This is an example to test GDBG system using particle swarm optimization algorithm (PSO), 
There are total 104 specific test cases in this example followed the instruction from CEC'09 competition.

******************Results format****************************
The results of each test case are saved in the following files:
"*_fit.txt" :  the average fitness of the best individual in each generation       
"*_relative.txt" : the relative value of the best individual to the global optima in each generation
"*_statistic.txt": final result of average best, average worst, average mean and STD for one test case

The format of "*" like:
F1_T2_D30_peak10
F1_T1_D30_peak50
......
F7_T7_D10_peak10

F1-F7: problem F1-F7;
T1-T7: changetype T1-T7;
D10, D30: the number of dimension is 10 or 30 (Only for T1-T6, the dimension of T7 is changed bewteen 10 and 50); 
peak10, peak50: number of peaks or basic funtion is 10 or 50.

"performance.txt": The overal performance for proposed algorithm. The mark of each test case obtained by 
the algorithm is saved in this file, and the last line gives the overall mark of the algorithm's performance
on the 104 test cases. 

The format of "performance.txt" is like:
problem change_type avg_r marking
1 1 0.204839 0.0105
1 1 0.209069 0.0105
..........
7 7 0.0455676 0.012
total mark: 7.71138
 
**************************************************************
Notes: 

1. The following files are used to generate rundom numbers of different distribution:
"include.h", "extreal.h", " extreal.cpp", "myexcep.h", "myexcept.cpp", "newran.h"
, "newran1.cpp", " newran2.cpp",  "simpstr.h", " simpstr.cpp"

2. If you have any problem about the program, please contact with Mr. Changhe Li at cl160@le.ac.uk
