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
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 scientific 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 scientific 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+).
