Interval Continuous-Time Markov Chains Simulation

In this paper we propose three ICTMC (Interval Continous-Time Markov Chain) algorithms to improve simulation when significant variabilities exist. The ICTMC models takes into account the effects of variabilities in exponential transition rates represented by intervals. A case study is presented doing a comparision between interval steady state probabilities obtained from interval linear systems of equations solution and from ICTMC simulation. ICTMC simulation incorporates variabilities and uncertainties based on imprecise probabilities, where the statistical distribution parameters in the simulation are intervals instead of precise real numbers. Interval arithmetic is used to simulate a set of scenarios simultaneously in each simulation run. This simulation procedure can be applied to support robust decision making.