|Position||Visiting Associate (Research Fellow)|
|phone||+61 2 4221 2353|
Dr Amirghasemi is a recent PhD graduate from the University of Wollongong in Computing and Information Technology (Operations Research). He has a master’s degree from Chalmers University of Technology, Gothenburg, Sweden in Intelligent Systems Design. He obtained a GPA of 5 (out of 5) for his master studies and received a scholarship award to pursue his PhD studies in University of Wollongong. The central theme of his research is the application of evolutionary computation and simulation in solving permutation problems. Permutations can be employed in the representation of an outsized number of problems in industry and business.
In his PhD thesis, a parallel metaheuristic framework has been proposed to tackle three permutation problems, namely Job-shop Scheduling (JSP), Permutation Flowshop Scheduling (PFSP) and Quadratic Assignment (QAP) problems. This model has been implemented in over 9000 lines of parallel C++ code. The computational results indicated that the proposed parallel strategy is highly effective; reaching high-quality solutions in a very short amount of time. He has received outstanding remarks and commendation from one his PhD examiners and published three journal papers based on his PhD thesis, before being graduated.
Dr Amirghasemi is currently involved in designing a metaheuristic vehicle routing strategy, for a real-life logistics problem, to optimise the delivery of items through DropPoint’s Sydney-based Network.
Research Areas and Expertise
- Evolutionary computation and simulation in solving permutation problems
- PhD (Information Technology (Operations Research)), 2015, University of Wollongong, UOW, Wollongong, Australia
- MSc (Intelligent Systems Design), 2011, Chalmers University of Technology, CTH, Gothenburg, Sweden
- BSc (Industrial Engineering – Industrial Technology), 2008, Isfahan University of Technology, IUT, Isfahan, Iran