English | 2022 | ISBN: 978-0367750497 | 310 Pages | PDF | 21 MB

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.

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