Optimization using evolutionary algorithms and metaheuristics : applications in engineering
著者
書誌事項
Optimization using evolutionary algorithms and metaheuristics : applications in engineering
(Science, technology, and management series / series editor, J. Paulo Davim)
CRC Press, c2019
大学図書館所蔵 件 / 全1件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographical references and index
内容説明・目次
内容説明
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 improvement in engineering and manufacturing technology and support an organization in this era of low product life cycle.
Features:
Covers the application of recent and new algorithms
Focuses on the development aspects such as including surrogate modeling, parallelization, game theory, and hybridization
Presents the advances of engineering applications for both single-objective and multi-objective optimization problems
Offers recent developments from a variety of engineering fields
Discusses Optimization using Evolutionary Algorithms and Metaheuristics applications in engineering
目次
Part I: Optimization. 1. Foundations and Principles. 2. Neural Networks. 3. Fuzzy Systems. 4. Evolutionary Computation. 5. Rough Sets. Part II: Applications of Optimization. 6. Mechanical Engineering. 7. Power Control and Optimization. 8. Nanoscience and Nanoengineering. 9. Mining Engineering. 10. Signal Processing. 11. Civil Engineering. 12. Optical Engineering. 13. Bioinformatics and Biomedical Engineering. 14. Ecology and Environmental Engineering.
「Nielsen BookData」 より