CN113378416A - Event network simulation-based optimization method and device and computer equipment - Google Patents
Event network simulation-based optimization method and device and computer equipment Download PDFInfo
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Abstract
The invention discloses an optimization method, a device and computer equipment based on event network simulation, which are applied to an event network system platform, wherein the method comprises the following steps: acquiring initial service data, a preset event and a preset algorithm of a target service scene, wherein the initial service data is a real number, and the preset algorithm comprises the following steps: a continuous calculation algorithm and/or a discrete calculation algorithm; constructing a service model based on an event network according to the initial service data, the preset event and the preset algorithm, wherein the event network is compatible with a discrete mode and a continuous mode; and optimizing the event network-based service model according to a first preset condition or a second preset condition to obtain a service optimization result, wherein the first preset condition is determined according to the content of the service model, and the second preset condition is determined according to the logic structure of the service model. By implementing the invention, different-dimension optimization can be more accurately carried out on continuous and discrete enterprise-level services.
Description
Technical Field
The invention relates to the technical field of computers, in particular to an event network simulation-based optimization method and device and computer equipment.
Background
The service scene may include mechanical, electronic, hydraulic and other technical scenes, and may also include: social, economic, enterprise and other non-technical scenes. When the system of the business scene operates, the simulation model is used as an observer to provide information related to the past, present or even future of the system for the user so that the user can make a correct decision in real time, and the optimization of the business scene refers to the strategy of changing a linear function type structure into a parallel flow network structure through continuously developing, perfecting and optimizing the business flow, optimizing the management resources and the market resource allocation, and improving the efficiency and the flexibility of the enterprise management system from the structural level so as to keep the competitive advantage of the enterprise.
In the related art, optimization is usually performed on various service scenes based on a model constructed by Petri Net (PN), but the PN is a mathematical representation of a discrete parallel system and is suitable for describing an asynchronous and concurrent computer system model. For continuous events such as business process, the optimization process is not accurate enough, so it is urgently needed to provide an event network simulation-based methodOptimizationThe method realizes the optimization of continuous events.
Disclosure of Invention
Therefore, the technical problem to be solved by the present invention is to overcome the defect of inaccurate expression of the optimization process based on PN to continuous events in the prior art, thereby providing an optimization method, device and computer equipment based on event network simulation.
According to a first aspect, the invention discloses an optimization method based on event network simulation, which is applied to an event network system platform and comprises the following steps: acquiring initial service data, a preset event and a preset algorithm of a target service scene, wherein the initial service data is a real number, and the preset algorithm comprises the following steps: a continuous calculation algorithm and/or a discrete calculation algorithm; constructing a service model based on an event network according to the initial service data, the preset event and the preset algorithm, wherein the event network is compatible with a discrete mode and a continuous mode; and optimizing the event network-based service model according to a first preset condition or a second preset condition to obtain a service optimization result, wherein the first preset condition is determined according to the content of the service model, and the second preset condition is determined according to the logic structure of the service model.
Optionally, the event network-based service model is represented by the following formula:
EN ＝（P，E，T，A，F）
wherein EN represents a business model based on an event network; p is a set of libraries, represents each place in a business model, and stores the initial business data and data generated by transition; e is a set of events, including the preset event and the event generated by transition; t is a set of transitions, and the transitions represent the occurrence process of events, including changes of a library owner and directed arcs; a is a set of directed arcs; wherein, a ⊊ ((P £) × T × (P uee)), F is a set of occurrence functions, each preset algorithm includes an occurrence function, and the occurrence function includes a precondition for occurrence of transition, a duration of occurrence, and a post function; the precondition comprises the following steps: time required for transition, prefix library required for transition and data in the library required to be consumed; the post function is used for calculating data after transition and events after transition.
Optionally, the method for constructing the event network-based service model includes: the method comprises the steps of preset algorithm calculation, scripting language compiling, machine learning model and finite element calculation.
