The SCA creates multiple initial random candidate solutions and requires them to fluctuate outwards or towards the best solution using a mathematical model based on sine and cosine functions. Several random and adaptive variables also are integrated to this algorithm to emphasize exploration and exploitation of the search space in different milestones of optimization.
This is the source codes of the paper:

S. Mirjalili, SCA: A Sine Cosine Algorithm for solving optimization problems, Knowledge-Based Systems, in press, 2015, DOI: http://dx.doi.org/10.1016/j.knosys.2015.12.022

Link: http://www.sciencedirect.com/science/article/pii/S0950705115005043

A Matlab toolbox for this algorithm can be found here: http://www.mathworks.com/matlabcentral/fileexchange/54949-sine-cosine-algorithm-toolbox

If you have no access to the paper, please drop me an email at ali.mirjalili@gmail.com and I will send you the paper.

All of the source codes and extra information as well as more optimization techniques can be found in my personal website at http://www.alimirjalili.com

I have a number of relevant courses in this area. You can enrol via the following links with 95% discount:

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