1 /*
2 * Licensed to the Hipparchus project 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 Hipparchus project 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 * https://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 */
17 package org.hipparchus.optim.nonlinear.vector.constrained;
18
19 import org.hipparchus.optim.OptimizationData;
20
21 /** Container for {@link ADMMQPOptimizer} settings.
22 * @since 3.1
23 */
24 public class ADMMQPOption implements OptimizationData {
25
26 /** Default Absolute and Relative Tolerance for convergence. */
27 public static final double DEFAULT_EPS = 1.0e-5;
28
29 /** Default Absolute and Relative Tolerance for Infeasible Criteria. */
30 public static final double DEFAULT_EPS_INFEASIBLE = 1.0e-7;
31
32 /** Default Value of regularization term sigma for Karush–Kuhn–Tucker solver. */
33 public static final double DEFAULT_SIGMA = 1.0e-12;
34
35 /** Default Value of Alpha filter for ADMM iteration. */
36 public static final double DEFAULT_ALPHA = 1.6;
37
38 /** Default Value for Enabling Problem Scaling. */
39 public static final boolean DEFAULT_SCALING = true;
40
41 /** Default Value for the Max Iteration for the scaling. */
42 public static final int DEFAULT_SCALING_MAX_ITERATION = 10;
43
44 /** Default Value for adapting the weight during iterations. */
45 public static final boolean DEFAULT_RHO_UPDATE = true;
46
47 /** Default Max Value for the Weight for ADMM iteration. */
48 public static final double DEFAULT_RHO_MAX = 1.0e6;
49
50 /** Default Min Value for the Weight for ADMM iteration. */
51 public static final double DEFAULT_RHO_MIN = 1.0e-6;
52
53 /** Default Max number of weight changes. */
54 public static final int DEFAULT_MAX_RHO_ITERATION = 10;
55
56 /** Default Value for enabling polishing the solution. */
57 public static final boolean DEFAULT_POLISHING = false;
58
59 /** Default Value for Iteration of polishing Algorithm. */
60 public static final int DEFAULT_POLISHING_ITERATION = 5;
61
62 /** Absolute and Relative Tolerance for convergence. */
63 private double eps;
64
65 /** Absolute and Relative Tolerance for Infeasible Criteria. */
66 private double epsInfeasible;
67
68 /** Value of regularization term sigma for Karush–Kuhn–Tucker solver. */
69 private double sigma;
70
71 /** Value of alpha filter for ADMM iteration. */
72 private double alpha;
73
74 /** Scaling enabling flag. */
75 private boolean scaling;
76
77 /** Value for the Max Iteration for the scaling. */
78 private int scaleMaxIteration;
79
80 /** Value for adapt the weight during iterations. */
81 private boolean updateRho;
82
83 /** Max Value for thr Weight for ADMM iteration. */
84 private double rhoMax;
85
86 /** Min Value for the Weight for ADMM iteration. */
87 private double rhoMin;
88
89 /** Max Value of changing the weight during iterations. */
90 private int maxRhoIteration;
91
92 /** Enabling flag for polishing the solution. */
93 private boolean polishing;
94
95 /** Value for Iteration of polishing Algorithm. */
96 private int polishingIteration;
97
98 /** Simple constructor.
99 */
100 public ADMMQPOption() {
101 eps = ADMMQPOption.DEFAULT_EPS;
102 epsInfeasible = ADMMQPOption.DEFAULT_EPS_INFEASIBLE;
103 sigma = ADMMQPOption.DEFAULT_SIGMA;
104 alpha = ADMMQPOption.DEFAULT_ALPHA;
105 scaling = ADMMQPOption.DEFAULT_SCALING;
106 scaleMaxIteration = ADMMQPOption.DEFAULT_SCALING_MAX_ITERATION;
107 updateRho = ADMMQPOption.DEFAULT_RHO_UPDATE;
108 rhoMax = ADMMQPOption.DEFAULT_RHO_MAX;
109 rhoMin = ADMMQPOption.DEFAULT_RHO_MIN;
110 maxRhoIteration = ADMMQPOption.DEFAULT_MAX_RHO_ITERATION;
111 polishing = ADMMQPOption.DEFAULT_POLISHING;
112 polishingIteration = ADMMQPOption.DEFAULT_POLISHING_ITERATION;
113 }
114
115 /** Set absolute and Relative Tolerance for convergence.
116 * @param eps absolute and Relative Tolerance for convergence
117 */
118 public void setEps(final double eps) {
119 this.eps = eps;
120 }
121
122 /** Get absolute and Relative Tolerance for convergence.
123 * @return absolute and Relative Tolerance for convergence
124 */
125 public double getEps() {
126 return eps;
127 }
128
129 /** Set absolute and Relative Tolerance for infeasible criteria.