Optionally, the first preset condition includes: the number of tokens in the library is greater than or less than a first preset number, the probability distribution of the number of tokens in the library is greater than or less than a first preset threshold, and the probability of occurrence of the target event in the event set.
Optionally, the optimizing the event network-based service model according to a first preset condition or a second preset condition to obtain an optimization result includes: acquiring service demand information; determining a target preset condition according to the service demand information, wherein the target preset condition comprises: a first preset condition and a second preset condition; and optimizing the event network-based service model according to the target preset condition to obtain an optimization result.
Optionally, the target preset condition is: the second preset condition, which is used for optimizing the event network-based service model according to the target preset condition to obtain an optimization result, includes: disassembling the second preset condition according to the logic structure of the event network-based service model to obtain a plurality of second preset sub-conditions; and optimizing the service model based on the event network according to the plurality of second preset sub-conditions to obtain an optimization result.
According to the second aspect, the invention also discloses an event network simulation-based optimization device, which comprises: the system comprises a first obtaining module, a first processing module and a first processing module, wherein the first obtaining module is used for obtaining initial service data, a preset event and a preset algorithm of a target service scene, the initial service data is a real number, and the preset algorithm comprises: a continuous calculation algorithm and/or a discrete calculation algorithm; the construction module is used for constructing a service model based on an event network according to the initial service data, the preset event and the preset algorithm, wherein the event network is compatible with a discrete mode and a continuous mode; and the optimization module is used for optimizing the service model based on the event network according to a first preset condition or a second preset condition to obtain a service optimization result, wherein the first preset condition is determined according to the content of the service model, and the second preset condition is determined according to the logic structure of the service model.
Optionally, the event network-based service model is represented by the following formula:
EN ＝（P，E，T，A，F）
wherein EN represents a business model based on an event network; p is a set of libraries, represents each place in a business model, and stores the initial business data and data generated by transition; e is a set of events, including the preset event and the event generated by transition; t is a set of transitions, and the transitions represent the occurrence process of events, including changes of a library owner and directed arcs; a is a set of directed arcs; wherein, a ⊊ ((P £) × T × (P uee)), F is a set of occurrence functions, each preset algorithm includes an occurrence function, and the occurrence function includes a precondition for occurrence of transition, a duration of occurrence, and a post function; the precondition comprises the following steps: time required for transition, prefix library required for transition and data in the library required to be consumed; the post function is used for calculating data after transition and events after transition.
According to a third aspect, the invention also discloses a computer device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the steps of the optimization method based on event-net simulation as described in the first aspect or any one of the optional embodiments of the first aspect.
According to a fourth aspect, the present invention further discloses a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the optimization method based on event-net simulation as described in the first aspect or any one of the optional embodiments of the first aspect.
The technical scheme of the invention has the following advantages:
the invention provides an event network simulation-based optimization method and device, which are characterized in that initial service data, a preset event and a preset algorithm of a target service scene are obtained, the initial service data is a real number, and the preset algorithm comprises the following steps: and a continuous calculation algorithm and/or a discrete calculation algorithm, wherein a service model based on an event network is constructed according to initial service data, a preset event and a preset algorithm, the event network is compatible with a discrete mode and a continuous mode, the service model based on the event network is optimized according to a first preset condition or a second preset condition, so as to obtain a service optimization result, the first preset condition is determined according to the content of the service model, and the second preset condition is determined according to the logic structure of the service model. According to the invention, the optimization of the optimal solution of the whole business process is carried out on the business model established based on the event network according to different preset conditions based on an analog simulation method instead of being limited to the optimization of a certain field or a certain scene, so that the optimization of continuous and discrete enterprise-level business can be realized more accurately, and the optimization of different dimensions of the business model can be realized according to different requirements.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flowchart of a specific example of an event net simulation-based optimization method according to an embodiment of the present invention;
FIG. 2 is a schematic block diagram of a specific example of an event-net simulation-based optimization device according to an embodiment of the present invention;
FIG. 3 is a diagram of an embodiment of a computer device.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; the two elements may be directly connected or indirectly connected through an intermediate medium, or may be communicated with each other inside the two elements, or may be wirelessly connected or wired connected. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The embodiment of the invention discloses an optimization method based on event network simulation, which comprises the following steps as shown in figure 1:
s11: acquiring initial service data, a preset event and a preset algorithm of a target service scene, wherein the initial service data is a real number, and the preset algorithm comprises the following steps: a continuous calculation algorithm and/or a discrete calculation algorithm.
