Contemporary Advancement in Evolutionary Multi-objective Optimization
Description
This endeavour presents a rich collection of contemporary advances in evolutionary multi-objective optimisation algorithms, blending foundational concepts with state-of-the-art research and real-world applications. Featuring contributions from leading experts, it offers clear insights into modern EMO methodologies, emerging AI-EC integrations, and diverse problem-solving domains. An essential reference for researchers, practitioners, and students exploring intelligent optimisation Algorithms.
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Persons
Somnath Mukhopadhyay is currently an Assistant Professor in the Department of Computer Science & Engineering at Assam University, Silchar, India. He is a former Associate Professor at the Department of Computer Applications, Sikkim University, Gangtok, India. He completed his M. Tech. and Ph.D. degrees in Computer Science and Engineering at the University of Kalyani, India, in 2011 and 2015, respectively. His research interests include Digital Image Processing, Soft Computing, Optimization Algorithms, and Hyperspectral Image Processing. He is a Senior member of IEEE, a Fellow of IETE, the General Secretary of the IEEE CIS Kolkata Chapter, a member of IEEE Young Professionals, the IEEE Geoscience and Remote Sensing Society, and a life member of the Computer Society of India.
Paramartha Dutta , born 1966, a B. Stat. (Hons.), M. Stat., M. Tech. (Computer Science), all from Indian Statistical Institute, and a Ph. D (Engineering) from the Bengal Engineering and Science University, Shibpur presently Indian Institute of Engineering Science and Technology is presently a Professor in the Department of Computer and System Sciences, Visva Bharati University, India. He is a recipient of a couple of prestigious national and international awards, he is a Fellow of IE(India), Fellow of IETE, Fellow of IET(UK), Fellow of Royal Society in Arts (UK), Senior Member of IEEE, Senior Member of ACM. Also he has (i) eight authored books (ii) thirty five edited books, (iii) around three hundred research articles published/accepted for publication in various esteemed journals, conference proceedings and book chapters in edited volumes of highly reputed International publishing houses apart from (iv) seventeen patents granted/published.
Sunita Sarkar is an Associate Professor in the Department of Computer Science & Engineering at Assam University, Silchar, India. She holds an M. Tech from Tezpur University and a PhD from Assam University, India. With over twenty years of experience in teaching and research, Dr. Sarkar has edited several books, including "AI to Improve E-Governance and Eminence of Life" with Springer Nature. She has also served as a guest editor for various journals, including "Innovations in Systems and Software Engineering" (Springer) and "SN Computer Science" (Springer).She has published over 50 papers in international journals and conference proceedings, as well as contributed chapters to edited volumes. Her research interests focus on natural language processing, soft computing, and machine learning. She is a Senior Member of IEEE, a member of IEEE Women in Engineering, and a member of the IEEE Computational Intelligence Society.
Kalyanmoy Deb is University Distinguished Professor and 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, modeling, and machine learning. He was awarded IEEE Evolutionary Computation Pioneer Award, 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 650 research papers with Google Scholar citation of over 235,000 with h-index 146. He is in the editorial board on 10 major international journals.
Content
"Balancing exploration-exploitation using Switching Mechanism Integrated with Adaptive Heterogeneous Comprehensive Learning PSO and L-SHADEBalancing exploration-exploitation using Switching Mechanism Integrated with Adaptive Heterogeneous Comprehensive Learning PSO and L-SHADE".- "Evolutionary Multi- and Many-objective Optimization: Enhancements using Machine Learning".- "A Many-Objective Optimized Folded Cross Regression Model (FCRM) with Unspecified Targets: A Critical Analysis".- "Emerging Techniques for Evolutionary Single- and Multi-Objective Optimization with Application to Humanoid Robot Gait Generation".- "Optimization models in Nurse Scheduling - A Review of last five years".- "A Review of Bilevel Optimization Methods, Emerging Applications, and Recent Advancements".- "A Review of Advances in Multi-Objective Optimization for Facility Location Problems".- "A Survey on Recent Advances in Multiobjective Evolutionary Clustering".