Constraint violation at a point
Check whether a point satisfies a constraint.
Set up optimization variables and two constraints.
x = optimvar('x'); y = optimvar('y'); cons = x + y <= 2; cons2 = x + y/4 <= 1;
Check whether the point x = 0
, y = 3
satisfies the constraint named cons
. A point is feasible when its infeasibility is zero.
pt.x = 0; pt.y = 3; infeas = infeasibility(cons,pt)
infeas = 1
The point is not feasible with respect to this constraint.
Check the feasibility with respect to the other constraint.
infeas = infeasibility(cons2,pt)
infeas = 0
The point is feasible with respect to this constraint.
Check whether a point satisfies a constraint that has multiple conditions.
Set up an optimization variable and a vector of constraints.
x = optimvar('x',3,2);
cons = sum(x,2) <= [1;3;2];
Check whether the point pt.x = [1,-1;2,3;3,-1]
satisfies these constraints.
pt.x = [1,-1;2,3;3,-1]; infeas = infeasibility(cons,pt)
infeas = 3×1
0
2
0
The point is not feasible with respect to the second constraint.
constr
— Optimization constraintOptimizationEquality
object | OptimizationInequality
object | OptimizationConstraint
objectOptimization constraint, specified as an OptimizationEquality
object, OptimizationInequality
object, or OptimizationConstraint
object. constr
can represent a
single constraint or an array of constraints.
Example: constr = x + y <= 1
is a single constraint when
x
and y
are scalar variables.
Example: constr = sum(x) == 1
is an array of constraints when
x
is an array of two or more dimensions.
pt
— Point to evaluatePoint to evaluate, specified as a structure with field names that match
the optimization variable names, for optimization variables in the
constraint. The size of each field in pt
must match the
size of the corresponding optimization variable.
Example: pt.x = 5*eye(3)
Data Types: struct
infeas
— Infeasibility of constraintInfeasibility of constraint, returned as a real array. Each zero entry
represents a feasible constraint, and each positive entry represents an
infeasible constraint. The size of infeas
is the same as
the size of the constraint constr
. For an example of
nonscalar infeas
, see Compute Multiple Constraint Violations.
The problem-based approach does not support complex values in an objective function, nonlinear equalities, or nonlinear inequalities. If a function calculation has a complex value, even as an intermediate value, the final result can be incorrect.
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