Illustratively, the target business scenario may be an enterprise business scenario, including: enterprise personnel, enterprise business, enterprise capital circulation, etc., may also be a certain product line: the system composed of raw material factories, processing factories and sales companies involved in raw material-production-sales is not particularly limited by the embodiment of the present invention, and those skilled in the art can determine the target business scenario according to the actual situation. The embodiment of the invention takes a target business scene as an enterprise business scene as an example for explanation.
When the target business scenario is a business scenario of an enterprise, the initial business data may be understood as the most original state of the enterprise, and these states all exist in the form of data (real number), and may include various data involved in the production and management process of the enterprise, including: human data, department data, financial data, product data, sales data, and purchase data, etc.; the preset event may be a business event that causes a change in initial business data, for example, a raw material shortage is found to require procurement when a certain product is produced, a change in selling price of the product with a change in market or a change in a shopping holiday, a lack of manpower due to a flow of people, a low production efficiency due to a shortage of productivity, etc., and may include: the historical events occurring at the enterprise and the events caused based on the historical events occurring at the enterprise may also include: artificially simulated business events. The preset event is not specifically limited in the embodiment of the present invention, and those skilled in the art can determine the preset event according to actual situations.
The preset algorithm refers to an algorithm used when the enterprise system performs the service flow, and may include: the continuous calculation algorithm such as differential calculation and differential calculation may include a discrete calculation algorithm such as count. The preset algorithm is not particularly limited in the embodiment of the present invention, and those skilled in the art can determine the algorithm according to actual situations.
The initial service data, the preset event and the preset algorithm can be uploaded to the processor through the wireless network after being counted by the user.
S12: and constructing a service model based on an event network according to the initial service data, the preset event and a preset algorithm, wherein the event network is compatible with a discrete mode and a continuous mode.
Illustratively, in the embodiment of the present invention, the event network is based on an event-driven implementation distributed concurrency, compatible discrete and continuous hybrid model, which presents a system platform for global simulation, diagnosis and optimization by means of dragging/pulling/dragging data, parameters and algorithms. The event network integrates a large number of processing continuous input algorithms (such as differential calculation, differential calculation and the like), discrete input algorithms (such as counting) and various machine learning algorithms, has stronger expression capability, freeness and clear network and topological layers compared with the current Petri Net (PN) based system, can simultaneously describe events of a physical world and a virtual world, and supports mixed modeling of discrete and continuous.
The specific method for constructing the event network-based service model according to the initial service data, the preset event and the preset algorithm may be as follows: the method comprises the steps of combining a Place, an Event, a Transition and an occurrence function in an Event network system platform in a dragging/pulling/dragging mode and the like, and guiding the flow direction of data among all service nodes through a directed Arc (Arc), so that a real physical world is mapped to a Cyberspace space (Cyberspace) to obtain the service model, wherein the Cyberspace space is an abstract concept in the fields of philosophy and computers and refers to virtual reality in computers and computer networks.
As an optional implementation manner of the embodiment of the present invention, the event network-based service model may be expressed as:
EN ＝（P，E，T，A，F）
wherein EN represents a business model based on an event network; p is a set of libraries representing various places in the service model, such as conference rooms, process plants, etc., where initial service data and data generated by transitions are stored, and the data may be real numbers; e is a set of events, which comprises preset events and events generated by transitions, and can trigger the work of a service system, including the change, transition and the like of data in a library; t is a set of transitions, and the transitions represent the occurrence process of events, including changes of a custody and a directed arc, for example, changes of products in a product sales process warehouse; a is a set of directed arcs; wherein A ⊊ ((P U E) x T U (T x (P U E)), F is a set of occurrence functions, each predetermined algorithm includes one occurrence function,
,
t is the occurrence time, t =0 is allowed, and the occurrence function ends after the t time is completed; the occurrence function comprises a precondition (pre) for the occurrence of the transition, a duration of the occurrence (ringing), and a post function (post); the precondition comprises the following steps: time required for transition, prefix library required for transition and data in the library required to be consumed; the postfunctions include the above mentioned algorithms for computing the data after the transition and the event after the transition and placing the data after the transition in its suffix repository.
