Safety storage location configuration method, electronic device and computer-readable storage medium

Abstract

The present application relates to the field of automation, and in particular to a method for configuring safe storage locations, an electronic device, and a computer-readable storage medium. The method comprises: obtaining simulation data of a target production line; the simulation data comprises simulation input parameters and downtime waiting time corresponding to the simulation input parameters, and the simulation input parameters comprise simulated safe storage locations of each loading port in the target production line; training a first model based on the simulation data to obtain the trained first model; constructing an integer linear mathematical model corresponding to the first model based on the trained first model; calling a solver to solve the integer linear mathematical model to obtain an optimal safe storage location; the optimal storage location is a safe storage location that minimizes the downtime waiting time of the target production line; and configuring the safe storage locations of each loading port in the target production line according to the optimal safe storage location. In this way, the efficiency of safe storage location configuration can be effectively improved.

Description

Technical Field

[0001] The present application relates to the field of automation, and in particular to a method for configuring secure storage locations, an electronic device, and a computer-readable storage medium. Background Art

[0002] The manufacturing process of new energy batteries involves multiple processing steps, requiring many types of raw materials or production materials. Different loading ports correspond to different safety storage locations. Establishing reasonable distribution scheduling parameters, such as reasonably setting the safety storage location of each loading port, is the key to reducing downtime waiting for materials and reducing the time required for production.

[0003] Currently, the configuration of the safety storage location of the loading port is mostly done through simulation experiments using simulation software and then configured according to the simulation results. However, when determining the safety storage location through simulation experiments, there is a problem that boundary condition exploration requires a large number of simulation experiments, which makes the safety storage location setting process time-consuming and inefficient. Summary of the Invention

[0004] The present application provides a safe storage location configuration method, electronic device and computer-readable storage medium, which can quickly determine the optimal safe storage location for each loading port in a logistics distribution system, thereby improving the efficiency of safe storage location configuration.

[0005] To achieve the above objectives, this application adopts the following technical solutions:

[0006] In a first aspect, a method for configuring a secure storage location is provided, comprising:

[0007] Acquire simulation data of a target production line; the simulation data includes simulation input parameters and downtime corresponding to the simulation input parameters, wherein the simulation input parameters include simulated safe storage locations of each loading port in the target production line;

[0008] Training the first model based on the simulation data to obtain the trained first model;

[0009] Constructing an integer linear mathematical model corresponding to the first model according to the trained first model;

[0010] Invoking a solver to solve the integer linear mathematical model to obtain an optimal safe storage location; the optimal storage location is a safe storage location that minimizes the downtime of the target production line;

[0011] The safety storage location of each loading port in the target production line is configured according to the optimal safety storage location.

[0012] In an embodiment of the present application, the first model can be trained through simulation data, and the trained first model can be used to construct an integer linear mathematical model that can be solved by a solver. The optimal safe storage location can be solved based on the goal of minimizing the downtime waiting for materials, and the optimal safe storage location can be quickly determined, reducing the time consumed in the safe storage location configuration process.

[0013] In an implementation of the first aspect, constructing an integer linear mathematical model corresponding to the first model based on the trained first model includes:

[0014] constructing a first mathematical model with the goal of minimizing the output of the first model;

[0015] Extracting model parameters of the trained first model and inputting them into the first mathematical model to obtain a second mathematical model including a linear rectification function;

[0016] The linear rectification function is linearized to obtain an integer linear mathematical model.

[0017] In the embodiment of the present application, a mathematical model is constructed with minimizing the model output as the objective function, thereby constructing an integer linear mathematical model that can be solved by a solver and takes the shortest downtime waiting time as the goal. This can effectively simplify the time-consuming solution of the storage location corresponding to the shortest downtime waiting time, that is, the optimal storage location.

[0018] In an implementation of the first aspect, before acquiring simulation data of the target production line, the method further includes:

[0019] Acquiring production line data of the target production line;

[0020] Perform simulation modeling based on the production line data of the target production line to obtain a simulation model corresponding to the target production line;

[0021] A simulation experiment is performed according to the simulation model to obtain simulation data of the target production line.

