actual operation. This data can be obtained through various sensors installed in the system, such as position sensors, speed sensors, and weight sensors, monitoring equipment, and system records. The simulated operating data is the data generated by the digital twin model simulating the operation of the target wheel sorting system.

[0071] By comparing the same type of data in actual and simulated operations, the difference between them is calculated. For example, if the actual number of goods sorted per hour is 1000, and the simulated number is 950, then the difference is 50. In practical applications, this difference can be expressed as an absolute value to intuitively measure the degree of difference between the data.

[0072] The magnitude of this difference reflects how closely the digital twin model approximates the actual operation of the target balance wheel sorting system. Generally, the smaller the difference, the closer the simulation results of the digital twin model are to the actual operation, and the higher the accuracy of the digital twin model. Conversely, the larger the difference, the greater the deviation between the simulation results of the digital twin model and the actual operation of the target balance wheel sorting system, indicating lower accuracy of the digital twin model.

[0073] In some feasible implementations, a threshold can be set to determine whether the accuracy of the digital twin model meets the requirements. For example, if the difference is less than the set threshold, the accuracy of the digital twin model is considered to be high; if the difference is greater than the set threshold, the accuracy of the digital twin model is considered to be low, requiring further optimization and adjustment.

[0074] According to the technical solution of this embodiment, the accuracy of the digital twin model is determined by acquiring actual operating data and simulated operating data and calculating the difference, thereby optimizing the balance wheel sorting system in a targeted manner, improving its operating efficiency and accuracy, reducing the sorting error rate, and improving overall performance.

[0075] To monitor and understand the operation of the balance wheel sorting scheme in real time, the method provided in this embodiment may further include: obtaining the real-time sorting operation progress in the target balance wheel sorting system through the digital twin model; comparing the real-time sorting operation progress with the balance wheel sorting scheme to determine that the real-time sorting operation progress is consistent with the balance wheel sorting scheme; and optimizing the balance wheel sorting scheme based on the real-time sorting operation progress and the optimization algorithm when the real-time sorting operation progress is inconsistent with the balance wheel sorting scheme, thereby adjusting the balance wheel sorting scheme.

[0076] Specifically, the digital twin model can reflect the actual status of the target wheel sorting system in real time, as well as the real-time progress of the wheel sorting scheme, such as the real-time location of the goods, the real-time status of the sorting lanes, and the real-time operating parameters of the equipment. Based on this, the digital twin model can calculate and present the current real-time sorting operation progress, such as how many goods have been sorted, which goods are currently being sorted, and the usage status of each sorting lane.

[0077] The swivel sorting plan is pre-defined and includes the overall planning of the sorting process, such as the sorting sequence of goods, the operating parameter settings of each piece of equipment, and the work arrangements of the operators. The real-time sorting progress is compared with the expected progress in the swivel sorting plan to check whether the actual sorting operation is proceeding according to the predetermined plan, such as whether the goods are being sorted at the planned speed and whether the specific sorting tasks have been completed within the specified time.

[0078] By comparison, if the actual real-time sorting progress is the same as the expected progress in the swing wheel sorting scheme or within the allowable error range, the two are considered to be consistent; otherwise, if the actual real-time sorting progress deviates significantly from the expected progress in the swing wheel sorting scheme, such as the sorting speed being too slow or goods accumulating at a certain stage, the two are determined to be inconsistent.

[0079] When a discrepancy is found between the real-time sorting operation progress and the wheel sorting scheme, it indicates that the current scheme may not be suitable for actual operation. In this case, by combining real-time sorting operation progress data, such as identifying the specific step causing the problem and its severity, an optimization algorithm is used to adjust the wheel sorting scheme. The optimization algorithm recalculates and adjusts the parameters and strategies in the scheme based on set objectives, such as improving sorting efficiency and reducing costs, and the actual situation. For example, it adjusts the rotation speed of the wheel, changes the sorting path of goods, and reassigns the tasks of operators to bring the actual sorting operation back on track.

[0080] According to the technical solution of this embodiment, by monitoring the sorting process in real time, sorting errors can be detected and corrected in a timely manner, ensuring that goods are sorted according to the correct path and destination. At the same time, the optimization solution based on digital twin technology can quickly respond to order changes and system disturbances, adjust the sorting plan, and improve the adaptability of the swing wheel sorting system to dynamic environments.

[0081] Exemplary device

[0082] Accordingly, embodiments of this application also provide an apparatus, such as Figure 5 As shown, the device 500 for generating the balance wheel sorting scheme provided in this embodiment may include: an acquisition module 510, a generation module 520, a simulation module 530, and an output module 540.

