Optimization using evolutionary algorithms and metaheuristics : applications in engineering /
edited by Kaushik Kumar and J. Paulo Davim.
- 1 online resource (pages cm.).
- Science, technology, and management series .
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
9780429293030 (electronic bk) 0429293038 (electronic bk) 9781000546804 1000546802 9781000541977 1000541975 9781000537147 1000537145
Engineering economy.
Mathematical optimization.
Genetic algorithms.
Metaheuristics.
TECHNOLOGY / Engineering / Industrial
TECHNOLOGY / Manufacturing
MATHEMATICS / Probability & Statistics / General
TA177.4 / .O68 2019
620.001/5196
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
9780429293030 (electronic bk) 0429293038 (electronic bk) 9781000546804 1000546802 9781000541977 1000541975 9781000537147 1000537145
Engineering economy.
Mathematical optimization.
Genetic algorithms.
Metaheuristics.
TECHNOLOGY / Engineering / Industrial
TECHNOLOGY / Manufacturing
MATHEMATICS / Probability & Statistics / General
TA177.4 / .O68 2019
620.001/5196