Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization

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Tác giả: Javier Del Ser, Eneko Osaba

Ngôn ngữ: eng

ISBN-13: 978-1789233285

ISBN-13: 978-1789233292

ISBN-13: 978-1838815721

ISBN: intechopen.71401

Ký hiệu phân loại: 570.151 Life sciences Biology

Thông tin xuất bản: London, UK : IntechOpen, 2018

Mô tả vật lý: 1 electronic resource (70 p.)

Bộ sưu tập: Tài liệu truy cập mở

ID: 224508

Nature-inspired algorithms have a great popularity in the current scientific community, being the focused scope of many research contributions in the literature year by year. The rationale behind the acquired momentum by this broad family of methods lies on their outstanding performance evinced in hundreds of research fields and problem instances. This book gravitates on the development of nature-inspired methods and their application to stochastic, dynamic and robust optimization. Topics covered by this book include the design and development of evolutionary algorithms, bio-inspired metaheuristics, or memetic methods, with empirical, innovative findings when used in different subfields of mathematical optimization, such as stochastic, dynamic, multimodal and robust optimization, as well as noisy optimization and dynamic and constraint satisfaction problems.
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