Stochastic radial basis function algorithm for global optimization in matlab

The following Matlab project contains the source code and Matlab examples used for stochastic radial basis function algorithm for global optimization. The Stochastic Radial Basis Function Algorithm aims at solving computationally expensive continuous black-box global optimization problems with box constraints.

The source code and files included in this project are listed in the project files section, please make sure whether the listed source code meet your needs there.

Project Files: 

File NameSize
license.txt 1564
ComputeRBF.m 1783
datainput_Ackley15.m 763
datainput_Ackley30.m 766
datainput_Branin.m 784
datainput_DixonPrice15.m 779
datainput_hartman3.m 1105
datainput_hartman6.m 1222
datainput_Levy20.m 827
datainput_Michalewicz25.m 757
datainput_Powell24.m 994
datainput_Rastrigin12.m 767
datainput_Rastrigin30.m 809
datainput_Rosenbrock10.m 754
datainput_Rosenbrock20.m 780
datainput_Schoen_10_4_3.m 11648
datainput_Schoen_17_2_5.m 9682
datainput_Shekel10.m 1161
datainput_Shekel5.m 1166
datainput_Shekel7.m 1149
datainput_Shubert.m 768
datainput_Sphere27.m 725
datainput_Zakharov11.m 782
InitialRBFMatrices.m 2155
LocalStochRBFrestart.m 3774
LocalStochRBFstop.m 9948
Minimize_Merit_Function.m 6267
phi.m 691
SLHDstandard.m 1032
StochasticRBF.m 8139
StochasticRBF.m~ 7924
TestLocalStochRBFrestart.m 2533
_Manual.pdf 100146

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