Representations of phase type distributions and their applications in stochastic modelling

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Performance analysis and optimal design of stochastic systems whose state space has a large number of states can be challenging problems. This is known as the "curse of dimensionality" problem common to queueing models, inventory models, and supply chains. The main issue at stake is computational efficiency. A number of approaches such as the state space reduction, approximation, and decomposition have been introduced to solve the problems. However, there is no universally effective method. Thus, there is a need to look for new solution methods. Following the state space reduction approach, we propose to study PH-representations of phase-type (PH) distributions and to develop efficient algorithms for computing minimal, simple, or specially structured PH-representations for PH-distributions.