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Data-Driven Evolutionary Optimization
Yaochu Jin, Handing Wang, Chaoli Sun, et al.
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Springer International Publishing 
Naturwissenschaften, Medizin, Informatik, Technik / Anwendungs-Software
Beschreibung
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.
![Cover "e;Looks Good to Me"e;](https://cdn.libreka.de/cover/796438d1-f461-4add-878c-3933b75dc776/m ""e;Looks Good to Me"e;")
