Capability Analytics Research

Complex systems are prevalent in nature and man-made world. Modelling plays an important role in studying the dynamics of complex systems which are often characterised by collective behaviour that cannot be determined from investigating its parts in isolation. Complex systems modelling involves use of cross-disciplinary theories and methods and a variety of approaches have been proposed to this end, such as system dynamics modelling, agent based modelling, graph-based modelling and so on.

Simulation generally refers to the act of reproducing and analysing behaviour of a system using an abstracted representation of the system or in other words a model. Simulations are commonly used to study behaviour of many real-world complex systems including natural as well as man-made or engineered systems. Simulation based learning refers to a training or education approach that uses simulation to teach targeted concepts through interaction with the computer implemented, or other types of simulation, models of real-world systems.

This research project aims at developing an enterprise-wide modelling and optimisation framework to support CBP. There are a number of challenges involved in this project. The first challenge is to identify the key CBP processes and functions common across large scale organizations. The second challenge is to identify the information sources associated with these processes and functions and develop their abstract models at appropriate levels of fidelity including strategic, tactical and operational levels.

Capability development decisions are complex; the implications of such decisions are therefore not well understood and could lead to major consequences including critical capability gaps and waste of valuable resources. The primary aim of this research is to develop computational models underpinning capability decisions using cross-disciplinary approaches including systems thinking, mathematical optimisation and computational intelligence and formalising the relationship between capability decision variables and design choices or capability options.

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