TOWARD A MODEL-DRIVEN ENGINEERING FRAMEWORK FOR REPRODUCIBLE SIMULATION EXPERIMENT LIFECYCLE MANAGEMENT


Teran-Somohano A., Dayibas O., Yilmaz L., Smith A.

Winter Simulation Conference, Savannakhet, Laos, 7 - 10 Aralık 2014, ss.2726-2737 identifier

  • Basıldığı Şehir: Savannakhet
  • Basıldığı Ülke: Laos
  • Sayfa Sayıları: ss.2726-2737

Özet

Goal-directed reproducible experimentation with simulation models is still a significant challenge. The underutilization of design of experiments, limited transparency in the collection and analysis of results, and ad-hoc adaptation of experiments as learning takes place continue to hamper reproducibility and hence cause a credibility gap. In this study, we propose a strategy that leverages the synergies between model-driven engineering, intelligent agent technology, and variability modeling to support the management of the lifecycle of a simulation experiment. Experiment design and workflow models are introduced for configurable experiment synthesis and execution. Feature-based variability modeling is used to design a family of experiments, which can be leveraged by ontology-driven software agents to configure, execute, and reproduce experiments. Online experiment adaptation is proposed as a strategy to facilitate dynamic experiment model updating as objectives shift from validation to variable screening, understanding, and optimization.