Systems Modelling, Operations Research and Decision Support

Field of Research: Computer Simulation Modelling, Optimisation, Decision-Support

Lecturer: Dr Brian van Vuuren

Using computer simulation modelling and/or other software to analyse complex systems taking into consideration the unpredictable, highly dynamic real-world environments in which these systems exist. This is typically in the context of building decision-support systems to aid in better understanding of systems, or finding optimal/near optimal solutions in terms of system configuration and parameter selection.

Field of Research: Systems Modelling, Operations Research, and Decision Support

Lecturer: Prof James Bekker

We study complex, stochastic dynamic systems with computer simulation with the aim of optimising system performance. Such systems include manufacturing plants, food processing plants, mining operations and services in hospitals, medical laboratories and commercial banks. We also analyse systems for Big Data potential and application of Big Data for business intelligence. The research strategy followed is to identify a suitable topic with a well-defined scope via preliminary research. Therefore, no specific topics are currently available.

Field of Research: Systems Modelling, Operations Research, and Decision Support

Lecturer: Prof Jan van Vuuren

The Stellenbosch Unit for Operations Research in Engineering (SUnORE) focuses its research on the design and implementation of mathematical and statistical modelling techniques in support of effective decision-making in industry. In order to achieve this, system responses to changes in their input parameters are considered in the form of sensitivity analyses and scenario planning. This knowledge of the system responses is then used to determine suitable trade-off solutions that may be recommended as desirable courses of action in complex management problems. The modelling techniques typically used derive from the fields of linear, integer, nonlinear and dynamic programming, multi-objective optimisation, utility theory, Markov chains, queuing theory, inventory theory, game theory, graph theory, simulation and forecasting. This modelling approach finds natural application in areas such as the banking and insurance sector, lean manufacturing, efficient retailing and warehousing, responsible natural resource management, the formulation of robust agricultural practices, military decision support and various instances of streamlining within the public sector (e.g. energy planning and urban traffic congestion alleviation).

Research Group Members

James Bekker
Associate Professor

Daniel Lötter

Jan H van Vuuren

Brian van Vuuren