[0022] In an implementation manner of the first aspect, the first model uses a linear rectification function as an activation function.

[0023] In the embodiment of the present application, the accuracy of the simulation data can be improved by constructing a simulation model corresponding to the target production line to obtain simulation data of the target production line.

[0024] In an implementation of the first aspect, the training of the first model based on the simulation data to obtain the trained first model includes:

[0025] Initialize the weights and biases of the first model;

[0026] Taking the simulation input parameters in the simulation data as input, calculating the output of each layer through the forward propagation of neurons in the first model to obtain the output of the first model;

[0027] Calculate the loss function based on the downtime waiting for material in the simulation data and the output of the first model;

[0028] The weights and biases of the first model are updated according to the loss function, and the training is iterated until a preset number of iterations is reached or the loss function reaches a preset loss threshold.

[0029] By using the above method, the simulation data is associated with the first model, so that the trained first model can output the corresponding downtime waiting time according to the input simulation input parameters.

[0030] In an implementation of the first aspect, linearizing the linear rectification function to obtain an integer linear mathematical model includes: linearizing the linear rectification function based on mixed integer linear programming.

[0031] Through the above method, mixed integer linear programming is used to optimize the form of neural network mathematical model to obtain the optimal safety storage location setting parameters in the material distribution task, which is convenient for determining the optimal safety storage location.

[0032] In an implementation of the first aspect, the production line data includes the position of the loading port of the production line, the total production quantity of the production line, and the AGV capacity data of the production line.

[0033] In an implementation of the first aspect, performing simulation modeling based on the production line data of the target production line to obtain a simulation model corresponding to the target production line includes:

[0034] Logistics simulation software is called to establish a simulation model corresponding to the production line data of the target production line.

[0035] In an embodiment of the present application, the logistics simulation software in the electronic device is called to establish a simulation model, which can combine the actual transportation capacity of the AGV and the specific location of the loading port to build a simulation model that is more in line with the actual production line, thereby further improving the accuracy of the simulation data.

[0036] In a second aspect, a safety storage location configuration device is provided, comprising:

[0037] An acquisition unit is configured to acquire simulation data of a target production line; the simulation data includes simulation input parameters and a downtime corresponding to the simulation input parameters, wherein the simulation input parameters include a simulated safe storage location of each loading port in the target production line;

[0038] A training unit, configured to train the first model based on the simulation data to obtain the trained first model;

[0039] A model construction unit, configured to construct an integer linear mathematical model corresponding to the first model based on the trained first model;

[0040] A solving unit, configured to call a solver to solve the integer linear mathematical model to obtain an optimal safe storage location; the optimal storage location is a safe storage location that minimizes the downtime of the target production line.

[0041] A configuration unit is used to configure the safety storage location of each loading port in the target production line according to the optimal safety storage location.

[0042] In a third aspect, an embodiment of the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the security storage location configuration method as described in any one of the first aspects above is implemented.

[0043] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for configuring a secure storage location as described in any one of the first aspects above is implemented.

[0044] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product is run on an electronic device, the electronic device executes the security storage location configuration method described in any one of the first aspects above.

[0045] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0046] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present application. The same reference numerals are used throughout the drawings to represent the same components. In the drawings:

[0048] Figure 1 This is a schematic diagram of an application scenario of a material distribution system provided in an embodiment of the present application;

[0049] Figure 2 This is a flow chart of a method for configuring secure storage locations provided in an embodiment of the present application;

[0050] Figure 3 This is a schematic diagram of the architecture of the first model provided in the embodiment of the present application;

[0051] Figure 4 This is a flow chart of S103 of a method for configuring secure storage locations provided in another embodiment of the present application;

[0052] Figure 5 This is a structural block diagram of a secure storage location configuration device provided in an embodiment of the present application;

[0053] Figure 6 It is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0054] The following embodiments of the technical solution of the present application will be described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present application and are therefore only examples and are not intended to limit the scope of protection of the present application.

[0055] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0056] In the description of the embodiments of this application, the technical terms "first" and "second" are used only to distinguish different objects and should not be understood to indicate or imply relative importance or implicitly specify the quantity, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, the meaning of "plurality" is more than two, unless otherwise clearly and specifically defined.

