A strategy model creation method, system, device, apparatus and storage medium

Abstract

The present disclosure provides a strategy model creation method, system, device, equipment and storage medium, wherein the method comprises: determining a strategy algorithm based on a target requirement, and initializing a first strategy model based on the strategy algorithm, the first strategy model comprising system nodes and sub-nodes; determining a first analysis process model template bound to the first strategy model; wherein the sub-nodes are updated based on the target requirement, a second strategy model is generated; in response to the update of the sub-nodes, the sub-process template is updated correspondingly, and a second analysis process model template is obtained; parameter information of the second strategy model is acquired, a variable role corresponding to the parameter information is determined, a data flow mapping relationship of the variable role is established based on a mapping relationship configuration rule; based on the variable role and the data flow mapping relationship, the second analysis process model template is updated to a bottom-layer analysis process model; and distributed computing resources are configured for the system nodes and the updated sub-nodes in the second strategy model based on a first allocation algorithm.

Description

Technical Field

[0001] This disclosure relates to the field of multidisciplinary design optimization, and in particular to a strategy model creation method, system, apparatus, device, and storage medium. Background Technology

[0002] Multidisciplinary design optimization (MDO), as a new and effective theory and method for solving complex product (system) design problems, has received increasing attention. MDO strategies include Bi-Level Integrated System Synthesis (BLISS), Collaborative Optimization (CO), Concurrent Subspace Optimization (CSSO), and Multidisciplinary Design Feasibility (MDF), each with its own complex MDO professional knowledge principles.

[0003] Existing MDO software platforms have weak support for MDO strategies, and the setup process is complex and lengthy. Therefore, creating an MDO strategy model using existing technologies is very difficult for designers who do not have MDO expertise. Summary of the Invention

[0004] This disclosure provides a strategy model creation method, system, apparatus, device, and storage medium to at least solve the above-mentioned technical problems existing in the prior art.

[0005] According to a first aspect of this disclosure, a method for creating a strategy model is provided, the method comprising:

[0006] The strategy algorithm is determined based on the target requirements, and a first strategy model is initialized based on the strategy algorithm. The first strategy model includes system nodes and sub-nodes. A first analysis process model template is determined and bound to the first strategy model, wherein the system node and the sub-node correspond to the sub-process template composed of process components and / or activity components in the first analysis process model template; The child node is updated based on the target requirements to generate a second strategy model; In response to the update of the child node, the corresponding sub-process template is updated to obtain the second analysis process model template; Obtain the parameter information of the second strategy model, determine the variable role corresponding to the parameter information, and establish the data flow mapping relationship of the variable role based on the mapping relationship configuration rules; Based on the variable roles and the data flow mapping relationship, the second analysis process model template is updated to the underlying analysis process model; Distributed computing resources are configured for the system nodes and the updated child nodes in the second strategy model based on the first allocation algorithm.

[0007] In one possible implementation, after generating the strategy model and before determining the strategy algorithm based on target requirements, the method further includes: The strategy algorithm code is determined based on the strategy algorithm interface specification; Obtain the strategy algorithm entry, and encapsulate the strategy algorithm code into the strategy algorithm entry; Determine the strategy algorithm interface parameters corresponding to the strategy algorithm code, bind the strategy algorithm interface parameters to the strategy algorithm entry, and package and publish the strategy algorithm interface parameters and the strategy algorithm code to the strategy algorithm library; The strategy algorithm entries are used to call the corresponding strategy algorithm from the strategy algorithm library according to the target requirements.

[0008] In one possible implementation, updating the child node based on the target requirement includes: The sub-nodes are divided into subsystem nodes and subtask analysis nodes; Perform at least one of the following operations based on the stated target requirements: Add the subsystem node and / or the subtask analysis node; Delete the subsystem node and / or the subtask analysis node; Configure the optimization-related algorithms for the subsystem nodes; Update the parameter information of the active component in the subtask analysis node.

[0009] In one possible implementation, determining the variable role corresponding to the parameter information includes: The variable role type is determined based on the aforementioned strategy algorithm; Based on the algorithm rules and parameter information attributes of the strategy algorithm, the variable role type and the parameter information are matched to obtain the variable role.

[0010] In one possible implementation, before configuring the optimization-related algorithms for the subsystem nodes based on the target requirements, the method further includes: The code for the optimization-related algorithms is determined based on the interface specifications of the optimization-related algorithms; Obtain optimization-related algorithm entries, and encapsulate the optimization-related algorithms into the optimization-related algorithm entries; Determine the optimization-related algorithm interface parameters corresponding to the optimization-related algorithm code, bind the optimization-related algorithm interface parameters to the optimization-related algorithm entries, and package and publish the optimization-related algorithm interface parameters and the optimization-related algorithm code to the optimization-related algorithm library; The optimization-related algorithm entries are used to call the corresponding optimization-related algorithms from the optimization-related algorithm library according to the target requirements.

