Optimization Using Evolutionary Algorithms and Metaheuristics (eBook, PDF)
Applications in Engineering
Redaktion: Kumar, Kaushik; Davim, J. Paulo
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Optimization Using Evolutionary Algorithms and Metaheuristics (eBook, PDF)
Applications in Engineering
Redaktion: Kumar, Kaushik; Davim, J. Paulo
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This book covers developments and advances of algorithm based optimization techniques These techniques were only used for non-engineering problems. This book applies them to engineering problems.
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This book covers developments and advances of algorithm based optimization techniques These techniques were only used for non-engineering problems. This book applies them to engineering problems.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Seitenzahl: 148
- Erscheinungstermin: 22. August 2019
- Englisch
- ISBN-13: 9781000537147
- Artikelnr.: 57541110
- Verlag: Taylor & Francis
- Seitenzahl: 148
- Erscheinungstermin: 22. August 2019
- Englisch
- ISBN-13: 9781000537147
- Artikelnr.: 57541110
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Kaushik Kumar, B.Tech (Mechanical Engineering, REC (Now NIT), Warangal), MBA (Marketing, IGNOU) and Ph.D (Engineering, Jadavpur University), is presently an Associate Professor in the Department of Mechanical Engineering, Birla Institute of Technology, Mesra, Ranchi, India. He has 16 years of Teaching & Research and over 11 years of industrial experience in a manufacturing unit of Global repute. His areas of teaching and research interest are Optimization, Conventional and Non-conventional Manufacturing, CAD / CAM, Rapid Prototyping, Quality Management Systems and Composites. He has 9 Patents, 28 Book, 15 Edited Book, 43 Book Chapters, 136 international Journal publications, 21 International and 8 National Conference publications to his credit. He is Guest Editor for many peer reviewed journals, editorial board and review panel member of many International and National Journals of global repute. He has been felicitated with many awards and honours. J. Paulo Davim received his Ph.D. in mechanical engineering in 1997, M.Sc. in mechanical engineering (materials and manufacturing processes) in 1991, Licentiate degree (5 years) in mechanical engineering in 1986 from the University of Porto (FEUP), the Aggregate title from the University of Coimbra in 2005 and D.Sc. from London Metropolitan University in 2013. He is EUR ING by FEANI and senior chartered engineer by the Portuguese Institution of Engineers with MBA and specialist title in engineering and industrial management. Currently, he is professor at the Department of Mechanical Engineering of the University of Aveiro. He has more than 30 years of teaching and research experience in manufacturing, materials and mechanical engineering with special emphasis in machining and tribology. Recently, he has also interest in management/industrial engineering and higher education for sustainability/engineering education. He has received several scienti¿c awards. He has worked as evaluator of projects for international research agencies as well as examiner of Ph.D. thesis for many universities. He is the editor in chief of several international journals, guest editor of journals, editor of books, series editor of books and scienti¿c advisor for many international journals and conferences. At present, he is an editorial board member of 25 international journals and acts as reviewer for more than 80 prestigious Web of Science journals. In addition, he has also published as editor (and co-editor) for more than 100 books and as author (and co-author) for more than 10 books, 80 book chapters and 400 articles in journals and conferences (more than 200 articles in journals indexed in Web of Science/h-index 45+ and SCOPUS/h-index 52+).
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.
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.
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.
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.