[Libreoffice-commits] core.git: nlpsolver/ThirdParty
Noel Grandin
noel at peralex.com
Thu Aug 7 02:39:21 PDT 2014
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/DEPSAgent.java | 254 ++++-----
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/AbsGTBehavior.java | 72 +-
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/DEGTBehavior.java | 162 ++---
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/PSGTBehavior.java | 234 ++++----
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/encode/IEncodeEngine.java | 48 -
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/BasicArray.java | 62 +-
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/BasicBound.java | 186 +++---
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/BasicTag.java | 80 +-
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/CompareValue.java | 40 -
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/GlobalCompare.java | 88 +--
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/IUpdateCycleEngine.java | 46 -
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/problem/ProblemEncoder.java | 246 ++++----
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/problem/UnconstrainedProblemEncoder.java | 78 +-
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/DesignSpace.java | 282 +++++-----
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/ILocationEngine.java | 50 -
15 files changed, 964 insertions(+), 964 deletions(-)
New commits:
commit 414a6e4e0ce35ead40d2a0476f18fba1f746b7bf
Author: Noel Grandin <noel at peralex.com>
Date: Thu Aug 7 11:37:32 2014 +0200
convert EvolutionarySolver source to unix LF
so I dont keep getting problems when moving patches between Windows
and Linux
Change-Id: Ia2323ecb388bf5996279686e1bd2b1676c5ae213
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/DEPSAgent.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/DEPSAgent.java
index 02043f5..3107fa8 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/DEPSAgent.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/DEPSAgent.java
@@ -1,127 +1,127 @@
-package net.adaptivebox.deps;
-
-/**
- * Description: The description of agent with hybrid differential evolution and particle swarm.
- *
- * @ Author Create/Modi Note
- * Xiaofeng Xie Jun 10, 2004
- * Xiaofeng Xie Jul 01, 2008
- *
- * 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.
- *
- * @version 1.0
- * @Since MAOS1.0
- *
- * @References:
- * [1] Zhang W J, Xie X F. DEPSO: hybrid particle swarm with differential
- * evolution operator. IEEE International Conference on Systems, Man & Cybernetics,
- * Washington D C, USA, 2003: 3816-3821
- * [2] X F Xie, W J Zhang. SWAF: swarm algorithm framework for numerical
- * optimization. Genetic and Evolutionary Computation Conference (GECCO),
- * Seattle, WA, USA, 2004: 238-250
- * -> an agent perspective
- */
-
-import net.adaptivebox.deps.behavior.*;
-import net.adaptivebox.goodness.IGoodnessCompareEngine;
-import net.adaptivebox.knowledge.*;
-import net.adaptivebox.problem.*;
-import net.adaptivebox.space.*;
-
-public class DEPSAgent implements ILibEngine {
-
- //Describes the problem to be solved
- protected ProblemEncoder problemEncoder;
- //Forms the goodness landscape
- protected IGoodnessCompareEngine qualityComparator;
-
- //store the point that generated in current learning cycle
- protected SearchPoint trailPoint;
-
- //temp variable
- private AbsGTBehavior selectGTBehavior;
-
- //The referred library
- protected Library socialLib;
- //the own memory: store the point that generated in old learning cycle
- protected BasicPoint pold_t;
- //the own memory: store the point that generated in last learning cycle
- protected BasicPoint pcurrent_t;
- //the own memory: store the personal best point
- protected SearchPoint pbest_t;
-
- //Generate-and-test Behaviors
- protected DEGTBehavior deGTBehavior;
- protected PSGTBehavior psGTBehavior;
- public double switchP = 0.5;
-
- public void setLibrary(Library lib) {
- socialLib = lib;
- deGTBehavior.setLibrary(socialLib);
- psGTBehavior.setLibrary(socialLib);
- }
-
- public void setProblemEncoder(ProblemEncoder encoder) {
- problemEncoder = encoder;
- trailPoint = problemEncoder.getFreshSearchPoint();
- pold_t = problemEncoder.getFreshSearchPoint();
- pcurrent_t = problemEncoder.getFreshSearchPoint();
- }
-
- public void setSpecComparator(IGoodnessCompareEngine comparer) {
- qualityComparator = comparer;
- }
-
- public void setPbest(SearchPoint pbest) {
- pbest_t = pbest;
- }
-
- protected AbsGTBehavior getGTBehavior() {
- if (Math.random()<switchP) {
- return deGTBehavior;
- } else {
- return psGTBehavior;
- }
- }
-
- public void setGTBehavior(AbsGTBehavior gtBehavior) {
- if (gtBehavior instanceof DEGTBehavior) {
- deGTBehavior = ((DEGTBehavior)gtBehavior);
- deGTBehavior.setPbest(pbest_t);
- return;
- }
- if (gtBehavior instanceof PSGTBehavior) {
- psGTBehavior = ((PSGTBehavior)gtBehavior);
- psGTBehavior.setMemPoints(pbest_t, pcurrent_t, pold_t);
- return;
- }
- }
-
- public void generatePoint() {
- // generates a new point in the search space (S) based on
- // its memory and the library
- selectGTBehavior = this.getGTBehavior();
- selectGTBehavior.generateBehavior(trailPoint, problemEncoder);
- //evaluate into goodness information
- problemEncoder.evaluate(trailPoint);
- }
-
- public void learn() {
- selectGTBehavior.testBehavior(trailPoint, qualityComparator);
- }
-
- public SearchPoint getMGState() {
- return trailPoint;
- }
-}
-
+package net.adaptivebox.deps;
+
+/**
+ * Description: The description of agent with hybrid differential evolution and particle swarm.
