quadprog

Quadratic programming.

📝Syntax

x = quadprog(H, f)
[x, fval, exitflag, output, lambda] = quadprog(H, f, A, b, Aeq, beq, lb, ub, x0, options)
x = quadprog(problem)

📥Input Arguments

Parameter	Description
H, f	quadratic and linear objective terms.
A, b, Aeq, beq	linear inequality and equality constraints.
lb, ub	lower and upper bounds.

📤Output Arguments

Parameter	Description
x	estimated solution.
fval	objective value.
lambda	constraint multiplier structure.

📄Description

quadprog solves dense convex quadratic programs with linear constraints and bounds using an active-set strategy.

The problem-structure form accepts H, f, Aineq or A, bineq or b, Aeq, beq, lb, ub, x0 and options. Problem-based quadratic expressions compiled by prob2struct are routed to quadprog.

💡Examples

H = [2 0; 0 2];
f = [-2; -4];
lb = [0; 0];
[x, fval] = quadprog(H, f, [], [], [], [], lb, [])

y = optimvar('y', 2, 1);
prob = optimproblem('Objective', (y(1) - 1)^2 + (y(2) + 3)^2);
[sol, fval] = solve(prob, struct('y', [0; 0]));
sol.y

🔗See Also

lsqnonneg optimoptions

Used Functions

optimoptions prob2struct

📚Bibliography

P. E. Gill, W. Murray and M. H. Wright, Practical Optimization, Academic Press, 1981. J. Nocedal and S. J. Wright, Numerical Optimization, Springer, 2006.

🕔Version History

Version	Description
2.0.0	initial version

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