• 9 Rainforest Walk, Room 352

    3800 Clayton Campus

    Australia

Accepting PhD Students

1994 …2021

Research activity per year

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Personal profile

Biography

Prof Andreas Ernst has over 20 years experience in the development of optimisation and simulation models to assist businesses with strategic and operational decision making. He was the director of MAXIMA, the Monash Academy for Cross and Interdisciplinary Mathematical Applications. In addition to his teaching & research role as a professor in the School of Mathematics, he is currently a Senior Research Fellow with the Australia Indonesia Centre,  and a Chief Investigator in OPTiMA, the ARC Training centre in Optimisation Technologies, Integrated Methods & Applications. His research interests focus on scheduling and optimisation for large-scale industrial applications, including high-performance combinatorial optimisation algorithms, parallel matheuristics, and network optimisation. Past projects have included optimisation of coal supply chains, scheduling of recreational vehicles (motorhomes), train scheduling, rostering, and research into hub location algorithms.

Research interests

Andreas Ernst's research is primarily in the area of optimisation and operations research. His interest is in methods for solving large scale integer programs including decomposition methods and matheuristics. These methods are important for dealing with real world applications. Andreas Ernst has a long track record of applying these methods in practice in a variety of areas including the mining industry, transport & logistics and energy. 

If you are looking for benchmark data from some of my papers, please see the following website: https://andreas-ernst.github.io/Mathprog-ORlib/

Supervision interests

Research projects for a PhD or research Masters are developed to suit the interests and background of the candidate, in areas such as:

  • Matheuristics that combine decomposition techniques such as Benders, Lagrangian or Dantzig-Wolfe decomposition with meta-heuristic search.
  • Use of machine learning for discrete optimization and vice versa - using discrete optimisation to train machine learning models.
  • Single track rail scheduling, based on work with the Australia-Indonesia Centre on the Makassar-Parepare railway in South Sulawesi, Indonesia
  • Development of integer programming methods for large-scale discrete optimisation problems arising in network design, hub location, transport & logistics, energy networks and mine planning.

Research area keywords

  • Operations Research
  • Optimization
  • Integer Programming
  • Scheduling

Network

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