[0057] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0058] In the description of the embodiments of this application, the term "and / or" is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0059] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0060] In the description of the embodiments of the present application, the technical terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing the embodiments of the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the embodiments of the present application.

[0061] In the description of the embodiments of the present application, unless otherwise expressly specified or limited, technical terms such as "installed," "connected," "connected," and "fixed" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integration; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; internal connections between two components or interactions between two components. Those skilled in the art can understand the specific meanings of the above terms in the embodiments of the present application based on specific circumstances.

[0062] An Automated Guided Vehicle (AGV) is a battery-powered, unmanned, automated vehicle that uses automated guidance devices such as magnetic strips, tracks, or lasers to travel along a planned path. It is equipped with safety features and various auxiliary mechanisms (such as transfer and assembly mechanisms). Automated material transportation and distribution by AGVs can effectively improve production line efficiency.

[0063] In the manufacturing process of new energy batteries, AGV can also be used in the battery pack production workshop to transport production materials to the designated loading port. Generally speaking, a safety storage position is set for each loading port. If the amount of material at the loading port is less than the safety storage position and the material is not replenished in time, production will stagnate, resulting in extended downtime waiting time and affecting production efficiency.

[0064] The safety storage space can specifically refer to the amount of buffer material required by the loading port. When the amount of material in the loading port is less than the safety storage space, restocking is required.

[0065] For example, Figure 1 As shown, Figure 1 A schematic diagram of an application scenario of a material distribution system is shown in FIG. Figure 1 As shown, AGV1 can be used to transport materials required by loading port 1, and AGV2 can be used to transport materials required by loading port 2. X1 is the safe storage location of loading port 1, and X2 is the safe storage location of loading port 2. When the amount of material at loading port 1 is less than the safe storage location X1, AGV1 is controlled to replenish the material. When the amount of material at loading port 2 is less than the safe storage location X2, AGV2 is controlled to replenish the material.

[0066] If the material quantity at a certain loading port is lower than the safety storage position corresponding to the loading port and is not replenished in time, production will stagnate. Therefore, reasonably setting the safety storage position for each loading port can effectively reduce the downtime due to waiting for materials.

[0067] The setting of safe storage locations for different loading ports in current logistics distribution systems is mostly determined through simulation results of simulation software. However, determining safe storage locations through simulation experiments requires a large number of simulation experiments to explore boundary conditions. Conducting a large number of simulation experiments takes a lot of time, which is time-consuming and inefficient.

[0068] Based on this, an embodiment of the present application provides a method for configuring safe storage locations, which can train a first model through simulation data, and use the trained first model to construct an integer linear mathematical model that can be solved by a solver. It can solve the optimal safe storage location based on the goal of minimizing the downtime waiting time for materials, and can quickly determine the optimal safe storage location, reducing the time consumed in the safe storage location configuration process.

[0069] See also Figure 2 , is a flow chart provided in the embodiment of the present application. The safe storage location configuration method provided in the embodiment of the present application can be applied to electronic equipment on the production line, and can also be applied to other electronic equipment with built-in processors, or data analysis capabilities or artificial intelligence analysis capabilities. The embodiment of the present application does not make a single limitation on this. As an example and not a limitation, Figure 2 As shown, the security location configuration method may include the following steps:

[0070] S101, obtaining simulation data of a target production line.

[0071] In one embodiment of the present application, the target production line is a production line that requires a safe storage location for a loading port, and the simulation data may include simulation input parameters and the downtime corresponding to the simulation input parameters. The simulation input parameters may be simulated safe storage locations for each loading port in the target production line.

[0072] In a specific application, the target production line may include multiple loading ports. In the simulation experiment, multiple sets of simulation input parameters may be input. Each set of simulation input parameters includes the simulated safe storage location of each loading port. For example, assuming that the target production line includes three loading ports, the first set of simulation input parameters may include the simulated safe storage location X of the first loading port. 11 , the second loading port simulation safety storage location X 21 , the third loading port simulation safety storage location X 31 The second set of simulation input parameters may include the simulation safety location X of the first loading port 12 , the second loading port simulation safety storage location X 22 , the third loading port simulation safety storage location X 32 etc.

