/* Copyright 2009-2016 David Hadka
 *
 * This file is part of the MOEA Framework.
 *
 * The MOEA Framework is free software: you can redistribute it and/or modify
 * it under the terms of the GNU Lesser General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or (at your
 * option) any later version.
 *
 * The MOEA Framework is distributed in the hope that it will be useful, but
 * WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
 * or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU Lesser General Public
 * License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public License
 * along with the MOEA Framework.  If not, see <http://www.gnu.org/licenses/>.
 */
package org.moeaframework.algorithm.single;

import java.io.Serializable;

import org.moeaframework.core.comparator.AggregateConstraintComparator;
import org.moeaframework.core.comparator.ChainedComparator;

/**
 * Weighted min-max aggregate function that supports constraints.
 * 
 * @see AggregateConstraintComparator
 * @see MinMaxObjectiveComparator
 */
public class MinMaxDominanceComparator extends ChainedComparator implements
AggregateObjectiveComparator, Serializable {

	private static final long serialVersionUID = -1433954844334603655L;

	/**
	 * Constructs a new dominance comparator using a weighted min-max aggregate
	 * function and constraints.  Equal weights are used for each objective.
	 */
	public MinMaxDominanceComparator() {
		super(new AggregateConstraintComparator(),
				new MinMaxObjectiveComparator());
	}
	
	/**
	 * Constructs a new dominance comparator using a weighted min-max aggregate
	 * function and constraints.  One weight should be given for each objective;
	 * if fewer weights are provided, the last weight is repeated for the 
	 * remaining objectives.
	 * 
	 * @param weights the weight vector
	 */
	public MinMaxDominanceComparator(double... weights) {
		super(new AggregateConstraintComparator(),
				new MinMaxObjectiveComparator(weights));
	}

}