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package org.apache.commons.math3.optimization.linear;
import java.util.Collection;
import org.apache.commons.math3.exception.MathIllegalStateException;
import org.apache.commons.math3.optimization.GoalType;
import org.apache.commons.math3.optimization.PointValuePair;
This interface represents an optimization algorithm for linear problems.
Optimization algorithms find the input point set that either
maximize or minimize an objective function. In the linear case the form of the function is restricted to
c1x1 + ... cnxn = v
and there may be linear constraints too, of one of the forms:
- c1x1 + ... cnxn = v
- c1x1 + ... cnxn <= v
- c1x1 + ... cnxn >= v
- l1x1 + ... lnxn + lcst =
r1x1 + ... rnxn + rcst
- l1x1 + ... lnxn + lcst <=
r1x1 + ... rnxn + rcst
- l1x1 + ... lnxn + lcst >=
r1x1 + ... rnxn + rcst
where the ci, li or ri are the coefficients of
the constraints, the xi are the coordinates of the current point and
v is the value of the constraint.
Deprecated: As of 3.1 (to be removed in 4.0). Since: 2.0
/**
* This interface represents an optimization algorithm for linear problems.
* <p>Optimization algorithms find the input point set that either {@link GoalType
* maximize or minimize} an objective function. In the linear case the form of
* the function is restricted to
* <pre>
* c<sub>1</sub>x<sub>1</sub> + ... c<sub>n</sub>x<sub>n</sub> = v
* </pre>
* and there may be linear constraints too, of one of the forms:
* <ul>
* <li>c<sub>1</sub>x<sub>1</sub> + ... c<sub>n</sub>x<sub>n</sub> = v</li>
* <li>c<sub>1</sub>x<sub>1</sub> + ... c<sub>n</sub>x<sub>n</sub> <= v</li>
* <li>c<sub>1</sub>x<sub>1</sub> + ... c<sub>n</sub>x<sub>n</sub> >= v</li>
* <li>l<sub>1</sub>x<sub>1</sub> + ... l<sub>n</sub>x<sub>n</sub> + l<sub>cst</sub> =
* r<sub>1</sub>x<sub>1</sub> + ... r<sub>n</sub>x<sub>n</sub> + r<sub>cst</sub></li>
* <li>l<sub>1</sub>x<sub>1</sub> + ... l<sub>n</sub>x<sub>n</sub> + l<sub>cst</sub> <=
* r<sub>1</sub>x<sub>1</sub> + ... r<sub>n</sub>x<sub>n</sub> + r<sub>cst</sub></li>
* <li>l<sub>1</sub>x<sub>1</sub> + ... l<sub>n</sub>x<sub>n</sub> + l<sub>cst</sub> >=
* r<sub>1</sub>x<sub>1</sub> + ... r<sub>n</sub>x<sub>n</sub> + r<sub>cst</sub></li>
* </ul>
* where the c<sub>i</sub>, l<sub>i</sub> or r<sub>i</sub> are the coefficients of
* the constraints, the x<sub>i</sub> are the coordinates of the current point and
* v is the value of the constraint.
* </p>
* @deprecated As of 3.1 (to be removed in 4.0).
* @since 2.0
*/
@Deprecated
public interface LinearOptimizer {
Set the maximal number of iterations of the algorithm.
Params: - maxIterations – maximal number of function calls
/**
* Set the maximal number of iterations of the algorithm.
* @param maxIterations maximal number of function calls
*/
void setMaxIterations(int maxIterations);
Get the maximal number of iterations of the algorithm.
Returns: maximal number of iterations
/**
* Get the maximal number of iterations of the algorithm.
* @return maximal number of iterations
*/
int getMaxIterations();
Get the number of iterations realized by the algorithm.
The number of evaluations corresponds to the last call to the optimize method. It is 0 if the method has not been called yet.
Returns: number of iterations
/**
* Get the number of iterations realized by the algorithm.
* <p>
* The number of evaluations corresponds to the last call to the
* {@link #optimize(LinearObjectiveFunction, Collection, GoalType, boolean) optimize}
* method. It is 0 if the method has not been called yet.
* </p>
* @return number of iterations
*/
int getIterations();
Optimizes an objective function.
Params: - f – linear objective function
- constraints – linear constraints
- goalType – type of optimization goal: either
GoalType.MAXIMIZE or GoalType.MINIMIZE - restrictToNonNegative – whether to restrict the variables to non-negative values
Throws: - MathIllegalStateException – if no solution fulfilling the constraints
can be found in the allowed number of iterations
Returns: point/value pair giving the optimal value for objective function
/**
* Optimizes an objective function.
* @param f linear objective function
* @param constraints linear constraints
* @param goalType type of optimization goal: either {@link GoalType#MAXIMIZE} or {@link GoalType#MINIMIZE}
* @param restrictToNonNegative whether to restrict the variables to non-negative values
* @return point/value pair giving the optimal value for objective function
* @exception MathIllegalStateException if no solution fulfilling the constraints
* can be found in the allowed number of iterations
*/
PointValuePair optimize(LinearObjectiveFunction f, Collection<LinearConstraint> constraints,
GoalType goalType, boolean restrictToNonNegative) throws MathIllegalStateException;
}