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I. Mathematical Expression:

$$f(X)=\sum_{i=1}^{n-1}\left[100\left(x_{i+1}-x^2_i\right)^2+\left(x_i-1\right)^2\right]$$

where:

\(\bullet\) \(-30\leq x_i\leq 30\) , \(i=1,2,\cdots,n\)

\(\bullet\) \(f_{min}(X^*)=0\)

\(\bullet\) \(x^*_i =1\)

\(\bullet\) This benchmark function is very popular and has many names as can be seen from its subject. Also, some references add Saddle instead of Valley \(\rightarrow\) "Generalized Rosenbrock's Saddle Function" as in [5, 11, 12]. Moreover, this function comes with different variable bounds, like \(|x_i|\leq 10\) as in [5] and \(|x_i|\leq 2.048\) as in [12]. Furthermore, there are many other functions are based on or extended from this function; see the listed functions. Please, note that the expression of this benchmark function (when \(n=2\)) is not similar to that of Leon's Function as many studies, by mistake, consider it.

 

II. Citation Policy:

If you publish material based on databases obtained from this repository, then, in your acknowledgments, please note the assistance you received by using this repository. This will help others to obtain the same data sets and replicate your experiments. We suggest the following pseudo-APA reference format for referring to this repository:

Ali R. Al-Roomi (2015). Unconstrained Single-Objective Benchmark Functions Repository [https://www.al-roomi.org/benchmarks/unconstrained]. Halifax, Nova Scotia, Canada: Dalhousie University, Electrical and Computer Engineering.

Here is a BiBTeX citation as well:

@MISC{Al-Roomi2015,
author = {Ali R. Al-Roomi},
title = {{Unconstrained Single-Objective Benchmark Functions Repository}},
year = {2015},
address = {Halifax, Nova Scotia, Canada},
institution = {Dalhousie University, Electrical and Computer Engineering},
url = {https://www.al-roomi.org/benchmarks/unconstrained}
}

 

III. 2&3D-Plots:

 

IV. Controllable 3D Model:

- In case you want to adjust the rendering mode, camera position, background color or/and 3D measurement tool, please check the following link

- In case you face any problem to run this model on your internet browser (it does not work on mobile phones), please check the following link

 

V. MATLAB M-File:

% Generalized Rosenbrock's Valley (Banana or 2nd De Jong's) Function
% Range of initial points: -2.048 < xj < 2.048 , j=1,2,...,n
% Some papers take the range as: -5 <= xj <= 10 or -30 <= xj <= 30
% Global minima: (x1,x2,...,xn)=1
% f(X)=0
% Coded by: Ali R. Alroomi | Last Update: 03 June 2015 | www.al-roomi.org 
 
clear
clc
warning off
    
x1min=-2.048;
x1max=2.048;
x2min=-2.048;
x2max=2.048;
R=1500; % steps resolution
x1=x1min:(x1max-x1min)/R:x1max;
x2=x2min:(x2max-x2min)/R:x2max;
    
for j=1:length(x1)
   
    for i=1:length(x2)
        f(i)=100*(x2(i)-x1(j)*x1(j)).^2+(1-x1(j)).^2;
    end
   
    f_tot(j,:)=f;
 
end
 
% 1-dimensional plot is not applicable with this benchmark function
 
figure(1)
meshc(x1,x2,f_tot);colorbar;set(gca,'FontSize',12);
xlabel('x_2','FontName','Times','FontSize',20,'FontAngle','italic');
set(get(gca,'xlabel'),'rotation',25,'VerticalAlignment','bottom');
ylabel('x_1','FontName','Times','FontSize',20,'FontAngle','italic');
set(get(gca,'ylabel'),'rotation',-25,'VerticalAlignment','bottom');
zlabel('f(X)','FontName','Times','FontSize',20,'FontAngle','italic');
title('3D View','FontName','Times','FontSize',24,'FontWeight','bold');
 
figure(2)
mesh(x1,x2,f_tot);view(0,90);colorbar;set(gca,'FontSize',12);
xlabel('x_2','FontName','Times','FontSize',20,'FontAngle','italic');
ylabel('x_1','FontName','Times','FontSize',20,'FontAngle','italic');
zlabel('f(X)','FontName','Times','FontSize',20,'FontAngle','italic');
title('X-Y Plane View','FontName','Times','FontSize',24,'FontWeight','bold');
 