[0073] In specific applications, the above-mentioned simulation data can be obtained by simulating the target production line through simulation software to obtain a simulation model corresponding to the target production line. In the process of the simulation experiment, each set of simulation input data is input into the simulation model corresponding to the target production line to obtain the downtime waiting time corresponding to the set of simulation input data.

[0074] Specifically, an AGV refueling simulation model corresponding to the target production line can be established through logistics simulation software, and the safety storage location parameters of different refueling ports can be set. The simulation model can be run and the downtime waiting time can be recorded to obtain the above simulation data.

[0075] It should be noted that the specific numerical value of the simulation input data can be determined based on experience or randomly, and the embodiments of the present application do not impose any specific restrictions on this.

[0076] It should also be noted that the above-mentioned simulation software can adopt existing simulation software, and the embodiments of the present application do not impose specific restrictions on this.

[0077] S102: Train the first model based on the simulation data to obtain a trained first model.

[0078] Among them, the above-mentioned first model can specifically be a neural network with a linear rectification function (ReLU function) as an activation function. The trained first model can associate simulation parameters with simulation results, that is, the trained first model can output corresponding simulation results according to the input simulation parameters.

[0079] In a specific application, the process of training the first model based on simulation data may include the following steps:

[0080] Initialize the weights and biases of the neural network. The weights and biases of the neural network are parameters in the neural network, corresponding to the weights of the connected neurons and the bias values ​​of each neuron, respectively.

[0081] The simulated input parameters in the simulated data are used as input, and the output of each layer is calculated through the forward propagation of the neural network; specifically, for each layer, the input data is linearly combined with the weights, and then processed through the activation function to generate the output of the layer.

[0082] After obtaining the output of the first model, it is necessary to calculate the loss function. The loss function measures the difference between the predicted value and the true value. Commonly used loss functions include mean square error (MSE), cross entropy loss, etc. In the embodiment of the present application, the predicted value is the output of the above-mentioned neural network, and the true value is the downtime waiting time corresponding to the input simulation input parameters in the simulation data.

[0083] Update the weights and biases of the network to minimize the loss function. During the backpropagation process, first calculate the gradient of the loss function with respect to each weight, and then update the weights and biases of each neuron according to algorithms such as gradient descent. Repeat the above steps until the preset number of iterations is reached or the loss function reaches the preset loss threshold. The first model is considered to have completed training.

[0084] It should be noted that the preset number of iterations and the preset loss function can be set according to actual application requirements, and the embodiments of the present application do not impose specific restrictions on this.

[0085] For example, Figure 3 As shown, by inputting the simulation input parameters into the first model for processing, the safety storage location corresponding to each loading port and the output result corresponding to each set of simulation input parameters, namely the downtime waiting time, can be obtained.

[0086] It is understandable that the trained first model can output corresponding simulation results according to the input simulation parameters. Therefore, multiple simulation results can be obtained without performing simulation experiments multiple times.

[0087] S103: Construct an integer linear mathematical model corresponding to the first model based on the trained first model.

[0088] In specific applications, since in actual applications, the shorter the downtime waiting for materials, the more reasonable the setting of the safety storage position of the loading port is, the integer linear mathematical model corresponding to the first model can be constructed with minimizing the downtime waiting for materials as the objective function.

[0089] It should be noted that the integer linear mathematical model can be implemented based on integer linear programming. For example, the integer linear mathematical model corresponding to the first model can be constructed based on mixed integer linear programming.

[0090] It can be understood that the integer linear mathematical model can be solved by a mathematical solver to obtain the required results, so the target model constructed in the embodiment of the present application is an integer linear mathematical model.

[0091] S104: Calling a solver to solve the integer linear mathematical model to obtain the optimal safe storage location.

[0092] In specific applications, a solver can be built into the electronic device. The solver can be a commonly used mathematical solver. After constructing an integer linear mathematical model corresponding to the first model, the built-in solver in the electronic device is directly called to solve the mathematical model to obtain the required optimal safety storage position.

[0093] The above-mentioned optimal safe storage location refers to the safe storage location that minimizes the downtime waiting time for the target production line, including the safe storage location of each loading port.

