Automated Generalized Petri Net Reduction Using an Evolutionary Approach Applied to a Manufacturing System Model

Petri Net (PN) is a graphical mathematical tool used to create models that provide a formal specification of systems, creating the possibility of running behaviour analysis and properties verification. This kind of model is used to specify several system types and a good example of area in which this formalism is applied is to develop Manufacturing Systems models. In general, using PN to model systems where too much detailing is needed, causes the problem called state space explosion, that consists of a great element profusion in the model. In order to mitigate this problem several kinds of reduction rules were created aiming at simplifying the models, so that they can be easily analysed or simulated, maintaining some properties like: bounded ness, liveness and fairness. The combination of rules together within an automated method motivates the development of the present research. The goal was to define a group of reduction rules and create a genetic algorithm to automatically reduce PN models. The method obtained good results when automatically reducing PN models using six well known reduction techniques.