The modeling and analysis of complex dynamic
systems, such as those in manufacturing, logistics and biology,
require powerful analysis methods for their study and optimization.
A significant modeling and analysis challenge posed by
both, artificial and natural systems, is the existence of uncertain
parameters. Flexible Nets is a novel modeling formalism, inspired
by Petri nets, that can handle different types of uncertain
parameters in a natural way. This paper develops an efficient
method to analyse the evolution of a system modeled by a Flexible
Net in the long run. More precisely, the method focuses on the
computation of steady state bounds for an objective function of
interest. The method makes use of a set of constraints, expressed
as linear inequalities, that the state variables must satisfy in
the steady state. In order to account for systems that do not
reach a constant steady state, the developed constraints allow
the system state to switch among different values, i.e. the steady
state variables are not forced to be constant.European Commission: FormalBio Contract No: 623995,
Call reference: FP7-PEOPLE-2013-IE
