source: src/main/java/agents/anac/y2019/harddealer/math3/genetics/RandomKey.java

Last change on this file was 204, checked in by Katsuhide Fujita, 5 years ago

Fixed errors of ANAC2019 agents

  • Property svn:executable set to *
File size: 11.5 KB
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1/*
2 * Licensed to the Apache Software Foundation (ASF) under one or more
3 * contributor license agreements. See the NOTICE file distributed with
4 * this work for additional information regarding copyright ownership.
5 * The ASF licenses this file to You under the Apache License, Version 2.0
6 * (the "License"); you may not use this file except in compliance with
7 * the License. You may obtain a copy of the License at
8 *
9 * http://www.apache.org/licenses/LICENSE-2.0
10 *
11 * Unless required by applicable law or agreed to in writing, software
12 * distributed under the License is distributed on an "AS IS" BASIS,
13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 * See the License for the specific language governing permissions and
15 * limitations under the License.
16 */
17package agents.anac.y2019.harddealer.math3.genetics;
18
19import java.util.ArrayList;
20import java.util.Arrays;
21import java.util.Collections;
22import java.util.Comparator;
23import java.util.List;
24
25import agents.anac.y2019.harddealer.math3.exception.DimensionMismatchException;
26import agents.anac.y2019.harddealer.math3.exception.MathIllegalArgumentException;
27import agents.anac.y2019.harddealer.math3.exception.util.LocalizedFormats;
28
29/**
30 * Random Key chromosome is used for permutation representation. It is a vector
31 * of a fixed length of real numbers in [0,1] interval. The index of the i-th
32 * smallest value in the vector represents an i-th member of the permutation.
33 * <p>
34 * For example, the random key [0.2, 0.3, 0.8, 0.1] corresponds to the
35 * permutation of indices (3,0,1,2). If the original (unpermuted) sequence would
36 * be (a,b,c,d), this would mean the sequence (d,a,b,c).
37 * <p>
38 * With this representation, common operators like n-point crossover can be
39 * used, because any such chromosome represents a valid permutation.
40 * <p>
41 * Since the chromosome (and thus its arrayRepresentation) is immutable, the
42 * array representation is sorted only once in the constructor.
43 * <p>
44 * For details, see:
45 * <ul>
46 * <li>Bean, J.C.: Genetic algorithms and random keys for sequencing and
47 * optimization. ORSA Journal on Computing 6 (1994) 154-160</li>
48 * <li>Rothlauf, F.: Representations for Genetic and Evolutionary Algorithms.
49 * Volume 104 of Studies in Fuzziness and Soft Computing. Physica-Verlag,
50 * Heidelberg (2002)</li>
51 * </ul>
52 *
53 * @param <T> type of the permuted objects
54 * @since 2.0
55 */
56public abstract class RandomKey<T> extends AbstractListChromosome<Double> implements PermutationChromosome<T> {
57
58 /** Cache of sorted representation (unmodifiable). */
59 private final List<Double> sortedRepresentation;
60
61 /**
62 * Base sequence [0,1,...,n-1], permuted according to the representation (unmodifiable).
63 */
64 private final List<Integer> baseSeqPermutation;
65
66 /**
67 * Constructor.
68 *
69 * @param representation list of [0,1] values representing the permutation
70 * @throws InvalidRepresentationException iff the <code>representation</code> can not represent a valid chromosome
71 */
72 public RandomKey(final List<Double> representation) throws InvalidRepresentationException {
73 super(representation);
74 // store the sorted representation
75 List<Double> sortedRepr = new ArrayList<Double> (getRepresentation());
76 Collections.sort(sortedRepr);
77 sortedRepresentation = Collections.unmodifiableList(sortedRepr);
78 // store the permutation of [0,1,...,n-1] list for toString() and isSame() methods
79 baseSeqPermutation = Collections.unmodifiableList(
80 decodeGeneric(baseSequence(getLength()), getRepresentation(), sortedRepresentation)
81 );
82 }
83
84 /**
85 * Constructor.
86 *
87 * @param representation array of [0,1] values representing the permutation
88 * @throws InvalidRepresentationException iff the <code>representation</code> can not represent a valid chromosome
89 */
90 public RandomKey(final Double[] representation) throws InvalidRepresentationException {
91 this(Arrays.asList(representation));
92 }
93
94 /**
95 * {@inheritDoc}
96 */
97 public List<T> decode(final List<T> sequence) {
98 return decodeGeneric(sequence, getRepresentation(), sortedRepresentation);
99 }
100
101 /**
102 * Decodes a permutation represented by <code>representation</code> and
103 * returns a (generic) list with the permuted values.
104 *
105 * @param <S> generic type of the sequence values
106 * @param sequence the unpermuted sequence
107 * @param representation representation of the permutation ([0,1] vector)
108 * @param sortedRepr sorted <code>representation</code>
109 * @return list with the sequence values permuted according to the representation
110 * @throws DimensionMismatchException iff the length of the <code>sequence</code>,
111 * <code>representation</code> or <code>sortedRepr</code> lists are not equal
112 */
113 private static <S> List<S> decodeGeneric(final List<S> sequence, List<Double> representation,
114 final List<Double> sortedRepr)
115 throws DimensionMismatchException {
116
117 int l = sequence.size();
118
119 // the size of the three lists must be equal
120 if (representation.size() != l) {
121 throw new DimensionMismatchException(representation.size(), l);
122 }
123 if (sortedRepr.size() != l) {
124 throw new DimensionMismatchException(sortedRepr.size(), l);
125 }
126
127 // do not modify the original representation
