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| author | Harpreet | 2015-12-22 14:51:05 +0530 |
|---|---|---|
| committer | Harpreet | 2015-12-22 14:51:05 +0530 |
| commit | 79583a44468943fad22ba1de2dd25dd86f7be167 (patch) | |
| tree | 54db759a8f856424f0c2ebd7f5306ffb881afdac /macros/lsqlin.sci | |
| parent | e12c133c99beee5a8dd04d4f6e8c2d5e07148408 (diff) | |
| download | FOSSEE-Optimization-toolbox-79583a44468943fad22ba1de2dd25dd86f7be167.tar.gz FOSSEE-Optimization-toolbox-79583a44468943fad22ba1de2dd25dd86f7be167.tar.bz2 FOSSEE-Optimization-toolbox-79583a44468943fad22ba1de2dd25dd86f7be167.zip | |
Bugs by prof fixed 2
Diffstat (limited to 'macros/lsqlin.sci')
| -rw-r--r-- | macros/lsqlin.sci | 25 |
1 files changed, 13 insertions, 12 deletions
diff --git a/macros/lsqlin.sci b/macros/lsqlin.sci index 4a5fa2d..1dc1fd5 100644 --- a/macros/lsqlin.sci +++ b/macros/lsqlin.sci @@ -14,11 +14,11 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin) // Solves a linear quadratic problem. // // Calling Sequence - // x = lsqlin(C,d,A,b) - // x = lsqlin(C,d,A,b,Aeq,beq) - // x = lsqlin(C,d,A,b,Aeq,beq,lb,ub) - // x = lsqlin(C,d,A,b,Aeq,beq,lb,ub,x0) - // x = lsqlin(C,d,A,b,Aeq,beq,lb,ub,x0,param) + // xopt = lsqlin(C,d,A,b) + // xopt = lsqlin(C,d,A,b,Aeq,beq) + // xopt = lsqlin(C,d,A,b,Aeq,beq,lb,ub) + // xopt = lsqlin(C,d,A,b,Aeq,beq,lb,ub,x0) + // xopt = lsqlin(C,d,A,b,Aeq,beq,lb,ub,x0,param) // [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin( ... ) // // Parameters @@ -36,8 +36,8 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin) // resnorm : a double, objective value returned as the scalar value norm(C*x-d)^2. // residual : a vector of doubles, solution residuals returned as the vector C*x-d. // exitflag : Integer identifying the reason the algorithm terminated. - // output : Structure containing information about the optimization. - // lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type). + // output : Structure containing information about the optimization. Right now it contains number of iteration. + // lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints. // // Description // Search the minimum of a constrained linear least square problem specified by : @@ -46,13 +46,13 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin) // \begin{eqnarray} // &\mbox{min}_{x} // & 1/2||C*x - d||_2^2 \\ - // & \text{subject to} & A.x \leq b \\ - // & & Aeq.x \leq beq \\ + // & \text{subject to} & A*x \leq b \\ + // & & Aeq*x = beq \\ // & & lb \leq x \leq ub \\ // \end{eqnarray} // </latex> // - // We are calling IPOpt for solving the linear least square problem, IPOpt is a library written in C++. The code has been written by Andreas Wächter and Carl Laird. + // We are calling IPOpt for solving the linear least square problem, IPOpt is a library written in C++. // // Examples // //A simple linear least square example @@ -73,8 +73,10 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin) // 0.2026 // 0.6721]; // [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin(C,d,A,b) + // // Press ENTER to continue // - // Examples + // Examples + // //A basic example for equality, inequality and bounds // C = [0.9501 0.7620 0.6153 0.4057 // 0.2311 0.4564 0.7919 0.9354 // 0.6068 0.0185 0.9218 0.9169 @@ -96,7 +98,6 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin) // lb = -0.1*ones(4,1); // ub = 2*ones(4,1); // [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin(C,d,A,b,Aeq,beq,lb,ub) - // // Authors // Harpreet Singh |