In this IEEE Distinguished Lecture, Professor Kalyanmoy Deb, from Michigan State University, presents a generic framework of a population-based optimisation algorithm and explains the advantages.
Optimisation problems are omnipresent in practice and researchers and practitioners have always been interested in developing computationally fast and reliable algorithms.Traditionally, optimisation algorithms were developed based on the improvement of a single solution through the search space. However, in the past three decades, population-based optimisation algorithms have dominated the field due to a number of niches that they provide.
In this IEEE DLP talk, Professor Deb will present a generic framework of a population-based optimisation algorithm and explain their advantages in handling various practicalities over their point-based counterparts. As a case study, he shall present a recent study in which a real-world resource allocation problem involving a staggering billion variables has been solved.
About the speaker
Kalyanmoy Deb is Koenig Endowed Chair Professor at the Department of Electrical and Computer Engineering in Michigan State University, USA. His research interests are in evolutionary optimisation and their application in optimisation, modelling, and machine learning.
He has been awarded the 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 a fellow of IEEE, ASME, and three Indian science and engineering academies. More information about Professor Deb and his research.
Registration and bookings
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