Move java examples

examples/java/KnapsackMIP.java

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+/*
+ * 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.
+ * 
+ * ************************************************************************
+ * 
+ * Each knapsack perceives a different weight for each item. Item values are 
+ * the same across knapsacks. Optimizing constrains the count of each item such 
+ * that all knapsack capacities are respected, and their values are maximized.
+ * 
+ * This model was created by Hakan Kjellerstrand (hakank@gmail.com)
+ */ 
+
+import com.google.ortools.linearsolver.*;
+
+public class KnapsackMIP {
+	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);
+		
+		/** variables */ 
+		int itemCount = 12;
+		int capacityCount = 7;
+		
+		int[] capacity = {18209, 7692, 1333, 924, 26638, 61188, 13360};
+		int[] value = {96, 76, 56, 11, 86, 10, 66, 86, 83, 12, 9, 81};
+		int[][] weights = {
+				{19, 1, 10, 1, 1, 14, 152, 11, 1, 1, 1, 1},
+				{0, 4, 53, 0, 0, 80, 0, 4, 5, 0, 0, 0},
+				{4, 660, 3, 0, 30, 0, 3, 0, 4, 90, 0, 0},
+				{7, 0, 18, 6, 770, 330, 7, 0, 0, 6, 0, 0},
+				{0, 20, 0, 4, 52, 3, 0, 0, 0, 5, 4, 0},
+				{0, 0, 40, 70, 4, 63, 0, 0, 60, 0, 4, 0},
+				{0, 32, 0, 0, 0, 5, 0, 3, 0, 660, 0, 9}
+		};
+		
+		int maxCapacity = -1;
+		for (int c : capacity) {
+			if (c > maxCapacity) {
+				maxCapacity = c;
+			}
+		}
+		
+		MPVariable[] taken = solver.makeIntVarArray(itemCount, 0, maxCapacity);
+		
+		/** constraints */
+		MPConstraint constraints[] = new MPConstraint[capacityCount];
+		for (int i = 0; i < capacityCount; i ++) {
+			constraints[i] = solver.makeConstraint(0, capacity[i]);
+			for (int j = 0; j < itemCount; j ++) {
+				constraints[i].setCoefficient(taken[j], weights[i][j]);
+			}
+		}
+
+		/** objective */
+		MPObjective obj = solver.objective();
+		obj.setMaximization();
+		for (int i = 0; i < itemCount; i ++) {
+			obj.setCoefficient(taken[i], value[i]);
+		}
+		
+		solver.solve();
+		
+		/** printing */
+		System.out.println("Max cost: " + obj.value());
+		System.out.print("Item quantities: ");
+		for (MPVariable var : taken) {
+			System.out.print((int) var.solutionValue() + " ");
+		}
+	}
+	
+	public static void main(String[] args) {
+		solve("CBC_MIXED_INTEGER_PROGRAMMING");
+	}
+}