Sine Cosine Algorithm Toolbox

A toolbox for the Sine Cosine Algorithm (SCA) for solving single-objective optimization problems
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Updated 22 May 2018

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This is a handy toolbox for the recently proposed SCA algorithm. 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

Th original version of this algorithm can be found here: http://www.mathworks.com/matlabcentral/fileexchange/54948-sca--a-sine-cosine-algorithm

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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A course on “Optimization Problems and Algorithms: how to understand, formulation, and solve optimization problems”:
https://www.udemy.com/optimisation/?couponCode=MATHWORKSREF

A course on “Introduction to Genetic Algorithms: Theory and Applications”
https://www.udemy.com/geneticalgorithm/?couponCode=MATHWORKSREF
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Cite As

Seyedali Mirjalili (2024). Sine Cosine Algorithm Toolbox (https://www.mathworks.com/matlabcentral/fileexchange/54949-sine-cosine-algorithm-toolbox), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2014a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
Find more on Global Optimization Toolbox in Help Center and MATLAB Answers
Acknowledgements

Inspired: Improved Sine-Cosine Algorithm

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