From e11bce7ad3e803e80883499fec0ad6e4540ffe43 Mon Sep 17 00:00:00 2001
From: Kristóf Marussy <marussy@mit.bme.hu>
Date: Tue, 30 Jun 2020 18:03:48 +0200
Subject: Add modified VIATRA-DSE version

---
 .../api/strategy/impl/HillClimbingStrategy.java    | 142 +++++++++++++++++++++
 1 file changed, 142 insertions(+)
 create mode 100644 Solvers/VIATRA-Solver/org.eclipse.viatra.dse/src/org/eclipse/viatra/dse/api/strategy/impl/HillClimbingStrategy.java

(limited to 'Solvers/VIATRA-Solver/org.eclipse.viatra.dse/src/org/eclipse/viatra/dse/api/strategy/impl/HillClimbingStrategy.java')

diff --git a/Solvers/VIATRA-Solver/org.eclipse.viatra.dse/src/org/eclipse/viatra/dse/api/strategy/impl/HillClimbingStrategy.java b/Solvers/VIATRA-Solver/org.eclipse.viatra.dse/src/org/eclipse/viatra/dse/api/strategy/impl/HillClimbingStrategy.java
new file mode 100644
index 00000000..0ccb0668
--- /dev/null
+++ b/Solvers/VIATRA-Solver/org.eclipse.viatra.dse/src/org/eclipse/viatra/dse/api/strategy/impl/HillClimbingStrategy.java
@@ -0,0 +1,142 @@
+/*******************************************************************************
+ * Copyright (c) 2010-2016, Andras Szabolcs Nagy, Zoltan Ujhelyi and Daniel Varro
+ * This program and the accompanying materials are made available under the
+ * terms of the Eclipse Public License v. 2.0 which is available at
+ * http://www.eclipse.org/legal/epl-v20.html.
+ * 
+ * SPDX-License-Identifier: EPL-2.0
+ *******************************************************************************/
+package org.eclipse.viatra.dse.api.strategy.impl;
+
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.Random;
+import java.util.concurrent.atomic.AtomicBoolean;
+
+import org.apache.log4j.Logger;
+import org.eclipse.viatra.dse.api.strategy.interfaces.IStrategy;
+import org.eclipse.viatra.dse.base.ThreadContext;
+import org.eclipse.viatra.dse.objectives.Fitness;
+import org.eclipse.viatra.dse.objectives.ObjectiveComparatorHelper;
+import org.eclipse.viatra.dse.objectives.TrajectoryFitness;
+
+public class HillClimbingStrategy implements IStrategy {
+
+    private AtomicBoolean isInterrupted = new AtomicBoolean(false);
+    private ThreadContext context;
+
+    private Logger logger = Logger.getLogger(IStrategy.class);
+
+    private Random random = new Random();
+    private double percentOfOpenedStates;
+    private ObjectiveComparatorHelper objectiveComparatorHelper;
+
+    public HillClimbingStrategy() {
+        this(2);
+    }
+
+    public HillClimbingStrategy(double percentOfOpenedStates) {
+        this.percentOfOpenedStates = percentOfOpenedStates;
+    }
+
+    @Override
+    public void initStrategy(ThreadContext context) {
+        this.context = context;
+        objectiveComparatorHelper = context.getObjectiveComparatorHelper();
+        logger.info("Hill climbing exploration strategy is initied.");
+    }
+
+    @Override
+    public void explore() {
+
+        boolean globalConstraintsAreSatisfied = context.checkGlobalConstraints();
+        if (!globalConstraintsAreSatisfied) {
+            boolean isSuccessfulUndo = context.backtrack();
+            if (!isSuccessfulUndo) {
+                logger.info("Global contraint is not satisifed and cannot backtrack.");
+                return;
+            }
+        }
+
+        mainloop: do {
+
+            Fitness previousFitness = context.calculateFitness();
+
+            logger.debug("Current depth: " + context.getDepth() + " Fitness: " + previousFitness);
+
+            Collection<Object> transitionsFromCurrentState = context.getCurrentActivationIds();
+
+            while (transitionsFromCurrentState.isEmpty()) {
+                logger.debug("No transitions from current state: considered as a solution.");
+                saveSolutionAndBacktrack();
+                continue mainloop;
+            }
+
+            ArrayList<Object> transitionsToTry = new ArrayList<>(transitionsFromCurrentState.size());
+            for (Object transition : transitionsFromCurrentState) {
+                transitionsToTry.add(transition);
+            }
+            double numberOfTransitionsToTry = transitionsToTry.size() * percentOfOpenedStates;
+
+            for (; numberOfTransitionsToTry > 0 && !transitionsToTry.isEmpty(); numberOfTransitionsToTry--) {
+                int index = random.nextInt(transitionsToTry.size());
+                Object transition = transitionsToTry.remove(index);
+
+                context.executeAcitvationId(transition);
+
+                if (!context.checkGlobalConstraints()) {
+                    logger.debug("Global contraint is not satisifed, backtrack.");
+                    context.backtrack();
+                    continue;
+                }
+                if (context.isCurrentStateInTrajectory()) {
+                    logger.debug("Current state is in trajectory, backtrack.");
+                    context.backtrack();
+                    continue;
+                }
+
+                Fitness fitness = context.calculateFitness();
+                objectiveComparatorHelper.addTrajectoryFitness(
+                        new TrajectoryFitness(context.getTrajectoryInfo().getLastActivationId(), fitness));
+                context.backtrack();
+            }
+
+            if (objectiveComparatorHelper.getTrajectoryFitnesses().isEmpty()) {
+                logger.debug("No viable transitions from current state: considered as a solution.");
+                saveSolutionAndBacktrack();
+                continue;
+            }
+
+            TrajectoryFitness randomBestFitness = objectiveComparatorHelper.getRandomBest();
+            objectiveComparatorHelper.clearTrajectoryFitnesses();
+
+            int compare = objectiveComparatorHelper.compare(previousFitness, randomBestFitness.fitness);
+
+            if (compare > 0) {
+                saveSolutionAndBacktrack();
+                continue;
+            } else {
+                previousFitness = randomBestFitness.fitness;
+                Object transition = randomBestFitness.trajectory[randomBestFitness.trajectory.length - 1];
+                context.executeAcitvationId(transition);
+            }
+
+        } while (!isInterrupted.get());
+
+        logger.info("Terminated.");
+    }
+
+    private void saveSolutionAndBacktrack() {
+        context.calculateFitness();
+        context.newSolution();
+        logger.debug("Found solution: " + context.getTrajectoryInfo().toString());
+        logger.debug("Backtrack for more solutions, if needed.");
+        context.backtrackUntilRoot();
+    }
+
+    @Override
+    public void interruptStrategy() {
+        isInterrupted.set(true);
+    }
+
+}
-- 
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