[0094] S105: Configure the safety storage location of each loading port in the target production line according to the optimal safety storage location.

[0095] In specific applications, during the actual production process, by setting the safety storage location of each loading port in the target production line to a safety storage location corresponding to the optimal safety storage location, the downtime waiting time of the target production line can be minimized.

[0096] For example, assuming that the target production line includes three loading ports, and assuming that the optimal safety storage location obtained includes the optimal safety storage location X of the first loading port 1tar , the optimal safe storage location X for the second loading port 2tar , the optimal safe storage location X of the third loading port 3tar, , the safety location of the first loading port can be set to X 1tar , set the safety location of the second loading port to X 2tar , set the safety location of the third loading port to X 3tar .

[0097] From the above, it can be seen that the safety storage location configuration method provided in the embodiment of the present application can train the first model through simulation data, and use the trained first model to construct an integer linear mathematical model that can be solved by a solver. It can solve the optimal safety storage location based on the goal of minimizing the downtime waiting time for materials, and can quickly determine the optimal safety storage location, thereby reducing the time consumed in the safety storage location configuration process.

[0098] In one embodiment, Figure 4 As shown, step S103 may include:

[0099] S1031: Constructing a first mathematical model with the goal of minimizing the first model output.

[0100] In a specific application, the output of the first model is the downtime waiting for material. The shorter the downtime waiting for material, the more reasonable the setting of the safety storage position of each loading port. Therefore, by minimizing the output of the first model as the goal, a first mathematical model is constructed. The above-mentioned first mathematical model can be expressed as:

[0101] ;

[0102] The constraints are expressed as:

[0103] ;

[0104] in, minNN () represents the minimum output of the first model, Represents a collection of multiple safety locations for the first loading port. Represents a collection of multiple safety locations for the second loading port. Represents the set of multiple safe storage locations of the nth loading port, Indicates the lower limit of the safety storage position of the first loading port. Indicates the upper limit of the safety storage space of the first loading port. Indicates the lower limit of the safety storage position of the second loading port. Indicates the upper limit of the safety storage position of the second loading port. Indicates the lower limit of the safety storage position of the nth loading port, Indicates the upper limit of the safety storage space for the nth loading port.

[0105] The upper limit of the safety storage location refers to the maximum limit of the quantity of materials stored in the loading port, and the lower limit of the safety storage location refers to the minimum requirement of the quantity of materials stored in the loading port.

[0106] S1032: Extract model parameters (weights) of the trained first model and input them into the first mathematical model to obtain a second mathematical model including a linear rectification function.

[0107] The second mathematical model can be expressed as:

[0108] ;

[0109] The constraints can be expressed as:

[0110]

[0111] in, minz () represents the minimum output of the first model, Represents a collection of multiple safety locations for the first loading port. Represents a collection of multiple safety locations for the second loading port. Indicates the collection of multiple safety storage locations of the third loading port. Indicates the weight corresponding to the first feeding port neuron, Represents the weight corresponding to the second feeding port neuron.

[0112] S1033: Linearize the linear rectification function to obtain an integer linear mathematical model.

[0113] The above integer linear mathematical model can be expressed as:

[0114] ;

[0115] The constraints can be expressed as:

[0116]

[0117] in, a is the integer variable of the above integer linear mathematical model.

[0118] From the above, it can be seen that the embodiment of the present application utilizes mixed integer linear programming to optimize the form of a neural network mathematical model to obtain the optimal safety storage location setting parameters in the material distribution task, thereby facilitating the determination of the optimal safety storage location.

[0119] In one embodiment, the method further comprises:

[0120] Obtain production line data of the target production line;

[0121] Perform simulation modeling based on the production line data of the target production line to obtain a simulation model corresponding to the target production line;

[0122] Conduct simulation experiments based on the simulation model to obtain simulation data for the target production line.

[0123] In specific applications, the above production line data may specifically include the location of the loading port of the production line, the total production quantity of the production line, the AGV capacity data of the production line, etc.

[0124] In this embodiment, the simulation data of the target production line is acquired by constructing a simulation model corresponding to the target production line, thereby improving the accuracy of the simulation data.