[0011] According to a second aspect of this disclosure, a strategy model creation system is provided, the system comprising: The strategy application module is used to store blank strategy models and perform debugging operations based on the blank strategy models. The strategy model design module is used to determine a strategy algorithm based on target requirements, and initialize a first strategy model based on the strategy algorithm, wherein the first strategy model includes system nodes and child nodes; determine a first analysis process model template bound to the first strategy model, wherein the system nodes and the child nodes correspond to sub-process templates composed of process components and / or activity components in the first analysis process model template; update the child nodes based on the target requirements to generate a second strategy model; update the sub-process templates in response to the update of the child nodes to obtain a second analysis process model template; obtain parameter information of the second strategy model, determine the variable roles corresponding to the parameter information, and establish a data flow mapping relationship of the variable roles based on mapping relationship configuration rules; and update the second analysis process model template to the underlying analysis process model based on the variable roles and the data flow mapping relationship. The strategy algorithm management module is used to write the strategy algorithm based on the interface specification of the strategy algorithm, and to publish and manage the strategy algorithm. The process model management module is used to store the first analysis process model template, the second analysis process model template, and the underlying analysis process model, and to debug the underlying analysis process model based on the target requirements. An optimization-related algorithm management module is used to write optimization-related algorithms based on the interface specifications of optimization-related algorithms, and to publish and manage the optimization-related algorithms. The computing resource scheduling module is used to configure distributed computing resources for the system nodes and the updated child nodes in the second strategy model based on the first allocation algorithm.

[0012] According to a third aspect of this disclosure, a strategy model creation apparatus is provided, the apparatus comprising: The strategy algorithm selection unit is used to determine the strategy algorithm based on the target requirements and initialize the first strategy model based on the strategy algorithm. The first strategy model includes system nodes and sub-nodes. An analysis process model configuration unit is used to determine a first analysis process model template bound to the first strategy model, wherein the system node and the sub-node correspond to the sub-process template composed of process components and / or activity components in the first analysis process model template; The analysis process model update unit is used to update the sub-nodes based on the target requirements and generate a second strategy model; in response to the update of the sub-nodes, the sub-process template is updated accordingly to obtain the second analysis process model template. The mapping unit is used to obtain parameter information of the second strategy model, determine the variable role corresponding to the parameter information, and establish the data flow mapping relationship of the variable role based on the mapping relationship configuration rules; The model generation unit is used to update the second analysis process model template to the underlying analysis process model based on the variable roles and the data flow mapping relationship; The resource allocation unit is used to configure distributed computing resources for the system nodes and the updated child nodes in the second strategy model based on the first allocation algorithm.

[0013] In one possible embodiment, the device further includes: The strategy algorithm configuration unit is used to determine the strategy algorithm code based on the strategy algorithm interface specification; obtain the strategy algorithm entry, encapsulate the strategy algorithm code into the strategy algorithm entry; determine the strategy algorithm interface parameters corresponding to the strategy algorithm code, bind the strategy algorithm interface parameters to the strategy algorithm entry, and package and publish the strategy algorithm interface parameters and the strategy algorithm code to the strategy algorithm library; the strategy algorithm entry is used to call the corresponding strategy algorithm from the strategy algorithm library according to the target requirements; An optimization-related algorithm configuration unit is used to determine the optimization-related algorithm code based on the interface specification of the optimization-related algorithm; obtain optimization-related algorithm entries, encapsulate the optimization-related algorithm into the optimization-related algorithm entries; determine the optimization-related algorithm interface parameters corresponding to the optimization-related algorithm code, bind the optimization-related algorithm interface parameters to the optimization-related algorithm entries, and package and publish the optimization-related algorithm interface parameters and the optimization-related algorithm code to the optimization-related algorithm library; the optimization-related algorithm entries are used to call the corresponding optimization-related algorithm from the optimization-related algorithm library according to the target requirements.

[0014] According to a fourth aspect of this disclosure, an electronic device is provided, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the methods described in this disclosure.

[0015] According to a fifth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions for causing the computer to perform the methods described in this disclosure.

