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This book covers the most recent advances in the field of
evolutionary multiobjective optimization. With the aim of drawing
the attention of up-and coming 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.
This book covers the most recent advances in the field of
evolutionary multiobjective optimization. With the aim of drawing
the attention of up-and coming 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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