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diff --git a/src/main/java/org/apache/commons/math3/optim/nonlinear/scalar/noderiv/SimplexOptimizer.java b/src/main/java/org/apache/commons/math3/optim/nonlinear/scalar/noderiv/SimplexOptimizer.java
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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.optim.nonlinear.scalar.noderiv;
+
+import java.util.Comparator;
+import org.apache.commons.math3.analysis.MultivariateFunction;
+import org.apache.commons.math3.exception.NullArgumentException;
+import org.apache.commons.math3.exception.MathUnsupportedOperationException;
+import org.apache.commons.math3.exception.util.LocalizedFormats;
+import org.apache.commons.math3.optim.nonlinear.scalar.GoalType;
+import org.apache.commons.math3.optim.ConvergenceChecker;
+import org.apache.commons.math3.optim.PointValuePair;
+import org.apache.commons.math3.optim.SimpleValueChecker;
+import org.apache.commons.math3.optim.OptimizationData;
+import org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer;
+
+/**
+ * This class implements simplex-based direct search optimization.
+ *
+ * <p>
+ *  Direct search methods only use objective function values, they do
+ *  not need derivatives and don't either try to compute approximation
+ *  of the derivatives. According to a 1996 paper by Margaret H. Wright
+ *  (<a href="http://cm.bell-labs.com/cm/cs/doc/96/4-02.ps.gz">Direct
+ *  Search Methods: Once Scorned, Now Respectable</a>), they are used
+ *  when either the computation of the derivative is impossible (noisy
+ *  functions, unpredictable discontinuities) or difficult (complexity,
+ *  computation cost). In the first cases, rather than an optimum, a
+ *  <em>not too bad</em> point is desired. In the latter cases, an
+ *  optimum is desired but cannot be reasonably found. In all cases
+ *  direct search methods can be useful.
+ * </p>
+ * <p>
+ *  Simplex-based direct search methods are based on comparison of
+ *  the objective function values at the vertices of a simplex (which is a
+ *  set of n+1 points in dimension n) that is updated by the algorithms
+ *  steps.
+ * <p>
+ * <p>
+ *  The simplex update procedure ({@link NelderMeadSimplex} or
+ * {@link MultiDirectionalSimplex})  must be passed to the
+ * {@code optimize} method.
+ * </p>
+ * <p>
+ *  Each call to {@code optimize} will re-use the start configuration of
+ *  the current simplex and move it such that its first vertex is at the
+ *  provided start point of the optimization.
+ *  If the {@code optimize} method is called to solve a different problem
+ *  and the number of parameters change, the simplex must be re-initialized
+ *  to one with the appropriate dimensions.
+ * </p>
+ * <p>
+ *  Convergence is checked by providing the <em>worst</em> points of
+ *  previous and current simplex to the convergence checker, not the best
+ *  ones.
+ * </p>
+ * <p>
+ *  This simplex optimizer implementation does not directly support constrained
+ *  optimization with simple bounds; so, for such optimizations, either a more
+ *  dedicated algorithm must be used like
+ *  {@link CMAESOptimizer} or {@link BOBYQAOptimizer}, or the objective
+ *  function must be wrapped in an adapter like
+ *  {@link org.apache.commons.math3.optim.nonlinear.scalar.MultivariateFunctionMappingAdapter
+ *  MultivariateFunctionMappingAdapter} or
+ *  {@link org.apache.commons.math3.optim.nonlinear.scalar.MultivariateFunctionPenaltyAdapter
+ *  MultivariateFunctionPenaltyAdapter}.
+ *  <br/>
+ *  The call to {@link #optimize(OptimizationData[]) optimize} will throw
+ *  {@link MathUnsupportedOperationException} if bounds are passed to it.
+ * </p>
+ *
+ * @since 3.0
+ */
+public class SimplexOptimizer extends MultivariateOptimizer {
+    /** Simplex update rule. */
+    private AbstractSimplex simplex;
+
+    /**
+     * @param checker Convergence checker.