[0016] This disclosure discloses a strategy model creation method, system, apparatus, device, and storage medium. Based on target requirements, a strategy algorithm is determined. A first strategy model is initialized based on the strategy algorithm, and a first analysis process model template bound to the first strategy model is determined. The child nodes of the first strategy model are updated according to the target requirements to generate a second strategy model. Correspondingly, the sub-process templates of the first analysis process model are updated to obtain the second analysis process model template. Variable roles are determined based on the parameter information of the second strategy model. Data flow mapping relationships between variable roles are established using mapping relationship configuration rules. The second analysis process model template is updated to the underlying analysis process model according to the mapping relationship, and computing resources are configured for the nodes in the second strategy model. The MDO process model, created in a standardized manner based on the MDO strategy algorithm, is placed in the background as the underlying analysis process model. Only key steps and data requiring user configuration are retained on the front end. Users only need to perform minimal configuration to complete the creation of the MDO strategy model, improving the efficiency of MDO development for complex products and lowering the development threshold.

[0017] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0018] The above and other objects, features, and advantages of this disclosure will become readily apparent from the following detailed description of exemplary embodiments, taken in conjunction with the accompanying drawings. Several embodiments of this disclosure are illustrated in the drawings by way of example and not limitation, in which: In the accompanying drawings, the same or corresponding reference numerals indicate the same or corresponding parts.

[0019] Figure 1 This illustration shows the implementation flow of a strategy model creation method according to an embodiment of the present disclosure. Figure 1 ; Figure 2 This illustration shows the implementation flow of a strategy model creation method according to an embodiment of the present disclosure. Figure 2 ; Figure 3A schematic diagram of a strategy model creation system according to an embodiment of this disclosure is shown; Figure 4 A schematic diagram of a strategy model creation apparatus according to an embodiment of the present disclosure is shown; Figure 5 A schematic diagram of the composition structure of an electronic device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0020] To make the objectives, features, and advantages of this disclosure more apparent and understandable, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort are within the scope of protection of this disclosure.

[0021] Figure 1 This illustration shows the implementation flow of a strategy model creation method according to an embodiment of the present disclosure. Figure 1 ,like Figure 1 As shown, the implementation process of a strategy model creation method according to an embodiment of this disclosure includes the following steps: Step 101: Determine the strategy algorithm based on the target requirements, and initialize the first strategy model based on the strategy algorithm. The first strategy model includes system nodes and sub-nodes.

[0022] In this embodiment, the strategy algorithm is an MDO strategy algorithm, including types such as BLISS, CO, CSSO, and MDF. Corresponding basic strategy model templates are stored in categories. The strategy algorithm is determined based on the target requirements, and the corresponding basic strategy model template is called to initialize and form the first strategy model. The complete implementation logic of the strategy model is composed of system nodes and child nodes, where the child nodes are divided into subsystem nodes and subtask analysis nodes.

[0023] In this embodiment, the strategy algorithm code is determined based on the interface specification of the strategy algorithm. The interface specification of the strategy algorithm is a set of pre-defined standardized interface constraint rules for enabling collaborative work with elements such as process model templates, variable roles, and optimization-related algorithms. Strategy algorithm entries are obtained, which can be created in the strategy algorithm management module. The strategy algorithm entries in the strategy algorithm management module are then obtained, and the strategy algorithm code is encapsulated into the strategy algorithm entries. The strategy algorithms include, but are not limited to, BLISS, CO, CSSO, and MDF. Strategy algorithm interface parameters corresponding to the strategy algorithm code are determined. These parameters include an identifier ID, constraint parameters, and core logic configuration parameters. The core logic configuration parameters correspond to the strategy algorithms; for example, the core logic configuration parameters of the BLISS algorithm include hierarchical partitioning parameters, hierarchical collaboration parameters, and sub-problem decomposition parameters. The strategy algorithm interface parameters are bound to the strategy algorithm entries, and the strategy algorithm interface parameters and the strategy algorithm code are packaged and published to the strategy algorithm library. The strategy algorithm entries are used to call the corresponding strategy algorithm from the strategy algorithm library according to the target requirements. The strategy algorithm library is the background data storage center of the strategy algorithm management module and is used to store strategy algorithms.

[0024] Step 102: Determine the first analysis process model template bound to the first strategy model, wherein the system node and the sub-node correspond to the sub-process template composed of process components and / or activity components in the first analysis process model template.

[0025] In this embodiment, the first analysis process model template and the first strategy model are bound together. That is, when the corresponding first strategy model is determined by the strategy algorithm, the first analysis process model template bound to the first strategy model is determined. The first analysis process model template is a pre-stored standard analysis process model template in the system, encapsulating a hierarchical process model of "system-level analysis model and subject-level analysis model." The first analysis process model template consists of process components and activity components, enabling it to implement the corresponding strategy algorithm. The aforementioned system nodes, subsystem nodes, and subtask analysis nodes are composed of process components and / or activity components to ensure the correspondence between the first analysis process model template and the first strategy model. Specifically, system nodes, subsystem nodes, and subtask analysis nodes are functional units in the hierarchical structure of the analysis process model, possessing clear analysis objectives and independent execution boundaries. They correspond to the analysis tasks of the analysis process model and are used to encapsulate a specific subject analysis, system performance calculation, or specific simulation task (such as structural strength analysis, energy consumption calculation, fluid dynamics simulation, etc.) of a complex product into an independent process unit.

