Metaheuristics-Based Materials Optimization

Auteur
Dr. Harbinder Singh received his B.Tech. (Hons.) degree in Electronics and Communication from Kurukshetra University, Kurukshetra, India, in 2011, followed by his M.Tech. degree in Antennas from Punjab Technical University, Jalandhar, India, in 2014. He completed his Ph.D. degree in Electronics and Communication Engineering from Chandigarh University, Gharuan, India, in 2019. With over ten years of teaching and research experience, Dr. Singh currently holds the position of Associate Professor at Chandigarh University, Punjab, India. He has authored more than 55 research articles in SCI and Scopus indexed journals, is a qualified GATE engineer, and author of the book 'Electromagnetics and Antennas'. His research interests include a range of topics such as metamaterials, smart antennas, antenna arrays, radio absorbers, sensors, frequency reconfigurable antennas, MIMO antennas, wearable antennas, SAR and UWB antennas. Dr. Singh has also actively participated in many international and national conferences as a session chair, member of steering, advisory and technical program committees, and has served as an editor and Convenor for several conference proceedings and guest editor for SCI indexed journals. In recognition of his outstanding achievements in the field of technical education and research, Dr. Singh was awarded the ISTE Section Best Teacher Award by the Indian Society for Technical Education in 2021. Dr. Shailendra Rajput is an Associate Professor at Department of Physics, University Centre for Research & Development, Chandigarh University, Mohali, India. He was a postdoctoral fellow at Ariel University, Israel (September 2017-April 2021) and Xi'an Jiaotong University, China (May 2015-July 2017). His main research work is associated with Energy harvesting, Solar energy, Energy storage, Ferroelectricity, Piezoelectricity, and biomedical application of electromagnetic waves.Dr. Abhishek Sharma received his master's degree in robotics engineering from the University of Petroleum and Energy Studies (UPES), Dehradun, India, in 2014. He was a Senior Research Fellow in a DST funded project under the Technology Systems Development Scheme and worked as an Assistant Professor with the Department of Electronics and Instrumentation, UPES. He also worked as a research fellow in Ariel university (Israel) and received Emerging Scientist award in 2021. Currently he is working as a research assistant professor at Graphic Era University (India). His research interests include machine learning, optimization theory, swarm intelligence, embedded system, control and robotics.

Texte du rabat

Metaheuristics-Based Materials Optimization: Enhancing Materials Applications provides a guide to using metaheuristics-based computational techniques to improve the design, performance, and broaden the applications of various materials. The book fuses optimization algorithms with materials engineering, enabling more accurate simulations and models for analyzing and predicting the behavior of materials under different conditions, allowing for design of materials with improved performance, durability, energy efficiency, cost-effectiveness, and other desired characteristics. Metaheuristic approaches for material synthesis and design, structural optimization, material characterization, property prediction, and process optimization are all covered, as are comparisons of different algorithms, step-by-step guidelines on how to implement them, and case studies of them being applied in real-world settings.

Contenu

1. Introduction to Metaheuristic Algorithms
   
   2. Overview of metaheuristic algorithms and their relevance to materials applications
   3. Introduction to optimization techniques commonly used in materials science
   4. Detailed exploration of metaheuristic algorithms applicable to materials-based optimization
   5. Guidelines for selecting and customizing metaheuristic algorithms for specific materials applications
   6. Real-world case studies demonstrating the successful application of metaheuristic algorithms in materials science and engineering
   7. Step-by-step methodologies for integrating metaheuristic algorithms into materials-based processes and designs
   8. Methods for evaluating and comparing the performance of metaheuristic algorithms in materials applications
   9. Discussion of challenges and limitations encountered when applying metaheuristic algorithms to materials applications
   10. Consideration of ethical, environmental, and societal implications associated with optimizing materials applications
   11. Summary of key insights, methodologies, and best practices discussed throughout the book