- Detailed description of the algorithms along with pseudocode and flowchart
- Easy translation to program code that is also readily available in Mathworks website for some of the algorithms
- Simple examples demonstrating the optimization strategies are provided to enhance understanding
- Standard applications and benchmark datasets for testing and validating the algorithms are included
This book is a reference for undergraduate and post-graduate students. It will be useful to faculty members teaching optimization. It is also a comprehensive guide for researchers who are looking for optimizing resources in attaining the best solution to a problem. The nature-inspired optimization algorithms are unconventional, and this makes them more efficient than their traditional counterparts.
- Detailed description of the algorithms along with pseudocode and flowchart
- Easy translation to program code that is also readily available in Mathworks website for some of the algorithms
- Simple examples demonstrating the optimization strategies are provided to enhance understanding
- Standard applications and benchmark datasets for testing and validating the algorithms are included
This book is a reference for undergraduate and post-graduate students. It will be useful to faculty members teaching optimization. It is also a comprehensive guide for researchers who are looking for optimizing resources in attaining the best solution to a problem. The nature-inspired optimization algorithms are unconventional, and this makes them more efficient than their traditional counterparts.

Nature-Inspired Optimization Algorithms
274