Dr Hamish Waterer

Dr Hamish Waterer

Senior Lecturer in Statistics

School of Mathematical and Physical Sciences (Mathematics)

Career Summary

Biography

Research Expertise
Operations Research
Prescriptive Analytics
Mathematical Optimization
Mixed Integer Programming


Qualifications

  • PhD, Georgia Institute of Technology

Keywords

  • Mathematical Optimization
  • Mathematics
  • Mixed Integer Programming
  • Operations Research
  • Prescriptive Analytics

Fields of Research

Code Description Percentage
010206 Operations Research 25
010303 Optimisation 50
010399 Numerical and Computational Mathematics not elsewhere classified 25

Professional Experience

UON Appointment

Title Organisation / Department
Senior Lecturer in Statistics University of Newcastle
School of Mathematical and Physical Sciences
Australia
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Publications

For publications that are currently unpublished or in-press, details are shown in italics.


Journal article (17 outputs)

Year Citation Altmetrics Link
2019 Kalinowski T, Matthews J, Waterer H, 'Scheduling of maintenance windows in a mining supply chain rail network', Computers and Operations Research, (2019)

© 2019 Rail infrastructure forms a critical part of the mining supply chain in Australia due to the high weight to volume ratio of the product and the long distances between the m... [more]

© 2019 Rail infrastructure forms a critical part of the mining supply chain in Australia due to the high weight to volume ratio of the product and the long distances between the mines and the ports. Across Australia, rail infrastructure has been steadily expanding to account for the growth in export volumes and the movement of mining operations further inland, and so the efficient and effective management of this critical infrastructure is vitally important. Maintenance plays a crucial role in this management as it ensures that the infrastructure assets are in a condition that allows safe, reliable, and efficient transport. In this paper we consider the annual planning of maintenance for Australia's largest coal rail network, the Central Queensland Coal Network (CQCN), that is owned, operated, and managed, by Aurizon Holdings Pty Ltd. The current planning approach at Aurizon uses the concept of a maintenance access window (MAW) which provides a train-free time window across geographically contiguous track locations that define a maintenance zone. These train-free time windows facilitate the scheduling of specific maintenance tasks at specific track locations within zones closer to day of operation and forms the basis for a planning framework. A MIP model is introduced which facilitates the planning of different maintenance resources across this network to schedule MAWs. The model takes into account maintenance requirement forecasts as well as the availability of resources. Candidate solutions are compared using a proxy for network throughput capacity. Due to the long computation times required to solve the MIP model at the annual planning horizon a matheuristic is developed and two variants are tested. On average 80% less computational time is required to find a good solution (average gap of 5%) using the matheuristic compared to solving the MIP model directly (average gap of 1.5%). The MIP model and associated matheuristic provides a suitable framework for semi-automated maintenance planning and is being integrated into the current suite of decision support tools used by Aurizon.

DOI 10.1016/j.cor.2019.03.016
Co-authors Thomas Kalinowski, Jason Matthews
2018 Lidén T, Kalinowski T, Waterer H, 'Resource considerations for integrated planning of railway traffic and maintenance windows', Journal of Rail Transport Planning and Management, 8 1-15 (2018) [C1]
DOI 10.1016/j.jrtpm.2018.02.001
Citations Scopus - 5Web of Science - 3
Co-authors Thomas Kalinowski
2016 Boland N, Clement R, Waterer H, 'A bucket indexed formulation for nonpreemptive single machine scheduling problems', INFORMS Journal on Computing, 28 14-30 (2016) [C1]

© 2016 INFORMS. Anew mixed-integer linear programming (MILP) formulation for nonpreemptive single machine scheduling problems is presented. The model is a generalisation of the cl... [more]

© 2016 INFORMS. Anew mixed-integer linear programming (MILP) formulation for nonpreemptive single machine scheduling problems is presented. The model is a generalisation of the classical time indexed (TI) model to one in which at most two jobs can be processing in each time period. Like the TI model, the new model, called the bucket indexed (BI) model, partitions the planning horizon into periods of equal length, or buckets. Unlike the TI model, the length of a period is a parameter of the BI model and can be chosen to be as long as the processing time of the shortest job. The two models are equivalent if a period is of unit length, but when longer periods are used in the BI model, it can have significantly fewer variables and nonzeros than the corresponding TI model. A computational study using weighted tardiness instances, and weighted completion time instances with release dates, reveals that the BI model significantly outperforms the TI model on instances where the minimum processing time of the jobs is large. Furthermore, the performance of the BI model is less vulnerable to increases in average processing time when the ratio of the largest processing time to the smallest is held constant.

