2 RESEARCH FELLOW POSITIONS
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SUPPLY CHAIN OPTIMISATION & AUTOMATED PLANNING AND SCHEDULING
The University of Melbourne is seeking two outstanding Research Fellows to conduct leading edge research in supply chain optimisation and automated planning for mine scheduling.
The positions will be located in the Department of Computing and Information Systems within the Melbourne School of Engineering.
Salary $100,355-$115,715 AUD p.a. (Senior Research Fellow) or $81,925-$97,283 (Research Fellow) plus 9% superannuation; Employment type: Full-time Fixed Term
The successful candidates will conduct leading-edge research and development in the area of optimisation for mine scheduling. The work is part of an ARC funded project, "Making the Pilbara Blend: Agile Mine Scheduling through Contingent Planning". As part of the team you would be involved in discovering more agile contingent planning techniques for solving new classes of scheduling and planning problems. The overarching responsibility of this position will be the development of optimisation techniques for synthesising more robust plans for short term production scheduling of iron ore in distributed, multi-mine pit settings.
The role of the Supply Chain Optimisation Fellow will involve computational approaches to optimising supply chain management, such as constraint solving techniques, combinatorial optimisation and/or network flow techniques, especially those for distributed multi-agent problems.
The role of the Automated Planning and Scheduling Fellow will involve planning languages such as those based on the situation calculus, classical planning techniques and/or model-checking techniques, especially those for distributed multi-agent problems.
This project tackles a challenging problem faced in mine scheduling. An increased need for consistent quality has occurred at the same time as the complexity of modern day mining operations has increased, across multiple mine sites with variable ore grades and increasing infrastructure constraints. There is a pressing need for more agile mining techniques that maximise net present value (NPV) while accommodating the complexities and uncertainties inherent in modern day mining operations.
The goal of this project is to bring together automated planning techniques with constraint programming to address this paradigm shift. The research tackles plan synthesis for the multi-commodity, multi-mine site supply chain problem and promises to lead to improved techniques for collaborative planning and solving hard constraint problems. The theoretical significance of this project derives from the fundamental challenge posed by the problem underlying dynamic scheduling. On the one hand, optimisation must take into account nondeterminism - the uncertain outcomes of actions inherent in the problem - and on the other must lead to feasible plans for each mine site - while continuing to solve the necessary constraints for the overall supply chain schedule during the course of continuing (non-terminating) execution.
The project will develop agile scheduling techniques of great economic importance. Carefully planned scheduling has the potential to reduce the need for new infrastructure, minimising environmental impacts and maximising regeneration after mining. More details can be found at http://www.agentlab.unimelb.edu.au/mining.html
RESEARCH GROUP
Optimisation group of NICTA: http://www.nicta.com.au/research/optimisation
Intelligent Agent Laboratory (Agentlab): http://www.agentlab.unimelb.edu.au/
G12 Constraint Programming Platform: http://www.nicta.com.au/research/projects/constraint_programming_platform
APPLICATION PROCEDURE
http://www.jobs.unimelb.edu.au
Research Fellow in Supply Chain Optimisation: position number 0028933 (closing 3 June 2012)
Research Fellow in Automated Planning and Scheduling: position number 0028932 (closing 3 June 2012)
Contact: For more information, please contact Adrian Pearce, adrianrp@unimelb.edu.au
Adrian
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Adrian Pearce
Department of Computing and Information Systems,
The University of Melbourne, Melbourne VIC 3010
Phone: +61 3 8344 1399 adrianrp@unimelb.edu.au
http://www.csse.unimelb.edu.au/~adrian/
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