OPEDo: A Tool for Optimization and Performance Evaluation of Stochastic Models

Abstract:
In most cases, model based analysis of discrete event systems is part of a more general process with the ultimate goal to find an optimal configuration for the modeled system. Consequently, there is a need for a seamless integration of analysis techniques and optimization methods into a framework in order to provide adequate support for the design of systems. However, most tools for performance or dependability modeling do not include support for optimization. In addition, most optimization methods require substantial refinements to match the challenging properties of stochastic models, e.g., that a model evaluation may yield statistical estimates instead of precise results, that a model evaluation may be computationally expensive, and that a model evaluation does not provide derivatives of the objective function. Currently optimization of discrete event systems is often done in an ad hoc manner by hand. The goal of OPEDo is twofold: First to customize state-of-the-art optimization methods for the specific needs of discrete event systems and second to combine these optimization methods with state-of-the-art approaches for the specification and analysis of discrete event systems.