S13: and optimizing the service model based on the event network according to a first preset condition or a second preset condition to obtain a service optimization result, wherein the first preset condition is determined according to the content of the service model, and the second preset condition is determined according to the logic structure of the service model.
Illustratively, the first preset result is determined according to the specific content of the business model, and specifically, may include: the number of tokens in the library is greater than or less than a first preset number, the probability distribution of the number of tokens in the library is greater than or less than a first preset threshold, the probability of occurrence of a target event in the event set, and the like. The first preset condition is not specifically limited in the embodiment of the present invention, and a person skilled in the art may set different first preset conditions according to different service requirements and contents of a service model. Taking the target business scenario as an enterprise business scenario as an example, the first preset condition may be that 10 ten thousand target products are produced.
After a first preset condition is set, exhaustive simulation can be adopted, that is, all possible initial conditions are taken into consideration, simulation is respectively carried out, and then the optimal initial condition is obtained; or, calculation may be performed based on a preset algorithm in the event network to obtain an initial condition that satisfies the first preset condition. The simulation method is not particularly limited in the embodiment of the present invention, and those skilled in the art can determine the simulation method according to actual situations.
The second preset condition is determined according to the logic structure of the business model, the second preset condition can be a comprehensive condition, after the second preset condition is determined, the second preset condition is disassembled according to the logic structure (relationship between nodes) of the business model to obtain a plurality of second preset sub-conditions, namely, the comprehensive condition is disassembled into the plurality of sub-conditions, and the business model based on the event network is optimized according to the plurality of second preset sub-conditions to obtain an optimization result.
For the plurality of disassembled second preset sub-conditions, simulation can be performed according to an optimization method of the first preset condition to obtain optimization results of the plurality of second preset sub-conditions, that is, a plurality of optimal initial conditions corresponding to the plurality of second preset sub-conditions, and then the plurality of optimal initial conditions are aggregated and summarized to obtain final optimization results of the second preset conditions. Here, the aggregation refers to a process of simply screening and calculating a plurality of optimal conditions, and the aggregation refers to a process of combining a plurality of optimal initial conditions.
Taking the target business scenario as an enterprise business scenario as an example, the second preset condition may be that the annual income of a company is 1000 ten thousand, and the number of each part should be allocated, for example, the production department: 200 ten thousand, sales department: 700 ten thousand, procurement department: 300 ten thousand, technical sector: 400 ten thousand.
The embodiment of the invention can realize the local or global optimization of the service model through the first preset condition and the second preset condition.
The invention provides an event network simulation-based optimization method, which comprises the following steps of obtaining initial service data, a preset event and a preset algorithm of a target service scene, wherein the initial service data is a real number, and the preset algorithm comprises the following steps: and a continuous calculation algorithm and/or a discrete calculation algorithm, wherein a service model based on an event network is constructed according to initial service data, a preset event and a preset algorithm, the event network is compatible with a discrete mode and a continuous mode, the service model based on the event network is optimized according to a first preset condition or a second preset condition, so as to obtain a service optimization result, the first preset condition is determined according to the content of the service model, and the second preset condition is determined according to the logic structure of the service model. According to the invention, the optimization of the optimal solution of the whole business process is carried out on the business model established based on the event network according to different preset conditions based on an analog simulation method instead of being limited to the optimization of a certain field or a certain scene, so that the optimization of continuous and discrete enterprise-level business can be realized more accurately, and the optimization of different dimensions of the business model can be realized according to different requirements.