+ *
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie Jun 10, 2004
+ * Xiaofeng Xie Jul 01, 2008
+ *
+ * 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.
+ *
+ * @version 1.0
+ * @Since MAOS1.0
+ *
+ * @References:
+ * [1] Zhang W J, Xie X F. DEPSO: hybrid particle swarm with differential
+ * evolution operator. IEEE International Conference on Systems, Man & Cybernetics,
+ * Washington D C, USA, 2003: 3816-3821
+ * [2] X F Xie, W J Zhang. SWAF: swarm algorithm framework for numerical
+ * optimization. Genetic and Evolutionary Computation Conference (GECCO),
+ * Seattle, WA, USA, 2004: 238-250
+ * -> an agent perspective
+ */
+
+import net.adaptivebox.deps.behavior.*;
+import net.adaptivebox.goodness.IGoodnessCompareEngine;
+import net.adaptivebox.knowledge.*;
+import net.adaptivebox.problem.*;
+import net.adaptivebox.space.*;
+
+public class DEPSAgent implements ILibEngine {
+
+ //Describes the problem to be solved
+ protected ProblemEncoder problemEncoder;
+ //Forms the goodness landscape
+ protected IGoodnessCompareEngine qualityComparator;
+
+ //store the point that generated in current learning cycle
+ protected SearchPoint trailPoint;
+
+ //temp variable
+ private AbsGTBehavior selectGTBehavior;
+
+ //The referred library
+ protected Library socialLib;
+ //the own memory: store the point that generated in old learning cycle
+ protected BasicPoint pold_t;
+ //the own memory: store the point that generated in last learning cycle
+ protected BasicPoint pcurrent_t;
+ //the own memory: store the personal best point
+ protected SearchPoint pbest_t;
+
+ //Generate-and-test Behaviors
+ protected DEGTBehavior deGTBehavior;
+ protected PSGTBehavior psGTBehavior;
+ public double switchP = 0.5;
+
+ public void setLibrary(Library lib) {
+ socialLib = lib;
+ deGTBehavior.setLibrary(socialLib);
+ psGTBehavior.setLibrary(socialLib);
+ }
+
+ public void setProblemEncoder(ProblemEncoder encoder) {
+ problemEncoder = encoder;
+ trailPoint = problemEncoder.getFreshSearchPoint();
+ pold_t = problemEncoder.getFreshSearchPoint();
+ pcurrent_t = problemEncoder.getFreshSearchPoint();
+ }
+
+ public void setSpecComparator(IGoodnessCompareEngine comparer) {
+ qualityComparator = comparer;
+ }
+
+ public void setPbest(SearchPoint pbest) {
+ pbest_t = pbest;
+ }
+
+ protected AbsGTBehavior getGTBehavior() {
+ if (Math.random()<switchP) {
+ return deGTBehavior;
+ } else {
+ return psGTBehavior;
+ }
+ }
+
+ public void setGTBehavior(AbsGTBehavior gtBehavior) {
+ if (gtBehavior instanceof DEGTBehavior) {
+ deGTBehavior = ((DEGTBehavior)gtBehavior);
+ deGTBehavior.setPbest(pbest_t);
+ return;
+ }
+ if (gtBehavior instanceof PSGTBehavior) {
+ psGTBehavior = ((PSGTBehavior)gtBehavior);
+ psGTBehavior.setMemPoints(pbest_t, pcurrent_t, pold_t);
+ return;
+ }
+ }
+
+ public void generatePoint() {
+ // generates a new point in the search space (S) based on
+ // its memory and the library
+ selectGTBehavior = this.getGTBehavior();
+ selectGTBehavior.generateBehavior(trailPoint, problemEncoder);
+ //evaluate into goodness information
+ problemEncoder.evaluate(trailPoint);
+ }
+
+ public void learn() {
+ selectGTBehavior.testBehavior(trailPoint, qualityComparator);
+ }
+
+ public SearchPoint getMGState() {
+ return trailPoint;
+ }
+}
+
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/AbsGTBehavior.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/AbsGTBehavior.java
index 159ce7c..b4b9b4c 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/AbsGTBehavior.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/AbsGTBehavior.java
@@ -1,36 +1,36 @@
-/**
- * Description: The description of generate-and-test behavior.