DOI 10.1287/ijoc.2015.0661
Citations Scopus - 6Web of Science - 4
2015 Boland N, Savelsbergh M, Waterer H, 'A decision support tool for generating shipping data for the Hunter Valley coal chain', Computers and Operations Research, 53 54-67 (2015) [C1]

Strategic capacity planning is a core activity for the Hunter Valley Coal Chain Coordinator as demand for coal is expected to double in the next decade. Optimization and simulatio... [more]

Strategic capacity planning is a core activity for the Hunter Valley Coal Chain Coordinator as demand for coal is expected to double in the next decade. Optimization and simulation models are used to suggest and evaluate infrastructure expansions and operating policy changes. These models require input data in the form of shipping stems, which are arrival streams of ships at the port, together with their cargo types and composition. Creating shipping stems that accurately represent future demand scenarios has been a time-consuming and daunting challenge. We describe an optimization-based decision support tool that facilitates and enhances this process, and which has become an integral part of the company's work flow. The tool embeds sampling to enable the generation of multiple shipping stems for a single demand scenario, employs targets, and desirable and permissable ranges to specify and control the characteristics of the shipping stems, and uses integer programming in a hierarchical fashion to generate shipping stems that best meet the set goals. © 2014 Elsevier Ltd.

DOI 10.1016/j.cor.2014.07.016
Citations Scopus - 2Web of Science - 3
2015 Phillips AE, Waterer H, Ehrgott M, Ryan DM, 'Integer programming methods for large-scale practical classroom assignment problems', Computers and Operations Research, 53 42-53 (2015) [C1]

In this paper we present an integer programming method for solving the Classroom Assignment Problem in University Course Timetabling. We introduce a novel formulation of the probl... [more]

In this paper we present an integer programming method for solving the Classroom Assignment Problem in University Course Timetabling. We introduce a novel formulation of the problem which generalises existing models and maintains tractability even for large instances. The model is validated through computational results based on our experiences at the University of Auckland, and on instances from the 2007 International Timetabling Competition. We also expand upon existing results into the computational difficulty of room assignment problems. © 2014 Elsevier Ltd.