As an optional implementation manner of the embodiment of the present invention, a method for constructing a service model based on an event network includes: the method comprises the steps of preset algorithm calculation, scripting language compiling, machine learning model and finite element calculation.
For logic analysis of some special scenes, existing event network system platforms do not have ready-disclosed components or algorithms or need to perform some property adjustment and update on the existing algorithms, and analog simulation needs to be described and performed through a direct programming or scripting language programming method.
As an optional implementation manner of the embodiment of the present invention, the step S13 includes:
first, service requirement information is acquired. The service requirement information can be sent to the processor by the user through a wired network or a wireless network.
Secondly, determining a target preset condition according to the service demand information.
For example, the target preset condition may be a first preset condition or a second preset condition, and may be specifically determined according to the service requirement information. For example, when the service demand information is a demand of a certain department or a certain product, the target condition may be a first preset condition to implement local optimization, and when the service demand information is a demand of a certain company, the target condition may be a second preset condition to implement global optimization.
And thirdly, optimizing the service model based on the event network according to the target preset condition to obtain an optimized result. The specific implementation manner is described in step S13 in the above embodiment, and is not described herein again.
The embodiment of the invention also discloses an optimization device based on event network simulation, as shown in fig. 2, comprising:
the first obtaining module 21 is configured to obtain initial service data, a preset event, and a preset algorithm of a target service scene, where the initial service data is a real number, and the preset algorithm includes: a continuous calculation algorithm and/or a discrete calculation algorithm; the specific implementation manner is described in step S11 in the above embodiment, and is not described herein again.
The construction module 22 is used for constructing a service model based on an event network according to the initial service data, the preset event and the preset algorithm, wherein the event network is compatible with a discrete mode and a continuous mode; the specific implementation manner is described in step S12 in the above embodiment, and is not described herein again.
The optimization module 23 is configured to optimize the service model based on the event network according to a first preset condition or a second preset condition, so as to obtain a service optimization result, where the first preset condition is determined according to the content of the service model, and the second preset condition is determined according to the logic structure of the service model. The specific implementation manner is described in step S13 in the above embodiment, and is not described herein again.
The invention provides an event network simulation-based optimization device, which obtains initial service data, a preset event and a preset algorithm of a target service scene, wherein the initial service data is a real number, and the preset algorithm comprises the following steps: and a continuous calculation algorithm and/or a discrete calculation algorithm, wherein a service model based on an event network is constructed according to initial service data, a preset event and a preset algorithm, the event network is compatible with a discrete mode and a continuous mode, the service model based on the event network is optimized according to a first preset condition or a second preset condition, so as to obtain a service optimization result, the first preset condition is determined according to the content of the service model, and the second preset condition is determined according to the logic structure of the service model. According to the invention, the optimization of the optimal solution of the whole business process is carried out on the business model established based on the event network according to different preset conditions based on an analog simulation method instead of being limited to the optimization of a certain field or a certain scene, so that the optimization of continuous and discrete enterprise-level business can be realized more accurately, and the optimization of different dimensions of the business model can be realized according to different requirements.
