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GraphMDO Documentation

Welcome to the official documentation for GraphMDO, a dynamic Multidisciplinary Design Optimization (MDO) framework.

GraphMDO bridges data engineering and MDO. It extracts topological data (solvers, variables, fidelity levels) to form an oriented graph, specifically utilizing GEMSEO for semantic formulation and execution. The execution is handled natively by GEMSEO and the Surrogate Modeling Toolbox (SMT), with optimization workflows currently centered on constrained Bayesian optimization (ax-platform) and DOE exploration through GEMSEO. The framework supports single- and multi-objective optimization over graph-derived design variables with explicit inequality constraints.

Key Features

  • Graph-Native Formulation: Define variables, tools, and dependencies as nodes and edges in a property graph.
  • Dynamic Translation: Automatically generate GEMSEO MDO formulations from the database state.
  • Multi-Fidelity Support: Built-in support for Co-Kriging and other multi-fidelity surrogate models.
  • Constrained Bayesian Optimization: Efficient global optimization with Gaussian Processes utilizing Ax Platform, supporting choices, range definitions, and explicit inequality constraints.
  • Microservices Architecture: Decoupled Graph, Execution, and Optimization services for scalability.