- *
- *
- * @ Author Create/Modi Note
- * Xiaofeng Xie May 17, 2004
- * Xiaofeng Xie Jul 01, 2008
- *
- * @version 1.0
- * @Since MAOS1.0
- *
- * @References:
- * [1] X F Xie, W J Zhang. SWAF: swarm algorithm framework for numerical
- * optimization. Genetic and Evolutionary Computation Conference (GECCO),
- * Seattle, WA, USA, 2004: 238-250
- * -> a generate-and-test behavior
- */
-package net.adaptivebox.deps.behavior;
-
-import net.adaptivebox.goodness.*;
-import net.adaptivebox.knowledge.*;
-import net.adaptivebox.problem.*;
-
-abstract public class AbsGTBehavior {
- //The referred social library
- protected Library socialLib;
-
- public void setLibrary(Library lib) {
- socialLib = lib;
- }
-
- abstract public void generateBehavior(SearchPoint trailPoint, ProblemEncoder problemEncoder);
-
- abstract public void testBehavior(SearchPoint trailPoint, IGoodnessCompareEngine qualityComparator);
-}
-
+/**
+ * Description: The description of generate-and-test behavior.
+ *
+ *
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie May 17, 2004
+ * Xiaofeng Xie Jul 01, 2008
+ *
+ * @version 1.0
+ * @Since MAOS1.0
+ *
+ * @References:
+ * [1] X F Xie, W J Zhang. SWAF: swarm algorithm framework for numerical
+ * optimization. Genetic and Evolutionary Computation Conference (GECCO),
+ * Seattle, WA, USA, 2004: 238-250
+ * -> a generate-and-test behavior
+ */
+package net.adaptivebox.deps.behavior;
+
+import net.adaptivebox.goodness.*;
+import net.adaptivebox.knowledge.*;
+import net.adaptivebox.problem.*;
+
+abstract public class AbsGTBehavior {
+ //The referred social library
+ protected Library socialLib;
+
+ public void setLibrary(Library lib) {
+ socialLib = lib;
+ }
+
+ abstract public void generateBehavior(SearchPoint trailPoint, ProblemEncoder problemEncoder);
+
+ abstract public void testBehavior(SearchPoint trailPoint, IGoodnessCompareEngine qualityComparator);
+}
+
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/DEGTBehavior.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/DEGTBehavior.java
index 50666ff..7867fdb 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/DEGTBehavior.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/DEGTBehavior.java
@@ -1,81 +1,81 @@
-/**
- * Description: The description of differential evolution Generate-and-Test Behavior.
-
- #Supported parameters:
- NAME VALUE_type Range DefaultV Description
- FACTOR real (0, 1.2] 0.5 DEAgent: scale constant
- CR real [0, 1] 0.9 DEAgent: crossover constant
- //Other choices for FACTOR and CR: (0.5, 0.1)
-
- *
- * @ Author Create/Modi Note
- * Xiaofeng Xie May 11, 2004
- * Xiaofeng Xie Jul 01, 2008
- *
- * @version 1.0
- * @Since MAOS1.0
- *
- * @References:
- * [1] Storn R, Price K. Differential evolution - a simple and efficient
- * heuristic for global optimization over continuous spaces. Journal of
- * Global Optimization, 1997, 11: 341-359
- * @ The original differential evolution idea
- * [2] X F Xie, W J Zhang. SWAF: swarm algorithm framework for numerical
- * optimization. Genetic and Evolutionary Computation Conference (GECCO),
- * Seattle, WA, USA, 2004: 238-250
- * -> a generate-and-test behavior
- */
-
-package net.adaptivebox.deps.behavior;
-
-import net.adaptivebox.goodness.*;
-import net.adaptivebox.global.*;
-import net.adaptivebox.knowledge.*;
-import net.adaptivebox.problem.*;
-import net.adaptivebox.space.*;
-
-public class DEGTBehavior extends AbsGTBehavior implements ILibEngine {
- public int DVNum = 2; //Number of differential vectors, normally be 1 or 2
- public double FACTOR = 0.5; //scale constant: (0, 1.2], normally be 0.5
- public double CR = 0.9; //crossover constant: [0, 1], normally be 0.1 or 0.9
-
- //the own memory: store the point that generated in last learning cycle
- protected SearchPoint pbest_t;
-
- public void setPbest(SearchPoint pbest) {
- pbest_t = pbest;
- }
-
- public void generateBehavior(SearchPoint trailPoint, ProblemEncoder problemEncoder) {
- SearchPoint gbest_t = socialLib.getGbest();
-
- BasicPoint[] referPoints = getReferPoints();
- int DIMENSION = problemEncoder.getDesignSpace().getDimension();
