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authorDaniel Baumann <daniel.baumann@progress-linux.org>2024-04-07 09:06:44 +0000
committerDaniel Baumann <daniel.baumann@progress-linux.org>2024-04-07 09:06:44 +0000
commited5640d8b587fbcfed7dd7967f3de04b37a76f26 (patch)
tree7a5f7c6c9d02226d7471cb3cc8fbbf631b415303 /nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/encode/EvalStruct.java
parentInitial commit. (diff)
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Adding upstream version 4:7.4.7.upstream/4%7.4.7upstream
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
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+/**
+ * Description: provide the information for evaluating a set of targets values
+ * into encoded information (For formation the goodness landscape by comparing)
+ *
+ * Author Create/Modi Note
+ * Xiaofeng Xie Mar 1, 2003
+ * Xiaofeng Xie May 11, 2004
+ *
+ * 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.
+ *
+ * Please acknowledge the author(s) if you use this code in any way.
+ *
+ * @References:
+ * [1] Deb K. An efficient constraint handling method for genetic algorithms.
+ * Computer Methods in Applied Mechanics and Engineering, 2000, 186(2-4): 311-338
+ */
+
+package net.adaptivebox.encode;
+
+public class EvalStruct {
+ // The information for evaluating all the responses
+ private EvalElement[] evalElems = null;
+
+ public EvalStruct(int elemsNum) {
+ evalElems = new EvalElement[elemsNum];
+ }
+
+ public void setElemAt(EvalElement dim, int index) {
+ evalElems[index] = dim;
+ }
+
+ // convert response values into encoded information double[2]
+ public void evaluate(double[] evalRes, double[] targetValues) {
+ evalRes[0] = evalRes[1] = 0;
+ for (int i = 0; i < evalElems.length; i++) {
+ if (evalElems[i].isOptType()) {
+ // The objectives (OPTIM type)
+ // The multi-objective will be translated into single-objective
+ evalRes[1] += evalElems[i].evaluateOPTIM(targetValues[i]);
+ } else {
+ // The constraints (CONS type)
+ // If evalRes[0] equals to 0, then be a feasible point, i.e. satisfies
+ // all the constraints
+ evalRes[0] += evalElems[i].evaluateCONS(targetValues[i]);
+ }
+ }
+ }
+}