[0125] Corresponding to the security storage location configuration method described in the above embodiment, Figure 5 This is a structural block diagram of the safe storage location configuration device provided in an embodiment of the present application. For the sake of convenience, only the parts related to the embodiment of the present application are shown.

[0126] Reference Figure 5 , the safe storage location configuration device 5 includes:

[0127] The acquisition unit 501 is used to acquire simulation data of the target production line; the simulation data includes simulation input parameters and downtime corresponding to the simulation input parameters, and the simulation input parameters include the simulated safe storage location of each loading port in the target production line;

[0128] The training unit 502 is configured to train the first model based on the simulation data to obtain the trained first model;

[0129] The model construction unit 503 is used to construct an integer linear mathematical model corresponding to the first model according to the trained first model;

[0130] The solving unit 504 is used to call a solver to solve the integer linear mathematical model to obtain an optimal safe storage location; the optimal storage location is a safe storage location that minimizes the downtime of the target production line.

[0131] The configuration unit 505 is used to configure the safety storage location of each loading port in the target production line according to the optimal safety storage location.

[0132] In some implementations, the model construction unit 503 is specifically used to construct a first mathematical model with the goal of minimizing the output of the first model; extract the model parameters of the trained first model and input them into the first mathematical model to obtain a second mathematical model including a linear rectification function; linearize the linear rectification function to obtain an integer linear mathematical model.

[0133] In some implementations, the above-mentioned safe storage location configuration device 5 may also include a simulation unit, which can be specifically used to obtain the production line data of the target production line; perform simulation modeling based on the production line data of the target production line to obtain a simulation model corresponding to the target production line; and perform simulation experiments based on the simulation model to obtain simulation data of the target production line.

[0134] In some implementations, the training unit 503 may be specifically used to initialize the weights and biases of the first model;

[0135] The simulation input parameters in the simulation data are used as input, and the output of each layer is calculated through forward propagation of neurons in the first model to obtain the output of the first model; the loss function is calculated according to the downtime waiting for material in the simulation data and the output of the first model; the weights and bias of the first model are updated according to the loss function, and training is iterated until a preset number of iterations is reached or the loss function reaches a preset loss threshold.

[0136] In some implementations, the first model uses a linear rectification function as an activation function.

[0137] In some implementations, the linear rectification function is linearized based on mixed integer linear programming.

[0138] In some implementations, the production line data includes the location of the loading port of the production line, the total production quantity of the production line, and the AGV capacity data of the production line.

[0139] Optionally, the simulation unit is further used to: call logistics simulation software to establish a simulation model corresponding to the production line data of the target production line.

[0140] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of this application. Their specific functions and technical effects can be found in the method embodiment section and will not be repeated here.

[0141] Based on this, the safety storage location configuration device provided in the embodiment of the present application can also train the first model through simulation data, and use the trained first model to construct an integer linear mathematical model that can be solved by a solver. It can solve the optimal safety storage location based on the goal of minimizing the downtime waiting time for materials, and can quickly determine the optimal safety storage location, reducing the time consumed in the safety storage location configuration process.

[0142] in addition, Figure 5 The secure storage location configuration device shown can be a software unit, a hardware unit, or a combination of software and hardware units built into an existing electronic device, or can be integrated into the electronic device as an independent pendant, or can exist as an independent electronic device.

[0143] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0144] Figure 6 Schematic diagram of the structure of the electronic device provided in the embodiment of the present application. Figure 6 As shown, the electronic device 6 of this embodiment includes: at least one processor 60 ( Figure 6 Only one is shown in the figure) a processor, a memory 61, and a computer program 62 stored in the memory 61 and executable on the at least one processor 60, wherein the processor 60 implements the steps of any of the above-mentioned embodiments of the security storage location configuration method when executing the computer program 62.

[0145] The electronic device may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art will understand that Figure 6 This is merely an example of the electronic device 6 and does not constitute a limitation on the electronic device 6 . The electronic device 6 may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device 6 may also include input and output devices, network access devices, etc.

[0146] The processor 60 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor may be a microprocessor or any conventional processor.