- int rj = RandomGenerator.intRangeRandom(0, DIMENSION-1);
- for (int k=0; k<DIMENSION; k++) {
- if (Math.random()<CR || k == DIMENSION-1) {
- double Dabcd = 0;
- for(int i=0; i<referPoints.length; i++) {
- Dabcd += Math.pow(-1, i%2)*referPoints[i].getLocation()[rj];
- }
- trailPoint.getLocation()[rj] = gbest_t.getLocation()[rj]+FACTOR*Dabcd;
- } else {
- trailPoint.getLocation()[rj] = pbest_t.getLocation()[rj];
- }
- rj = (rj+1)%DIMENSION;
- }
- }
-
- public void testBehavior(SearchPoint trailPoint, IGoodnessCompareEngine qualityComparator) {
- Library.replace(qualityComparator, trailPoint, pbest_t);
- }
-
- protected SearchPoint[] getReferPoints() {
- SearchPoint[] referPoints = new SearchPoint[DVNum*2];
- for(int i=0; i<referPoints.length; i++) {
- referPoints[i] = socialLib.getSelectedPoint(RandomGenerator.intRangeRandom(0, socialLib.getPopSize()-1));
- }
- return referPoints;
- }
-}
-
+/**
+ * Description: The description of differential evolution Generate-and-Test Behavior.
+
+ #Supported parameters:
+ NAME VALUE_type Range DefaultV Description
+ FACTOR real (0, 1.2] 0.5 DEAgent: scale constant
+ CR real [0, 1] 0.9 DEAgent: crossover constant
+ //Other choices for FACTOR and CR: (0.5, 0.1)
+
+ *
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie May 11, 2004
+ * Xiaofeng Xie Jul 01, 2008
+ *
+ * @version 1.0
+ * @Since MAOS1.0
+ *
+ * @References:
+ * [1] Storn R, Price K. Differential evolution - a simple and efficient
+ * heuristic for global optimization over continuous spaces. Journal of
+ * Global Optimization, 1997, 11: 341-359
+ * @ The original differential evolution idea
+ * [2] X F Xie, W J Zhang. SWAF: swarm algorithm framework for numerical
+ * optimization. Genetic and Evolutionary Computation Conference (GECCO),
+ * Seattle, WA, USA, 2004: 238-250
+ * -> a generate-and-test behavior
+ */
+
+package net.adaptivebox.deps.behavior;
+
+import net.adaptivebox.goodness.*;
+import net.adaptivebox.global.*;
+import net.adaptivebox.knowledge.*;
+import net.adaptivebox.problem.*;
+import net.adaptivebox.space.*;
+
+public class DEGTBehavior extends AbsGTBehavior implements ILibEngine {
+ public int DVNum = 2; //Number of differential vectors, normally be 1 or 2
+ public double FACTOR = 0.5; //scale constant: (0, 1.2], normally be 0.5
+ public double CR = 0.9; //crossover constant: [0, 1], normally be 0.1 or 0.9
+
+ //the own memory: store the point that generated in last learning cycle
+ protected SearchPoint pbest_t;
+
+ public void setPbest(SearchPoint pbest) {
+ pbest_t = pbest;
+ }
+
+ public void generateBehavior(SearchPoint trailPoint, ProblemEncoder problemEncoder) {
+ SearchPoint gbest_t = socialLib.getGbest();
+
+ BasicPoint[] referPoints = getReferPoints();
+ int DIMENSION = problemEncoder.getDesignSpace().getDimension();
+ int rj = RandomGenerator.intRangeRandom(0, DIMENSION-1);
+ for (int k=0; k<DIMENSION; k++) {
+ if (Math.random()<CR || k == DIMENSION-1) {
+ double Dabcd = 0;
+ for(int i=0; i<referPoints.length; i++) {
+ Dabcd += Math.pow(-1, i%2)*referPoints[i].getLocation()[rj];
+ }
+ trailPoint.getLocation()[rj] = gbest_t.getLocation()[rj]+FACTOR*Dabcd;
+ } else {
+ trailPoint.getLocation()[rj] = pbest_t.getLocation()[rj];
+ }
+ rj = (rj+1)%DIMENSION;
+ }
+ }
+
+ public void testBehavior(SearchPoint trailPoint, IGoodnessCompareEngine qualityComparator) {
+ Library.replace(qualityComparator, trailPoint, pbest_t);
+ }
+
+ protected SearchPoint[] getReferPoints() {
+ SearchPoint[] referPoints = new SearchPoint[DVNum*2];
+ for(int i=0; i<referPoints.length; i++) {
+ referPoints[i] = socialLib.getSelectedPoint(RandomGenerator.intRangeRandom(0, socialLib.getPopSize()-1));
+ }
+ return referPoints;
+ }
+}
+
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/PSGTBehavior.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/PSGTBehavior.java
index b4ae001..c1e8db0 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/PSGTBehavior.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/PSGTBehavior.java
@@ -1,117 +1,117 @@
-/**
- * Description: The description of particle swarm (PS) Generate-and-test Behavior.
