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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.
+ * <p>
+ * 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<LinearConstraint> 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.
+ * <p>The maximal number of evaluation is set to its default value.</p>
+ */
+ 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<LinearConstraint> 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<LinearConstraint> 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;
+
+}