+     */
+    public SimplexOptimizer(ConvergenceChecker<PointValuePair> checker) {
+        super(checker);
+    }
+
+    /**
+     * @param rel Relative threshold.
+     * @param abs Absolute threshold.
+     */
+    public SimplexOptimizer(double rel, double abs) {
+        this(new SimpleValueChecker(rel, abs));
+    }
+
+    /**
+     * {@inheritDoc}
+     *
+     * @param optData Optimization data. In addition to those documented in
+     * {@link MultivariateOptimizer#parseOptimizationData(OptimizationData[])
+     * MultivariateOptimizer}, this method will register the following data:
+     * <ul>
+     *  <li>{@link AbstractSimplex}</li>
+     * </ul>
+     * @return {@inheritDoc}
+     */
+    @Override
+    public PointValuePair optimize(OptimizationData... optData) {
+        // Set up base class and perform computation.
+        return super.optimize(optData);
+    }
+
+    /** {@inheritDoc} */
+    @Override
+    protected PointValuePair doOptimize() {
+        checkParameters();
+
+        // Indirect call to "computeObjectiveValue" in order to update the
+        // evaluations counter.
+        final MultivariateFunction evalFunc
+            = new MultivariateFunction() {
+                /** {@inheritDoc} */
+                public double value(double[] point) {
+                    return computeObjectiveValue(point);
+                }
+            };
+
+        final boolean isMinim = getGoalType() == GoalType.MINIMIZE;
+        final Comparator<PointValuePair> comparator
+            = new Comparator<PointValuePair>() {
+            /** {@inheritDoc} */
+            public int compare(final PointValuePair o1,
+                               final PointValuePair o2) {
+                final double v1 = o1.getValue();
+                final double v2 = o2.getValue();
+                return isMinim ? Double.compare(v1, v2) : Double.compare(v2, v1);
+            }
+        };
+
+        // Initialize search.
+        simplex.build(getStartPoint());
+        simplex.evaluate(evalFunc, comparator);
+
+        PointValuePair[] previous = null;
+        int iteration = 0;
+        final ConvergenceChecker<PointValuePair> checker = getConvergenceChecker();
+        while (true) {
+            if (getIterations() > 0) {
+                boolean converged = true;
+                for (int i = 0; i < simplex.getSize(); i++) {
+                    PointValuePair prev = previous[i];
+                    converged = converged &&
+                        checker.converged(iteration, prev, simplex.getPoint(i));
+                }
+                if (converged) {
+                    // We have found an optimum.
+                    return simplex.getPoint(0);
+                }
+            }
+
+            // We still need to search.
+            previous = simplex.getPoints();
+            simplex.iterate(evalFunc, comparator);
+
+            incrementIterationCount();
+        }
+    }
+
+    /**
+     * Scans the list of (required and optional) optimization data that
+     * characterize the problem.
+     *
+     * @param optData Optimization data.
+     * The following data will be looked for:
+     * <ul>
+     *  <li>{@link AbstractSimplex}</li>
+     * </ul>
+     */
+    @Override
+    protected void parseOptimizationData(OptimizationData... optData) {
+        // Allow base class to register its own data.
+        super.parseOptimizationData(optData);
+
+        // The existing values (as set by the previous call) are reused if
+        // not provided in the argument list.
+        for (OptimizationData data : optData) {
+            if (data instanceof AbstractSimplex) {
+                simplex = (AbstractSimplex) data;
+                // If more data must be parsed, this statement _must_ be
+                // changed to "continue".
+                break;
+            }
+        }
+    }
+
+    /**
+     * @throws MathUnsupportedOperationException if bounds were passed to the
+     * {@link #optimize(OptimizationData[]) optimize} method.
+     * @throws NullArgumentException if no initial simplex was passed to the
+     * {@link #optimize(OptimizationData[]) optimize} method.
+     */
+    private void checkParameters() {
+        if (simplex == null) {
+            throw new NullArgumentException();
+        }
+        if (getLowerBound() != null ||
+            getUpperBound() != null) {
+            throw new MathUnsupportedOperationException(LocalizedFormats.CONSTRAINT);
+        }
+    }
+}