[0026] Step 103: Update the sub-nodes based on the target requirements to generate a second strategy model; in response to the update of the sub-nodes, update the corresponding sub-process template to obtain a second analysis process model template.

[0027] In this embodiment, the sub-nodes are divided into subsystem nodes and subtask analysis nodes. Based on the target requirements, at least one of the following operations is performed: adding the subsystem node and / or the subtask analysis node; deleting the subsystem node and / or the subtask analysis node; configuring the optimization-related algorithms of the subsystem node; and updating the parameter information of the active components in the subtask analysis node. After updating the sub-nodes, a second strategy model is generated. The second strategy model is a strategy model obtained by updating the nodes based on the first strategy model, used to execute the strategy algorithm and meet the target requirements. Since the nodes correspond to the sub-process templates, the sub-process templates are updated accordingly in response to the updates of the sub-nodes, resulting in a second analysis process model template. The second analysis process model template corresponds to the second strategy model.

[0028] In this embodiment of the disclosure, a component is the smallest functional unit used to implement a single, specific calculation or data processing function. It can be connected in series or in parallel according to a logical order to form a complete analysis logic, realize the performance calculation function of a discipline / system, and then form a sub-process template corresponding to the sub-node.

[0029] In this embodiment of the disclosure, before configuring optimization-related algorithms for each sub-node in the analysis process model, the optimization-related algorithm code is determined based on the interface specification of the optimization-related algorithm, optimization-related algorithm entries are obtained, and the optimization-related algorithms are encapsulated into the optimization-related algorithm entries. Optimization-related algorithm entries can be created in the optimization-related algorithm management module. Optimization-related algorithm interface parameters corresponding to the optimization-related algorithm code are determined, the optimization-related algorithm interface parameters are bound to the optimization-related algorithm entries, and the optimization-related algorithm interface parameters and the optimization-related algorithm code are packaged and published to the optimization-related algorithm library. The optimization-related algorithm entries are used to call the corresponding optimization-related algorithm from the optimization-related algorithm library according to target requirements.

[0030] Step 104: Obtain the parameter information of the second strategy model, determine the variable role corresponding to the parameter information, and establish the data flow mapping relationship of the variable role based on the mapping relationship configuration rules.

[0031] In this embodiment, the parameter information of the second strategy model specifically includes the parameter information of components in the second analysis process model template corresponding to the second strategy model, including model design parameters and performance parameters. The variable role type is determined based on the strategy algorithm; according to the algorithm rules of the strategy algorithm and the attributes of the parameter information, the variable role type and the parameter information are matched to obtain the variable role. Specifically, the parameter information includes: parameter attribute information, parameter value information, and parameter association information of the input analysis model; parameter attribute information, parameter performance information, and parameter association information of the output analysis model; and calculation accuracy information of the analysis process model calculation rules. By extracting parameters that meet the requirements, the parameter information and the variable role type are matched based on the rules of the strategy algorithm and the attributes of the parameter information to obtain the variable role.

[0032] In this embodiment of the disclosure, the mapping relationship configuration rules include, but are not limited to: association matching rules, data transmission rules and transmission constraint rules. The above variable roles are configured based on the mapping relationship configuration rules to form a data flow mapping relationship, and the mapping relationship configuration rule verification engine determines that there is no logical conflict in the mapping relationship.

[0033] Step 105: Based on the variable roles and the data flow mapping relationship, update the second analysis process model template to the underlying analysis process model.

[0034] In this embodiment of the disclosure, based on the above-mentioned variable roles and data flow mapping relationship, the association link between variables in each sub-process template in the second analysis process model template corresponding to the second strategy model is established, and after logical verification and data verification, the underlying analysis process model is generated.

[0035] Step 106: Configure distributed computing resources for the system nodes and the updated child nodes in the second strategy model based on the first allocation algorithm.

[0036] In this embodiment of the disclosure, the first allocation algorithm is a load balancing algorithm. Users can specify distributed computing resources, that is, specify computing workstations for system-level or subject-level analysis and computing respectively, to perform distributed computing. If the user does not specify computing resources, the distributed computing resources of the system nodes and the updated child nodes in the second strategy model are automatically configured based on the load balancing principle to complete the construction of the strategy model.

