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Optimization Using Evolutionary Algorithms and Metaheuristics

Download or Read eBook Optimization Using Evolutionary Algorithms and Metaheuristics PDF written by Kaushik Kumar and published by CRC Press. This book was released on 2019-08-22 with total page 127 pages. Available in PDF, EPUB and Kindle.
Optimization Using Evolutionary Algorithms and Metaheuristics
Author :
Publisher : CRC Press
Total Pages : 127
Release :
ISBN-10 : 9781000546804
ISBN-13 : 1000546802
Rating : 4/5 (04 Downloads)

Book Synopsis Optimization Using Evolutionary Algorithms and Metaheuristics by : Kaushik Kumar

Book excerpt: 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


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