PhD Project: Decomposition and Duality: New Approaches to Integer and Stochastic Integer Programming

School of Mathematical and Geospatial Sciences

Posted on: Thu Dec 2013

A stipend for this project will be paid under ARC Discovery Project DP140100985:

Tuition fees will be covered and the successful applicant will receive $28,392p.a.

Applications for this PhD scholarship will be accepted until a suitable applicant has been found.


The successful applicant will join a team of postdocs and researchers at RMIT University and the University of Newcastle working on of this project. This PhD scholarship will be administered at RMIT and the student will work under the supervision of Prof. Andrew Eberhard and Prof. Natashia Boland.

One of Australia's original educational institutions founded in 1887, RMIT is now the nation's largest tertiary institution. The University offers an extensive range of postgraduate, undergraduate and vocational programs. The School of Mathematical & Geospatial Sciences draws together disciplines involving the collection of data with the analysis of data and the understanding and optimisation of systems through modelling and visualisation. The School has about 50 academic staff and over 70 postgraduate research students. RMIT is a founding member of the Australasian Mathematical Sciences Institute and was ranked 4 and the top in Victoria in Applied Mathematics in the last ERA round. Newcastle has been ranked 5 in Applied mathematics in the last two ERA rounds.

Project aims

Because of their rich modelling capabilities, integer programs are widely used in industry for decision making and planning. However their solution algorithms do not have the maturity of their cousins in convex optimization, where the theory of strong duality is ubiquitous. Efficient methods for convex optimization under uncertainty do not apply to the integer case, which is highly nonconvex. Furthermore integer models usually assume the data is known with certainty, which is often not the case in the real world. This project looks towards the development of new theory and algorithms to enhance the analysis of integer models, including those that incorporating uncertainty, while also enabling the use of parallel computing paradigms.

Desired Skill Set

We are looking for a good student with strong mathematical, computational and programming skills. An interest and willingness in learning new theory and methods. A background in optimization theory and a sound grounding in modern programming languages is desirable.


Prof. Andrew Eberhard
+61 3 9925 2616

Prof. Natashia Boland
+61 2 4921 6717

**Mention you saw it on the AustMS website**