The text discusses nature inspired algorithms and their applications in a comprehensive manner. It will be an ideal reference text for graduate students in the field of electrical engineering, electronics engineering, computer science and engineering.
The text discusses nature inspired algorithms and their applications in a comprehensive manner. It will be an ideal reference text for graduate students in the field of electrical engineering, electronics engineering, computer science and engineering.
K. K. Mishra is presently working as an assistant professor, department of computer science and engineering, Motilal Nehru National Institute of Technology Allahabad, India. His research areas include genetic algorithm, analysis of algorithm, automata theory, microprocessor and multi-objective optimization. He has taught courses including computer architecture, data structures, advanced computer architecture, programming in C++, microprocessor and automata theory at undergraduate and graduate level. He is a regular reviewer of the Journal of Supercomputing (Springer), Applied Intelligence, Applied Soft Computing, IEEE Transaction on Cybernetics, IEEE System Journal, Neural computing and application, and IETE journals.
Inhaltsangabe
Preface. Acknowledgments. About the Author. Introduction. Binary Genetic Algorithms. Real-Parameter Genetic Algorithm. Differential Evolution. Particle Swarm Optimization. Grey Wolf Optimization. Environmental Adaptation Method. Other Important Optimization Algorithms. Application of Genetic Algorithms, Partial Swarm Optimization, and Differential Evolution in Software Testing. Application of Genetic Algorithms, Partial Swarm Optimization, and Differential Evolution in Regression Testing. Application of Genetic Algorithms and Partial Swarm Optimization in Cloud Computing. References and Further Reading. Index.
Preface. Acknowledgments. About the Author. Introduction. Binary Genetic Algorithms. Real-Parameter Genetic Algorithm. Differential Evolution. Particle Swarm Optimization. Grey Wolf Optimization. Environmental Adaptation Method. Other Important Optimization Algorithms. Application of Genetic Algorithms, Partial Swarm Optimization, and Differential Evolution in Software Testing. Application of Genetic Algorithms, Partial Swarm Optimization, and Differential Evolution in Regression Testing. Application of Genetic Algorithms and Partial Swarm Optimization in Cloud Computing. References and Further Reading. Index.
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