Evolution of petrinet modeled knowledge intensive processes

Abstract

The domain of Knowledge Intensive Process Improvement (Knowi$π$) will be considered in this paper. For the improvement of knowledge intensive processes (KnowiP) we suggest Genetic Algorithms (GAs). The representation needed by the GA depends on the modelling language of KnowiPs. We will use Petrinets for the process modelling and then use the incidence matrix of the corresponding Petrinet as problem representation. The processes are evaluated according to performance metrics adapted to knowledge intensive processes. Two particular GAs are applied to improve a special class of KnowiPs, one single objective GA and one multi objective GA, namely the Multi-Sexual GA (MSGA) multiple criteria simultaneously.