[0083] The system includes the following modules: Acquisition module 510, which acquires the sorting target of the pendulum sorting scheme to be generated in the target pendulum sorting system, wherein the sorting target refers to the expected goal to be achieved during the sorting process; Generation module 520, which generates at least one candidate pendulum sorting scheme based on the sorting target; Simulation module 530, which simulates the at least one candidate pendulum sorting scheme using a digital twin model corresponding to the target pendulum sorting system, and obtains simulation results for each candidate pendulum sorting scheme; and Output module 540, which outputs the pendulum sorting scheme of the target pendulum sorting system based on the simulation results.

[0084] In some exemplary embodiments, the output module 540 may specifically be used to determine a target candidate balance wheel sorting scheme from the at least one candidate balance wheel sorting schemes based on the simulation results and the sorting target. The target candidate balance wheel sorting scheme is then optimized using an optimization algorithm to obtain the balance wheel sorting scheme of the target balance wheel sorting system.

[0085] In some exemplary embodiments, the output module 540 may also be used to compare the performance indicators corresponding to the candidate balance wheel sorting schemes in the simulation results with the sorting target, thereby determining the target candidate balance wheel sorting scheme whose performance indicators are closest to the sorting target.

[0086] In some exemplary embodiments, the acquisition module 510 can also be used to acquire historical balance wheel sorting schemes of the target balance wheel sorting system at preset time intervals. The device 500 may also include an optimization module for optimizing the optimization algorithm based on the historical balance wheel sorting schemes. Correspondingly, the output module 540 can be used to optimize the target candidate balance wheel sorting scheme based on the optimized optimization algorithm.

[0087] In some exemplary embodiments, the device 500 may further include a control module for controlling the target balance wheel sorting system to perform the balance wheel sorting scheme for sorting operations.

[0088] In some exemplary embodiments, the acquisition module 510 can also be used to acquire actual operating data and simulated operating data of the balance wheel sorting scheme. The device 500 may also include a determination module for determining the difference between the actual operating data and the simulated operating data; and determining the accuracy of the digital twin model based on the difference.

[0089] In some exemplary embodiments, the acquisition module 510 can also be used to acquire the real-time sorting operation progress in the target balance wheel sorting system through the digital twin model. The determination module can also be used to compare the real-time sorting operation progress with the balance wheel sorting scheme to determine that the real-time sorting operation progress is consistent with the balance wheel sorting scheme. Accordingly, when the determination module determines that the real-time sorting operation progress is inconsistent with the balance wheel sorting scheme, the optimization module can also be used to optimize the balance wheel sorting scheme based on the real-time sorting operation progress and the optimization algorithm to adjust the balance wheel sorting scheme.

[0090] The apparatus for generating a balance wheel sorting scheme provided in this embodiment belongs to the same concept as the method for generating a balance wheel sorting scheme provided in the above embodiments of this application. It can execute the method for generating a balance wheel sorting scheme provided in any of the above embodiments of this application and has the corresponding functional modules and beneficial effects for executing the method for generating a balance wheel sorting scheme. Technical details not described in detail in this embodiment can be found in the specific processing content of the method for generating a balance wheel sorting scheme provided in the above embodiments of this application, and will not be repeated here.

[0091] It should be understood that the modules in the above device can be implemented by a processor calling software. For example, the device includes a processor connected to a memory containing instructions. The processor calls the instructions stored in the memory to implement any of the above methods or to implement the functions of each unit of the device. The processor can be a general-purpose processor, such as a CPU or microprocessor, and the memory can be internal or external to the device. Alternatively, the units in the device can be implemented as hardware circuits. By designing the hardware circuits, some or all of the unit functions can be implemented. The hardware circuits can be understood as one or more processors. For example, in one implementation, the hardware circuit is an ASIC, and the functions of some or all of the above units are implemented by designing the logical relationships between the components within the circuit. In another implementation, the hardware circuit can be implemented by a PLD, such as an FPGA, which can include a large number of logic gates. The connection relationships between the logic gates are configured through configuration files to implement the functions of some or all of the above units. All units of the above device can be implemented entirely by a processor calling software, entirely by hardware circuits, or partially by a processor calling software with the remaining parts implemented by hardware circuits.

[0092] In this application embodiment, a processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction reading and execution capabilities, such as a CPU, microprocessor, GPU, or DSP. In another implementation, the processor can implement certain functions through the logical relationships of hardware circuits. These logical relationships are fixed or reconfigurable. For example, the processor may be a hardware circuit implemented as an ASIC or PLD, such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document and configuring the hardware circuit can be understood as the processor loading instructions to implement the functions of some or all of the above units. Furthermore, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as an NPU, TPU, or DPU.

[0093] As can be seen, each unit in the above device can be one or more processors (or processing circuits) configured to implement the above methods, such as: CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA, or a combination of at least two of these processor forms.

