Dr Michelle Blom
- AI Algorithms
- Algorithms for Electoral Analysis
- Optimisation for Supply Chains
Dr Michelle Blom is a Research Fellow in the Department of Computing and Information Systems at The University of Melbourne. Michelle completed her PhD in the Department of Computer Science and Software Engineering at the University of Melbourne in 2011. Her thesis explored the use of argumentation-based approaches for automated decision-making and planning. Michelle is a currently a research fellow at the University of Melbourne, working on an ARC Linkage Project with Rio Tinto Iron Ore. Her research involves developing new algorithms and heuristics for scheduling operations in large open-pit mining supply chains.
- Blom M, Pearce A, Stuckey P. A Decomposition-Based Algorithm for the Scheduling of Open-Pit Networks Over Multiple Time Periods. MANAGEMENT SCIENCE. INFORMS Applied Probability Society. 2016, Vol. 62, Issue 10.
- Blom M, Teague V, Stuckey P, Tidhar R. Efficient Computation of Exact IRV Margins. 22nd European Conference on Artificial Intelligence (ECAI). IOS Press. 2016, Vol. 285. Editors: Kaminka GA, Fox M, Bouquet P, Hullermeier E, Dignum V, Dignum F, Vanharmelen F.
- Blom M, Pearce A, Stuckey P. Short-term scheduling of an open-pit mine with multiple objectives. Engineering Optimization. 2016.
- Blom M, Burt C, Pearce A, Stuckey P. A Decomposition-Based Heuristic for Collaborative Scheduling in a Network of Open-Pit Mines. INFORMS Journal on Computing. INFORMS Applied Probability Society. 2014, Vol. 26, Issue 4.
- Blom M, Pearce A. Relaxing regression for a heuristic GOLOG. Proceedings of the 2010 conference on STAIRS 2010: Proceedings of the 5th Starting AI Researchers' Symposium. IOS Press. 2010.
- Blom M, Pearce A. An Argumentation-Based Interpreter for Golog Programs. 21st International Joint Conference on Artificial Intelligence (IJCAI-09). IJCAI Incorporated. 2009.