130 * @param epsInfeasible absolute and Relative Tolerance for infeasible criteria
131 */
132 public void setEpsInfeasible(final double epsInfeasible) {
133 this.epsInfeasible = epsInfeasible;
134 }
135
136 /** Get absolute and Relative Tolerance for infeasible criteria.
137 * @return absolute and Relative Tolerance for infeasible criteria
138 */
139 public double getEpsInfeasible() {
140 return epsInfeasible;
141 }
142
143 /** Set value of regularization term sigma for Karush–Kuhn–Tucker solver.
144 * @param sigma value of regularization term sigma for Karush–Kuhn–Tucker solver
145 */
146 public void setSigma(final double sigma) {
147 this.sigma = sigma;
148 }
149
150 /** Get value of regularization term sigma for Karush–Kuhn–Tucker solver.
151 * @return value of regularization term sigma for Karush–Kuhn–Tucker solver
152 */
153 public double getSigma() {
154 return sigma;
155 }
156
157 /** Set value of alpha filter for ADMM iteration.
158 * @param alpha value of alpha filter for ADMM iteration
159 */
160 public void setAlpha(final double alpha) {
161 this.alpha = alpha;
162 }
163
164 /** Get value of alpha filter for ADMM iteration.
165 * @return value of alpha filter for ADMM iteration
166 */
167 public double getAlpha() {
168 return alpha;
169 }
170
171 /** Set scaling enabling flag.
172 * @param scaling if true, scaling is enabled
173 */
174 public void setScaling(final boolean scaling) {
175 this.scaling = scaling;
176 }
177
178 /** Check if scaling is enabled.
179 * @return true if scaling is enabled
180 */
181 public boolean isScaling() {
182 return scaling;
183 }
184
185 /** Set max iteration for the scaling.
186 * @param scaleMaxIteration max iteration for the scaling
187 */
188 public void setScaleMaxIteration(final int scaleMaxIteration) {
189 this.scaleMaxIteration = scaleMaxIteration;
190 }
191
192 /** Get max iteration for the scaling.
193 * @return max iteration for the scaling
194 */
195 public int getScaleMaxIteration() {
196 return scaleMaxIteration;
197 }
198
199 /** Set weight updating flag.
200 * @param updateRho if true, weight is updated during iterations
201 */
202 public void setUpdateRho(final boolean updateRho) {
203 this.updateRho = updateRho;
204 }
205
206 /** Check if weight updating is enabled.
207 * @return true if weight is updated during iterations
208 */
209 public boolean updateRho() {
210 return updateRho;
211 }
212
213 /** Set min Value for the Weight for ADMM iteration.
214 * @param rhoMin min Value for the Weight for ADMM iteration
215 */
216 public void setRhoMin(final double rhoMin) {
217 this.rhoMin = rhoMin;
218 }
219
220 /** Get min Value for the Weight for ADMM iteration.
221 * @return min Value for the Weight for ADMM iteration
222 */
223 public double getRhoMin() {
224 return rhoMin;
225 }
226
227 /** Set max Value for the Weight for ADMM iteration.
228 * @param rhoMax max Value for the Weight for ADMM iteration
229 */
230 public void setRhoMax(final double rhoMax) {
231 this.rhoMax = rhoMax;
232 }
233
234 /** Get max Value for the Weight for ADMM iteration.
235 * @return max Value for the Weight for ADMM iteration
236 */
237 public double getRhoMax() {
238 return rhoMax;
239 }
240
241 /** Set max number of weight changes.
242 * @param maxRhoIteration max number of weight changes
243 */
244 public void setMaxRhoIteration(final int maxRhoIteration) {
245 this.maxRhoIteration = maxRhoIteration;
246 }
247
248 /** Get max number of weight changes.
249 * @return max number of weight changes
250 */
251 public int getMaxRhoIteration() {
252 return maxRhoIteration;
253 }
254
255 /** Set polishing enabling flag.
256 * @param polishing if true, polishing is enabled
257 */
258 public void setPolishing(final boolean polishing) {
259 this.polishing = polishing;
260 }
261
262 /** Check if polishing is enabled.
263 * @return true if polishing is enabled
264 */
265 public boolean isPolishing() {
266 return polishing;
267 }
268
269 /** Set number of iterations of polishing algorithm.
270 * @param polishingIteration number of iterations of polishing algorithm
271 */
272 public void setPolishingIteration(final int polishingIteration) {
273 this.polishingIteration = polishingIteration;
274 }
275
276 /** Get number of iterations of polishing algorithm.
277 * @return number of iterations of polishing algorithm
278 */
279 public int getPolishIteration() {
280 return polishingIteration;
281 }
282
283 }