Move java examples

examples/java/DietMIP.java

@@ -0,0 +1,92 @@
+
+/*
+ * Copyright 2017 Darian Sastre darian.sastre@minimaxlabs.com
+ * Licensed 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.
+ * 
+ * ************************************************************************
+ * 
+ * This model was created by Hakan Kjellerstrand (hakank@gmail.com)
+ */
+
+import com.google.ortools.linearsolver.MPConstraint;
+import com.google.ortools.linearsolver.MPObjective;
+import com.google.ortools.linearsolver.MPSolver;
+import com.google.ortools.linearsolver.MPVariable;
+
+public class DietMIP {
+	static {
+		System.loadLibrary("jniortools");
+	}
+
+	private static MPSolver createSolver(String solverType) {
+		try {
+			return new MPSolver("MIPDiet", MPSolver.OptimizationProblemType.valueOf(solverType));
+		} catch (java.lang.IllegalArgumentException e) {
+			System.err.println("Bad solver type: " + e);
+			return null;
+		}
+	}
+
+	private static void solve(String solverType) {
+		MPSolver solver = createSolver(solverType);
+		double infinity = MPSolver.infinity();
+
+		int n = 4; // variables number
+		int m = 4; // constraints number
+
+		int[] price = { 50, 20, 30, 80 };
+
+		int[] limits = { 500, 6, 10, 8 };
+
+		int[] calories = { 400, 200, 150, 500 };
+		int[] chocolate = { 3, 2, 0, 0 };
+		int[] sugar = { 2, 2, 4, 4 };
+		int[] fat = { 2, 4, 1, 5 };
+
+		int[][] values = { calories, chocolate, sugar, fat };
+
+		MPVariable[] x = solver.makeIntVarArray(n, 0, 100, "x");
+		MPObjective objective = solver.objective();
+		MPConstraint[] targets = new MPConstraint[4];
+
+		for (int i = 0; i < n; i++) {
+			objective.setCoefficient(x[i], price[i]);
+
+			// constraints
+			targets[i] = solver.makeConstraint(limits[i], infinity);
+			for (int j = 0; j < m; j++) {
+				targets[i].setCoefficient(x[j], values[i][j]);
+			}
+		}
+
+		final MPSolver.ResultStatus resultStatus = solver.solve();
+
+		/** printing */
+		if (resultStatus != MPSolver.ResultStatus.OPTIMAL) {
+			System.err.println("The problem does not have an optimal solution!");
+			return;
+		} else {
+			System.out.println("Optimal objective value = " + solver.objective().value());
+
+			System.out.print("Item quantities: ");
+			System.out.print((int) x[0].solutionValue() + " ");
+			System.out.print((int) x[1].solutionValue() + " ");
+			System.out.print((int) x[2].solutionValue() + " ");
+			System.out.print((int) x[3].solutionValue() + " ");
+		}
+	}
+
+	public static void main(String[] args) throws Exception {
+		solve("CBC_MIXED_INTEGER_PROGRAMMING");
+	}
+}