Multi-objective optimization and decision-making

Multi-objective Optimization (MO) problems are those which involve more than one conflicting objectives to be maximized/minimized. Such problems occur frequently in engineering design, and development of efficient algorithms for MO is a highly active field of research. Many-objective optimization (MaO) problems are further differentiated as the MO problems which contain four or more objectives. 

MaO problems are significantly challenging compared to 2-3 objective problems for a number of reasons: 

1. The foremost is that Pareto-dominance/non-domination principle, which forms the key ranking procedure for evolutionary multi-objective algorithms scales poorly beyond 2-3 objectives. Thus, there is a loss of selection pressure required to drive the solutions towards the Pareto-optimal front (POF). As a result, the convergence to POF is not achieved even after exorbitant computational effort. 
2. The number of solutions required to cover the POF grows exponentially with number of objectives. Thus it becomes increasingly challenging to achieve a good representation of the POF using a finite set of solutions. 
3. There is no definitively established way of visualizing POF of MaO problems, since they contain more than three dimensions. Therefore, selection of final solutions for implementation from the POF is not straightforward. 

This research aims to address some of the open issues in the area through development of effective decomposition based evolutionary algorithms and quantitative metrics for identifying solutions of interest. 

Required Background:

• Good programming (e.g. Matlab/Python) and analytical skills, preferably with a Masters Degree in Engineering / Computer Science
• Prior research experience in optimization is desirable but not necessary
• Demonstrated competence in academic writing and oral presentation skills will be beneficial

You can find more details of the research conducted in our Multidisciplinary Design Optimization (MDO) group at http://www.mdolab.net/. Please feel free to reach out and discuss regarding this project, or have a discussion about other potential topics for undertaking Masters (research) or PhD with us.   

How to Apply

Express your interest in this project by emailing Associate Professor Hemant Kumar Singh at h.singh@unsw.edu.au. Include a copy of your CV and your academic transcript(s).