% Prepared by Jane J. Liang. Email: liangjing@pmail.ntu.edu.sg February 20, 2005.
benchmark_func.m is the main function for these minimization problems
f=benchmark_func(x,func_num)
x is the variable, f is the function value, func_num is the function num,
data files save the necessary information.
func_plot.m is used to plot the 2-D function map
25 functions in all, from 1 to 25, are
Unimodal Functions (5):
1. Shifted Sphere Function Bounds[-100,100] f_bias=-450
2. Shifted Schwefel's Problem 1.2 Bounds[-100,100] f_bias=-450
3. Shifted Rotated High Conditioned Elliptic Function Bounds[-100,100] f_bias=-450
4. Shifted Schwefel's Problem 1.2 with Noise in Fitness Bounds[-100,100] f_bias=-450
5. Schwefel's Problem 2.6 with Global Optimum on Bounds Bounds[-100,100] f_bias=-310
Multimodal Functions (20):
Basic Functions (7):
6. Shifted Rosenbrock's Function Bounds[-100,100] f_bias=390
7. Shifted Rotated Griewank's Function without Bounds Intilization Range [0, 600] f_bias=-180
8. Shifted Rotated Ackley's with Global Optimum on Bounds Bounds[-32,32] f_bias=-140
9. Shifted Rastrigin's Function Bounds[-5,5] f_bias=-330
10. Shifted Rotated Rastrigin's Function Bounds[-5,5] f_bias=-330
11. Shifted Rotated Weierstrass Function Bounds[-0.5,0.5] f_bias=90
12. Schwefel's Problem 2.13 Bounds[-100,100] f_bias=-460
Expanded Functions (2):
13. Expanded Extended Griewank's + Rosenbrock's (F8F2) Bounds[-3,1] f_bias=-130
14. Expanded Rotated Extended Scaffe's F6 Bounds[-100,100] f_bias=-300
Hybrid Composition Functions (11):
15. Hybrid Composition Function 1 Bounds[-5,5] f_bias= 120
16. Rotated Hybrid Comp. Fn 1 Bounds[-5,5] f_bias= 120
17. Rotated Hybrid Comp. Fn 1 with Noise in Fitness Bounds[-5,5] f_bias= 120
18. Rotated Hybrid Comp. Fn 2 Bounds[-5,5] f_bias=10
19. Rotated Hybrid Comp. Fn 2 with Narrow Global Optimal Basin Bounds[-5,5]] f_bias=10
20. Rotated Hybrid Comp. Fn 2 with the Global Optimum on Bounds Bounds[-5,5] f_bias=10
21. Rotated Hybrid Comp. Fn 3 Bounds[-5,5] f_bias=360
22. Rotated Hybrid Comp. Fn 3 with High Condition Number Matrix Bounds[-5,5] f_bias=360
23. Non-Continuous Rotated Hybrid Comp. Fn 3 Bounds[-5,5] f_bias=360
24. Rotated Hybrid Comp. Fn 4 Bounds[-5,5] f_bias=260
25. Rotated Hybrid Comp. Fn 4 without Bounds Intilization Range[-2,5] f_bias=260
***Please note:
When you use the test function, remember to set a global variable initial_flag, and make
sure initial_flag=0 before each search.
For details of the test functions, please read intro-2-functions.doc file
%~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~%
Files:
%~~~~~~~~~~~~~~~%
Matlab *.m files:
%~~~~~~~~~~~~~~~%
benchmark_func.m
%benchmark_func.m is the main function with all the minimization problems
%f=benchmark_func(x,func_num)
%x is the variable, f is the function value, func_num is the function number (1 to 25),
func_plot.m
%used to plot the 2-D function map
%~~~~~~~~~~~~~~~%
Matlab *.mat data files:
%~~~~~~~~~~~~~~~%
test_data.mat
% 10 points (50D each) & corresponding fitnesses given to assist verification for code translation.
% Variables:x1,x2,x3,....x25
% Corresponding Function Values: f1,f2,f3,....f25
***Notice, for function 4,17,24,25, since they have noise, please set noise to 0 (e.g setting 0.0*N(0,1)) before test.
fbias_data.mat
% contain a 1*25 vector f_bias which are the global optimal function values.
