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diff --git a/src/main/java/org/apache/commons/math3/optimization/general/AbstractScalarDifferentiableOptimizer.java b/src/main/java/org/apache/commons/math3/optimization/general/AbstractScalarDifferentiableOptimizer.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.optimization.general;
+
+import org.apache.commons.math3.analysis.DifferentiableMultivariateFunction;
+import org.apache.commons.math3.analysis.MultivariateVectorFunction;
+import org.apache.commons.math3.analysis.FunctionUtils;
+import org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableFunction;
+import org.apache.commons.math3.optimization.DifferentiableMultivariateOptimizer;
+import org.apache.commons.math3.optimization.GoalType;
+import org.apache.commons.math3.optimization.ConvergenceChecker;
+import org.apache.commons.math3.optimization.PointValuePair;
+import org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer;
+
+/**
+ * Base class for implementing optimizers for multivariate scalar
+ * differentiable functions.
+ * It contains boiler-plate code for dealing with gradient evaluation.
+ *
+ * @deprecated As of 3.1 (to be removed in 4.0).
+ * @since 2.0
+ */
+@Deprecated
+public abstract class AbstractScalarDifferentiableOptimizer
+    extends BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>
+    implements DifferentiableMultivariateOptimizer {
+    /**
+     * Objective function gradient.
+     */
+    private MultivariateVectorFunction gradient;
+
+    /**
+     * Simple constructor with default settings.
+     * The convergence check is set to a
+     * {@link org.apache.commons.math3.optimization.SimpleValueChecker
+     * SimpleValueChecker}.
+     * @deprecated See {@link org.apache.commons.math3.optimization.SimpleValueChecker#SimpleValueChecker()}
+     */
+    @Deprecated
+    protected AbstractScalarDifferentiableOptimizer() {}
+
+    /**
+     * @param checker Convergence checker.
+     */
+    protected AbstractScalarDifferentiableOptimizer(ConvergenceChecker<PointValuePair> checker) {
+        super(checker);
+    }
+
+    /**
+     * Compute the gradient vector.
+     *
+     * @param evaluationPoint Point at which the gradient must be evaluated.
+     * @return the gradient at the specified point.
+     * @throws org.apache.commons.math3.exception.TooManyEvaluationsException
+     * if the allowed number of evaluations is exceeded.
+     */
+    protected double[] computeObjectiveGradient(final double[] evaluationPoint) {
+        return gradient.value(evaluationPoint);
+    }
+
+    /** {@inheritDoc} */
+    @Override
+    protected PointValuePair optimizeInternal(int maxEval,
+                                              final DifferentiableMultivariateFunction f,
+                                              final GoalType goalType,
+                                              final double[] startPoint) {
+        // Store optimization problem characteristics.
+        gradient = f.gradient();
+
+        return super.optimizeInternal(maxEval, f, goalType, startPoint);
+    }
+
+    /**
+     * Optimize an objective function.
+     *
+     * @param f Objective function.
+     * @param goalType Type of optimization goal: either
+     * {@link GoalType#MAXIMIZE} or {@link GoalType#MINIMIZE}.
+     * @param startPoint Start point for optimization.
+     * @param maxEval Maximum number of function evaluations.
+     * @return the point/value pair giving the optimal value for objective
+     * function.
+     * @throws org.apache.commons.math3.exception.DimensionMismatchException
+     * if the start point dimension is wrong.
+     * @throws org.apache.commons.math3.exception.TooManyEvaluationsException
+     * if the maximal number of evaluations is exceeded.
+     * @throws org.apache.commons.math3.exception.NullArgumentException if
+     * any argument is {@code null}.
+     */
+    public PointValuePair optimize(final int maxEval,
+                                   final MultivariateDifferentiableFunction f,
+                                   final GoalType goalType,
+                                   final double[] startPoint) {
+        return optimizeInternal(maxEval,
+                                FunctionUtils.toDifferentiableMultivariateFunction(f),
+                                goalType,
+                                startPoint);
+    }
+}