Nature-Inspired Algorithms (Paperback)

Krishn Kumar Mishra

ISBN 10: 1032322640 / ISBN 13: 9781032322643

Published by Taylor & Francis Ltd, London, 2024

About this Item

Paperback. This comprehensive reference text discusses nature inspired algorithms and their applications. It presents the methodology to write new algorithms with the help of MATLAB programs and instructions for better understanding of concepts. It covers well-known algorithms including evolutionary algorithms, genetic algorithm, particle Swarm optimization and differential evolution, and recent approached including gray wolf optimization. A separate chapter discusses test case generation using techniques such as particle swarm optimization, genetic algorithm, and differential evolution algorithm.The book- Discusses in detail various nature inspired algorithms and their applications Provides MATLAB programs for the corresponding algorithm Presents methodology to write new algorithms Examines well-known algorithms like the genetic algorithm, particle swarm optimization and differential evolution, and recent approaches like gray wolf optimization. Provides conceptual linking of algorithms with theoretical concepts The text will be useful for graduate students in the field of electrical engineering, electronics engineering, computer science and engineering. Discussing nature inspired algorithms and their applications in a single volume, this text will be useful as a reference text for graduate students in the field of electrical engineering, electronics engineering, computer science and engineering. It discusses important algorithms including deterministic algorithms, randomized algorithms, evolutionary algorithms, particle swarm optimization, big bang big crunch (BB-BC) algorithm, genetic algorithm and grey wolf optimization algorithm. " 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9781032322643

Bibliographic Details

• Title: Nature-Inspired Algorithms (Paperback)
• Publisher: Taylor & Francis Ltd, London
• Publication Date: 2024
• Language: English
• ISBN 10: 1032322640
• ISBN 13: 9781032322643
• Binding: Paperback
• Condition: new

About this title

Synopsis

This comprehensive reference text discusses nature inspired algorithms and their applications. It presents the methodology to write new algorithms with the help of MATLAB programs and instructions for better understanding of concepts. It covers well-known algorithms including evolutionary algorithms, genetic algorithm, particle Swarm optimization and differential evolution, and recent approached including gray wolf optimization. A separate chapter discusses test case generation using techniques such as particle swarm optimization, genetic algorithm, and differential evolution algorithm.

The book-

• Discusses in detail various nature inspired algorithms and their applications
• Provides MATLAB programs for the corresponding algorithm
• Presents methodology to write new algorithms
• Examines well-known algorithms like the genetic algorithm, particle swarm optimization and differential evolution, and recent approaches like gray wolf optimization.
• Provides conceptual linking of algorithms with theoretical concepts

The text will be useful for graduate students in the field of electrical engineering, electronics engineering, computer science and engineering.

Discussing nature inspired algorithms and their applications in a single volume, this text will be useful as a reference text for graduate students in the field of electrical engineering, electronics engineering, computer science and engineering. It discusses important algorithms including deterministic algorithms, randomized algorithms, evolutionary algorithms, particle swarm optimization, big bang big crunch (BB-BC) algorithm, genetic algorithm and grey wolf optimization algorithm. "

About the Author

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.