Parameters
- nbVar : -
a 1 x 1 matrix of doubles, number of variables
+ a double, number of variables
- nbCon : -
a 1 x 1 matrix of doubles, number of constraints
+ a double, number of constraints
- Q : -
a n x n symmetric matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.
+ a symmetric matrix of doubles, represents coefficients of quadratic in the quadratic problem.
- p : -
a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem
+ a vector of doubles, represents coefficients of linear in the quadratic problem
- LB : -
a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables.
+ a vector of doubles, contains lower bounds of the variables.
- UB : -
a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables.
+ a vector of doubles, where n is number of variables, contains upper bounds of the variables.
- conMatrix : -
a m x n matrix of doubles, where n is number of variables and m is number of constraints, contains matrix representing the constraint matrix
+ a matrix of doubles, contains matrix representing the constraint matrix
- conLB : -
a m x 1 matrix of doubles, where m is number of constraints, contains lower bounds of the constraints.
+ a vector of doubles, contains lower bounds of the constraints.
- conUB : -
a m x 1 matrix of doubles, where m is number of constraints, contains upper bounds of the constraints.
+ a vector of doubles, contains upper bounds of the constraints.
- x0 : -
a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables.
+ a vector of doubles, contains initial guess of variables.
- param :
a list containing the the parameters to be set.
- xopt : -
a 1xn matrix of doubles, the computed solution of the optimization problem.
+ a vector of doubles, the computed solution of the optimization problem.
- fopt : -
a 1x1 matrix of doubles, the function value at x.
+ a double, the function value at x.
- exitflag :
Integer identifying the reason the algorithm terminated.
- output :
diff --git a/help/en_US/scilab_en_US_help/qpipoptmat.html b/help/en_US/scilab_en_US_help/qpipoptmat.html
index 5e7518e..a9f97aa 100644
--- a/help/en_US/scilab_en_US_help/qpipoptmat.html
+++ b/help/en_US/scilab_en_US_help/qpipoptmat.html
@@ -47,29 +47,29 @@
Parameters
- H : -
a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.
+ a vector of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.
- f : -
a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem
+ a vector of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem
- A : -
a m x n matrix of doubles, represents the linear coefficients in the inequality constraints
+ a vector of doubles, represents the linear coefficients in the inequality constraints
- b : -
a column vector of doubles, represents the linear coefficients in the inequality constraints
+ a vector of doubles, represents the linear coefficients in the inequality constraints
- Aeq : -
a meq x n matrix of doubles, represents the linear coefficients in the equality constraints
+ a matrix of doubles, represents the linear coefficients in the equality constraints
- beq :
a vector of doubles, represents the linear coefficients in the equality constraints
- LB : -
a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables.
+ a vector of doubles, where n is number of variables, contains lower bounds of the variables.
- UB : -
a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables.
+ a vector of doubles, where n is number of variables, contains upper bounds of the variables.
- x0 : -
a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables.
+ a vector of doubles, contains initial guess of variables.
- param :
a list containing the the parameters to be set.
- xopt : -
a nx1 matrix of doubles, the computed solution of the optimization problem.
+ a vector of doubles, the computed solution of the optimization problem.
- fopt : -
a 1x1 matrix of doubles, the function value at x.
+ a double, the function value at x.
- exitflag :
Integer identifying the reason the algorithm terminated.
- output :
@@ -100,7 +100,7 @@ find the minimum of f(x) such that
param = list("MaxIter", 300, "CpuTime", 100);
//and minimize 0.5*x'*Q*x + p'*x with
f=[1; 2; 3; 4; 5; 6]; H=eye(6,6);
-[xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param);
+[xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param)
clear H f A b Aeq beq lb ub;
