Nature-Inspired Algorithms: For Engineers and Scientists

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. "