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The James core module is part of the James framework for optimization using local search metaheuristics in Java. The core contains general components to model problems, objectives and constraints, as well as generic algorithms to solve the problems. Moreover, the core provides implementations of specific utilities for subset selection.
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//  Copyright 2014 Herman De Beukelaer
//
//  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.jamesframework.core.search.algo.exh;

import java.util.NoSuchElementException;
import java.util.Set;
import org.jamesframework.core.problems.solutions.SubsetSolution;

/**
 * A subset solution iterator generates all possible subsets within a given size range, given a
 * set of IDs from which to select. It can be plugged into an exhaustive search algorithm
 * to generate and evaluate all possible subset solutions.
 * 
 * The implemented generation algorithm is the revolving door algorithm from
 * "Combinatorial Algorithms: Generation, Enumeration and Search", Donald Kreher
 * and Douglas Stinson, CRC Press, 1999 (chapter 2, p. 43-52). This algorithm generates
 * k-subsets in a specific minimal change ordering called the revolving door ordering.
 * 
 * @author Herman De Beukelaer
 */
public class SubsetSolutionIterator implements SolutionIterator {

    // maximum subset size
    private final int maxSubsetSize;
    
    // collection of IDs to select from
    private final Set IDs;
    // array representation (arbitrary order)
    private final Integer[] IDsArray;
    
    // indices (in IDs array) of IDs selected in next generated subset solution
    // NOTE: last element of t is a dummy element set to |IDs|
    private int[] t;
    
    /**
     * Create a subset solution iterator that generates all subsets within the given size range,
     * sampled from the given set of IDs.
     * 
     * @param IDs set of IDs to select from 
     * @param minSubsetSize minimum subset size
     * @param maxSubsetSize maximum subset size
     * @throws NullPointerException if IDs is null
     * @throws IllegalArgumentException if IDs is empty,
     *                                     minSubsetSize ≤ 0,
     *                                     minSubsetSize > |IDs|,
     *                                     or minSubsetSize > maxSubsetSize
     */
    public SubsetSolutionIterator(Set IDs, int minSubsetSize, int maxSubsetSize){
        // check collection of IDs
        if(IDs.isEmpty()){
            throw new IllegalArgumentException("Error while creating subset solution iterator: collection of IDs to select from "
                                                + "can not be empty.");
        }
        // store set of IDs
        this.IDs = IDs;
        // convert set of IDs to array (impose arbitrary order)
        this.IDsArray = IDs.toArray(new Integer[0]);
        // check minimum/maximum size
        if(minSubsetSize <= 0){
            throw new IllegalArgumentException("Error while creating subset solution iterator: minimum subset size should be "
                                                + "strictly positive.");
        }
        if(minSubsetSize > IDs.size()){
            throw new IllegalArgumentException("Error while creating subset solution iterator: minimum subset size can not be "
                                                + "larger than number of IDs to select from.");
        }
        if(minSubsetSize > maxSubsetSize){
            throw new IllegalArgumentException("Error while creating subset solution iterator: minimum subset size can not be "
                                                + "larger than maximum subset size.");
        }
        // set indices of selected IDs in first generated solution (t = {0,1,...,k-1}, with k = minimum subset size)
        t = new int[minSubsetSize+1];
        for(int i=0; iIDs is null
     * @throws IllegalArgumentException if IDs is empty,
     *                                     fixedSubsetSize ≤ 0,
     *                                     or fixedSubsetSize > |IDs|
     */
    public SubsetSolutionIterator(Set IDs, int fixedSubsetSize){
        this(IDs, fixedSubsetSize, fixedSubsetSize);
    }
    
    /**
     * Checks whether more subset solutions are to be generated.
     * 
     * @return true if not all possible subsets of all valid size have already been generated
     */
    @Override
    public boolean hasNext() {
        return t != null;
    }

    /**
     * Generate the next subset solution. The returned subset will either have the same size as the previously generated solution,
     * if any, or it will be a larger subset.
     * 
     * @return next subset solution within the size bounds
     * @throws NoSuchElementException if there is no next solution to be generated
     */
    @Override
    public SubsetSolution next() {
        // check if there is a next solution to generate
        if(!hasNext()){
            throw new NoSuchElementException("No more subset solutions to be generated.");
        }
        // create subset solution based on currently selected indices (returned at the end of the method)
        SubsetSolution sol = new SubsetSolution(IDs);
        for(int i=0; i= 0){
                        t[j-2] = j-1;
                    }
                }
            } else {
                if(t[j+1] != t[j]+1){
                    if(j-1 >= 0){
                        t[j-1] = t[j];
                    }
                    t[j] = t[j] + 1;
                } else {
                    t[j+1] = t[j];
                    t[j] = j;
                }
            }
        }
        
        // return current solution
        return sol;
    }

}