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diff --git a/src/main/java/org/apache/commons/math/optimization/DifferentiableMultivariateVectorialOptimizer.java b/src/main/java/org/apache/commons/math/optimization/DifferentiableMultivariateVectorialOptimizer.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.math.optimization;
+
+import org.apache.commons.math.analysis.DifferentiableMultivariateVectorialFunction;
+import org.apache.commons.math.FunctionEvaluationException;
+
+/**
+ * This interface represents an optimization algorithm for {@link DifferentiableMultivariateVectorialFunction
+ * vectorial differentiable objective functions}.
+ * <p>Optimization algorithms find the input point set that either {@link GoalType
+ * maximize or minimize} an objective function.</p>
+ * @see MultivariateRealOptimizer
+ * @see DifferentiableMultivariateRealOptimizer
+ * @version $Revision: 1073158 $ $Date: 2011-02-21 22:46:52 +0100 (lun. 21 févr. 2011) $
+ * @since 2.0
+ */
+public interface DifferentiableMultivariateVectorialOptimizer {
+
+    /** 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.
+     * @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 evaluation correspond to the last call to the
+     * {@link #optimize(DifferentiableMultivariateVectorialFunction,
+     * double[], double[], 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 jacobian .
+     * <p>
+     * The number of evaluation correspond to the last call to the
+     * {@link #optimize(DifferentiableMultivariateVectorialFunction,
+     * double[], double[], double[]) optimize} method. It is 0 if
+     * the method has not been called yet.
+     * </p>
+     * @return number of evaluations of the objective function jacobian
+     */
+    int getJacobianEvaluations();
+
+    /** Set the convergence checker.
+     * @param checker object to use to check for convergence
+     */
+    void setConvergenceChecker(VectorialConvergenceChecker checker);
+
+    /** Get the convergence checker.
+     * @return object used to check for convergence
+     */
+    VectorialConvergenceChecker getConvergenceChecker();
+
+    /** Optimizes an objective function.
+     * <p>
+     * Optimization is considered to be a weighted least-squares minimization.
+     * The cost function to be minimized is
+     * &sum;weight<sub>i</sub>(objective<sub>i</sub>-target<sub>i</sub>)<sup>2</sup>
+     * </p>
+     * @param f objective function
+     * @param target target value for the objective functions at optimum
+     * @param weights weight for the least squares cost computation
+     * @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
+     */
+    VectorialPointValuePair optimize(DifferentiableMultivariateVectorialFunction f,
+                                     double[] target, double[] weights,
+                                     double[] startPoint)
+        throws FunctionEvaluationException, OptimizationException, IllegalArgumentException;
+
+}