/**
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You 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.apache.mahout.ga.watchmaker.travellingsalesman;

import java.util.List;

import org.uncommons.watchmaker.framework.FitnessEvaluator;

/**
 * Fitness evalator that measures the total distance of a route in the travelling salesman problem. The
 * fitness score of a route is the total distance (in km). A route is represented as a list of cities in the
 * order that they will be visited. The last leg of the journey is from the last city in the list back to the
 * first.
 * 
 * <br>
 * The original code is from <b>the Watchmaker project</b> (https://watchmaker.dev.java.net/).
 */
public class RouteEvaluator implements FitnessEvaluator<List<String>> {
  private final DistanceLookup distances;
  
  /**
   * @param distances
   *          Provides distances between a set of cities.
   */
  public RouteEvaluator(DistanceLookup distances) {
    this.distances = distances;
  }
  
  /**
   * Calculates the length of an evolved route.
   * 
   * @param candidate
   *          The route to evaluate.
   * @param population
   *          {@inheritDoc}
   * @return The total distance (in kilometres) of a journey that visits each city in order and returns to the
   *         starting point.
   */
  @Override
  public double getFitness(List<String> candidate, List<? extends List<String>> population) {
    int totalDistance = 0;
    int cityCount = candidate.size();
    for (int i = 0; i < cityCount; i++) {
      int nextIndex = i < cityCount - 1 ? i + 1 : 0;
      totalDistance += distances.getDistance(candidate.get(i), candidate.get(nextIndex));
    }
    return totalDistance;
  }
  
  /**
   * {@inheritDoc} Returns false since shorter distances represent fitter candidates.
   * 
   * @return false
   */
  @Override
  public boolean isNatural() {
    return false;
  }
}