Evolutionary multi-objective optimization (EMO) has emerged as a sub-discipline of multi-objective optimization, combining the fields of evolutionary computation and classical multiple criteria decision making. This field has applications in artificial intelligence, machine learning, and data mining. This book will present new trends, methods, algorithms, and applications in EMO for system design, featuring contributions from leading experts.

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Nadia Nedjah, Luiza De Macedo Mourelle, Heitor Silverio Lopes

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