figure(3)
mesh(x1,x2,f_tot);view(90,0);colorbar;set(gca,'FontSize',12);
xlabel('x_2','FontName','Times','FontSize',20,'FontAngle','italic');
ylabel('x_1','FontName','Times','FontSize',20,'FontAngle','italic');
zlabel('f(X)','FontName','Times','FontSize',20,'FontAngle','italic');
title('X-Z Plane View','FontName','Times','FontSize',24,'FontWeight','bold');
 
figure(4)
mesh(x1,x2,f_tot);view(0,0);colorbar;set(gca,'FontSize',12);
xlabel('x_2','FontName','Times','FontSize',20,'FontAngle','italic');
ylabel('x_1','FontName','Times','FontSize',20,'FontAngle','italic');
zlabel('f(X)','FontName','Times','FontSize',20,'FontAngle','italic');
title('Y-Z Plane View','FontName','Times','FontSize',24,'FontWeight','bold');

Click here to download m-file

 

VI. References:

[1] H. H. Rosenbrock, "An Automatic Method for Finding the Greatest or Least Value of a Function," The Computer Journal, vol. 3, no. 3, pp. 175-184, Jan. 1960. [Online]. Available: http://comjnl.oxfordjournals.org/content/3/3/175.full.pdf
[2] X. Yao, Y. Liu, and G. Lin, "Evolutionary Programming Made Faster," IEEE Transactions on Evolutionary Computation, vol. 3, no. 2, pp. 82-102, Jul. 1999.
[3] M. M. Ali, C. Khompatraporn, and Z. B. Zabinsky, "A Numerical Evaluation of Several Stochastic Algorithms on Selected Continuous Global Optimization Test Problems," Journal of Global Optimization, vol. 31, no. 4, pp. 635-672, Apr. 2005.
[4] M. Subotic, M. Tuba, and N. Stanarevic, "Different Approaches in Parallelization of the Artificial Bee Colony Algorithm," International Journal of Mathematical Models and Methods in Applied Sciences, vol. 5, no. 4, pp. 755-762, Mar. 2011.
[5] E. P. Adorio, "MVF - Multivariate Test Functions Library in C for Unconstrained Global Optimization," Quezon City, Metro Manila, Philippines, Jan. 2005. [Online]. Available: http://geocities.ws/eadorio/mvf.pdf
[6] R. Chelouah and P. Siarry, "Tabu Search Applied to Global Optimization," European Journal of Operational Research, vol. 123, no. 2, pp. 256-270, Jun. 2000.
[7] M. Molga and C. Smutnicki, "Test Functions for Optimization Needs," Apr. 2005, [Accessed March 28, 2013]. [Online]. Available: http://www.zsd.ict.pwr.wroc.pl/files/docs/functions.pdf
[8] S. Rahnamayan, H. R. Tizhoosh, and M. M. A. Salama, "A Novel Population Initialization Method for Accelerating Evolutionary Algorithms," Computers & Mathematics with Applications, vol. 53, no. 10, pp. 1605-1614, May 2007.
[9] S. Rahnamayan, H. Tizhoosh, and M. Salama, "Opposition-Based Differential Evolution for Optimization of Noisy Problems," IEEE Congress on in Evolutionary Computation, 2006 (CEC 2006), Jul. 2006, pp. 1865-1872.
[10] A. K. Qin, V. L. Huang, and P. Suganthan, "Differential Evolution Algorithm with Strategy Adaptation for Global Numerical Optimization," IEEE Transactions on Evolutionary Computation, vol. 13, no. 2, pp. 398-417, April 2009.
[11] D. R. M. Jr., "The Uses of the Slime Mold Lifecycle as a Model for Numerical Optimization," Ph.D. Dissertation, Oklahoma State University, Oklahoma City, OK, Jul. 2010, [Accessed Apr. 30, 2013]. [Online]. Available: http://www.cs.okstate.edu/~monismi/dissertation/MonismithDissertation.pdf
[12] R. Storn and K. Price, "Differential Evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces," Journal of Global Optimization, vol. 11, no. 4, pp. 341-359, Dec. 1997.
[13] Ali R. Alroomi, "The Farm of Unconstrained Benchmark Functions," University of Bahrain, Electrical and Electronics Department, Bahrain, Oct. 2013. [Online]. Available: http://www.al-roomi.org/cv/publications