Speaker: Kalyanmoy Deb, University Distinguished Professor, Michigan State University, USA, This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract:
Many practical problem-solving tasks require a consideration of multiple conflicting criteria, rather than a single one. Such problems usually give rise to not one, but multiple trade-off Pareto-optimal (PO) solutions. Instead of finding one PO solution at a time, evolutionary multi-criterion optimization (EMO) algorithms can find multiple diverse PO solutions in a single simulation run. In this talk, we shall introduce principles of multi-criterion computational problems and discuss a number of classical and evolutionary optimization algorithms for solving them. Results from a number of practical problems will be show-cased with mention of a number of current research trends on the topic including the use of machine learning and AI methods.

Bio-sketch of the Speaker:
Kalyanmoy Deb is University Distinguished 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, 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 ACM, IEEE, and ASME. He has published over 640 research papers with Google Scholar citation of over 217.000 with h-index 146. He is in the editorial board on 10 major international journals. More information about his research contribution can be found from https://www.coin-lab.org.