Started in early Nineties, evolutionary computation methods for solving multi-criterion optimization problems were increasingly adopted by researchers and practitioners alike. In this two-hour long tutorial, we shall briefly introduce early methods which started the field and focus more on recent methods which are currently used for research and applications. Related pragmatic topics, such as multi-criterion decision-making, visualization, “innovization” principles, surrogate-assisted methods, will be introduced. Case studies from industrial applications will also presented as a support of the importance and usefulness of this fast-growing field on multi-criterion optimization in practice.
Presenter:
Kalyanmoy Deb is Koenig Endowed Chair Professor at Department of Electrical and Computer Engineering in Michigan State University, USA. Prof. Deb’s research interests are in evolutionary optimization and their application in multi-criterion optimization (EMO), modeling, and machine learning. He was awarded IEEE Evolutionary Computation Pioneer Award for his sustained work in EMO, Infosys Prize, TWAS Prize in Engineering Sciences, CajAstur Mamdani Prize, Distinguished Alumni Award from IIT Kharagpur, Edgeworth-Pareto award, Bhatnagar Prize in Engineering Sciences, and Bessel Research award from Germany. He is fellow of IEEE, ASME, and three Indian science and engineering academies. He has published over 570 research papers with Google Scholar citation of over 160,000 with h-index 124. He is in the editorial board on 18 major international journals. More information about his research contribution can be found from https://www.coin-lab.org.