As an optional implementation manner of the embodiment of the present invention, the event network-based service model is represented by the following formula:
EN ＝（P，E，T，A，F）
wherein EN represents a business model based on an event network; p is a set of libraries, represents each place in the business model, and stores initial business data and data generated by transition; e is a set of events, including preset events and events generated by transitions; t is a set of transitions, and the transitions represent the occurrence process of events, including changes of a library owner and directed arcs; a is a set of directed arcs; wherein, a ⊊ ((P { [ u ] E) × T { (T × (P { [ u ]))), F is a set of occurrence functions, each preset algorithm includes one occurrence function, and the occurrence function includes a precondition (pre) for occurrence of transition, a duration of occurrence (ringing), and a postamble (post); the precondition comprises the following steps: time required for transition, prefix library required for transition and data in the library required to be consumed; the post function is used to calculate the data after the transition and the event after the transition. For details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
As an optional implementation manner of the embodiment of the present invention, a method for constructing a service model based on an event network includes: the method comprises the steps of preset algorithm calculation, scripting language compiling, machine learning model and finite element calculation. For details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
As an optional implementation manner of the embodiment of the present invention, the first preset condition includes: the number of tokens in the library is greater than or less than a first preset number, the probability distribution of the number of tokens in the library is greater than or less than a first preset threshold, and the probability of occurrence of the target event in the event set. For details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
As an optional implementation manner of the embodiment of the present invention, the optimization module 23 includes:
the second acquisition module is used for acquiring the service requirement information; for details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
The determining module is used for determining a target preset condition according to the service demand information, wherein the target preset condition comprises the following steps: a first preset condition and a second preset condition; for details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
And the first optimization submodule is used for optimizing the service model based on the event network according to the target preset condition to obtain an optimization result. For details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
As an optional implementation manner of the embodiment of the present invention, the target preset condition is: the optimization module 23 includes, under a second preset condition:
the disassembling module is used for disassembling the second preset condition according to the logic structure of the event network-based service model to obtain a plurality of second preset sub-conditions; for details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
First, theIIAnd the optimization submodule is used for optimizing the event network-based service model by a plurality of second preset sub-conditions to obtain an optimization result. For details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
An embodiment of the present invention further provides a computer device, as shown in fig. 3, the computer device may include a processor 31 and a memory 32, where the processor 31 and the memory 32 may be connected by a bus or in another manner, and fig. 3 takes the example of being connected by a bus as an example.
The processor 31 may be a Central Processing Unit (CPU). The Processor 31 may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, or combinations thereof.
The memory 32, which is a non-transitory computer readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the optimization method based on event network simulation in the embodiment of the present invention (for example, the first obtaining module 21, the building module 22, and the optimization module 23 shown in fig. 2). The processor 31 executes various functional applications and data processing of the processor by running non-transitory software programs, instructions and modules stored in the memory 32, namely, implements the optimization method based on event network simulation in the above method embodiment.
The memory 32 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created by the processor 31, and the like. Further, the memory 32 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 32 may optionally include memory located remotely from the processor 31, and these remote memories may be connected to the processor 31 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more modules are stored in the memory 32 and when executed by the processor 31 perform an event-net simulation based optimization method as in the embodiment shown in fig. 1.
The details of the computer device can be understood with reference to the corresponding related descriptions and effects in the embodiment shown in fig. 1, and are not described herein again.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope defined by the appended claims.
Claims (10)
1. An optimization method based on event network simulation is characterized in that the optimization method is applied to an event network system platform and comprises the following steps:
acquiring initial service data, a preset event and a preset algorithm of a target service scene, wherein the initial service data is a real number, and the preset algorithm comprises the following steps: a continuous calculation algorithm and/or a discrete calculation algorithm;
constructing a service model based on an event network according to the initial service data, the preset event and the preset algorithm, wherein the event network is compatible with a discrete mode and a continuous mode;
and optimizing the event network-based service model according to a first preset condition or a second preset condition to obtain a service optimization result, wherein the first preset condition is determined according to the content of the service model, and the second preset condition is determined according to the logic structure of the service model.
2. The method of claim 1, wherein the event net based business model is represented by the following formula:
EN ＝（P，E，T，A，F）
wherein EN represents a business model based on an event network; p is a set of libraries, represents each place in a business model, and stores the initial business data and data generated by transition; e is a set of events, including the preset event and the event generated by transition; t is a set of transitions, and the transitions represent the occurrence process of events, including changes of a library owner and directed arcs; a is a set of directed arcs; wherein, a ⊊ ((P £) × T × (P uee)), F is a set of occurrence functions, each preset algorithm includes an occurrence function, and the occurrence function includes a precondition for occurrence of transition, a duration of occurrence, and a post function; the precondition comprises the following steps: time required for transition, prefix library required for transition and data in the library required to be consumed; the post function is used for calculating data after transition and events after transition.
