Optimisation in the Darkness of Uncertainty: when you don’t know what you don’t know, and what you do know isn’t much!

How do we find the optimal solution for a constrained multiobjective optimisation problem when we have no analytical expression for the objective functions, and very limited function evaluations within the huge search space due to the expense of measuring the objective functions? Calculus can’t help you, and trial and error is not an option! This talk will describe a common practical optimisation problem found in many industrial settings with these challenges, and introduce some methods for expensive black-box optimisation. Finally, we will address the question of how best to evaluate the performance of such methods by generating new test instances with controllable characteristics.

Professor Kate Smith-Miles

Professor Kate Smith-Miles

Professor, School of Mathematics and Statistics, The University of Melbourne

Kate Smith-Miles is a Professor of Applied Mathematics in the School of Mathematics and Statistics at The University of Melbourne, and holds a five-year Laureate Fellowship from the Australian Research Council. She is also President of the Australian Mathematical Society, and a member of the Australian Research Council College of Experts from 2017-2019. Prior to joining The University of Melbourne in September 2017, she was Professor of Applied Mathematics at Monash University, where she was also Head of the School of Mathematical Sciences (2009-2014), and inaugural Director of the Monash Academy for Cross & Interdisciplinary Mathematical Applications (MAXIMA) from 2013-2017. She was also previously Head of the School of Engineering and Information Technology at Deakin University (2006-2009) with a Chair in Engineering. She obtained her first Professorship in Information Technology at Monash University, where she worked from 1996-2006. Professorships in three disciplines (mathematics, engineering, and information technology) have given her an interdisciplinary breadth reflected in much of her research.

Kate obtained a B.Sc(Hons) in Mathematics and a Ph.D. in Electrical Engineering, both from The University of Melbourne. Commencing her academic career in 1996, she has published 2 books on neural networks and data mining, and over 240 refereed journal and international conference papers in the areas of neural networks, optimisation, data mining, and various applied mathematics topics. She has supervised to completion 22 PhD students, and has been awarded over AUD$12 million in competitive grants, including 12 Australian Research Council grants and industry awards.

Kate was elected Fellow of the Institute of Engineers Australia (FIEAust) in 2006, and Fellow of the Australian Mathematical Society (FAustMS) in 2008. Awards include: the Australian Mathematical Society Medal in 2010 for distinguished research; the EO Tuck Medal from ANZIAM in 2017 for outstanding research and distinguished service; and the Monash University Vice-Chancellor’s Award for Excellence in Postgraduate Supervision in 2012.

In addition to her academic activities, she regularly acts as a consultant to industry in the areas of optimisation, data mining, and intelligent systems. She also actively involved in mentoring, particularly with the aim of encouraging greater female participation in mathematics, and she is Chair the Advisory Board for the AMSI Choose Maths program.