代码搜索:optimization

找到约 10,000 项符合「optimization」的源代码

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m ex1.m

% Chapter 2: Optimization with Matlab % Dr. P.Venkataraman % Example 1 (Sec 2.1- 2.2) % % graphical solution using matlab (two design variables) % the following script should allow the graphical
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m upperbound_nvar.m

% % Ch 5: Numerical Techniques - 1 D optimization % Optimzation with MATLAB, Section 5.4.1 % Generic Scanning Procedure - n Variables % copyright Dr. P.Venkataraman % % An m-file to bracket t
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m goldsection_nvar.m

% % Ch 5: Numerical Techniques - 1 D optimization % Optimzation with MATLAB, Section 5.4.1 % Golden Section Method - many variables % copyright (code) Dr. P.Venkataraman % % An m-file to appl
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m upperbound_nvar.m

% % Ch 5: Numerical Techniques - 1 D optimization % Optimzation with MATLAB, Section 5.4.1 % Generic Scanning Procedure - n Variables % copyright Dr. P.Venkataraman % % An m-file to bracket t
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m goldsection_nvar.m

% % Ch 5: Numerical Techniques - 1 D optimization % Optimzation with MATLAB, Section 5.4.1 % Golden Section Method - many variables % copyright (code) Dr. P.Venkataraman % % An m-file to appl
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c mt19937ar-cok.c

/* A C-program for MT19937, with initialization improved 2002/2/10. Coded by Takuji Nishimura and Makoto Matsumoto. This is a faster version by taking Shawn Cokus's optimization, Matthe B
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txt readme.txt

README FOR THE BNBGUI INSTALLATION To function BNB needs: Matlab 5.3 or newer Optimization Toolbox 2.0 the Courier-LD font (8 points, regular) Unzip BNB.zip to an empty directory that's i
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m nsga_2.m

function nsga_2(pop,gen) %% function nsga_2(pop,gen) % is a multi-objective optimization function where the input arguments are % pop - Population size % gen - Total number of generations %
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m f6_spiral_dyn.m

% f6_spiral_dyn.m % Schaffer's F6 function % commonly used to test optimization/global minimization problems % % This version moves the minimum about a Fermat Spiral % according to the equation:
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m nsga_2.m

function nsga_2(pop,gen) %% function nsga_2(pop,gen) % is a multi-objective optimization function where the input arguments are % pop - Population size % gen - Total number of generations %