Overview
Background
Dr Forbes has an extensive background in applying optimisation methods to industrial problems. He spent over 20 years working in industry before returning to academia in 2010. Dr Forbes now focuses on building Mixed Integer Programming models for industrial applications and specialised techniques for solving difficult Mixed Integer Programming models.
Dr Forbes has experience in many application areas including
- vehicle routing;
- supply chain optimisation;
- mine planning;
- public transport vehicle and crew scheduling and rostering (buses, trains and planes);
- hospital staff scheduling and rostering, including operation scheduling and room allocation;
- power generation and planning;
- network design (communications, electricity, gas, water);
- maintenance scheduling.
Availability
- Dr Michael Forbes is:
- Available for supervision
Fields of research
Qualifications
- Doctor of Philosophy, The University of Queensland
Research interests
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Combining Dantzig-Wolfe and Benders Decomposition
Dantzig-Wolfe decomposition is relatively straightforward to apply when all composite variables can be enumerated. However, this is often not the case. Instead we can enumerate variables corresponding to the solution of some smaller subproblem and have a more complex master problem that joins them. This often entails the use of Benders decomposition to solve the master problem. This technique has been successfully applied to a number of vehicle routing problems. My team is investigating how to apply the techique to other areas. Honours and HDR projects are available.
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Multi-objective robust mine planning
Traditional mine planning has focussed on economic objectives (e.g. maximum profit) and assumed the data is deterministic. More realistically, multiple objectives should be considered, including profit, environmental impact and social impact. Additionally, the underlying uncertainty of the data (cost of mining, selling price of ore, ore grade, etc) should be considered so that solutions are robust across many scenarios. This research looks to acheive these outcomes. Honours and HDR projects are available.
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No overlap constraints
No overlap constraints are powerful constraints used by Constraint Programming engines such as Google's OR-Tools. On many scheduling problems they substantially outperform equivalent Mixed Integer Programming (MIP) models. This research will look at the implementation of no overlap constraints to decide if it can be understood as a classical MIP extension (e.g. Logic Based Benders Decomposition) and implemented more directly using a MIP solver. An Honours project is available.
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Optimal tanglegrams
A tanglegram is a pair of trees on the same set of leaves with matching leaves in the two trees joined by an edge. Tanglegrams are widely used in biology to compare evolutionary histories of host and parasite species and to analyze genes of species in the same geographical area. The problem arises as to how to sort the trees so as to minimise various objectives relating to edges crossing or edge length. New formulations and solution techniques may be possible. An Honours project is available.
Research impacts
Dr Forbes' work has had practical impact in many areas.
- His early work on vehicle scheduling for public transport is still widely cited and the basic approach is used in many implementations.
- Algorithms he initially developed are still the mainstay of rail journey planning in many countries, especially the UK.
- He holds a patent for fibre optic network design using integer programming. Versions of the algorithms described in the this patent are used to design fibre optic networks around the world, including for the NBN in Australia.