[0147] In some embodiments, the memory 61 may be an internal storage unit of the electronic device 6, such as a hard drive or memory of the electronic device 6. In other embodiments, the memory 61 may also be an external storage device of the electronic device 6, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. equipped on the electronic device 6. Furthermore, the memory 61 may include both an internal storage unit of the electronic device 6 and an external storage device. The memory 61 is used to store an operating system, application programs, a boot loader, data, and other programs, such as the program code of the computer program. The memory 61 may also be used to temporarily store data that has been output or is about to be output.

[0148] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned various method embodiments can be implemented.

[0149] An embodiment of the present application provides a computer program product. When the computer program product is run on an electronic device, the electronic device can implement the steps of the above-mentioned method embodiments when executing the computer program product.

[0150] If the integrated unit is implemented as a software functional unit and sold or used as a standalone product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the process steps in the above-mentioned method embodiments by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When executed by a processor, the computer program can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a device / electronic device, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signals, telecommunication signals, and software distribution media. Examples include USB flash drives, removable hard drives, magnetic disks, or optical disks. In some jurisdictions, based on legislation and patent practice, computer-readable media cannot be electric carrier signals or telecommunication signals.

[0151] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0152] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel 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.

[0153] In the embodiments provided in the present application, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely schematic. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0154] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0155] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A method for configuring safe storage locations, characterized in that: include: Acquire simulation data of a target production line; the simulation data includes simulation input parameters and downtime corresponding to the simulation input parameters, wherein the simulation input parameters include simulated safe storage locations of each loading port in the target production line; Training the first model based on the simulation data to obtain a trained first model; wherein the first model is a neural network with a linear rectifier function as an activation function, and the trained first model is used to output corresponding simulation results according to simulation input parameters; Based on the trained first model, an integer linear mathematical model corresponding to the first model is constructed with minimizing the downtime waiting for material as the objective function; wherein the integer linear mathematical model is a mathematical model that can be solved by a mathematical solver; Invoking a solver to solve the integer linear mathematical model to obtain an optimal safe storage location; the optimal storage location is a safe storage location that minimizes the downtime of the target production line; Configuring the safety storage location of each loading port in the target production line according to the optimal safety storage location; The step of training the first model based on the simulation data to obtain the trained first model includes: Initialize the weights and biases of the first model; Taking the simulation input parameters in the simulation data as input, calculating the output of each layer through the forward propagation of neurons in the first model to obtain the output of the first model; Calculate the loss function based on the downtime waiting for material in the simulation data and the output of the first model; The weights and biases of the first model are updated according to the loss function, and the training is iterated until a preset number of iterations is reached or the loss function reaches a preset loss threshold.

2. The method for configuring safe storage locations according to claim 1, wherein: The step of constructing an integer linear mathematical model corresponding to the first model according to the trained first model includes: constructing a first mathematical model with the goal of minimizing the output of the first model; Extracting model parameters of the trained first model and inputting them into the first mathematical model to obtain a second mathematical model including a linear rectification function; The linear rectification function is linearized to obtain an integer linear mathematical model.

3. The method for configuring safe storage locations according to claim 1 or 2, characterized in that: Before obtaining the simulation data of the target production line, the method further includes: Acquiring production line data of the target production line; Perform simulation modeling based on the production line data of the target production line to obtain a simulation model corresponding to the target production line; A simulation experiment is performed according to the simulation model to obtain simulation data of the target production line.

4. The method for configuring safe storage locations according to claim 2, wherein: The linear rectification function is linearized to obtain an integer linear mathematical model, including: The linear rectifier function is linearized based on mixed integer linear programming.

5. The method for configuring safe storage locations according to claim 3, wherein: The production line data includes the location of the loading port of the production line, the total production quantity of the production line, and the AGV capacity data of the production line.

6. The method for configuring safe storage locations according to claim 3, characterized in that: The performing simulation modeling according to the production line data of the target production line to obtain a simulation model corresponding to the target production line includes: Logistics simulation software is called to establish a simulation model corresponding to the production line data of the target production line.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for configuring secure storage locations according to any one of claims 1 to 6 is implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for configuring secure storage locations according to any one of claims 1 to 6 is implemented.

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