Hybrid models as transdisciplinary research enablers

Area of Science:

• Operations Research
• Modelling and Simulation
• Computational Sciences

Background:

• Operations Research (OR) frequently employs Modelling and Simulation (M&S) for decision-making.
• Increasing system complexity drives the use of hybrid simulation (HS) and hybrid models (HM).
• HM integrates diverse theories, methods, and tools, extending M&S through multidisciplinary, interdisciplinary, and transdisciplinary approaches.

Purpose of the Study:

• To address the limited evidence of conjoined methods for building hybrid models (HM) within M&S.
• To propose a conceptual framework for developing HM that requires cross-disciplinary research engagement.
• To enable the synthesis of discipline-specific methods and foster transdisciplinary research in M&S.

Main Methods:

• The study proposes a conceptual framework for developing hybrid models (HM).
• This framework facilitates the synthesis of discipline-specific methods and techniques.
• It aims to align M&S research with domain knowledge, hypotheses, and theories from diverse disciplines.

Main Results:

• The proposed framework supports the development of new composable HM methods, tools, and applications.
• It encourages cross-disciplinary research engagement within the M&S community.
• The framework is generally applicable to disciplines with a computational element.

Conclusions:

• Hybrid models (HM) necessitate a cross-disciplinary approach and a robust conceptual framework.
• The proposed framework promotes transdisciplinarity, enabling collaboration across multiple disciplines.
• This approach enhances the development and application of sophisticated M&S techniques for complex systems.