[0037] Figure 2 This illustration shows the implementation flow of a strategy model creation method according to an embodiment of the present disclosure. Figure 2 ,like Figure 2 As shown, the implementation process of a strategy model creation method according to an embodiment of this disclosure includes the following steps: Step 201: Create a new strategy model and select a strategy algorithm.

[0038] In this embodiment, the strategy model is an MDO strategy model, and the strategy algorithm is an MDO strategy algorithm, including at least BLISS, CO, CSSO, and MDF. The strategy algorithm is determined based on the target requirements, and the corresponding strategy model model is initialized by calling the basic strategy model template. Before selecting an MDO strategy algorithm, the MDO strategy algorithm code is written based on the MDO strategy algorithm interface specification, which defines the rules that the algorithm must follow to be embedded in the platform. A new MDO strategy algorithm entry is created on the platform. The MDO strategy algorithm code written based on the MDO strategy algorithm interface specification is added to the MDO strategy algorithm entry. The MDO strategy algorithm interface parameters are configured. The MDO strategy algorithm is packaged and published to the platform, where the platform is an MDO integration platform that provides a carrier for building the strategy model.

[0039] Step 202: Bind the analysis process model template.

[0040] In this embodiment of the disclosure, the analysis process model template is a process model used for instantiation to generate system or subject performance calculations. It includes one system-level analysis sub-process model template and no less than two subject-level analysis sub-process model templates. The analysis process model template and the corresponding analysis sub-process model template are preset in the platform backend and do not require user editing. Different MDO strategy algorithms correspond to different analysis process model templates.

[0041] Step 203: Define variable roles and set up relevant optimization algorithms.

[0042] In this embodiment of the disclosure, the variable role is the MDO variable role, which includes system design variables, discipline design variables, coupled state variables, uncoupled state variables, etc. The variable role corresponding to the MDO strategy algorithm is selected.

[0043] In this embodiment of the disclosure, the code for optimization-related algorithms is written based on the interface specification of optimization-related algorithms. Optimization-related algorithms include: optimization algorithms, Design of Experiments (DOE) algorithms, surrogate model algorithms, etc. The interface specification of optimization-related algorithms is the rule that the algorithm must follow to be embedded in the platform. A new algorithm entry is created in the platform; the optimization-related algorithm code written based on the interface specification of optimization-related algorithms is added to the algorithm entry; the interface parameters of optimization-related algorithms are configured; the algorithm is packaged and published to the platform for selection when setting optimization-related algorithms.

[0044] Step 204: Establish data flow mapping relationship.

[0045] In this embodiment, the complete implementation logic of the strategy model is composed of system nodes and sub-nodes, wherein the sub-nodes are divided into subsystem nodes and subtask analysis nodes. Users create data flow mapping relationships between variable roles according to data flow mapping rules to achieve data transfer and mapping between system nodes, subsystem nodes, and subtask analysis nodes.

[0046] Step 205: Select distributed computing resources.

[0047] In this embodiment of the disclosure, the user can specify distributed computing resources, that is, specify computing workstations for system-level or subject-specific analysis and computing, to perform distributed computing. If the user does not specify computing resources, computing workstations are automatically allocated based on the load balancing principle of the computing resource scheduling module. Distributed computing resources refer to workstations registered on the system server, which can be distributed across different physical machines, supporting heterogeneous environments such as Windows and Linux systems.

[0048] Step 206: Generate the underlying process model.

[0049] In this embodiment of the disclosure, the underlying process model of MDO is generated. Specifically, based on the variable roles set in step 203, the optimization-related algorithms, the data flow mapping relationship established in step 204, and the distributed computing resources selected in step 205, the analysis process model template bound in step 202 is instantiated into the underlying analysis process model according to the MDO strategy algorithm rules selected in step 201.

[0050] Figure 3 A schematic diagram of a strategy model creation system according to an embodiment of this disclosure is shown, such as... Figure 3 As shown, an embodiment of this disclosure provides a strategy model creation system including: The strategy application module 301 is used to store blank strategy models and perform debugging operations based on the blank strategy models. The debugging operations include creating, viewing, editing, deleting, and sharing MDO strategy models.

[0051] The strategy model design module 302 is used to determine a strategy algorithm based on target requirements, initialize a first strategy model based on the strategy algorithm, the first strategy model including system nodes and child nodes; determine a first analysis process model template bound to the first strategy model, wherein the system nodes and the child nodes correspond to sub-process templates composed of process components and / or activity components in the first analysis process model template; update the child nodes based on the target requirements to generate a second strategy model; update the sub-process templates in response to the update of the child nodes to obtain the second analysis process model template; obtain parameter information of the second strategy model, and determine the... The variable roles corresponding to the parameter information are defined, and the data flow mapping relationship of the variable roles is established based on the mapping relationship configuration rules. Based on the variable roles and the data flow mapping relationship, the second analysis process model template is updated to the underlying analysis process model. Specifically, a new strategy model is created, a strategy algorithm is selected from the strategy algorithm management module, the first analysis process model and the second analysis process model in the process model management module 304 are bound, variable roles are defined, and the optimization algorithm, DOE algorithm and approximate modeling algorithm are set according to the optimization related algorithm management module 305. The data flow mapping relationship is established, distributed computing resources are selected, and the underlying strategy process model is generated.