- *
- #Supported parameters:
- NAME VALUE_type Range DefaultV Description
- c1 real [0, 2] 1.494 PSAgent: learning factor for pbest
- c2 real [0, 2] 1.494 PSAgent: learning factor for gbest
- w real [0, 1] 0.729 PSAgent: inertia weight
- CL real [0, 0.1] 0 PSAgent: chaos factor
- //Other choices for c1, c2, w, and CL: (2, 2, 0.4, 0.001)
-
- * @ Author Create/Modi Note
- * Xiaofeng Xie May 11, 2004
- * Xiaofeng Xie Jul 01, 2008
- *
- * 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.
- *
- * @version 1.0
- * @Since MAOS1.0
- *
- * @References:
- * [1] Kennedy J, Eberhart R C. Particle swarm optimization. IEEE Int. Conf. on
- * Neural Networks, Perth, Australia, 1995: 1942-1948
- * @ For original particle swarm idea
- * [2] Shi Y H, Eberhart R C. A Modified Particle Swarm Optimizer. IEEE Inter. Conf.
- * on Evolutionary Computation, Anchorage, Alaska, 1998: 69-73
- * @ For the inertia weight: adjust the trade-off between exploitation & exploration
- * [3] Clerc M, Kennedy J. The particle swarm - explosion, stability, and
- * convergence in a multidimensional complex space. IEEE Trans. on Evolutionary
- * Computation. 2002, 6 (1): 58-73
- * @ Constriction factor: ensures the convergence
- * [4] Xie X F, Zhang W J, Yang Z L. A dissipative particle swarm optimization.
- * Congress on Evolutionary Computation, Hawaii, USA, 2002: 1456-1461
- * @ The CL parameter
- * [5] Xie X F, Zhang W J, Bi D C. Optimizing semiconductor devices by self-
- * organizing particle swarm. Congress on Evolutionary Computation, Oregon, USA,
- * 2004: 2017-2022
- * @ Further experimental analysis on the convergence of PSO
- * [6] X F Xie, W J Zhang. SWAF: swarm algorithm framework for numerical
- * optimization. Genetic and Evolutionary Computation Conference (GECCO),
- * Seattle, WA, USA, 2004: 238-250
- * -> a generate-and-test behavior
- *
- */
-
-package net.adaptivebox.deps.behavior;
-
-import net.adaptivebox.goodness.*;
-import net.adaptivebox.knowledge.*;
-import net.adaptivebox.problem.*;
-import net.adaptivebox.space.*;
-
-public class PSGTBehavior extends AbsGTBehavior {
- // Two normally choices for (c1, c2, weight), i.e., (2, 2, 0.4), or (1.494, 1.494, 0.729)
- // The first is used in dissipative PSO (cf. [4]) as CL>0, and the second is achieved by using
- // constriction factors (cf. [3])
- public double c1=2;
- public double c2=2;
- public double weight = 0.4; //inertia weight
-
- public double CL=0; //See ref[4], normally be 0.001~0.005
-
- //the own memory: store the point that generated in old learning cycle
- protected BasicPoint pold_t;
- //the own memory: store the point that generated in last learning cycle
- protected BasicPoint pcurrent_t;
- //the own memory: store the personal best point
- protected SearchPoint pbest_t;
-
- public void setMemPoints(SearchPoint pbest, BasicPoint pcurrent, BasicPoint pold) {
- pcurrent_t = pcurrent;
- pbest_t = pbest;
- pold_t = pold;
- }
-
- public void generateBehavior(SearchPoint trailPoint, ProblemEncoder problemEncoder) {
- SearchPoint gbest_t = socialLib.getGbest();
- DesignSpace designSpace = problemEncoder.getDesignSpace();
- int DIMENSION = designSpace.getDimension();
- double deltaxb, deltaxbm;
- for (int b=0;b<DIMENSION;b++) {
- if (Math.random()<CL) {
- designSpace.mutationAt(trailPoint.getLocation(), b);
- } else {
- deltaxb = weight*(pcurrent_t.getLocation()[b]-pold_t.getLocation()[b])
- + c1*Math.random()*(pbest_t.getLocation()[b]-pcurrent_t.getLocation()[b])
- + c2*Math.random()*(gbest_t.getLocation()[b]-pcurrent_t.getLocation()[b]);
- //limitation for delta_x
- deltaxbm = 0.5*designSpace.getMagnitudeIn(b);
- if(deltaxb<-deltaxbm) {
- deltaxb = -deltaxbm;
- } else if (deltaxb>deltaxbm) {
- deltaxb = deltaxbm;
- }
- trailPoint.getLocation()[b] = pcurrent_t.getLocation()[b]+deltaxb;
- }
- }
- }
-
- public void testBehavior(SearchPoint trailPoint, IGoodnessCompareEngine qualityComparator) {
- Library.replace(qualityComparator, trailPoint, pbest_t);
- pold_t.importLocation(pcurrent_t);
- pcurrent_t.importLocation(trailPoint);
- }
-
-}
-
+/**
+ * Description: The description of particle swarm (PS) Generate-and-test Behavior.
