Advances in Metaheuristics(English, Electronic book text, Ganesan Timothy)

Advances in Metaheuristics(English, Electronic book text, Ganesan Timothy)

  • Ganesan Timothy
Publisher:CRC PressISBN 13: 9781315297644ISBN 10: 1315297647

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Advances in Metaheuristics(English, Electronic book text, Ganesan Timothy) is written by Ganesan Timothy and published by Taylor & Francis Ltd. It's available with International Standard Book Number or ISBN identification 1315297647 (ISBN 10) and 9781315297644 (ISBN 13).

Advances in Metaheuristics: Applications in Engineering Systems provides details on current approaches utilized in engineering optimization. It gives a comprehensive background on metaheuristic applications, focusing on main engineering sectors such as energy, process, and materials. It discusses topics such as algorithmic enhancements and performance measurement approaches, and provides insights into the implementation of metaheuristic strategies to multi-objective optimization problems. With this book, readers can learn to solve real-world engineering optimization problems effectively using the appropriate techniques from emerging fields including evolutionary and swarm intelligence, mathematical programming, and multi-objective optimization. The ten chapters of this book are divided into three parts. The first part discusses three industrial applications in the energy sector. The second focusses on process optimization and considers three engineering applications: optimization of a three-phase separator, process plant, and a pre-treatment process. The third and final part of this book covers industrial applications in material engineering, with a particular focus on sand mould-systems. It also includes discussions on the potential improvement of algorithmic characteristics via strategic algorithmic enhancements. This book helps fill the existing gap in literature on the implementation of metaheuristics in engineering applications and real-world engineering systems. It will be an important resource for engineers and decision-makers selecting and implementing metaheuristics to solve specific engineering problems.