[0052] The strategy algorithm management module 303 is used to manage MDO strategy algorithms, including creating, editing, publishing, viewing, deleting, and sharing MDO strategy algorithms. It writes the strategy algorithms based on the strategy algorithm interface specification and publishes and manages them. Specifically, the publishing process for the strategy algorithm is as follows: write the strategy algorithm based on the strategy algorithm interface specification, create a new strategy algorithm entry, add the strategy algorithm code to the strategy algorithm entry, configure the strategy algorithm interface parameters, and package and publish it to the strategy algorithm library.

[0053] The process model management module 304 is used to store the first analysis process model template, the second analysis process model template, and the underlying analysis process model, and to debug the underlying analysis process model based on the target requirements. The debugging includes viewing and verifying the underlying analysis process model.

[0054] The optimization-related algorithm management module 305 is used to publish and manage optimization algorithms, DOE algorithms, proxy model algorithms, etc., including creating, editing, publishing, viewing, deleting, and sharing algorithms. Specifically, the process for publishing optimization-related algorithms is as follows: write the optimization-related algorithm based on the interface specification, create a new optimization-related algorithm, add the optimization-related algorithm code, configure the optimization-related algorithm parameters, and package and publish it to the optimization-related algorithm library.

[0055] The computing resource scheduling module 306 is used to configure the distributed computing resources of the system nodes and the updated child nodes in the second strategy model based on the first allocation algorithm. System-level or subject-specific analytical computing can be scheduled to be executed on different workstations. If the user does not specify computing resources, the computing resource scheduling module automatically allocates computing workstations.

[0056] Figure 4 A schematic diagram of a strategy model creation apparatus according to an embodiment of the present disclosure is shown, such as Figure 4 As shown, an embodiment of this disclosure provides a strategy model creation apparatus comprising: The strategy algorithm selection unit 401 is used to determine the strategy algorithm based on the target requirements and initialize the first strategy model based on the strategy algorithm. The first strategy model includes system nodes and sub-nodes.

[0057] The analysis process model configuration unit 402 is used to determine a first analysis process model template bound to the first strategy model, wherein the system node and the sub-node correspond to the sub-process template composed of process components and / or activity components in the first analysis process model template.

[0058] The analysis process model update unit 403 is used to update the sub-nodes based on the target requirements and generate a second strategy model; in response to the update of the sub-nodes, the sub-process template is updated accordingly to obtain the second analysis process model template.

[0059] The analysis process model update unit 403 is further configured to: divide the sub-nodes into subsystem nodes and subtask analysis nodes; and perform at least one of the following operations based on the target requirements: add the subsystem node and / or the subtask analysis node; delete the subsystem node and / or the subtask analysis node; configure the optimization-related algorithms of the subsystem node; and update the parameter information of the active components in the subtask analysis node.

[0060] The mapping unit 404 is used to obtain parameter information of the second strategy model, determine the variable role corresponding to the parameter information, and establish the data flow mapping relationship of the variable role based on the mapping relationship configuration rules.

[0061] The mapping unit 404 is further configured to: determine the variable role type based on the strategy algorithm; and match the variable role type with the parameter information according to the algorithm rules of the strategy algorithm and the attributes of the parameter information to obtain the variable role.

[0062] The model generation unit 405 is used to update the second analysis process model template to the underlying analysis process model based on the variable roles and the data flow mapping relationship.

[0063] Resource configuration unit 406 is used to configure distributed computing resources for the system nodes and the updated child nodes in the second strategy model based on the first allocation algorithm.

[0064] The optimization-related algorithm configuration unit 407 is used to determine the optimization-related algorithm code based on the interface specification of the optimization-related algorithm, create optimization-related algorithm entries in the optimization-related algorithm management module, and add the optimization-related algorithm code to the optimization-related algorithm entries; based on the optimization-related algorithm entries, bind the interface parameters of the optimization-related algorithm to the optimization-related algorithm entries, and package and publish them to the optimization-related algorithm library based on the interface parameters and the optimization-related algorithm code; wherein, the optimization-related algorithm entries are used to call the corresponding optimization-related algorithm according to the strategy algorithm.

