Research in Multidisciplinary Design Optimization

Problem Statement

The utilization of Multidisciplinary Design Optimization (MDO) is an increasingly popular field of R&D in several industries such as oil, aerospace, energy, automotive, etc. ARL MLS has been at the forefront of applying novel MDO methodologies in several such applications and continues to expand its domain based on complimentary technological practices such as computational mechanics, engineering design, biomedical product development, concurrent engineering, virtual product development and many more. Dealing with large systems problems, we provide sustainable optimization solutions while considering uncertainties and tailored developing Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods. Some of our interests include:

  • Accurate Coupled System modelling and execution.
  • Cost efficient computational framework for large systems.
  • Lack of application specific methodologies and guidelines.
  • Advanced decision-making processes for smart automation.
  • Visualization of multidimensional systems and their interaction.
  • Uncertainty handling for reliable design solutions.


To overcome the many global challenges in the field of MDO, ARL – MLS has been actively developing cutting edge solutions such as:

  • Realtime validated system models for precise analysis and optimization.
  • Tested algorithms and advanced surrogate models for efficient computation.
  • Avionics targeted design methodologies with high fidelity constraints for improved performance.
  • Multi Criteria Decision Making (MCDM) infused Machine Learning (ML) and Artificial Intelligence (AI) induced models for higher order decision making.
  • State of the art architectures and frameworks for system mapping and formulation.
  • Advanced Reliability/ Possibility Based Design Optimization (RBDO / PBDO) methods to compute uncertainties for reliable system design.
  • Applying multiple optimization regimes such as topology, topography, DFX and DOE methods to enrich subsystem and component design.