net.sf.cpsolver.coursett.heuristics
Class HeuristicSelector

java.lang.Object
  net.sf.cpsolver.coursett.heuristics.HeuristicSelector

public class HeuristicSelector
extends Object

General hierarchical selection.

We have implemented a hierarchical handling of the value selection criteria. There are three levels of comparison. At each level a weighted sum of the criteria described below is computed. Only solutions with the smallest sum are considered in the next level. The weights express how quickly a complete solution should be found. Only hard constraints are satisfied in the first level sum. Distance from the initial solution (MPP), and a weighting of major preferences (including time, classroom requirements and student conflicts), are considered in the next level. In the third level, other minor criteria are considered. In general, a criterion can be used in more than one level, e.g., with different weights.

The above sums order the values lexicographically: the best value having the smallest first level sum, the smallest second level sum among values with the smallest first level sum, and the smallest third level sum among these values. As mentioned above, this allows diversification between the importance of individual criteria.

Furthermore, the value selection heuristics also support some limits (e.g., that all values with a first level sum smaller than a given percentage Pth above the best value [typically 10%] will go to the second level comparison and so on). This allows for the continued feasibility of a value near to the best that may yet be much better in the next level of comparison. If there is more than one solution after these three levels of comparison, one is selected randomly. This approach helped us to significantly improve the quality of the resultant solutions.

In general, there can be more than three levels of these weighted sums, however three of them seem to be sufficient for spreading weights of various criteria for our problem.

Version:

CourseTT 1.1 (University Course Timetabling)
Copyright (C) 2006 Tomáš Müller
muller@unitime.org
Lazenska 391, 76314 Zlin, Czech Republic

This library 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 2.1 of the License, or (at your option) any later version.

This library 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 this library; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA

See Also:

PlacementSelection

Nested Class Summary

class

HeuristicSelector.Element An element in heuristical selection

Constructor Summary

HeuristicSelector(double[] threshKoef)
Constructor

Method Summary

boolean	add(double[] values, Object object) Adds an object to selection
Double	firstLevelThreshold()
Vector	selection() Do the selection.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

HeuristicSelector

public HeuristicSelector(double[] threshKoef)

Constructor

Parameters:

threshKoef - limit for each level, e.g., new double[] {0.1, 0.1, 0.1} for three level selection with 10% limit on each level

Method Detail

add

public boolean add(double[] values,
                   Object object)

Adds an object to selection

Parameters:

values - weighted sum for each level

object - object to be returned if selected

Returns:

true if added (it is not added if it is obvious that it cannot be selected)

firstLevelThreshold

public Double firstLevelThreshold()

selection

public Vector selection()

Do the selection.

Returns:

inserted objects which met the criteria