Probability Arc Petri Nets And Its Application In Path Optimization

In modeling business processes,more and more people use Petri Nets to model business processes.The Petri nets can intuitively and dynamically describe the running process of business processes.By analyzing the model established by Petri nets for business processes,analyzing the nature of business processes and optimizing business processes to improve the performance of business processes.However,in the present Petri Nets,there is no proper model to describe the business process with choice structures and it is impossible to judge which branch is optimal with respect to the entire process.Therefore,we propose a Probability Arc Petri Nets for this problem and combined it with our propose Dynamic Path Optimization Algorithm based on Ant Colony Algorithm in intelligent road traffic system to modeling and analysis.The optimal path can be derived by simulationof a Probability Arc Petri Nets.The research content of this thesis is as follows:(1)Probability Arc Petri nets are proposed based on Logical Petri nets and Probability Petri nets for the problem of path optimization in business processes.The Probability Arc Petri nets add the Probability on the input arc of the place base on Logical Petri Nets and this Probability can decide the token entering which one place.At the same time,the prediction function is added to the place,and the prediction function is based on the attribute set of the place to predict the transition firing time while tokens enter the place.There are two kinds of tokens in the Probability Arc Petri nets,one of which is the simulate token,which is used to simulate the operation of business processes and find the optimal path in the business process.The other is the mainly token.The mainly token enters different places according to the Probability on the input of the place.And the transition firing rule is redefined for the Probability Arc Petri nets.The Probability Arc Petri nets have the flexibility by change the prediction function and the transfer rate expression according to different business processes,so that the Stochatic Arc Petri nets can find the optimal path for the business process.(2)Aiming at the problem of accuracy for dynamic optimal path finding in intelligent road systems,a Dynamic Path Optimization Algorithm based on Ant Colony Algorithm is proposed.First,the traffic flow in the road and the initial vehicle density are obtained through the intelligent road traffic system,and the speed of the vehicle at the time of arrival of the vehicle on the road is predicted according to the Prediction function of Probability Arc Petri nets.The predicted speed is added when calculating the ant colony to move to the next road,so that the improved path optimization algorithm can find the shortest path for the vehicle.Whenever a vehicle enters a new intersection,a Dynamic Path Optimization Algorithm is performed to continuously correct the optimal path to the destination for the vehicle,and to avoid the vehicles entering road congestion due to unexpected events.At the same time,the intelligent road traffic system is modeled by the Probability Arc Petri nets,and the optimal path in the road is found according to the transition firing rule.According to the Reachable Graph of the Probability Arc Petri nets,the intersection passing through the optimal path is found.And analyze the shortcomings of other Petri nets in modeling business processes with choice structures.