Stochastic Programming for Business
by Alan Brown
Abstract: The OR community expends considerable effort in developing decision support packages for use at the tactical level. These models are often complex and take account of a large number of constraints. Computer
run times can be significant. Extending these packages to support decisions at the strategic level is not easy. It becomes necessary to make risk adjustments for errors that may occur in many estimates of
The aim of this talk is to introduce a method for building into models a process of risk adjustment which does not incur excessive overheads. The method has both strengths and weaknesses, which will be exposed
using examples from linear, quadratic and integer programming.
Interest in this topic is prompted by the integer programming models for open pit mining being developed at the University of Melbourne for BHP-Billiton. The thoughts on this particular project have led to a
consideration of the wider application of a method of risk adjustment in practice.
For More Information: Mark Fackrell tel. 8344-8053 email: M.Fackrell@ms.unimelb.edu.au