Symphony Toolbox

//Find x in R^6 such that: + +conMatrix= [1,-1,1,0,3,1; +-1,0,-3,-4,5,6; +2,5,3,0,1,0 +0,1,0,1,2,-1; +-1,0,2,1,1,0]; +conLB=[1 2 3 -%inf -%inf]'; +conUB = [1 2 3 -1 2.5]'; +//with x between ci and cs: +lb=[-1000 -10000 0 -1000 -1000 -1000]; +ub=[10000 100 1.5 100 100 1000]; +//and minimize 0.5*x'*Q*x + p'*x with +p=[1;2;3;4;5;6]; Q=eye(6,6); +nbVar = 6; +nbCon = 5; +[xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)

//min. -8*x1 -16*x2 + x1^2 + 4* x2^2 +// such that +// x1 + x2 <= 5, +// x1 <= 3, +// x1 >= 0, +// x2 >= 0 +conMatrix= [1 1]; +conLB=[-%inf]; +conUB = [5]; +//with x between ci and cs: +lb=[0,0]; +ub=[3,%inf]; +//and minimize 0.5*x'*Q*x + p'*x with +p=[-8,-16]; +Q=[1,0;0,4]; +nbVar = 2; +nbCon = 1; +[xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)

- << Symphony Toolbox + << qpipopt	@@ -40,7 +40,7 @@ xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB) xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense) xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options) -[xopt,fopt,iter] = symphony( ... ) +[xopt,fopt,status,output] = symphony( ... ) Parameters nbVar : @@ -69,15 +69,16 @@ a 1xn matrix of doubles, the computed solution of the optimization problem fopt : a 1x1 matrix of doubles, the function value at x - iter : - a 1x1 matrix of doubles, contains the number od iterations done by symphony + status : + status flag from symphony + output : + The output data structure contains detailed informations about the optimization process. Description Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by : find the minimum or maximum of f(x) such that - - + We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by Ted Ralphs, Menal Guzelsoy and Ashutosh Mahajan. Examples @@ -196,7 +197,7 @@ find the minimum or maximum of f(x) such that
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- << Symphony Toolbox + << qpipopt	diff --git a/help/en_US/scilab_en_US_help/symphony_mat.html b/help/en_US/scilab_en_US_help/symphony_mat.html index d87fb63..cc337f4 100644 --- a/help/en_US/scilab_en_US_help/symphony_mat.html +++ b/help/en_US/scilab_en_US_help/symphony_mat.html @@ -41,7 +41,7 @@ xopt = symphony_mat(f,intcon,A,b,Aeq,beq) xopt = symphony_mat(f,intcon,A,b,Aeq,beq,lb,ub) xopt = symphony_mat(f,intcon,A,b,Aeq,beq,lb,ub,options) -[xopt,fopt,iter] = symphony_mat( ... ) +[xopt,fopt,status,output] = symphony_mat( ... ) Parameters f : @@ -66,13 +66,14 @@ a 1xn matrix of doubles, the computed solution of the optimization problem fopt : a 1x1 matrix of doubles, the function value at x - iter : - a 1x1 matrix of doubles, contains the number od iterations done by symphony + output : + The output data structure contains detailed informations about the optimization process. Description Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by : find the minimum or maximum of f(x) such that - + + We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by Ted Ralphs, Menal Guzelsoy and Ashutosh Mahajan. Examples diff --git a/help/en_US/symphony.xml b/help/en_US/symphony.xml index f71920f..86ad4b7 100644 --- a/help/en_US/symphony.xml +++ b/help/en_US/symphony.xml @@ -27,7 +27,7 @@ xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB) xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense) xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options) - [xopt,fopt,iter] = symphony( ... ) + [xopt,fopt,status,output] = symphony( ... ) @@ -61,8 +61,10 @@ a 1xn matrix of doubles, the computed solution of the optimization problem fopt : a 1x1 matrix of doubles, the function value at x - iter : - a 1x1 matrix of doubles, contains the number od iterations done by symphony + status : + status flag from symphony + output : + The output data structure contains detailed informations about the optimization process. @@ -77,14 +79,13 @@ find the minimum or maximum of f(x) such that \begin{eqnarray} &\mbox{min}_{x} & f(x) \\ -& \text{subject to} & conLB \geq C(x) \leq conUB \\ -& & lb \geq x \leq ub \\ +& \text{subject to} & conLB \leq C(x) \leq conUB \\ +& & lb \leq x \leq ub \\ \end{eqnarray} - - +We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by Ted Ralphs, Menal Guzelsoy and Ashutosh Mahajan. diff --git a/help/en_US/symphony_mat.xml b/help/en_US/symphony_mat.xml index ef379a1..4f6e9c9 100644 --- a/help/en_US/symphony_mat.xml +++ b/help/en_US/symphony_mat.xml @@ -28,7 +28,7 @@ xopt = symphony_mat(f,intcon,A,b,Aeq,beq) xopt = symphony_mat(f,intcon,A,b,Aeq,beq,lb,ub) xopt = symphony_mat(f,intcon,A,b,Aeq,beq,lb,ub,options) - [xopt,fopt,iter] = symphony_mat( ... ) + [xopt,fopt,status,output] = symphony_mat( ... ) @@ -58,8 +58,8 @@ a 1xn matrix of doubles, the computed solution of the optimization problem fopt : a 1x1 matrix of doubles, the function value at x - iter : - a 1x1 matrix of doubles, contains the number od iterations done by symphony + output : + The output data structure contains detailed informations about the optimization process. @@ -72,16 +72,17 @@ find the minimum or maximum of f(x) such that \begin{eqnarray} -\mbox{min}_{x} & f(x) \\ -\mbox{subject to} & c(x) \leq 0 \\ -& c_{eq}(x) = 0 \\ -& Ax \leq b \\ -& A_{eq} x = b_{eq} \\ -& lb \leq x \leq ub +&\mbox{min}_{x} +& f(x) \\ +& \text{subject to} & conLB \leq C(x) \leq conUB \\ +& & lb \leq x \leq ub \\ \end{eqnarray} +We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by Ted Ralphs, Menal Guzelsoy and Ashutosh Mahajan. + + -- cgit

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+ << Symphony Toolbox + +	+ Symphony Toolbox + +	+ symphony >> + +

qpipopt

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