Simulated Annnealing fixes (#907)

* @Async and Spring Security

* @Async with SecurityContext propagated

* Spring and @Async

* Simulated Annealing algorithm

* Simulated Annealing algorithm

* Rebase

* Rebase

core-java/README.md

@@ -45,3 +45,4 @@
 - [Getting Started with Java Properties](http://www.baeldung.com/java-properties)
 - [Grep in Java](http://www.baeldung.com/grep-in-java)
 - [Java - Combine Multiple Collections](http://www.baeldung.com/java-combine-multiple-collections)
+- [Simulated Annealing for Travelling Salesman Problem](http://www.baeldung.com/java-simulated-annealing-for-traveling-salesman)

core-java/src/main/java/com/baeldung/algorithms/City.java

@@ -5,18 +5,18 @@ import lombok.Data;
 @Data
 public class City {
 
-    private int x;
-    private int y;
+	private int x;
+	private int y;
 
-    public City() {
-        this.x = (int) (Math.random() * 500);
-        this.y = (int) (Math.random() * 500);
-    }
+	public City() {
+		this.x = (int) (Math.random() * 500);
+		this.y = (int) (Math.random() * 500);
+	}
 
-    public double distanceToCity(City city) {
-        int x = Math.abs(getX() - city.getX());
-        int y = Math.abs(getY() - city.getY());
-        return Math.sqrt(Math.pow(x, 2) + Math.pow(y, 2));
-    }
+	public double distanceToCity(City city) {
+		int x = Math.abs(getX() - city.getX());
+		int y = Math.abs(getY() - city.getY());
+		return Math.sqrt(Math.pow(x, 2) + Math.pow(y, 2));
+	}
 
 }

core-java/src/main/java/com/baeldung/algorithms/SimulatedAnnealing.java

@@ -25,6 +25,8 @@ public class SimulatedAnnealing {
                     currentSolution.revertSwap();
                 }
                 t *= coolingRate;
+            } else {
+            	continue;
             }
             if (i % 100 == 0) {
                 System.out.println("Iteration #" + i);
@@ -34,7 +36,7 @@ public class SimulatedAnnealing {
     }
 
     public static void main(String[] args) {
-        System.out.println("Optimized distance for travel: " + simulateAnnealing(10, 10000, 0.9));
+        System.out.println("Optimized distance for travel: " + simulateAnnealing(10, 10000, 0.9995));
     }
 
 }

core-java/src/main/java/com/baeldung/algorithms/Travel.java

@@ -27,7 +27,10 @@ public class Travel {
         int a = generateRandomIndex();
         int b = generateRandomIndex();
         previousTravel = travel;
-        travel.set(a, travel.get(b));
+        City x = travel.get(a);
+        City y = travel.get(b);
+        travel.set(a, y);
+        travel.set(b, x);
     }
 
     public void revertSwap() {