DE-and-NSGA2
所属分类：matlab编程
开发工具：matlab
文件大小：1155KB
下载次数：45
上传日期：2014-11-21 09:33:51
上 传 者：
19910202132
说明： 这里面是我最近下载的所有的差分进化和NSGA2的代码，还有个很好用的NSGA2和DE的结合。
(There is all the difference in the evolution and NSGA2 I recently downloaded the code, there is a good use of a combination of NSGA2 and DE.)
文件列表:
DE and NSGA2 (0, 2014-11-21)
DE and NSGA2\(DE)MOEA-NSGA-II (0, 2014-11-21)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II (0, 2014-11-21)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\NSGA_2.pdf (373682, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\crowding_distance.m (1273, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\evaluate_objective.m (970, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\genetic_operator.asv (3324, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\genetic_operator.m (3324, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\genetic_operator2.asv (4224, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\genetic_operator2.m (4227, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\html (0, 2014-11-21)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\html\crowding_distance.html (5128, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\html\genetic_operator.html (10289, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\html\initialize_variables.html (4434, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\html\non_domination_sort_mod.html (11714, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\html\nsga_2.html (13753, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\html\replace_chromosome.html (6346, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\html\tournament_selection.html (6186, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\initialize_variables.asv (972, 2014-10-18)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\initialize_variables.m (991, 2014-10-17)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\non_domination_sort_mod.m (4116, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\nsga_2.m (5888, 2014-10-17)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\plot_objective.m (476, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\replace_chromosome.m (1977, 2011-05-09)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\solution.txt (27400, 2014-10-17)
DE and NSGA2\(DE)MOEA-NSGA-II\(DE)MOEA-NSGA-II\tournament_selection.m (1743, 2011-05-09)
DE and NSGA2\038097196NSGA2 (0, 2014-11-21)
DE and NSGA2\038097196NSGA2\NSGA2 (0, 2014-11-21)
DE and NSGA2\038097196NSGA2\NSGA2\NSGA-II (0, 2014-11-21)
DE and NSGA2\038097196NSGA2\NSGA2\NSGA-II\NSGA II(鼻祖).pdf (134157, 2006-03-19)
DE and NSGA2\038097196NSGA2\NSGA2\NSGA-II\evaluate_objective.m (2216, 2006-03-16)
DE and NSGA2\038097196NSGA2\NSGA2\NSGA-II\genetic_operator.m (5695, 2006-03-16)
DE and NSGA2\038097196NSGA2\NSGA2\NSGA-II\initialize_variables.m (2480, 2008-04-11)
DE and NSGA2\038097196NSGA2\NSGA2\NSGA-II\non_domination_sort_mod.m (7654, 2008-04-11)
DE and NSGA2\038097196NSGA2\NSGA2\NSGA-II\nsga_2.m (8127, 2012-04-24)
DE and NSGA2\038097196NSGA2\NSGA2\NSGA-II\objective_description_function.m (2200, 2006-03-19)
DE and NSGA2\038097196NSGA2\NSGA2\NSGA-II\replace_chromosome.m (2719, 2006-03-16)
DE and NSGA2\038097196NSGA2\NSGA2\NSGA-II\solution.txt (13000, 2012-04-24)
DE and NSGA2\038097196NSGA2\NSGA2\NSGA-II\tournament_selection.m (3627, 2006-03-16)
DE and NSGA2\1401823NSGA-II 少一个plot文件 (0, 2014-11-21)
... ...
From
Price, K., Storn, R., Lampinen, J.,
Differential Evolution - A Practical Approach to Global Optimization
Springer, 2005
The default problem in this directory (main directory) is
the Chebyshev problem. If any of the other problems
shall be treated, go to the appropriate subdirectory
and copy the files objfun.m, PlotIt.m, and Rundeopt.m
to the main directory.
The script file Rundeopt.m (Run DE optimization) is
the main control file in the MATLAB environment.
Plotting can be turned off by setting the variable
I_plotting=0 in rundeopt.m. Per default this variable
is set to 1.
Various ways of plotting have been used for the
different examples. Only the two-dimensional
problems allow an animated view how the population
evolves on the objective function surface. Other
problems may simply use a progress plot for the
objective function value. It is best to try the
different examples to see how plotting has been
used to monitor the optimization.
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