This book provides fundamental concepts related to various types of genetic algorithms and practical applications in various domains such as medical imaging, manufacturing, and engineering design. The book discusses genetic algorithms which are used to solve a variety of optimization problems. The genetic algorithms are demonstrated to offer reliable search in complex spaces. The book presents high-quality research work by academics and researchers which is useful for young researchers and students.

Discusses genetic algorithms which are used to solve a variety of optimization problems Provides fundamental concepts related to various types of genetic algorithms and practical applications Serves as a reference for the researchers working in this area

Autorentext

Nilanjan Dey is Associate Professor, Department of Computer Science and Engineering, Techno International New Town, Kolkata, India. He is Visiting Fellow of the University of Reading, UK. He was Honorary Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012-2015). He was awarded his Ph.D. from Jadavpur University in 2015. He has authored/edited more than 70 books with Elsevier, CRC Press, and Springer and published more than 300 papers. He is Editor-in-Chief of International Journal of Ambient Computing and Intelligence, IGI Global, and Associated Editor of International Journal of Information Technology, Springer. He is Series Co-editor of Springer Tracts in Nature-Inspired Computing, Springer, Series Co-editor of Advances in Ubiquitous Sensing Applications for Healthcare, Elsevier, and Series Editor of Computational Intelligence in Engineering Problem Solving and Intelligent Signal processing and data analysis, CRC. He is Fellow of IETE and Senior Member of IEEE.

Inhalt
Variants of Genetics Algorithm and their Applications.- Genetic Algorithms Applications for Challenging Real-World Problems: Some Recent Advances and Future Trends.- Genetic Algorithm for Route Optimization.- Design weight minimization of a reinforced concrete beam through genetic algorithm and its variants.- IGA: an improved genetic algorithm for real-optimization problem.- Application of Genetic Algorithm based controllers in Wind Energy Systems for Smart Energy Management.- Application of Genetic Algorithm in Predicting Mental Illness: A Case Study of Schizophrenia.- Comparison of Biological Inspired Algorithm with Socio Inspired Technique on Load Frequency Control of Multisource Single Area Power system.- Genetic Algorithm and Accelerating Fuzzification for Optimum Sizing and Topology Design of Real-Size Tall Building Systems.- Evaluation of Underwater Images using Genetic Algorithm Monitored Preprocessing and Morphological Segmentation.