+ *
+ #Supported parameters:
+ NAME VALUE_type Range DefaultV Description
+ c1 real [0, 2] 1.494 PSAgent: learning factor for pbest
+ c2 real [0, 2] 1.494 PSAgent: learning factor for gbest
+ w real [0, 1] 0.729 PSAgent: inertia weight
+ CL real [0, 0.1] 0 PSAgent: chaos factor
+ //Other choices for c1, c2, w, and CL: (2, 2, 0.4, 0.001)
+
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie May 11, 2004
+ * Xiaofeng Xie Jul 01, 2008
+ *
+ * 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.
+ *
+ * @version 1.0
+ * @Since MAOS1.0
+ *
+ * @References:
+ * [1] Kennedy J, Eberhart R C. Particle swarm optimization. IEEE Int. Conf. on
+ * Neural Networks, Perth, Australia, 1995: 1942-1948
+ * @ For original particle swarm idea
+ * [2] Shi Y H, Eberhart R C. A Modified Particle Swarm Optimizer. IEEE Inter. Conf.
+ * on Evolutionary Computation, Anchorage, Alaska, 1998: 69-73
+ * @ For the inertia weight: adjust the trade-off between exploitation & exploration
+ * [3] Clerc M, Kennedy J. The particle swarm - explosion, stability, and
+ * convergence in a multidimensional complex space. IEEE Trans. on Evolutionary
+ * Computation. 2002, 6 (1): 58-73
+ * @ Constriction factor: ensures the convergence
+ * [4] Xie X F, Zhang W J, Yang Z L. A dissipative particle swarm optimization.
+ * Congress on Evolutionary Computation, Hawaii, USA, 2002: 1456-1461
+ * @ The CL parameter
+ * [5] Xie X F, Zhang W J, Bi D C. Optimizing semiconductor devices by self-
+ * organizing particle swarm. Congress on Evolutionary Computation, Oregon, USA,
+ * 2004: 2017-2022
+ * @ Further experimental analysis on the convergence of PSO
+ * [6] X F Xie, W J Zhang. SWAF: swarm algorithm framework for numerical
+ * optimization. Genetic and Evolutionary Computation Conference (GECCO),
+ * Seattle, WA, USA, 2004: 238-250
+ * -> a generate-and-test behavior
+ *
+ */
+
+package net.adaptivebox.deps.behavior;
+
+import net.adaptivebox.goodness.*;
+import net.adaptivebox.knowledge.*;
+import net.adaptivebox.problem.*;
+import net.adaptivebox.space.*;
+
+public class PSGTBehavior extends AbsGTBehavior {
+ // Two normally choices for (c1, c2, weight), i.e., (2, 2, 0.4), or (1.494, 1.494, 0.729)
+ // The first is used in dissipative PSO (cf. [4]) as CL>0, and the second is achieved by using
+ // constriction factors (cf. [3])
+ public double c1=2;
+ public double c2=2;
+ public double weight = 0.4; //inertia weight
+
+ public double CL=0; //See ref[4], normally be 0.001~0.005
+
+ //the own memory: store the point that generated in old learning cycle
+ protected BasicPoint pold_t;
+ //the own memory: store the point that generated in last learning cycle
+ protected BasicPoint pcurrent_t;
+ //the own memory: store the personal best point
+ protected SearchPoint pbest_t;
+
+ public void setMemPoints(SearchPoint pbest, BasicPoint pcurrent, BasicPoint pold) {
+ pcurrent_t = pcurrent;
+ pbest_t = pbest;
+ pold_t = pold;
+ }
+
+ public void generateBehavior(SearchPoint trailPoint, ProblemEncoder problemEncoder) {
+ SearchPoint gbest_t = socialLib.getGbest();
+ DesignSpace designSpace = problemEncoder.getDesignSpace();
+ int DIMENSION = designSpace.getDimension();
+ double deltaxb, deltaxbm;
+ for (int b=0;b<DIMENSION;b++) {
+ if (Math.random()<CL) {
+ designSpace.mutationAt(trailPoint.getLocation(), b);
+ } else {
+ deltaxb = weight*(pcurrent_t.getLocation()[b]-pold_t.getLocation()[b])
+ + c1*Math.random()*(pbest_t.getLocation()[b]-pcurrent_t.getLocation()[b])
