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 /*
  * Copyright 2010 JBoss Inc
  *
  * 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.
 */
package org.drools.planner.core.localsearch.decider.acceptor.simulatedannealing;
TODO this will be removed once the time gradient based SimulatedAnnealingAcceptor is always better.
    protected double startingTemperature = -1.0;
    protected double temperatureSurvival = 0.997;
    protected double temperature;
    public void setStartingTemperature(double startingTemperature) {
        this. = startingTemperature;
    }
    public void setTemperatureSurvival(double temperatureSurvival) {
        this. = temperatureSurvival;
    }
    // ************************************************************************
    // Worker methods
    // ************************************************************************
    @Override
    public void phaseStarted(LocalSearchSolverPhaseScope localSearchSolverPhaseScope) {
        if ( <= 0.0) {
            throw new IllegalArgumentException("The startingTemperature (" + 
                    + ") cannot be negative or zero.");
        }
        if ( <= 0.0) {
            throw new IllegalArgumentException("The temperatureSurvival (" + 
                    + ") cannot be negative or zero.");
        }
         = ;
    }
    public double calculateAcceptChance(MoveScope moveScope) {
        LocalSearchSolverPhaseScope localSearchSolverPhaseScope = moveScope.getLocalSearchStepScope().getLocalSearchSolverPhaseScope();
        Score lastStepScore = localSearchSolverPhaseScope.getLastCompletedLocalSearchStepScope().getScore();
        Score moveScore = moveScope.getScore();
        if (moveScore.compareTo(lastStepScore) > 0) {
            return 1.0;
        }
        Score scoreDifference = lastStepScore.subtract(moveScore);
        // TODO don't abuse translateScoreToGraphValue
        Double diff = localSearchSolverPhaseScope.getScoreDefinition().translateScoreToGraphValue(scoreDifference);
        if (diff == null) {
            // more hard constraints broken, ignore it for now
            return 0.0;
        }
        double acceptChance = Math.exp(-diff / );
        if (moveScope.getWorkingRandom().nextDouble() < acceptChance) {
            return 1.0;
        } else {
            return 0.0;
        }
    }
    @Override
    public void stepTaken(LocalSearchStepScope localSearchStepScope) {
        super.stepTaken(localSearchStepScope);
         *= ;
    }
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