Pandian Vasant

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.

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.

As the world continues to evolve technologically, people depend more heavily on energy-dependent systems to fulfill their daily needs. However, as these needs grow, it is important to develop sustainable systems that are reliable, as well as environmentally sound. Sustaining Power Resources through Energy Optimization and Engineering highlights the sustainable development and efficient operation of energy systems being provided to consumers. Featuring emergent research and trends within the area of power optimization and engineering, this book is a crucial reference source for engineers, researchers, sustainability experts, and professionals interested in the improvement and usage of infrastructural energy systems.

As technologies grow more complex, modelling and simulation of new intelligent systems becomes increasingly challenging and nuanced; specifically in diverse fields such as medicine, engineering, and computer science. Soft Computing Intelligent Algorithms in Engineering, Management, and Technology explores emerging technologies and best practices to effectively address concerns inherent in properly optimising advanced systems. With applications in areas such as bio-engineering, space exploration, industrial informatics, information security, and nuclear and renewable energies, this exceptional reference will serve as an important tool for decision makers, managers, researchers, economists, and industrialists across a wide range of scientific fields.