Abstract
This paper defines the concept of fuzzy stochastic Petri net (FSPN) based on Petri net theory and credibility theory and proposes an approach for modelling and analysis of reverse logistics using FSPN in both stochastic and fuzzy environments. The presented methods consist of two stages. The first stage is same as the traditional stochastic Petri net with the difference that the transition firing rates are characterised as fuzzy variable. In the second stage, the fuzzy expected values of the transition firing rates are calculated based on credibility theory and then the FSPN model is degenerated to a conventional stochastic Petri net model. A numerical example for modelling and analysis of a remanufacturing reverse logistics system is given to show the effectiveness of proposed method. The contribution of the proposed approach is that it provide theory basis for modelling time critical, dynamic and complex systems in both stochastic and fuzzy environments using FSPN.
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