Works
Search Professor Michael Forbes’s works on UQ eSpace
2017
Journal Article
Puzzle - The Fillomino Puzzle
Pearce, Robin and Forbes, Michael (2017). Puzzle - The Fillomino Puzzle. INFORMS Transactions on Education, 17 (2), 85-89. doi: 10.1287/ited.2016.0166
2017
Conference Publication
Approach to large distribution network optimisation using modern implementation of benders decomposition
D'Addio, Nathan, Abeygunawardana, Anula, Forbes, Michael, Ledwich, Gerard and Shafiei, Mehdi (2017). Approach to large distribution network optimisation using modern implementation of benders decomposition. 24th International Conference and Exhibition on Electricity Distribution, CIRED 2017, Glasgow, Scotland, 12-15 June 2017. IEEE. doi: 10.1049/oap-cired.2017.0727
2017
Conference Publication
Planning dragline positioning sequence with A* search algorithm
Liu, Haoquan, Kearney, Michael and Forbes, Michael (2017). Planning dragline positioning sequence with A* search algorithm. 20th World Congress of the International-Federation-of-Automatic-Control (IFAC), Toulouse, France, 9 - 14 July 2017. Amsterdam, Netherlands: Elsevier Science BV. doi: 10.1016/j.ifacol.2017.08.1924
1999
Journal Article
Production of locomotive rosters for a multi-class single-locomotive problem
Al-Amin, M, Forbes, MA and Noble, DH (1999). Production of locomotive rosters for a multi-class single-locomotive problem. Journal of the Operational Research Society, 50 (10), 1004-1010. doi: 10.1057/palgrave.jors.2600802
1994
Journal Article
Budi - a Software System for Bus Dispatching
Forbes, MA, Holt, JN, Kilby, PJ and Watts, AM (1994). Budi - a Software System for Bus Dispatching. Journal of the Operational Research Society, 45 (5), 497-508. doi: 10.1057/jors.1994.77
1994
Journal Article
Network Optimization Applied to Reclamation Works in Coal-Mining
Forbes, MA, Holt, JN and Watts, AM (1994). Network Optimization Applied to Reclamation Works in Coal-Mining. Journal of the Operational Research Society, 45 (2), 143-150. doi: 10.1057/jors.1994.20
1991
Journal Article
Exact Solution of Locomotive Scheduling Problems
Forbes, MA, Holt, JN and Watts, AM (1991). Exact Solution of Locomotive Scheduling Problems. Journal of the Operational Research Society, 42 (10), 825-831. doi: 10.1057/jors.1991.163
Funding
Current funding
Supervision
Availability
- Dr Michael Forbes is:
- Available for supervision
Looking for a supervisor? Read our advice on how to choose a supervisor.
Supervision history
Current supervision
-
Doctor Philosophy
Applying Operations Research techniques to Pure Mathematics problems
Principal Advisor
Other advisors: Professor Benjamin Burton
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Doctor Philosophy
The method of fragments: beyond vehicle routing
Principal Advisor
Other advisors: Associate Professor Michael Bulmer
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Doctor Philosophy
Novel Approximations for Chance Constrained Blending Problems
Principal Advisor
Other advisors: Associate Professor Michael Bulmer
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Doctor Philosophy
Solving University Course Timetabling Problems in Indonesia
Principal Advisor
Other advisors: Associate Professor Michael Bulmer
-
Doctor Philosophy
Rethinking Benders Decomposition
Principal Advisor
Other advisors: Dr Thomas Taimre
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Doctor Philosophy
Merger of natural and engineered biological sequence space
Associate Advisor
Other advisors: Professor Mikael Boden
Completed supervision
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2025
Doctor Philosophy
New Algorithms for Sub-path Based Formulations of Vehicle Routing Problems
Principal Advisor
Other advisors: Dr Slava Vaisman
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2023
Doctor Philosophy
Acceleration techniques for Combinatorial Benders Decomposition with Applications
Principal Advisor
Other advisors: Associate Professor Michael Bulmer
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2020
Doctor Philosophy
Rich Variants of the Vehicle Routing Problem
Principal Advisor
Other advisors: Associate Professor Michael Bulmer
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2019
Doctor Philosophy
Towards a general formulation of lazy constraints
Principal Advisor
Other advisors: Associate Professor Michael Bulmer
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2024
Doctor Philosophy
A Novel Strategic Planning and Sequencing Optimisation Model for Fully Mobile In-pit Crushing and Conveying (FMIPCC) Systems
Associate Advisor
Other advisors: Associate Professor Mehmet Kizil, Professor Peter Knights, Dr Micah Nehring
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2020
Doctor Philosophy
Photovoltaic Variability and Uncertainty Characterization and Management Strategies
Associate Advisor
-
2018
Doctor Philosophy
Strategic Planning for Dragline Excavation Sequencing
Associate Advisor
Other advisors: Dr Kevin Austin
-
2017
Doctor Philosophy
Efficient Exploration of Large State Space: Applications in Graph Compression
Associate Advisor
Media
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