Fuzzy discrete event simulation: A new tool for rapid analysis of production systems under vague information

Abstract

Information availability is often a critical point for the application of classical quantitative techniques for production system analysis. In several production problems, indeed, managers have considered the possibility to incorporate “expert” estimates of production data into a model as a substitute for hard data as very interesting. Furthermore, the use of qualitative representations to model physical systems is attractive because it allows to capture the inherent ambiguity characterizing real systems. Fuzzy set theory allows to gain such attractive options, since it provides tools to process vague information.

This paper concerns the new and interesting topic of fuzzy discrete event simulation. In particular, the problem of processing fuzzy data within a discrete event simulation process is discussed and new methods, able to limit time paradox problems, are proposed. Furthermore, the paper addresses the comparison among fuzzy and classical simulation, pointing out peculiarities, potentialities and application fields of such a new tool; finally, the research highlights the necessity to develop proper and specific fuzzy simulation packages by demonstrating that, even under specific and simplifying hypotheses about process uncertainties, fuzzy simulation analysis results cannot be obtained through classical simulation packages.