Recent Advances in Evolutionary Multi-objective Optimization (eBook, PDF)
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This book covers the most recent advances in the field of evolutionary multiobjectiveoptimization. With the aim of drawing the attention of up-andcomingscientists towards exciting prospects at the forefront of computationalintelligence, the authors have made an effort to ensure that the ideas conveyedherein are accessible to the widest audience. The book begins with a summaryof the basic concepts in multi-objective optimization. This is followed by briefdiscussions on various algorithms that have been proposed over the years forsolving such problems, ranging from classical (mathematical) appro...
This book covers the most recent advances in the field of evolutionary multiobjective
optimization. With the aim of drawing the attention of up-andcoming
scientists towards exciting prospects at the forefront of computational
intelligence, the authors have made an effort to ensure that the ideas conveyed
herein are accessible to the widest audience. The book begins with a summary
of the basic concepts in multi-objective optimization. This is followed by brief
discussions on various algorithms that have been proposed over the years for
solving such problems, ranging from classical (mathematical) approaches to
sophisticated evolutionary ones that are capable of seamlessly tackling practical
challenges such as non-convexity, multi-modality, the presence of multiple
constraints, etc. Thereafter, some of the key emerging aspects that are likely
to shape future research directions in the field are presented. These include:<
optimization in dynamic environments, multi-objective bilevel programming,
handling high dimensionality under many objectives, and evolutionary multitasking.
In addition to theory and methodology, this book describes several
real-world applications from various domains, which will expose the readers
to the versatility of evolutionary multi-objective optimization.
optimization. With the aim of drawing the attention of up-andcoming
scientists towards exciting prospects at the forefront of computational
intelligence, the authors have made an effort to ensure that the ideas conveyed
herein are accessible to the widest audience. The book begins with a summary
of the basic concepts in multi-objective optimization. This is followed by brief
discussions on various algorithms that have been proposed over the years for
solving such problems, ranging from classical (mathematical) approaches to
sophisticated evolutionary ones that are capable of seamlessly tackling practical
challenges such as non-convexity, multi-modality, the presence of multiple
constraints, etc. Thereafter, some of the key emerging aspects that are likely
to shape future research directions in the field are presented. These include:<
optimization in dynamic environments, multi-objective bilevel programming,
handling high dimensionality under many objectives, and evolutionary multitasking.
In addition to theory and methodology, this book describes several
real-world applications from various domains, which will expose the readers
to the versatility of evolutionary multi-objective optimization.
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