Mathematical Definition

\[f(\mathbf{x})=f(x_1, ..., x_n)=(\sum_{i=1}^{n}|x_i|)exp(-\sum_{i=1}^{n}sin(x_i^2))\]

Plots

Xin-She Yang N. 2 Function

Xin-She Yang N. 2 Function

Xin-She Yang N. 2 Function

Xin-She Yang N. 2 Function

Xin-She Yang N. 2 Function

Xin-She Yang N. 2 Function

Xin-She Yang N. 2 Function

Xin-She Yang N. 2 Function

Two contours of the function are presented below:

Xin-She Yang N. 2 Function

Xin-She Yang N. 2 Function

Description and Features

  • The function is not convex.
  • The function is defined on n-dimensional space.
  • The function is non-separable.
  • The function is non-differentiable.

Input Domain

The function can be defined on any input domain but it is usually evaluated on $x_i \in [-2\pi, 2\pi]$ for $i=1, …, n$.

Global Minima

The global minimum $f(\textbf{x}^{\ast})=0$ are located at $\mathbf{x^\ast}=(0, …, 0)$.

Implementation

Python

For Python, the function is implemented in the benchmarkfcns package, which can be installed from command line with pip install benchmarkfcns.

from benchmarkfcns import xinsheyang2

print(xinsheyang2([[0, 0, 0],
              [1, 1, 1]]))

MATLAB

An implementation of the Xin-She Yang N. 2 Function with MATLAB is provided below.

% Computes the value of the Xin-She Yang N. 2 function.
% SCORES = XINSHEYANGN2FCN(X) computes the value of the Xin-She Yang N. 2
% function at point X. XINSHEYANGN2FCN accepts a matrix of size M-by-N and 
% returns a vetor SCORES of size M-by-1 in which each row contains the 
% function value for the corresponding row of X.
% 
% Author: Mazhar Ansari Ardeh
% Please forward any comments or bug reports to mazhar.ansari.ardeh at
% Google's e-mail service or feel free to kindly modify the repository.
function scores = xinsheyangn2fcn(x)
    n = size(x, 2);
    
    scores = sum(abs(x), 2) .* exp(-sum(sin(x .^2), 2));
end 

The function can be represented in Latex as follows:

f(\mathbf{x})=f(x_1, ..., x_n)=(\sum_{i=1}^{n}|x_i|)exp(-\sum_{i=1}^{n}sin(x_i^2))

References:

  • Momin Jamil and Xin-She Yang, A literature survey of benchmark functions for global optimization problems, Int. Journal of Mathematical Modelling and Numerical Optimisation}, Vol. 4, No. 2, pp. 150–194 (2013), arXiv:1308.4008
  • X. S. Yang, “Test Problems in Optimization,” Engineering Optimization: An Introduction with Metaheuristic Applications John Wliey & Sons, 2010. [Available Online]: http://arxiv.org/abs/1008.0549