Kay Chen Tan
Title: Evolutionary Multi-objective Optimization in Engineering and Prognostic Applications

    Abstract:  Multi-objective optimization is widely found in many fields, such as logistics, economics, engineering, or whenever optimal decisions need to be made in the presence of trade-offs. The problem is challenging because it involves the simultaneous optimization of several conflicting objectives in the Pareto optimal sense and requires researchers to address many issues that are unique to MO problems. This talk will provide an overview of evolutionary computation for multi-objective optimization (EMO). It will then present various applications of EMO for solving engineering problems particularly in the area of robust prognostic. As one of the key enablers of condition based maintenance, prognostic involves the core task of determining the remaining useful life (RUL) of the system. This talk will discuss the use of neural network ensembles to improve the prediction accuracy of RUL estimation as well as the use of EMO to optimize the ensemble hyper-parameters in order to achieve the trade-off between accuracy and diversity of deep neural networks as ensemble members. A case study involving the estimation of RUL for turbofan engines will also be presented in the talk.  

    Kay Chen Tan (SM’05) (SM’08–F’14) received the B.Eng. (Hons.) degree in electronics and electrical engineering and the Ph.D. degree from University of Glasgow, Glasgow, U.K., in 1994 and 1997, respectively. He is an Associate Professor with the Department of Electrical and Computer Engineering, National University of Singapore, Singapore. His research interests include computational and artificial intelligence, with applications to multiobjective optimization, scheduling, automation, data mining, and games. He has published over 100 journal papers and over 100 papers in conference proceedings, and also co-authored five books. Dr. Tan received the 2012 IEEE Computational Intelligence Society Outstanding Early Career Award for his contributions to evolutionary computation in multiobjective optimization. He was an Editor-in-Chief of IEEE Computational Intelligence Magazine. He also is an Associate Editor/Editorial Board member of over 15 international journals.  

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