[0094] Furthermore, the units in the above devices can be integrated in whole or in part, or they can be implemented independently. In one implementation, these units are integrated together and implemented in the form of a System-on-Chip (SoC). The SoC may include at least one processor for implementing any of the above methods or implementing the functions of the units in the device. The at least one processor may be of different types, such as CPU and FPGA, CPU and artificial intelligence processor, CPU and GPU, etc.

[0095] Exemplary electronic devices

[0096] This application provides an electronic device, see [link to relevant documentation] Figure 6 As shown, the electronic device includes a memory 600 and a processor 610 connected to the memory 600.

[0097] The memory 600 is used to store programs.

[0098] The processor 610 is configured to execute any of the above embodiments' methods for generating a balance wheel sorting scheme, by obtaining the sorting target of the balance wheel sorting scheme to be generated in the target balance wheel sorting system, wherein the sorting target refers to the expected target to be achieved during the sorting process; generating at least one candidate balance wheel sorting scheme based on the sorting target; simulating the at least one candidate balance wheel sorting scheme using a digital twin model corresponding to the target balance wheel sorting system, obtaining simulation results corresponding to each candidate balance wheel sorting scheme; and outputting the balance wheel sorting scheme of the target balance wheel sorting system based on the simulation results. This ensures that the formulated balance wheel sorting scheme can fully and rationally utilize the balance wheel sorting system, thereby improving sorting efficiency.

[0099] For details on the specific processing procedure of the processor 610 described above, please refer to the description of the above method embodiments. For details on the specific implementation of the processor 610, please refer to the description of the above embodiments.

[0100] Specifically, the aforementioned electronic device may also include: a bus, a communication interface 620, an input device 630, and an output device 640.

[0101] The processor 610, memory 600, communication interface 620, input device 630, and output device 640 are interconnected via a bus. Among them:

[0102] A bus can include a pathway for transmitting information between various components of a computer system.

[0103] The processor 610 can be a general-purpose processor, such as a general-purpose central processing unit (CPU), a microprocessor, etc., or an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the program of the present invention. It can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0104] The processor 610 may include a main processor, as well as a baseband chip, modem, etc.

[0105] The memory 600 stores a program that executes the technical solution of this invention, and may also store an operating system and other key business functions. Specifically, the program may include program code, which includes computer operation instructions. More specifically, the memory 600 may include read-only memory (ROM), other types of static storage devices capable of storing static information and instructions, random access memory (RAM), other types of dynamic storage devices capable of storing information and instructions, disk storage, flash memory, etc.

[0106] Input device 630 may include a device for receiving user input data and information, such as an error microphone, keyboard, mouse, camera, scanner, light pen, voice input device, touch screen, pedometer, or gravity sensor.

[0107] Output device 640 may include devices that allow information to be output to a user, such as a speaker, display screen, printer, etc.

[0108] The communication interface 620 may include a device that uses any transceiver to communicate with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), etc.

[0109] The processor 610 executes the program stored in the memory 600 and calls other devices, which can be used to implement the various steps of the generation method of any of the balance wheel sorting schemes provided in the above embodiments of this application.

[0110] This application also proposes a chip, which includes a processor and a data interface. The processor reads and runs a program stored in the memory through the data interface to execute the method for generating the balance wheel sorting scheme described in any of the above embodiments. For the specific processing procedure and its beneficial effects, please refer to the above embodiments of the method for generating the balance wheel sorting scheme.

[0111] Exemplary computer program products and storage media

[0112] In addition to the methods and devices described above, embodiments of this application may also be computer program products, which include computer program instructions that, when executed by a processor, cause the processor to perform the steps in the method for generating a balance wheel sorting scheme according to various embodiments of this application as described in any of the above embodiments of this specification.

[0113] Computer program products can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0114] Furthermore, embodiments of this application may also be storage media storing a computer program, which is executed by a processor to perform the steps in the method for generating the balance wheel sorting scheme according to various embodiments of this application as described in any of the above embodiments of this specification. Specifically, the following steps can be implemented:

[0115] Step 100: Obtain the sorting target of the balance wheel sorting scheme to be generated in the target balance wheel sorting system. The sorting target refers to the expected goal to be achieved during the sorting process. Step 110: Generate at least one candidate balance wheel sorting scheme based on the sorting target. Step 120: Simulate the at least one candidate balance wheel sorting scheme using a digital twin model corresponding to the target balance wheel sorting system, obtaining simulation results for each candidate balance wheel sorting scheme. Step 130: Output the balance wheel sorting scheme of the target balance wheel sorting system based on the simulation results.

