Development of algorithms for solving multi-concept design optimization problems

Concept design requires identification of potential concepts that are subsequently developed in preliminary design phase. Concept and preliminary design phases are known to have a major impact on the life cycle cost of products and this is extremely important to get it right. The concepts are usually characterized using a number of performance measures, some of which are in conflict. This necessitates the need for multi-objective optimization and trade-off analysis. While multi-objective optimization is a fairly developed area, solution of optimization problems involving different number of variables (concepts defined using different set of variables) is an open problem. This research aims to develop optimization methods that can deal with optimization problems involving solutions that are defined using different set of variables. Development of such methods would enable efficient solution of problems encountered in concept design across several domains. 

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).