In my opinion, the best way of learning the metaheuristics is to study the natural behaviors closely, such as human genetics, human brain study etc. Secondly, one should, study correlation of multiple statistical and mathematical methods with the laws of nature.

Some books on genetic algorithms and related methods that I found useful are:

1. Introduction to Genetic Algorithms

by S.N. Sivanandam and S.N. Deepa,

Springer. 2008. It explains GAs right from the basics;

2. Nature-Inspired Optimization Algorithms

by Xin-She Yang, Elsevier Science and Technology Books, Inc., 2014;

3. A classic book is: An Introduction to Genetic Algorithms, by Melanie Mitchell, 1998;

4. Multi-objective Optimization Using Evolutionary Algorithms by Kalyanmoy Deb.

It helped a lot to go through actual code implementing the algorithms, such as the examples in the Global Optimization Toolbox in MATLAB and user-contributed code in MATLAB FileExchange.

I learnt a lot during actual application of the algorithms to solve particular problems.

What can also help is a search for some review and survey papers, as well as original papers that explain the basics, especially as applies to a particular problem domain.

Thank you very much Prof. Badar and Prof. Ayo for the suggestions. I will follow the materials you have suggested and will come back to you for any further assistance.

Talbi's metaheuristics book is very good.

ISBN-13: 978-0470278581

ISBN-10: 0470278587

Best is to start with reading books in this domain. Secondly, you can download and read good research articles from the web. In particular a start with genetic algorithms and particle swarms may be beneficial for you.