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Optimization Using Evolutionary Algorithms and Metaheuristics: Applications in Engineering (Science, Technology, and Management) by Kumar, Kaushik (editor);Davim, J. Paulo (editor) is a nonfiction available to read on EtoBox.

What is Optimization Using Evolutionary Algorithms and Metaheuristics: Applications in Engineering (Science, Technology, and Management) about?

Recognized as a "Recommended" title by Choice for their April 2021 issue. Choice is a publishing unit at the Association of College & Research Libraries (ACR&L), a division of the American Library Association. Choice has been the acknowledged leader in the provision of objective, high-quality evaluations of nonfiction academic writing.　 Metaheuristic optimization is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem, especially with incomplete or imperfect information or limited computation capacity. This is usually applied when two or more objectives are to be optimized simultaneously. This book is presented with two major objectives. Firstly, it features chapters by eminent researchers in the field providing the readers about the current status of the subject. Secondly, algorithm-based optimization or advanced optimization techniques, which are applied to mostly non-engineering problems, are applied to engineering problems. This book will also serve as an aid to both research and industry. Usage of these methodologies would enable the improvemen

Who reads Optimization Using Evolutionary Algorithms and Metaheuristics: Applications in Engineering (Science, Technology, and Management)?

Author

Kumar, Kaushik (editor);Davim, J. Paulo (editor)

Publisher

Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T & F Informa, plc

Published

2019

Language

EN

ISBN

9780429293030

Category

nonfiction

Subjects

Mathematics, Engineering, Optimization. Operations Research