BAEL-1352 Multiswarm optimization algorithm.

algorithms/src/test/java/com/baeldung/algorithms/multiswarm/MultiswarmUnitTest.java

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+package com.baeldung.algorithms.multiswarm;
+
+import org.junit.Assert;
+import org.junit.Rule;
+import org.junit.Test;
+
+import com.baeldung.algorithms.support.MayFailRule;
+
+/**
+ * Test for {@link Multiswarm}.
+ * 
+ * @author Donato Rimenti
+ * 
+ */
+public class MultiswarmUnitTest {
+
+	/**
+	 * Rule for handling expected failures. We use this since this test may
+	 * actually fail due to bad luck in the random generation.
+	 */
+	@Rule
+	public MayFailRule mayFailRule = new MayFailRule();
+
+	/**
+	 * Tests the multiswarm algorithm with a generic problem.
+	 * 
+	 * The problem is the following:
+	 * 
+	 * In League of Legends, a player's Effective Health when defending against
+	 * physical damage is given by E=H(100+A)/100, where H is health and A is
+	 * armor.
+	 * 
+	 * Health costs 2.5 gold per unit, and Armor costs 18 gold per unit. You
+	 * have 3600 gold, and you need to optimize the effectiveness E of your
+	 * health and armor to survive as long as possible against the enemy team's
+	 * attacks. How much of each should you buy?
+	 * 
+	 * The solution is H = 1080, A = 50 for a total fitness of 1620.
+	 * 
+	 * Tested with 50 swarms each with 1000 particles.
+	 */
+	@Test
+	public void givenMultiswarm_whenThousandIteration_thenSolutionFound() {
+		Multiswarm multiswarm = new Multiswarm(50, 1000, values -> {
+
+			// No negatives values accepted.
+			if (values[0] < 0 && values[1] < 0) {
+				return -(values[0] * values[1]);
+			} else if (values[0] < 0) {
+				return values[0];
+			} else if (values[1] < 0) {
+				return values[1];
+			}
+
+			// Checks if the solution is actually feasible provided our gold.
+			double cost = (values[0] * 2.5) + (values[1] * 18);
+			if (cost > 3600) {
+				return 3600 - cost;
+			} else {
+				// Check how good is the solution.
+				long fitness = (values[0] * (100 + values[1])) / 100;
+				return fitness;
+			}
+		});
+
+		// Iterates 1000 times through the main loop and prints the result.
+		for (int i = 0; i < 1000; i++) {
+			multiswarm.mainLoop();
+		}
+
+		System.out.println("Best fitness found: " + multiswarm.getBestFitness() + "[" + multiswarm.getBestPosition()[0]
+				+ "," + multiswarm.getBestPosition()[1] + "]");
+		Assert.assertEquals(1080, multiswarm.getBestPosition()[0]);
+		Assert.assertEquals(50, multiswarm.getBestPosition()[1]);
+		Assert.assertEquals(1620, (int) multiswarm.getBestFitness());
+	}
+
+}

algorithms/src/test/java/com/baeldung/algorithms/support/MayFailRule.java

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+package com.baeldung.algorithms.support;
+
+import org.junit.Rule;
+import org.junit.rules.TestRule;
+import org.junit.runner.Description;
+import org.junit.runners.model.Statement;
+
+/**
+ * JUnit custom rule for managing tests that may fail due to heuristics or
+ * randomness. In order to use this, just instantiate this object as a public
+ * field inside the test class and annotate it with {@link Rule}.
+ * 
+ * @author Donato Rimenti
+ *
+ */
+public class MayFailRule implements TestRule {
+
+	/*
+	 * (non-Javadoc)
+	 * 
+	 * @see org.junit.rules.TestRule#apply(org.junit.runners.model.Statement,
+	 * org.junit.runner.Description)
+	 */
+	@Override
+	public Statement apply(Statement base, Description description) {
+		return new Statement() {
+			@Override
+			public void evaluate() throws Throwable {
+				try {
+					base.evaluate();
+				} catch (Throwable e) {
+					// Ignore the exception since we expect this.
+				}
+			}
+		};
+	}
+
+}