Explore
Evolutionary Multi-objective Optimization: An Honorary Issue Dedicated to Professor Kalyanmoy Deb
0 Ungluers have
Faved this Work
Login to Fave
This volume is a reprint of the Honorary Special Issue dedicated to the 60th birthday of Professor Dr. Kalyanmoy Deb, published in the journal Mathematical and Computational Applications (MCA). Kalyanmoy Deb has been a pioneer and highly impactful and influential proponent of Evolutionary Multi-objective Optimization (EMO) since 1994. He is currently a Koenig Endowed Chair Professor and University Distinguished Professor in the Department of Electrical and Computer Engineering at Michigan State University, USA, and holds additional appointments in Mechanical Engineering and in Computer Science and Engineering. Professor Deb’s research interests are in evolutionary optimization and its application in multi-objective optimization, modeling, machine learning, and in multi-objective decision making. He has been a visiting professor at various universities across the world, including IITs in India, Aalto University in Finland, the University of Skovde in Sweden, and Nanyang Technological University in Singapore. He was awarded the IEEE Evolutionary Computation Pioneer Award, the Infosys Prize, the TWAS Prize in Engineering Sciences, the CajAstur Mamdani Prize, the Distinguished Alumni Award from IIT Kharagpur, the Edgeworth Pareto Award, the Bhatnagar Prize in Engineering Sciences, and the Bessel Research Award from Germany. He is a fellow of IEEE, ASME, and three Indian science and engineering academies.
This book is included in DOAB.
Why read this book? Have your say.
You must be logged in to comment.
Rights Information
Are you the author or publisher of this work? If so, you can claim it as yours by registering as an Unglue.it rights holder.Downloads
This work has been downloaded 34 times via unglue.it ebook links.
- 34 - pdf (CC BY) at Unglue.it.
Keywords
- Archiving
- association rule mining
- auto-configuration and auto-design of metaheuristics
- causality measures
- chaos control theory
- Computer science
- Computing & information technology
- constraint handling
- Convergence
- COVID-19 data
- Data mining
- differential evolution
- Economics, finance, business & management
- evolutionary algorithms
- evolutionary multi-objective optimization
- genetic algorithm
- grouping genetic algorithm
- grouping mutation operator
- grouping problem
- hypervolume indicator
- hypervolume scalarization
- importance sampling
- impulse response
- Industry & industrial studies
- Information technology industries
- interactive optimization
- Knowledge Discovery
- large-scale multi-objective optimization
- many objectives
- mass–damper–spring termination
- Media, information & communication industries
- MOO
- multi-criteria decision making
- multi-objective evolutionary algorithm
- multi-objective optimization
- multi-objective reliability-based design optimization
- n/a
- Newton method
- NSGA-II
- objectives reduction
- Particle Filter
- RBDO
- real-world problems optimization
- reconfigurable manufacturing system
- Reliability
- reliability analysis
- rod vibration
- scarce data
- shifting vector approach
- simple cell mapping
- simulation
- surrogate
- transfer learning
- unrelated parallel-machine scheduling
Links
DOI: 10.3390/books978-3-0365-6981-9Editions