[0065] The strategy algorithm configuration unit 408 is used to determine the strategy algorithm code based on the strategy algorithm interface specification; obtain the strategy algorithm entry, encapsulate the strategy algorithm code into the strategy algorithm entry; determine the strategy algorithm interface parameters corresponding to the strategy algorithm code, bind the strategy algorithm interface parameters to the strategy algorithm entry, and package and publish the strategy algorithm interface parameters and the strategy algorithm code to the strategy algorithm library; the strategy algorithm entry is used to call the corresponding strategy algorithm from the strategy algorithm library according to the target requirements.

[0066] In an exemplary embodiment, the strategy algorithm selection unit 401, analysis process model configuration unit 402, analysis process model update unit 403, mapping unit 404, model generation unit 405, resource configuration unit 406, optimization-related algorithm configuration unit 407, and strategy algorithm configuration unit 408 may be implemented by one or more central processing units (CPUs), graphics processing units (GPUs), application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers (MCUs), microprocessors, or other electronic components.

[0067] Regarding the apparatus in the above embodiments, the specific manner in which each module and unit performs its operations has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0068] According to embodiments of this disclosure, this disclosure also provides an electronic device and a readable storage medium.

[0069] Figure 5 A schematic block diagram of an example electronic device 800 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0070] like Figure 5 As shown, the electronic device 800 includes a computing unit 801, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 into a random access memory (RAM) 803. The RAM 803 may also store various programs and data required for the operation of the electronic device 800. The computing unit 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0071] Multiple components in electronic device 800 are connected to I / O interface 805, including: input unit 806, such as keyboard, mouse, etc.; output unit 807, such as various types of displays, speakers, etc.; storage unit 808, such as disk, optical disk, etc.; and communication unit 809, such as network card, modem, wireless transceiver, etc. Communication unit 809 allows electronic device 800 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0072] The computing unit 801 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 801 performs the various methods and processes described above, such as a policy model creation method. For example, in some embodiments, a policy model creation method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 808. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 800 via ROM 802 and / or communication unit 809. When the computer program is loaded into RAM 803 and executed by the computing unit 801, one or more steps of a policy model creation method described above may be performed. Alternatively, in other embodiments, the computing unit 801 may be configured to perform a policy model creation method by any other suitable means (e.g., by means of firmware).

[0073] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0074] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0075] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0076] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0077] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0078] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0079] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0080] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means two or more, unless otherwise explicitly specified.

[0081] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A method for creating a strategy model, characterized in that, The method includes: The strategy algorithm is determined based on the target requirements, and a first strategy model is initialized based on the strategy algorithm. The first strategy model includes system nodes and sub-nodes. A first analysis process model template is determined and bound to the first strategy model, wherein the system node and the sub-node correspond to the sub-process template composed of process components and / or activity components in the first analysis process model template; The child node is updated based on the target requirements to generate a second strategy model; In response to the update of the child node, the corresponding sub-process template is updated to obtain the second analysis process model template; Obtain the parameter information of the second strategy model, determine the variable role corresponding to the parameter information, and establish the data flow mapping relationship of the variable role based on the mapping relationship configuration rules; Based on the variable roles and the data flow mapping relationship, the second analysis process model template is updated to the underlying analysis process model; Distributed computing resources are configured for the system nodes and the updated child nodes in the second strategy model based on the first allocation algorithm.

2. The method according to claim 1, characterized in that, Prior to the algorithm for determining the strategy based on target requirements, the method further includes: The strategy algorithm code is determined based on the strategy algorithm interface specification; Obtain the strategy algorithm entry, and encapsulate the strategy algorithm code into the strategy algorithm entry; Determine the strategy algorithm interface parameters corresponding to the strategy algorithm code, bind the strategy algorithm interface parameters to the strategy algorithm entry, and package and publish the strategy algorithm interface parameters and the strategy algorithm code to the strategy algorithm library; The strategy algorithm entries are used to call the corresponding strategy algorithm from the strategy algorithm library according to the target requirements.

3. The method according to claim 1, characterized in that, Updating the child node based on the target requirement includes: The sub-nodes are divided into subsystem nodes and subtask analysis nodes; Perform at least one of the following operations based on the stated target requirements: Add the subsystem node and / or the subtask analysis node; Delete the subsystem node and / or the subtask analysis node; Configure the optimization-related algorithms for the subsystem nodes; Update the parameter information of the active component in the subtask analysis node.

4. The method according to claim 1, characterized in that, Determining the variable role corresponding to the parameter information includes: The variable role type is determined based on the aforementioned strategy algorithm; Based on the algorithm rules of the strategy algorithm and the attributes of the parameter information, the variable role type and the parameter information are matched to obtain the variable role.

