Research On Bottleneck Detection And Optimization Technology Based On Stochastic Petri Net

With the rapid development of information technology,informatization and digitization have gradually become mainstream in industrial production.Stochastic Petri nets are networks that can adapt to flexible and changeable production modes and have good mathematical properties that are isomorphic to Markov chains.In order to solve the problem of state space explosion in the process of bottleneck detection and the scheduling optimization problem of flexible manufacturing system,this paper analyzes these two problems based on the stochastic Petri net model.On the one hand,to solve the problem of state space explosion in the bottleneck detection process,the commonly used Kronecker decomposition method has the problem of generating a large amount of invalid state space.Current research often needs to store a large amount of additional information and generate a large number of calculations but lack the analysis of the structural characteristics of the network.This paper mainly uses the P-invariant to optimize the Kronecker decomposition method and proves that the Pinvariant generated by the decomposition of the local network still retains its properties in the global network,then using this conclusion,the upper bound of the local network is obtained.The improved method is applied to the actual model,and the results show that the improved method can effectively reduce the number of invalid states,which enriches the research methods of stochastic Petri net state space optimization.On the other hand,the scheduling optimization problem of stochastic Petri nets currently lack effective and general methods.This paper establishes a corresponding stochastic Petri net model for flexible manufacturing systems and designs a genetic algorithm for this model.Markov chain proves the convergence properties of the algorithm and uses the tabu search algorithm to further optimize the genetic algorithm and obtains a hybrid algorithm of genetic and tabu search.The hybrid algorithm is applied to the intelligent manufacturing system.The algorithm has better performance,which shows the practical feasibility and superiority of the hybrid algorithm and expands the research ideas of the stochastic Petri net scheduling optimization problem.