DOI 10.1016/j.cor.2014.07.012
Citations Scopus - 18Web of Science - 17
2015 Savelsbergh M, Waterer H, Dall M, Moffiet C, 'Possession assessment and capacity evaluation of the Central Queensland Coal Network', EURO Journal on Transportation and Logistics, 4 139-173 (2015) [C1]
DOI 10.1007/s13676-014-0066-0
Citations Scopus - 5Web of Science - 4
2014 Boland N, Kalinowski T, Waterer H, Zheng L, 'Scheduling arc maintenance jobs in a network to maximize total flow over time', DISCRETE APPLIED MATHEMATICS, 163 34-52 (2014) [C1]
DOI 10.1016/j.dam.2012.05.027
Citations Scopus - 11Web of Science - 12
Co-authors Thomas Kalinowski
2014 Foster JD, Berry AM, Boland N, Waterer H, 'Comparison of mixed-integer programming and genetic algorithm methods for distributed generation planning', IEEE Transactions on Power Systems, 29 833-843 (2014) [C1]
DOI 10.1109/TPWRS.2013.2287880
Citations Scopus - 33Web of Science - 26
2013 Akartunali K, Boland N, Evans I, Wallace M, Waterer H, 'Airline planning benchmark problems-Part I: Characterising networks and demand using limited data', COMPUTERS & OPERATIONS RESEARCH, 40 775-792 (2013) [C1]
DOI 10.1016/j.cor.2012.02.012
Citations Scopus - 3Web of Science - 1
2013 Akartunali K, Boland N, Evans I, Wallace M, Waterer H, 'Airline planning benchmark problems-Part II: Passenger groups, utility and demand allocation', COMPUTERS & OPERATIONS RESEARCH, 40 793-804 (2013) [C1]
DOI 10.1016/j.cor.2012.03.005
Citations Scopus - 5Web of Science - 3
2013 Boland N, Kalinowski T, Waterer H, Zheng L, 'Mixed integer programming based maintenance scheduling for the Hunter Valley coal chain', JOURNAL OF SCHEDULING, 16 649-659 (2013) [C1]
DOI 10.1007/s10951-012-0284-y
Citations Scopus - 17Web of Science - 14
Co-authors Thomas Kalinowski
2012 Smith OJ, Boland NL, Waterer HA, 'Solving shortest path problems with a weight constraint and replenishment arcs', Computers & Operations Research, 39 964-984 (2012) [C1]
DOI 10.1016/j.cor.2011.07.017
Citations Scopus - 43Web of Science - 28
2011 Archer R, Nates G, Donovan S, Waterer HA, 'Wind turbine interference in a wind farm layout optimization mixed integer linear programming model', Wind Engineering, 35 165-175 (2011) [C1]
Citations Scopus - 27Web of Science - 15
2009 Zink F, Waterer H, Archer R, Schaefer L, 'Geometric optimization of a thermoacoustic regenerator', INTERNATIONAL JOURNAL OF THERMAL SCIENCES, 48 2309-2322 (2009) [C1]
DOI 10.1016/j.ijthermalsci.2009.05.007
Citations Scopus - 30Web of Science - 27
2007 Waterer H, 'Lot sizing with inventory gains', OPERATIONS RESEARCH LETTERS, 35 759-766 (2007) [C1]
DOI 10.1016/j.orl.2007.01.005
Citations Scopus - 2Web of Science - 2
2002 Waterer H, Johnson EL, Nobili P, Savelsbergh MWP, 'The relation of time indexed formulations of single machine scheduling problems to the node packing problem', MATHEMATICAL PROGRAMMING, 93 477-494 (2002)
DOI 10.1007/s10107-002-0335-9
Citations Scopus - 14Web of Science - 13
2000 Philpott AB, Craddock M, Waterer H, 'Hydro-electric unit commitment subject to uncertain demand', EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 125 410-424 (2000)
DOI 10.1016/S0377-2217(99)00172-1
Citations Scopus - 47Web of Science - 34
Show 14 more journal articles

Conference (6 outputs)

Year Citation Altmetrics Link
2017 Charkhgard P, Kalinowski T, Waterer HAR, 'The network maintenance problem', MODSIM2017, 22nd International Congress on Modelling and Simulation, Hobart, Tas (2017) [E1]
Co-authors Thomas Kalinowski
2017 Eskandarzadeh S, Kalinowski T, Waterer HAR, 'Maintenance scheduling in a railway corridor', MODSIM2017 22nd International Congress on Modelling and Simulation, Hobart, TAS (2017) [E1]
Co-authors Thomas Kalinowski
2013 Clement R, Boland NL, Waterer H, 'A Variable Sized Bucket Indexed Formulation for Nonpreemptive Single Machine Scheduling Problems', MODSIM2013, Proceedings of the 20th International Congress on Modelling and Simulation, Adelaide, SA (2013) [E1]
Citations Web of Science - 1
2012 Boland NL, Evans I, Mears C, Niven T, Pattison M, Wallace M, Waterer HA, 'Rail disruption: Passenger focused recovery', Computers in Railways XIII, New Forest, UK (2012) [E1]
2011 Boland NL, Engineer F, Reisi Ardali M, Savelsbergh M, Waterer HA, 'Data generation in the Hunter Valley Coal Chain: A case study in capacity assessment', Proceedings of the 35th Application of Computers and Operations Research in the Minerals Industry Symposium, Wollongong, NSW (2011) [E1]
Citations Scopus - 1
2011 Boland NL, Kalinowski T, Waterer H, Zheng L, 'An optimisation approach to maintenance scheduling for capacity alignment in the Hunter Valley coal chain', Proceedings of the 35th Application of Computers and Operations Research in the Minerals Industry Symposium, Wollongong, NSW (2011) [E1]
Citations Scopus - 3
Co-authors Thomas Kalinowski
Show 3 more conferences

Report (1 outputs)

Year Citation Altmetrics Link
2013 Boland NL, Waterer H, Clement R, 'A big bucket time indexed formulation for non-preemptive single machine scheduling problems', Centre for Optimal Planning and Operations Report Series, 1 (2013) [R1]
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Grants and Funding

Summary

Number of grants 5
Total funding $424,720

Click on a grant title below to expand the full details for that specific grant.