global_optima.mat
% all 25 global optimal points (25 x 100 matrix) for the 25 test functions,
% please note, function 5,8,20 set the global optima on the bounds, so the corresponding
% global optima are:
% if func_num==5,o(1:ceil(D/4))=-100;x(max(floor(0.75*D),1):D)=100;end
% if func_num==8,o(2.*[1:floor(D/2)]-1)=-32;end
% if func_num==20,o(1,2.*[1:floor(D/2)])=5;end
sphere_func_data.mat
schwefel_102_data.mat
high_cond_elliptic_rot_data.mat
elliptic_M_D2.mat
elliptic_M_D10.mat
elliptic_M_D30.mat
elliptic_M_D50.mat
schwefel_206_data.mat
rosenbrock_func_data.mat
griewank_func_data.mat
griewank_M_D2.mat
griewank_M_D10.mat
griewank_M_D30.mat
griewank_M_D50.mat
ackley_func_data.mat
ackley_M_D2.mat
ackley_M_D10.mat
ackley_M_D30.mat
ackley_M_D50.mat
rastrigin_func_data.mat
rastrigin_M_D2.mat
rastrigin_M_D10.mat
rastrigin_M_D30.mat
rastrigin_M_D50.mat
weierstrass_data.mat
weierstrass_M_D2.mat
weierstrass_M_D10.mat
weierstrass_M_D30.mat
weierstrass_M_D50.mat
schwefel_213_data.mat
EF8F2_func_data.mat
E_ScafferF6_func_data.mat
E_ScafferF6_M_D2.mat
E_ScafferF6_M_D10.mat
E_ScafferF6_M_D30.mat
E_ScafferF6_M_D50.mat
hybrid_func1_data.mat
hybrid_func1_M_D2.mat
hybrid_func1_M_D10.mat
hybrid_func1_M_D30.mat
hybrid_func1_M_D50.mat
hybrid_func2_data.mat
hybrid_func2_M_D2.mat
hybrid_func2_M_D10.mat
hybrid_func2_M_D30.mat
hybrid_func2_M_D50.mat
hybrid_func3_data.mat
hybrid_func3_M_D2.mat
hybrid_func3_M_D10.mat
hybrid_func3_M_D30.mat
hybrid_func3_M_D50.mat
hybrid_func4_data.mat
hybrid_func4_M_D2.mat
hybrid_func4_M_D10.mat
hybrid_func4_M_D30.mat
hybrid_func4_M_D50.mat
%%%%%%%%%%
PLEASE NOTE:
hybrid_func1_M_D......matrix data in matlab mat format contain a structure variable M,
and M.M1,M.M2...M.M10 are ten D*D matrix
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MATLAB优化算法测试函数 (135个子文件)
benchmark_mat.tar.gz 1.57MB
benchmark_func.m 28KB
benchmark_func.m 28KB
func_plot.m 2KB
func_plot.m 2KB
hybrid_func3_M_D50.mat 196KB
hybrid_func4_M_D50.mat 196KB
hybrid_func4_M_D50.mat 196KB
hybrid_func2_M_D50.mat 196KB
hybrid_func1_M_D50.mat 196KB
hybrid_func3_HM_D50.mat 196KB
hybrid_func1_M_D50.mat 196KB
hybrid_func3_HM_D50.mat 196KB
hybrid_func2_M_D50.mat 196KB
hybrid_func3_M_D50.mat 196KB
test_data.mat 102KB
test_data.mat 102KB
hybrid_func3_HM_D30.mat 71KB
hybrid_func4_M_D30.mat 71KB
hybrid_func3_M_D30.mat 71KB
hybrid_func4_M_D30.mat 71KB
hybrid_func3_M_D30.mat 71KB
hybrid_func1_M_D30.mat 71KB
hybrid_func1_M_D30.mat 71KB
hybrid_func2_M_D30.mat 71KB
hybrid_func3_HM_D30.mat 71KB
hybrid_func2_M_D30.mat 71KB
schwefel_213_data.mat 40KB
schwefel_213_data.mat 40KB
schwefel_206_data.mat 21KB
schwefel_206_data.mat 21KB
weierstrass_M_D50.mat 20KB
elliptic_M_D50.mat 20KB
griewank_M_D50.mat 20KB
ackley_M_D50.mat 20KB
rastrigin_M_D50.mat 20KB
elliptic_M_D50.mat 20KB
global_optima.mat 20KB
weierstrass_M_D50.mat 20KB
E_ScafferF6_M_D50.mat 20KB
rastrigin_M_D50.mat 20KB
global_optima.mat 20KB
E_ScafferF6_M_D50.mat 20KB
ackley_M_D50.mat 20KB
griewank_M_D50.mat 20KB
hybrid_func3_M_D10.mat 9KB
hybrid_func1_M_D10.mat 9KB
hybrid_func1_M_D10.mat 9KB
hybrid_func4_M_D10.mat 9KB
hybrid_func2_M_D10.mat 9KB
hybrid_func3_HM_D10.mat 9KB
hybrid_func2_M_D10.mat 9KB
hybrid_func3_HM_D10.mat 9KB
hybrid_func3_M_D10.mat 9KB
hybrid_func4_M_D10.mat 9KB
hybrid_func4_data.mat 8KB
hybrid_func2_data.mat 8KB
hybrid_func4_data.mat 8KB
hybrid_func3_data.mat 8KB
hybrid_func3_data.mat 8KB
hybrid_func1_data.mat 8KB
hybrid_func1_data.mat 8KB
hybrid_func2_data.mat 8KB
hybrid_func1_M_D2.mat 7KB
hybrid_func1_M_D2.mat 7KB
ackley_M_D30.mat 7KB
E_ScafferF6_M_D30.mat 7KB
E_ScafferF6_M_D30.mat 7KB
elliptic_M_D30.mat 7KB
ackley_M_D30.mat 7KB
rastrigin_M_D30.mat 7KB
weierstrass_M_D30.mat 7KB
elliptic_M_D30.mat 7KB
weierstrass_M_D30.mat 7KB
griewank_M_D30.mat 7KB
griewank_M_D30.mat 7KB
rastrigin_M_D30.mat 7KB
hybrid_func4_M_D2.mat 1KB
hybrid_func2_M_D2.mat 1KB
hybrid_func3_M_D2.mat 1KB
hybrid_func3_M_D2.mat 1KB
hybrid_func2_M_D2.mat 1KB
hybrid_func3_HM_D2.mat 1KB
hybrid_func4_M_D2.mat 1KB
hybrid_func3_HM_D2.mat 1KB
griewank_func_data.mat 984B
griewank_M_D10.mat 984B
E_ScafferF6_M_D10.mat 984B
EF8F2_func_data.mat 984B
E_ScafferF6_func_data.mat 984B
high_cond_elliptic_rot_data.mat 984B
E_ScafferF6_M_D10.mat 984B
griewank_M_D10.mat 984B
weierstrass_data.mat 984B
ackley_func_data.mat 984B
sphere_func_data.mat 984B
weierstrass_data.mat 984B
schwefel_102_data.mat 984B
rosenbrock_func_data.mat 984B
rosenbrock_func_data.mat 984B
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