3. The method according to claim 2, wherein the event network-based business model is constructed in a manner that includes: the method comprises the steps of preset algorithm calculation, scripting language compiling, machine learning model and finite element calculation.
4. The method according to claim 1, wherein the first preset condition comprises: the number of tokens in the library is greater than or less than a first preset number, the probability distribution of the number of tokens in the library is greater than or less than a first preset threshold, and the probability of occurrence of the target event in the event set.
5. The method according to claim 1, wherein the optimizing the event network-based service model according to a first preset condition or a second preset condition to obtain an optimized result comprises:
acquiring service demand information;
determining a target preset condition according to the service demand information, wherein the target preset condition comprises: a first preset condition and a second preset condition;
and optimizing the event network-based service model according to the target preset condition to obtain an optimization result.
6. The method according to claim 5, characterized in that the target preset conditions are: the second preset condition, which is used for optimizing the event network-based service model according to the target preset condition to obtain an optimization result, includes:
disassembling the second preset condition according to the logic structure of the event network-based service model to obtain a plurality of second preset sub-conditions;
and optimizing the service model based on the event network according to the plurality of second preset sub-conditions to obtain an optimization result.
7. An event net simulation-based optimization device, comprising:
the system comprises a first obtaining module, a first processing module and a first processing module, wherein the first obtaining module is used for obtaining initial service data, a preset event and a preset algorithm of a target service scene, the initial service data is a real number, and the preset algorithm comprises: a continuous calculation algorithm and/or a discrete calculation algorithm;
the construction module is used for constructing a service model based on an event network according to the initial service data, the preset event and the preset algorithm, wherein the event network is compatible with a discrete mode and a continuous mode;
and the optimization module is used for optimizing the service model based on the event network according to a first preset condition or a second preset condition to obtain a service optimization result, wherein the first preset condition is determined according to the content of the service model, and the second preset condition is determined according to the logic structure of the service model.
8. The apparatus of claim 7, wherein the event net based business model is represented by the following formula:
EN ＝（P，E，T，A，F）
wherein EN represents a business model based on an event network; p is a set of libraries, represents each place in a business model, and stores the initial business data and data generated by transition; e is a set of events, including the preset event and the event generated by transition; t is a set of transitions, and the transitions represent the occurrence process of events, including changes of a library owner and directed arcs; a is a set of directed arcs; wherein, a ⊊ ((P £) × T × (P uee)), F is a set of occurrence functions, each preset algorithm includes an occurrence function, and the occurrence function includes a precondition for occurrence of transition, a duration of occurrence, and a post function; the precondition comprises the following steps: time required for transition, prefix library required for transition and data in the library required to be consumed; the post function is used for calculating data after transition and events after transition.
9. A computer device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the steps of the method for event-net simulation based optimization of an object according to any of claims 1-6.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method for event-net simulation-based optimization of a simulation according to any of claims 1 to 6.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101276437A (en) * | 2008-05-15 | 2008-10-01 | 王坚 | Enterprise energy consumption process model building and emulation method |
| CN108510106A (en) * | 2018-03-06 | 2018-09-07 | 中国人民解放军国防科技大学 | Airport security check flow optimization method based on queuing theory and generalized random petri net |
| US20190340614A1 (en) * | 2018-05-04 | 2019-11-07 | International Business Machines Corporation | Cognitive methodology for sequence of events patterns in fraud detection using petri-net models |
-
2021
- 2021-08-16 CN CN202110934063.4A patent/CN113378416A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101276437A (en) * | 2008-05-15 | 2008-10-01 | 王坚 | Enterprise energy consumption process model building and emulation method |
| CN108510106A (en) * | 2018-03-06 | 2018-09-07 | 中国人民解放军国防科技大学 | Airport security check flow optimization method based on queuing theory and generalized random petri net |
| US20190340614A1 (en) * | 2018-05-04 | 2019-11-07 | International Business Machines Corporation | Cognitive methodology for sequence of events patterns in fraud detection using petri-net models |
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