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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.math.optimization;
+
+import org.apache.commons.math.FunctionEvaluationException;
+import org.apache.commons.math.analysis.DifferentiableMultivariateRealFunction;
+
+/**
+ * This interface represents an optimization algorithm for
+ * {@link DifferentiableMultivariateRealFunction scalar differentiable objective
+ * functions}.
+ * Optimization algorithms find the input point set that either {@link GoalType
+ * maximize or minimize} an objective function.
+ *
+ * @see MultivariateRealOptimizer
+ * @see DifferentiableMultivariateVectorialOptimizer
+ * @version $Revision: 1065484 $ $Date: 2011-01-31 06:45:14 +0100 (lun. 31 janv. 2011) $
+ * @since 2.0
+ */
+public interface DifferentiableMultivariateRealOptimizer {
+
+    /** 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.
+     * @return maximal number of iterations
+     */
+    int getMaxIterations();
+
+    /** Get the number of iterations realized by the algorithm.
+     * <p>
+     * The number of evaluations corresponds to the last call to the
+     * {@code optimize} method. It is 0 if the method has not been called yet.
+     * </p>
+     * @return number of iterations
+     */
+    int getIterations();
+
+    /** Set the maximal number of functions evaluations.
+     * @param maxEvaluations maximal number of function evaluations
+     */
+    void setMaxEvaluations(int maxEvaluations);
+
+    /** Get the maximal number of functions evaluations.
+     * @return maximal number of functions evaluations
+     */
+    int getMaxEvaluations();
+
+    /** Get the number of evaluations of the objective function.
+     * <p>
+     * The number of evaluations corresponds to the last call to the
+     * {@link #optimize(DifferentiableMultivariateRealFunction, GoalType, double[]) optimize}
+     * method. It is 0 if the method has not been called yet.
+     * </p>
+     * @return number of evaluations of the objective function
+     */
+    int getEvaluations();
+
+    /** Get the number of evaluations of the objective function gradient.
+     * <p>
+     * The number of evaluations corresponds to the last call to the
+     * {@link #optimize(DifferentiableMultivariateRealFunction, GoalType, double[]) optimize}
+     * method. It is 0 if the method has not been called yet.
+     * </p>
+     * @return number of evaluations of the objective function gradient
+     */
+    int getGradientEvaluations();
+
+    /** Set the convergence checker.
+     * @param checker object to use to check for convergence
+     */
+    void setConvergenceChecker(RealConvergenceChecker checker);
+
+    /** Get the convergence checker.
+     * @return object used to check for convergence
+     */
+    RealConvergenceChecker getConvergenceChecker();
+
+    /** Optimizes an objective function.
+     * @param f objective function
+     * @param goalType type of optimization goal: either {@link GoalType#MAXIMIZE}
+     * or {@link GoalType#MINIMIZE}
+     * @param startPoint the start point for optimization
+     * @return the point/value pair giving the optimal value for objective function
+     * @exception FunctionEvaluationException if the objective function throws one during
+     * the search
+     * @exception OptimizationException if the algorithm failed to converge
+     * @exception IllegalArgumentException if the start point dimension is wrong
+     */
+    RealPointValuePair optimize(DifferentiableMultivariateRealFunction f,
+                                  GoalType goalType,
+                                  double[] startPoint)
+        throws FunctionEvaluationException, OptimizationException, IllegalArgumentException;
+
+}