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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.commons.math3.optimization.linear;
import java.util.Collection;
import java.util.Collections;
import org.apache.commons.math3.exception.MathIllegalStateException;
import org.apache.commons.math3.exception.MaxCountExceededException;
import org.apache.commons.math3.optimization.GoalType;
import org.apache.commons.math3.optimization.PointValuePair;
/**
* Base class for implementing linear optimizers.
*
* This base class handles the boilerplate methods associated to thresholds
* settings and iterations counters.
*
* @deprecated As of 3.1 (to be removed in 4.0).
* @since 2.0
*/
@Deprecated
public abstract class AbstractLinearOptimizer implements LinearOptimizer {
/** Default maximal number of iterations allowed. */
public static final int DEFAULT_MAX_ITERATIONS = 100;
/**
* Linear objective function.
* @since 2.1
*/
private LinearObjectiveFunction function;
/**
* Linear constraints.
* @since 2.1
*/
private Collection linearConstraints;
/**
* Type of optimization goal: either {@link GoalType#MAXIMIZE} or {@link GoalType#MINIMIZE}.
* @since 2.1
*/
private GoalType goal;
/**
* Whether to restrict the variables to non-negative values.
* @since 2.1
*/
private boolean nonNegative;
/** Maximal number of iterations allowed. */
private int maxIterations;
/** Number of iterations already performed. */
private int iterations;
/**
* Simple constructor with default settings.
* The maximal number of evaluation is set to its default value.
*/
protected AbstractLinearOptimizer() {
setMaxIterations(DEFAULT_MAX_ITERATIONS);
}
/**
* @return {@code true} if the variables are restricted to non-negative values.
*/
protected boolean restrictToNonNegative() {
return nonNegative;
}
/**
* @return the optimization type.
*/
protected GoalType getGoalType() {
return goal;
}
/**
* @return the optimization type.
*/
protected LinearObjectiveFunction getFunction() {
return function;
}
/**
* @return the optimization type.
*/
protected Collection getConstraints() {
return Collections.unmodifiableCollection(linearConstraints);
}
/** {@inheritDoc} */
public void setMaxIterations(int maxIterations) {
this.maxIterations = maxIterations;
}
/** {@inheritDoc} */
public int getMaxIterations() {
return maxIterations;
}
/** {@inheritDoc} */
public int getIterations() {
return iterations;
}
/**
* Increment the iterations counter by 1.
* @exception MaxCountExceededException if the maximal number of iterations is exceeded
*/
protected void incrementIterationsCounter()
throws MaxCountExceededException {
if (++iterations > maxIterations) {
throw new MaxCountExceededException(maxIterations);
}
}
/** {@inheritDoc} */
public PointValuePair optimize(final LinearObjectiveFunction f,
final Collection constraints,
final GoalType goalType, final boolean restrictToNonNegative)
throws MathIllegalStateException {
// store linear problem characteristics
this.function = f;
this.linearConstraints = constraints;
this.goal = goalType;
this.nonNegative = restrictToNonNegative;
iterations = 0;
// solve the problem
return doOptimize();
}
/**
* Perform the bulk of optimization algorithm.
* @return the 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
*/
protected abstract PointValuePair doOptimize() throws MathIllegalStateException;
}