128 List<Double> reprCopy = new ArrayList<Double> (representation);
129
130 // now find the indices in the original repr and use them for permuting
131 List<S> res = new ArrayList<S> (l);
132 for (int i=0; i<l; i++) {
133 int index = reprCopy.indexOf(sortedRepr.get(i));
134 res.add(sequence.get(index));
135 reprCopy.set(index, null);
136 }
137 return res;
138 }
139
140 /**
141 * Returns <code>true</code> iff <code>another</code> is a RandomKey and
142 * encodes the same permutation.
143 *
144 * @param another chromosome to compare
145 * @return true iff chromosomes encode the same permutation
146 */
147 @Override
148 protected boolean isSame(final Chromosome another) {
149 // type check
150 if (! (another instanceof RandomKey<?>)) {
151 return false;
152 }
153 RandomKey<?> anotherRk = (RandomKey<?>) another;
154 // size check
155 if (getLength() != anotherRk.getLength()) {
156 return false;
157 }
158
159 // two different representations can still encode the same permutation
160 // the ordering is what counts
161 List<Integer> thisPerm = this.baseSeqPermutation;
162 List<Integer> anotherPerm = anotherRk.baseSeqPermutation;
163
164 for (int i=0; i<getLength(); i++) {
165 if (thisPerm.get(i) != anotherPerm.get(i)) {
166 return false;
167 }
168 }
169 // the permutations are the same
170 return true;
171 }
172
173 /**
174 * {@inheritDoc}
175 */
176 @Override
177 protected void checkValidity(final List<Double> chromosomeRepresentation)
178 throws InvalidRepresentationException {
179
180 for (double val : chromosomeRepresentation) {
181 if (val < 0 || val > 1) {
182 throw new InvalidRepresentationException(LocalizedFormats.OUT_OF_RANGE_SIMPLE,
183 val, 0, 1);
184 }
185 }
186 }
187
188
189 /**
190 * Generates a representation corresponding to a random permutation of
191 * length l which can be passed to the RandomKey constructor.
192 *
193 * @param l length of the permutation
194 * @return representation of a random permutation
195 */
196 public static final List<Double> randomPermutation(final int l) {
197 List<Double> repr = new ArrayList<Double>(l);
198 for (int i=0; i<l; i++) {
199 repr.add(GeneticAlgorithm.getRandomGenerator().nextDouble());
200 }
201 return repr;
202 }
203
204 /**
205 * Generates a representation corresponding to an identity permutation of
206 * length l which can be passed to the RandomKey constructor.
207 *
208 * @param l length of the permutation
209 * @return representation of an identity permutation
210 */
211 public static final List<Double> identityPermutation(final int l) {
212 List<Double> repr = new ArrayList<Double>(l);
213 for (int i=0; i<l; i++) {
214 repr.add((double)i/l);
215 }
216 return repr;
217 }
218
219 /**
220 * Generates a representation of a permutation corresponding to the
221 * <code>data</code> sorted by <code>comparator</code>. The
222 * <code>data</code> is not modified during the process.
223 *
224 * This is useful if you want to inject some permutations to the initial
225 * population.
226 *
227 * @param <S> type of the data
228 * @param data list of data determining the order
229 * @param comparator how the data will be compared
230 * @return list representation of the permutation corresponding to the parameters
231 */
232 public static <S> List<Double> comparatorPermutation(final List<S> data,
233 final Comparator<S> comparator) {
234 List<S> sortedData = new ArrayList<S>(data);
235 Collections.sort(sortedData, comparator);
236
237 return inducedPermutation(data, sortedData);
238 }
239
240 /**
241 * Generates a representation of a permutation corresponding to a
242 * permutation which yields <code>permutedData</code> when applied to
243 * <code>originalData</code>.
244 *
245 * This method can be viewed as an inverse to {@link #decode(List)}.
246 *
247 * @param <S> type of the data
248 * @param originalData the original, unpermuted data
249 * @param permutedData the data, somehow permuted
250 * @return representation of a permutation corresponding to the permutation
251 * <code>originalData -> permutedData</code>
252 * @throws DimensionMismatchException iff the length of <code>originalData</code>
253 * and <code>permutedData</code> lists are not equal
254 * @throws MathIllegalArgumentException iff the <code>permutedData</code> and
255 * <code>originalData</code> lists contain different data
256 */
257 public static <S> List<Double> inducedPermutation(final List<S> originalData,
258 final List<S> permutedData)
259 throws DimensionMismatchException, MathIllegalArgumentException {
260
261 if (originalData.size() != permutedData.size()) {
262 throw new DimensionMismatchException(permutedData.size(), originalData.size());
263 }
264 int l = originalData.size();
265
266 List<S> origDataCopy = new ArrayList<S> (originalData);
267
268 Double[] res = new Double[l];
269 for (int i=0; i<l; i++) {
270 int index = origDataCopy.indexOf(permutedData.get(i));
271 if (index == -1) {
272 throw new MathIllegalArgumentException(LocalizedFormats.DIFFERENT_ORIG_AND_PERMUTED_DATA);
273 }
274 res[index] = (double) i / l;
275 origDataCopy.set(index, null);
276 }
277 return Arrays.asList(res);
278 }
279
280 /** {@inheritDoc} */
281 @Override
282 public String toString() {
283 return String.format("(f=%s pi=(%s))", getFitness(), baseSeqPermutation);
284 }
285
286 /**
287 * Helper for constructor. Generates a list of natural numbers (0,1,...,l-1).
288 *
289 * @param l length of list to generate
290 * @return list of integers from 0 to l-1
291 */
292 private static List<Integer> baseSequence(final int l) {
293 List<Integer> baseSequence = new ArrayList<Integer> (l);
294 for (int i=0; i<l; i++) {
295 baseSequence.add(i);
296 }
297 return baseSequence;
298 }
299}
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