Development Of A Simulation Management System

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The main contribution of the proposed research is the development of a Simulation Management System. Simulation models are vital to modern scientific research. These models tend to be extremely complex, often with many sources of uncertainties and numerous factors. To understand the impact of these factors and their interactions, on the simulation model results, requires effective design of experiments. DoE allows construction of well defined procedures for ordering experiment outcomes and offers a framework that can be used to replicate and validate those outcomes. In this study, we propose an approach that integrates concepts of model-driven engineering, intelligent agent technology, and variability modeling to support the management of the lifecycle of a simulation experiment. The Model-Driven Engineering (MDE) methodology provides a framework and strategy to move from the platform-independent experiment domain space to the technical space involving platform-specific executable simulation experiment scripts. Experiment design modeling is introduced for configurable experiment synthesis and execution. Feature-oriented variability modeling is used to design a family of experiments by allowing explicit specification of variability in the configuration of experiments Adaptation is needed for continuous management of stochastic simulation experiments. In simulation lifecycle management systems, adaptation is proposed for dynamic experiment model updating.

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