Solve nonnegative least squares problems.
Solve nonnegative least squares problems.
x = cplexlsqnonneglin(C, d) x = cplexlsqnonneglin(C, d, Aineq, bineq) x = cplexlsqnonneglin(C, d, Aineq, bineq, Aeq, beq) x = cplexlsqnonneglin(C, d, Aineq, bineq, Aeq, beq, x0) x = cplexlsqnonneglin(C, d, Aineq, bineq, Aeq, beq, x0, options) x = cplexlsqnonneglin(problem) [x, resnorm] = cplexlsqnonneglin(...) [x, resnorm, residual] = cplexlsqnonneglin(...) [x, resnorm, residual, exitflag] = cplexlsqnonneglin(...) [x, resnorm, residual, exitflag, output] = cplexlsqnonneglin(...) [x, resnorm, residual, exitflag, output, lambda] = cplexlsqnonneglin(...)
Finds the minimum of a problem specified by
min min norm(C*x-d)^2
st. Aineq*x <= bineq
Aeq*x = beq
x >= 0
problem | Structure containing the following fields | |
C | Double matrix for objective function | |
d | Double column vector for objective function | |
Aineq | Double matrix for linear inequality constraints | |
bineq | Double column vector for linear inequality constraints | |
Aeq | Double matrix for linear equality constraints | |
beq | Double column vector for linear equality constraints | |
x0 | Double column vector of initial point of x | |
options | Options structure created with cplexoptimset |
x | Solution found by the optimization function. If exitflag > 0, then x is a solution; otherwise, x is the value of the optimization routine when it terminated prematurely. | |
resnorm | Value of the objective function at the solution x | |
residual | Residual at the solution | |
exitflag | Integer identifying the reason the optimization algorithm terminated | |
output | Structure containing information about the optimization. The fields of the structure are: iterations: Number of iterations algorithm: Optimization algorithm used message: Exit message time: Execution time of the algorithm cplexstatus: Status code of the solution cplexstatusstring: Status string of the solution | |
lambda | Structure containing the Lagrange multipliers at the solution x (separated by constraint type). This is only available for problems that do not contain quadratic constraints. See cplexqp() for details. |
x = cplexlsqnonneglin(C, d) solves the least squares problem min norm(C*x-d)^2 such that x >= 0.x = cplexlsqnonneglin(C, d, Aineq, bineq) solves the preceding problem with the additional inequality constraints Aineq*x <= bineq.
x = cplexlsqnonneglin(C, d, Aineq, bineq, Aeq, beq) solves the preceding problem with the additional equality constraints Aeq*x = beq. If no inequalities exist, set Aineq=[] and bineq=[].
x = cplexlsqnonneglin(C, d, Aineq, bineq, Aeq, beq, x0) sets the starting point for the algorithm to x0. If no equalities exist, set Aeq=[] and beq=[].
x = cplexlsqnonneglin(C, d, Aineq, bineq, Aeq, beq, x0, options) minimizes with the default optimization options replaced by values in the structure options, which can be created using the function cplexoptimset. If you do not want to give an initial point, set x0=[].
x = cplexlsqnonneglin(problem) where problem is a structure.
[x,resnorm] = cplexlsqnonneglin(...) returns the value of the objective function at the solution x: resnorm = norm(C*x-d)^2.
[x,resnorm,residual] = cplexlsqnonneglin(...) returns the residual at the solution: C*x-d.
[x,resnorm,residual,exitflag] = cplexlsqnonneglin(...) returns a value exitflag that describes the exit condition of cplexlsqnonneglin.
[x,resnorm,residual,exitflag,output] = cplexlsqnonneglin(...) returns a structure output that contains information about the optimization.
[x,resnorm,residual,exitflag,output,lambda] = cplexlsqnonneglin(...) returns a structure lambda whose fields contain the Lagrange multipliers at the solution x.
See cplexmiqcp for a description of exitflag values.
See also cplexoptimset.