+ + c2*Math.random()*(gbest_t.getLocation()[b]-pcurrent_t.getLocation()[b]);
+ //limitation for delta_x
+ deltaxbm = 0.5*designSpace.getMagnitudeIn(b);
+ if(deltaxb<-deltaxbm) {
+ deltaxb = -deltaxbm;
+ } else if (deltaxb>deltaxbm) {
+ deltaxb = deltaxbm;
+ }
+ trailPoint.getLocation()[b] = pcurrent_t.getLocation()[b]+deltaxb;
+ }
+ }
+ }
+
+ public void testBehavior(SearchPoint trailPoint, IGoodnessCompareEngine qualityComparator) {
+ Library.replace(qualityComparator, trailPoint, pbest_t);
+ pold_t.importLocation(pcurrent_t);
+ pcurrent_t.importLocation(trailPoint);
+ }
+
+}
+
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/encode/IEncodeEngine.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/encode/IEncodeEngine.java
index 9ca77d3..637d9d0 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/encode/IEncodeEngine.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/encode/IEncodeEngine.java
@@ -1,24 +1,24 @@
-/**
- * Description: provide the encoded information for objectives
- *
- * @ Author Create/Modi Note
- * Xiaofeng Xie Feb 10, 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.
- */
-
-package net.adaptivebox.encode;
-
-public interface IEncodeEngine{
- abstract public double[] getEncodeInfo();
-}
+/**
+ * Description: provide the encoded information for objectives
+ *
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie Feb 10, 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.
+ */
+
+package net.adaptivebox.encode;
+
+public interface IEncodeEngine{
+ abstract public double[] getEncodeInfo();
+}
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/BasicArray.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/BasicArray.java
index 4071cf8..98feb56 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/BasicArray.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/BasicArray.java
@@ -1,31 +1,31 @@
-/**
- * Description: basic operations on Arrays
- *
- * @ Author Create/Modi Note
- * Xiaofeng Xie Oct. 9, 2002
- *
- */
-
-package net.adaptivebox.global;
-
-public class BasicArray {
- public static double getMinValue(double[] v) {
- double mv = Double.MAX_VALUE;
- for (int i=0; i<v.length; i++) {
- if (v[i]<mv) {
- mv=v[i];
- }
- }
- return mv;
- }
- public static double getMaxValue(double[] v) {
- double mv = -Double.MAX_VALUE;
- for (int i=0; i<v.length; i++) {
- if (v[i]>mv) {
- mv=v[i];
- }
- }
- return mv;
- }
-
-}
\ No newline at end of file
+/**
+ * Description: basic operations on Arrays
+ *
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie Oct. 9, 2002
+ *
+ */
+
+package net.adaptivebox.global;
+
+public class BasicArray {
+ public static double getMinValue(double[] v) {
+ double mv = Double.MAX_VALUE;
+ for (int i=0; i<v.length; i++) {
+ if (v[i]<mv) {
+ mv=v[i];
+ }
+ }
+ return mv;
+ }
+ public static double getMaxValue(double[] v) {
+ double mv = -Double.MAX_VALUE;
+ for (int i=0; i<v.length; i++) {
+ if (v[i]>mv) {
+ mv=v[i];
+ }
+ }
+ return mv;
+ }
+
+}
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/BasicBound.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/BasicBound.java
index f6e063f..383e9c2 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/BasicBound.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/BasicBound.java
@@ -1,93 +1,93 @@
-/**
- * Description: provide an bound, and the corresponding operations
- *
- * @ Author Create/Modi Note
- * Xiaofeng Xie Oct. 9, 2002
- *
- * 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.
