Supervisors:

Prof. Holger Maier (holger.maier@adelaide.edu.au), Dr. Aaron Zecchin (aaron.zecchin.adelaide.edu.au), A/Prof. Hedwig van Delden (hvdelden@riks.nl)Institution: The University of Adelaide, School of Civil, Environmental and Mining Engineering

Disaster mitigation planning is characterised by the need to make decisions in an increasingly complex environment.  This complexity comes in a number of forms, such as (i) the need to make decisions by selecting from a very large number of options, making it difficult to know which is best, (ii) the need to consider multiple, often competing, objectives during decision-making processes to account for a range of social, economic and environmental criteria.  This makes it difficult to identify the mitigation options that represent the best possible trade-offs between objectives.  In order to address this shortcoming, evolutionary optimisation methods, such as genetic algorithms, can be linked with simulation models in order to sift through the large number of potential options in order to identify alternatives that deserve further consideration.

However, this process generally requires the simulation model(s) to be run many thousands of times, making the process computationally expensive or even infeasible if complex simulation models are used (e.g. spatially distributed land use models).  Consequently, the purpose of this project is to develop approaches that increase the computational efficiency of the combined simulation – optimisation process for disaster mitigation planning using a variety of methods, such as using domain knowledge and/or analytical techniques for selecting the starting populations of evolutionary algorithms, using surrogate- or meta-models to speed up the simulation process and using distributed computing to increase computing power.

The research will be carried out in an international project team with researchers and industry partners. The PhD will be part of the Decision Support System for Assessment of Policy & Planning Investment Options for Optimal Natural Hazard Mitigation project, which will enable the work to be applied to real case studies. Also, a research stay abroad could be part of the PhD project.