11月2日：Hemant Kumar Singh
报告题目: Multi-objective design optimization and decision making: some recent developments and applications
报告人：Hemant Kumar Singh博士，澳大利亚新南威尔士大学
Simultaneous optimization of multiple conflicting criteria is a problem commonly encountered in several disciplines, such as engineering, operations research and finance. The solution to such problems consists of not one but a set of best trade-off designs in the objective space, known as the Pareto Optimal Front (POF). Metaheuristics such as Evolutionary algorithms (EAs) are commonly used to solve these problems owing to a number of advantages, which include parallelizability, global nature of search and ability to deal with highly non-linear/black-box functions. However, EAs are also known to require large numbers of function evaluations to deliver good results, which becomes prohibitive if each design evaluation is done using a computationally expensive experiment (such as Finite Element Analysis, Computational Fluid Dynamics, etc.). This has motivated a number of past and ongoing studies towards developing strategies for reducing the number of design evaluations during the search. This talk discusses some of the recent efforts in overcoming this challenge using spatially distributed surrogates and decomposition based methods. Thereafter, two mechanisms to support informed decision making (i.e. selecting the solutions or regions of interest from the POF) will also be discussed. A brief snapshot of some of the practical applications will also be presented.
Dr Hemant Singh is a Senior Lecturer in the School of Engineering and Information Technology at the University of New South Wales, Australia. He obtained his Bachelors in Technology in Mechanical Engineering from the Indian Institute of Technology Kanpur in 2007, and Doctor of Philosophy from the University of New South Wales in 2011. He worked in General Electric Aviation for two years before the current academic appointment in UNSW.
The main focus of Dr Singh’s research is development of computationally efficient evolutionary computation methods for design optimization with a focus towards engineering problems. Over the years, he has worked on a number of strategies towards addressing the challenges in the domain, including constraint handling, robust optimization, Pareto corner based dimensionality reduction and surrogate assisted evolutionary algorithms.
Dr Singh has published over 60 peer-reviewed papers in the various journals, books and conferences relating to evolutionary computation and design optimization. He is the recipient of the Australia-China Young Scientists Exchange Program fellowship 2017, Australia Bicentennial Fellowship 2016, World Congress on Structural and Multidisciplinary Optimization ECR fellowship 2015 and the Australian Society for Defence Engineering Prize 2011, among others. He was the Publicity and Proceedings Chair of the Australasian Conference on Artificial Life and Computational Intelligence (ACALCI) 2016, and Program Chair of the Asia Pacific Symposium on Intelligent Evolutionary Systems (IES) 2016. He is a professional member of IEEE, ACM and ISSMO, and the Activities Chair of the Canberra chapter of IEEE Computational Intelligence Society.
More information is available from his homepage:www.mdolab.net/Hemant