Yin Yang Pair Optimization

Single Objective Yin Yang Pair Optimization (Termination Criterion: Number of Iterations)
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Updated Sat, 30 Dec 2017 00:50:55 +0000

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Yin-Yang-Pair Optimization (YYPO) is a meta-heuristic optimization technique and is based on maintaining a balance between exploration and exploitation of the search space. It is a low complexity stochastic algorithm which works with two points and generates additional points depending on the number of decision variables in the optimization problem. The termination criterion employed in this code is the number of Iterations.

This code helps one to easily understand the working of YYPO. A detailed step-by-step demonstration of YYPO is available in the given pdf file.
YYPO with the termination criterion of maximum number of functional evaluations is available at .
https://in.mathworks.com/matlabcentral/fileexchange/65558-yin-yang-pair-optimization--yypo-

It might be easier for beginners to understand YYPO with the termination criterion as maximum iterations rather than maximum functional evaluations.

A p-coded GUI (along with its execution on CEC2013 functions) can be downloaded from https://goo.gl/aLXuM5

Note:
(i) The fitness function should be able to evaluate the fitness function for a set of points and not just a single point.
(ii) If D is the dimension of the problem, exactly 4D functional evaluations are required in a complete iteration of YYPO.
(iii) If T is the number of iterations, the total number of functional evaluations used in YYPO is 4DT + 2.
(iv) YYPO has three user defined parameters, viz., (i) Imin, (ii) Imax and (iii) alpha.
(v) YYPO does not employ a population and works with two points.
(vi) YYPO inherently scales the variables to 0 and 1.
(vii) YYPO is not monotonically convergent with respect to each iteration but is monotonically convergent with respect to each archive update. However, it does not lose the best determined solution due to the Archive. This code keeps track of the best solution discovered (till a particular iteration) to depict monotonic convergence.

Refer to the following article for additional details.
Yin-Yang-pair Optimization: A novel lightweight optimization algorithm
http://www.sciencedirect.com/science/article/pii/S0952197616300811
https://doi.org/10.1016/j.engappai.2016.04.004

Cite As

SKS Labs (2024). Yin Yang Pair Optimization (https://www.mathworks.com/matlabcentral/fileexchange/65556-yin-yang-pair-optimization), MATLAB Central File Exchange. Retrieved .

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Version Published Release Notes
1.0.0.0

Description Updated
Description Updated