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GaussianMultivariate_OfflineHPProtein

PURPOSE ^

EXAMPLE 12: Multivariate Gaussian EDA for the Offline HP Model continuous function

SYNOPSIS ^

This is a script file.

DESCRIPTION ^

 EXAMPLE 12:  Multivariate Gaussian EDA for  the Offline HP Model continuous function 
 For reference on the Offline HP model see:
-- H. P. Hsu, V. Mehra and  P. Grassberger (2003)  Structure optimization in an off-lattice protein model.
-- Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Sep;68(3 Pt 2):037703. Epub 2003 Sep 30. 
-- http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=PLEEE8000068000003037703000001&idtype=cvips&gifs=yes

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001  % EXAMPLE 12:  Multivariate Gaussian EDA for  the Offline HP Model continuous function
0002  % For reference on the Offline HP model see:
0003  %-- H. P. Hsu, V. Mehra and  P. Grassberger (2003)  Structure optimization in an off-lattice protein model.
0004  %-- Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Sep;68(3 Pt 2):037703. Epub 2003 Sep 30.
0005  %-- http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=PLEEE8000068000003037703000001&idtype=cvips&gifs=yes
0006   
0007  Fibbonacci_n = 7; % Fibbonacci_n: Value n for the construction of the Fibbonacci sequence. NumbVar = F(n)
0008  global HPInitConf;
0009  HPInitConf = CreateFibbInitConf(Fibbonacci_n); % HP Fibbonacci configuration
0010  NumbVar = size(HPInitConf,2);
0011  PopSize = 100; 
0012  F = 'EvaluateOffHPProtein';
0013  cache  = [0,0,0,0,0]; Card = [zeros(1,NumbVar);2*pi*ones(1,NumbVar)];
0014  edaparams{1} = {'learning_method','LearnGaussianFullModel',{}};
0015  edaparams{2} = {'sampling_method','SampleGaussianFullModel',{PopSize,1}};
0016  edaparams{3} = {'replacement_method','best_elitism',{'ParetoRank_ordering'}};
0017  selparams(1:2) = {0.5,'ParetoRank_ordering'};
0018  edaparams{4} = {'selection_method','truncation_selection',selparams};
0019  edaparams{5} = {'stop_cond_method','max_gen',{500}};
0020  %edaparams{6} = {'local_opt_method','local_search_OffHP',{}};
0021  %edaparams{6} = {'local_opt_method','CMAS_search_OffHP',{}};
0022  edaparams{6} = {'local_opt_method','Greedy_search_OffHP',{50}};
0023  %edaparams{7} = {'repairing_method','SetWithinBounds_repairing',{}};
0024  [AllStat,Cache]=RunEDA(PopSize,NumbVar,F,Card,cache,edaparams) 
0025  % To draw the resulting solution use function OffPrintProtein(vector),
0026  % where vector is the best solution found.

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