20163 grants / $136,720

Pacific National Haulage Project$62,520

Funding body: Pacific National

Funding body Pacific National
Project Team Doctor Hamish Waterer, Professor Richard Bush, Doctor Thomas Kalinowski
Scheme Research Grant
Role Lead
Funding Start 2016
Funding Finish 2016
GNo G1601141
Type Of Funding C3111 - Aust For profit
Category 3111
UON Y

Entrepreneurs Programme: Automated planning of the Koppers Inventory Routing Problem$37,100

Funding body: Department of Industry, Innovation and Science

Funding body Department of Industry, Innovation and Science
Project Team Doctor Hamish Waterer, Doctor Thomas Kalinowski
Scheme Entrepreneurs' Programme: Innovation Connections
Role Lead
Funding Start 2016
Funding Finish 2016
GNo G1601320
Type Of Funding C2110 - Aust Commonwealth - Own Purpose
Category 2110
UON Y

Entrepreneurs Programme: Automated planning of the Koppers Inventory Routing Problem$37,100

Funding body: Koppers Australia Pty Ltd

Funding body Koppers Australia Pty Ltd
Project Team Doctor Hamish Waterer, Doctor Thomas Kalinowski
Scheme Entrepreneurs' Programme: Innovation Connections
Role Lead
Funding Start 2016
Funding Finish 2016
GNo G1700295
Type Of Funding C3111 - Aust For profit
Category 3111
UON Y

20151 grants / $12,000

Automated Planning of Maritime Inventory Routing for Koppers$12,000

Funding body: Koppers Australia Pty Ltd

Funding body Koppers Australia Pty Ltd
Project Team Doctor Hamish Waterer, Dr Andreas Ernst
Scheme Research Consultancy
Role Lead
Funding Start 2015
Funding Finish 2015
GNo G1500550
Type Of Funding Grant - Aust Non Government
Category 3AFG
UON Y

20131 grants / $276,000

Possession Assessment and Capacity Evaluator Extensions$276,000

Funding body: Aurizon Network Pty Ltd

Funding body Aurizon Network Pty Ltd
Project Team Professor Martin Savelsbergh, Doctor Hamish Waterer
Scheme Research Project
Role Investigator
Funding Start 2013
Funding Finish 2014
GNo G1300619
Type Of Funding Grant - Aust Non Government
Category 3AFG
UON Y
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Research Supervision

Number of supervisions

Completed2
Current2

Current Supervision

Commenced Level of Study Research Title Program Supervisor Type
2015 PhD Hierarchical Location-Routing Problems PhD (Mathematics), Faculty of Science, The University of Newcastle Co-Supervisor
2015 PhD The Network Maintenance Problem PhD (Mathematics), Faculty of Science, The University of Newcastle Principal Supervisor

Past Supervision

Year Level of Study Research Title Program Supervisor Type
2015 PhD Mixed Integer Linear Programming Models for Machine Scheduling PhD (Mathematics), Faculty of Science, The University of Newcastle Co-Supervisor
2014 PhD Mixed-Integer Quadratically-Constrained Programming, Piecewise-Linear Approximation and Error Analysis with Applications in Power Flow PhD (Mathematics), Faculty of Science, The University of Newcastle Co-Supervisor
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Dr Hamish Waterer

Position

Senior Lecturer in Statistics
Centre for Optimal Planning and Operations (C-OPT)
School of Mathematical and Physical Sciences
Faculty of Science

Focus area

Mathematics

Contact Details

Email hamish.waterer@newcastle.edu.au
Phone (02) 4921 5951

Office

Room SR221
Building Social Sciences Building
Location Callaghan
University Drive
Callaghan, NSW 2308
Australia
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