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Intended for researchers and practitioners alike, this book covers
carefully selected yet broad topics in optimization, machine
learning, and metaheuristics. Written by world-leading academic
researchers who are extremely experienced in industrial
applications, this self-contained book is the first of its kind
that provides comprehensive background knowledge, particularly
practical guidelines, and state-of-the-art techniques. New
algorithms are carefully explained, further elaborated with
pseudocode or flowcharts, and full working source code is made
freely available. This is followed by a presentation of a variety
of data-driven single- and multi-objective optimization algorithms
that seamlessly integrate modern machine learning such as deep
learning and transfer learning with evolutionary and swarm
optimization algorithms. Applications of data-driven optimization
ranging from aerodynamic design, optimization of industrial
processes, to deep neural architecture search are included.
Intended for researchers and practitioners alike, this book covers
carefully selected yet broad topics in optimization, machine
learning, and metaheuristics. Written by world-leading academic
researchers who are extremely experienced in industrial
applications, this self-contained book is the first of its kind
that provides comprehensive background knowledge, particularly
practical guidelines, and state-of-the-art techniques. New
algorithms are carefully explained, further elaborated with
pseudocode or flowcharts, and full working source code is made
freely available. This is followed by a presentation of a variety
of data-driven single- and multi-objective optimization algorithms
that seamlessly integrate modern machine learning such as deep
learning and transfer learning with evolutionary and swarm
optimization algorithms. Applications of data-driven optimization
ranging from aerodynamic design, optimization of industrial
processes, to deep neural architecture search are included.
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Evolutionary Multi-Criterion Optimization - 11th International Conference, EMO 2021, Shenzhen, China, March 28-31, 2021, Proceedings (Paperback, 1st ed. 2021)
Hisao Ishibuchi, Qingfu Zhang, Ran Cheng, Ke Li, Hui Li, …
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R2,789
Discovery Miles 27 890
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Ships in 18 - 22 working days
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This book constitutes the refereed proceedings of the 11th
International Conference on Evolutionary Multi-Criterion
Optimization, EMO 2021 held in Shenzhen, China, in March 2021.The
47 full papers and 14 short papers were carefully reviewed and
selected from 120 submissions. The papers are divided into the
following topical sections: theory; algorithms; dynamic
multi-objective optimization; constrained multi-objective
optimization; multi-modal optimization; many-objective
optimization; performance evaluations and empirical studies; EMO
and machine learning; surrogate modeling and expensive
optimization; MCDM and interactive EMO; and applications.
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