cec09

所属分类:matlab编程
开发工具:matlab
文件大小:11332KB
下载次数:43
上传日期:2013-11-07 08:56:20
上 传 者albertxfq
说明:  智能优化算法标准测试函数,cec09动态问题测试函数
(Benchmark Generator for CEC 2009 Competition on Dynamic Optimization)

文件列表:
CPP (0, 2008-09-18)
CPP\linux (0, 2008-09-18)
CPP\linux\DBG (0, 2008-09-21)
CPP\linux\DBG\Composition_DBG.cpp (10388, 2008-09-21)
CPP\linux\DBG\Composition_DBG.h (2483, 2008-08-13)
CPP\linux\DBG\extreal.cpp (2645, 2008-08-09)
CPP\linux\DBG\extreal.h (1003, 2008-08-09)
CPP\linux\DBG\General_DBG.cpp (3062, 2008-09-18)
CPP\linux\DBG\General_DBG.h (2243, 2008-10-29)
CPP\linux\DBG\Global.cpp (1586, 2008-09-24)
CPP\linux\DBG\Global.h (4453, 2008-08-29)
CPP\linux\DBG\include.h (8136, 2008-08-09)
CPP\linux\DBG\main (702683, 2008-09-18)
CPP\linux\DBG\main.cpp (7563, 2008-09-24)
CPP\linux\DBG\makefile (365, 2008-08-13)
CPP\linux\DBG\Matrix.cpp (1486, 2008-08-11)
CPP\linux\DBG\Matrix.h (811, 2008-08-11)
CPP\linux\DBG\myexcept.cpp (13953, 2008-08-09)
CPP\linux\DBG\myexcept.h (12455, 2008-08-09)
CPP\linux\DBG\newran.h (26853, 2008-08-11)
CPP\linux\DBG\newran1.cpp (24440, 2008-08-11)
CPP\linux\DBG\newran2.cpp (39932, 2008-08-11)
CPP\linux\DBG\Real_DBG.cpp (6661, 2008-09-18)
CPP\linux\DBG\Real_DBG.h (3680, 2008-08-13)
CPP\linux\DBG\Rotation_DBG.cpp (5542, 2008-09-09)
CPP\linux\DBG\Rotation_DBG.h (1649, 2008-08-14)
CPP\linux\DBG\simpstr.cpp (5486, 2008-08-09)
CPP\linux\DBG\simpstr.h (1559, 2008-08-09)
CPP\linux\PSO (0, 2008-09-21)
CPP\linux\PSO\Composition_DBG.cpp (10388, 2008-09-21)
CPP\linux\PSO\Composition_DBG.h (2483, 2008-08-13)
CPP\linux\PSO\extreal.cpp (2645, 2008-03-20)
CPP\linux\PSO\extreal.h (1003, 2008-03-20)
CPP\linux\PSO\General_DBG.cpp (3062, 2008-09-18)
CPP\linux\PSO\General_DBG.h (2243, 2008-10-29)
CPP\linux\PSO\Global.cpp (1661, 2008-09-24)
CPP\linux\PSO\Global.h (4716, 2008-08-29)
CPP\linux\PSO\include.h (8136, 2005-09-29)
CPP\linux\PSO\main (837639, 2008-09-18)
... ...

Generalized Dynamic Benchmark Generator for CEC'2009 Competition on Dynamic Optimization The programs are written in MATLAB (ver. 7.0.4). Last Modification: October 25, 2008 For enquiries, please email to YuLing@ntu.edu.sg. ===============Contents=============== DBG.m DynamicChange.m h_original.mat w_original.mat x_peaks_original.mat phi.mat composition_func_data.mat composition_func_M_D5.mat composition_func_M_D6.mat composition_func_M_D7.mat composition_func_M_D8.mat composition_func_M_D9.mat composition_func_M_D10.mat composition_func_M_D11.mat composition_func_M_D12.mat composition_func_M_D13.mat composition_func_M_D14.mat composition_func_M_D15.mat performance.m scoring_Info.mat readme.txt Please put all the files in the same folder. The main function is DBG.m. The format is "[f,x,FES,dim] = DBG(x,fun_num,change_instance,FES,num_runs,dim,fun_opts)". Please see the comments in the program for notations of inputs and outputs. Always let FES=0 in the first place, so that neccessary initialization can be performed. Similarly, let num_runs=1 first. In the process of the implementation, the following data will be recorded for use afterwards: x_peaks (peak positions), h (heights of peaks), w (widths of peaks), theta (rotation angle), dim_change (sign of dimension change increment), FES_last_change (number of performed function evaluations at last change), and change_count (count of changes) for F1; o (optimal positions), h (parameter H in the formula), theta (rotation angle), dim_change (sign of dimension change increment), FES_last_change (number of performed function evaluations at last change), and change_count (count of changes) for F2~F6. The algorithm should detect the non-dimensional change by itself, therefore, it is not allowed to make use of the above information for the detection of a non-dimensional change. On the other hand, the algorithm is informed when a dimensional change occurs by the output value "dim". P.S. As the function continues to call external files, running a few examples at the same time will cause interference. To avoid this limitation, users may consider specify the names of the memory files for every run of the algorithm or put them in different folders. Performance marking is done by the function "performance". After all the runs of the 49 test cases, the entire vector "marks" will be formed in the file "scoring_Info.mat". To get the total score, just add all the components in the vector "marks".

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