IDD-MC is a symbolic analysis tool for bounded Stochastic Petri nets. The restriction regarding the boundedness can be circumvented by a simulative approach. Besides that, the simulation is going to be capable of handling extended Stochastic Petri nets. In this paper we report on the integration of a multi-scaling stochastic simulation engine into IDD-MC. We present some experimental results wh...

Natural systems are, almost by definition, heterogeneous: this can be either a boon or an obstacle to be overcome, depending on the situation. Traditionally, when constructing mathematical models of these systems, heterogeneity has typically been ignored, despite its critical role. However, in recent years, stochastic computational methods have become commonplace in science. They are able to ap...

Because of random nature of many dependent variables in coastal engineering, treatment of effective parameters is generally associated with uncertainty. Numerical models are often used for dynamic analysis of complex structures, including mechanical systems. Furthermore, deterministic models are not sufficient for exact anticipation of structure’s dynamic response, but probabilistic models...

Quantitative stochastic simulation is an important tool in assessing the performance of complex dynamic systems such as modern communication networks. Because of the proliferation of computers and devices that use and rely on networks such as the internet, assessing the performance of these networks is important to ensure future reliability and service. The current methodology for the analysis ...

We provide an overview of two select topics in Monte Carlo simulationbased methods for stochastic optimization: problems with stochastic constraints and variance reduction techniques. While Monte Carlo simulation-based methods have been successfully used for stochastic optimization problems with deterministic constraints, there is a growing body of work on its use for problems with stochastic c...