5. The method according to claim 3, characterized in that, Before configuring the optimization-related algorithms for the subsystem nodes based on the target requirements, the method further includes: The code for the optimization-related algorithms is determined based on the interface specifications of the optimization-related algorithms; Obtain optimization-related algorithm entries, and encapsulate the optimization-related algorithms into the optimization-related algorithm entries; Determine the optimization-related algorithm interface parameters corresponding to the optimization-related algorithm code, bind the optimization-related algorithm interface parameters to the optimization-related algorithm entries, and package and publish the optimization-related algorithm interface parameters and the optimization-related algorithm code to the optimization-related algorithm library; The optimization-related algorithm entries are used to call the corresponding optimization-related algorithms from the optimization-related algorithm library according to the target requirements.

6. A strategy model creation system, characterized in that, The system includes: The strategy application module is used to store blank strategy models and perform debugging operations based on the blank strategy models. The strategy model design module is used to determine a strategy algorithm based on target requirements, and initialize a first strategy model based on the strategy algorithm, wherein the first strategy model includes system nodes and sub-nodes; determine a first analysis process model template bound to the first strategy model, wherein the system nodes and the sub-nodes correspond to sub-process templates composed of process components and / or activity components in the first analysis process model template; update the sub-nodes based on the target requirements to generate a second strategy model; update the sub-process templates in response to the update of the sub-nodes to obtain the second analysis process model template; obtain parameter information of the second strategy model, determine the variable roles corresponding to the parameter information, and establish a data flow mapping relationship of the variable roles based on mapping relationship configuration rules; and update the second analysis process model template to the underlying analysis process model based on the variable roles and the data flow mapping relationship. The strategy algorithm management module is used to write the strategy algorithm based on the interface specification of the strategy algorithm, and to publish and manage the strategy algorithm. The process model management module is used to store the first analysis process model template, the second analysis process model template, and the underlying analysis process model, and to debug the underlying analysis process model based on the target requirements. An optimization-related algorithm management module is used to write optimization-related algorithms based on the interface specifications of optimization-related algorithms, and to publish and manage the optimization-related algorithms. The computing resource scheduling module is used to configure distributed computing resources for the system nodes and the updated child nodes in the second strategy model based on the first allocation algorithm.

7. A strategy model creation apparatus, characterized in that, The device includes: The strategy algorithm selection unit is used to determine the strategy algorithm based on the target requirements and initialize the first strategy model based on the strategy algorithm. The first strategy model includes system nodes and sub-nodes. An analysis process model configuration unit is used to determine a first analysis process model template bound to the first strategy model, wherein the system node and the sub-node correspond to the sub-process template composed of process components and / or activity components in the first analysis process model template; The analysis process model update unit is used to update the sub-nodes based on the target requirements and generate a second strategy model; in response to the update of the sub-nodes, the sub-process template is updated accordingly to obtain the second analysis process model template. The mapping unit is used to obtain parameter information of the second strategy model, determine the variable role corresponding to the parameter information, and establish the data flow mapping relationship of the variable role based on the mapping relationship configuration rules; The model generation unit is used to update the second analysis process model template to the underlying analysis process model based on the variable roles and the data flow mapping relationship; The resource allocation unit is used to configure distributed computing resources for the system nodes and the updated child nodes in the second strategy model based on the first allocation algorithm.

8. The apparatus according to claim 7, characterized in that, The device further includes: The strategy algorithm configuration unit is used to determine the strategy algorithm code based on the strategy algorithm interface specification; obtain the strategy algorithm entry, encapsulate the strategy algorithm code into the strategy algorithm entry; determine the strategy algorithm interface parameters corresponding to the strategy algorithm code, bind the strategy algorithm interface parameters to the strategy algorithm entry, and package and publish the strategy algorithm interface parameters and the strategy algorithm code to the strategy algorithm library; the strategy algorithm entry is used to call the corresponding strategy algorithm from the strategy algorithm library according to the target requirements; An optimization-related algorithm configuration unit is used to determine the optimization-related algorithm code based on the interface specification of the optimization-related algorithm; obtain optimization-related algorithm entries, encapsulate the optimization-related algorithms into the optimization-related algorithm entries; determine the optimization-related algorithm interface parameters corresponding to the optimization-related algorithm code, bind the optimization-related algorithm interface parameters to the optimization-related algorithm entries, and package and publish the optimization-related algorithm interface parameters and the optimization-related algorithm code to the optimization-related algorithm library; the optimization-related algorithm entries are used to call the corresponding optimization-related algorithm from the optimization-related algorithm library according to the target requirements.

9. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-5.

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