[0116] For the foregoing method embodiments, in order to simplify the description, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0117] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For apparatus embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0118] The steps in the methods of the various embodiments of this application can be adjusted, merged, or deleted in order according to actual needs, and the technical features described in each embodiment can be replaced or combined.

[0119] The modules and sub-modules in the various embodiments of the present application's devices and terminals can be merged, divided, and deleted according to actual needs.

[0120] It should be understood that the disclosed terminals, devices, and methods can be implemented in other ways, given the several embodiments provided in this application. For example, the terminal embodiments described above are merely illustrative. For instance, the division of modules or sub-modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple sub-modules or modules may be combined or integrated into another module, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0121] The modules or submodules described as separate components may or may not be physically separate. The components that constitute a module or submodule may or may not be physical modules or submodules; that is, they may be located in one place or distributed across multiple network modules or submodules. Some or all of the modules or submodules can be selected to achieve the purpose of this embodiment's solution, depending on actual needs.

[0122] Furthermore, the functional modules or sub-modules in the various embodiments of this application can be integrated into one processing module, or each module or sub-module can exist physically separately, or two or more modules or sub-modules can be integrated into one module. The integrated modules or sub-modules described above can be implemented in hardware or in the form of software functional modules or sub-modules.

[0123] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0124] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software unit executed by a processor, or a combination of both. The software unit can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0125] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0126] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for generating a balance wheel sorting scheme, characterized in that, The method includes: Obtain the sorting target of the balance wheel sorting scheme that needs to be generated in the target balance wheel sorting system. The sorting target refers to the target that is expected to be achieved during the sorting process. Based on the sorting target, at least one candidate balance wheel sorting scheme is generated; By using a digital twin model corresponding to the target balance wheel sorting system, the at least one candidate balance wheel sorting scheme is simulated to obtain the simulation results corresponding to each candidate balance wheel sorting scheme; Based on the simulation results, the pendulum sorting scheme of the target pendulum sorting system is output.

2. The method according to claim 1, characterized in that, The step of outputting the balance wheel sorting scheme of the target balance wheel sorting system based on the simulation results includes: Based on the simulation results and the sorting target, a target candidate balance wheel sorting scheme is determined from the at least one candidate balance wheel sorting scheme; The target candidate balance wheel sorting scheme is optimized based on the optimization algorithm to obtain the balance wheel sorting scheme of the target balance wheel sorting system.

3. The method according to claim 2, characterized in that, The step of determining a target candidate balance wheel sorting scheme from the at least one candidate balance wheel sorting schemes based on the simulation results and the sorting target includes: The performance indicators corresponding to the candidate balance wheel sorting schemes in the simulation results are compared with the sorting target to determine the target candidate balance wheel sorting scheme whose performance indicators are closest to the sorting target.

4. The method according to claim 2, characterized in that, The method further includes: The historical balance wheel sorting schemes of the target balance wheel sorting system are acquired at preset time intervals. The optimization algorithm is optimized based on the historical balance wheel sorting scheme. The step of optimizing the target candidate balance wheel sorting scheme based on the optimization algorithm includes: The target candidate balance wheel sorting scheme is optimized based on the optimized algorithm.

5. The method according to claim 2, characterized in that, After outputting the balance wheel sorting scheme of the target balance wheel sorting system based on the simulation results, the method further includes: The target pendulum sorting system is controlled to execute the pendulum sorting scheme to perform sorting operations.

6. The method according to claim 5, characterized in that, The method further includes: Obtain the actual operation data and simulated operation data of the balance wheel sorting scheme; Determine the difference between the actual operating data and the simulated operating data; The accuracy of the digital twin model is determined based on the difference.

7. The method according to claim 5, characterized in that, After the target balance wheel sorting system is controlled to execute the balance wheel sorting scheme to perform sorting operations, the method further includes: The real-time sorting operation progress in the target balance wheel sorting system is obtained through the digital twin model; The real-time sorting operation progress is compared with the balance wheel sorting scheme to determine that the real-time sorting operation progress is consistent with the balance wheel sorting scheme; When the real-time sorting operation progress is inconsistent with the balance wheel sorting scheme, the balance wheel sorting scheme is optimized based on the real-time sorting operation progress and the optimization algorithm to adjust the balance wheel sorting scheme.

8. An electronic device, characterized in that, include: Memory and processor; The memory is connected to the processor and is used to store programs; The processor is configured to implement the method for generating the balance wheel sorting scheme as described in any one of claims 1-7 by running a program in the memory.

9. A storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the method for generating the balance wheel sorting scheme as described in any one of claims 1-7.

10. A computer program product, characterized in that, It includes computer program instructions that, when executed by a processor, cause the processor to implement the method for generating a balance wheel sorting scheme as described in any one of claims 1 to 7.

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