- */
-
-package net.adaptivebox.global;
-
-public class BasicBound {
- public static final double MINDOUBLE= -1e308;
- public static final double MAXDOUBLE= 1e308;
-
- public double minValue = MINDOUBLE;
- public double maxValue = MAXDOUBLE;
- public BasicBound() {
- }
-
- public BasicBound(double min, double max) {
- minValue = Math.min(min, max);
- maxValue = Math.max(min, max);
- }
-
- public double getLength() {
- return Math.abs(maxValue-minValue);
- }
-
- public boolean isSatisfyCondition(double child){
- if(child > maxValue || child < minValue) {
- return(false);
- }
- return(true);
- }
-
- public double boundAdjust(double value){
- if(value > maxValue) {
- value = maxValue;
- } else if (value < minValue) {
- value = minValue;
- }
- return value;
- }
-
- public double annulusAdjust (double value) {
- if(value > maxValue) {
- double extendsLen = (value-maxValue)%getLength();
- value = minValue+extendsLen;
- } else if (value < minValue) {
- double extendsLen = (minValue-value)%getLength();
- value = maxValue-extendsLen;
- }
- return value;
- }
-
- public static BasicBound getBound(double[] data) {
- BasicBound bound = new BasicBound();
- if(data!=null) {
- if(data.length>0) {
- bound.minValue = data[0];
- bound.maxValue = data[0];
- for(int i=1; i<data.length; i++) {
- bound.minValue = Math.min(bound.minValue, data[i]);
- bound.maxValue = Math.max(bound.maxValue, data[i]);
- }
-
- }
- }
- return bound;
- }
-
- public double randomAdjust (double value){
- if(value > maxValue || value < minValue) {
- value = getRandomValue();
- }
- return value;
- }
-
- public double getRandomValue(){
- return RandomGenerator.doubleRangeRandom(minValue, maxValue);
- }
-}
+/**
+ * Description: provide an bound, and the corresponding operations
+ *
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie Oct. 9, 2002
+ *
+ * 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.
+ */
+
+package net.adaptivebox.global;
+
+public class BasicBound {
+ public static final double MINDOUBLE= -1e308;
+ public static final double MAXDOUBLE= 1e308;
+
+ public double minValue = MINDOUBLE;
+ public double maxValue = MAXDOUBLE;
+ public BasicBound() {
+ }
+
+ public BasicBound(double min, double max) {
+ minValue = Math.min(min, max);
+ maxValue = Math.max(min, max);
+ }
+
+ public double getLength() {
+ return Math.abs(maxValue-minValue);
+ }
+
+ public boolean isSatisfyCondition(double child){
+ if(child > maxValue || child < minValue) {
+ return(false);
+ }
+ return(true);
+ }
+
+ public double boundAdjust(double value){
+ if(value > maxValue) {
+ value = maxValue;
+ } else if (value < minValue) {
+ value = minValue;
+ }
+ return value;
+ }
+
+ public double annulusAdjust (double value) {
+ if(value > maxValue) {
+ double extendsLen = (value-maxValue)%getLength();
+ value = minValue+extendsLen;
+ } else if (value < minValue) {
+ double extendsLen = (minValue-value)%getLength();
+ value = maxValue-extendsLen;
+ }
+ return value;
+ }
+
+ public static BasicBound getBound(double[] data) {
+ BasicBound bound = new BasicBound();
+ if(data!=null) {
+ if(data.length>0) {
+ bound.minValue = data[0];
+ bound.maxValue = data[0];
+ for(int i=1; i<data.length; i++) {
+ bound.minValue = Math.min(bound.minValue, data[i]);
+ bound.maxValue = Math.max(bound.maxValue, data[i]);
+ }
+
+ }
+ }
+ return bound;
+ }
+
+ public double randomAdjust (double value){
+ if(value > maxValue || value < minValue) {
+ value = getRandomValue();
+ }
+ return value;
+ }
+
+ public double getRandomValue(){
+ return RandomGenerator.doubleRangeRandom(minValue, maxValue);
+ }
+}
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/BasicTag.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/BasicTag.java
index 435577e..8c21d8d 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/BasicTag.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/BasicTag.java
@@ -1,40 +1,40 @@
-/**
- * Description: defines some static constant values.
- *
- * @ Author Create/Modi Note
- * Xiaofeng Xie Sep 22, 2000 xiaofengxie at tsinghua.org.cn
- *
- * @version 1.0
- * @Since MAOS1.0
- */
-
-package net.adaptivebox.global;
-
-
-public class BasicTag {
- public static final String COMMAND_TAG = "%";
- public static final String TAB_TAG = "\t";
- public static final String LEFT_SMALL_BRACKET_TAG = "(";
- public static final String RIGHT_SMALL_BRACKET_TAG = ")";
- public static final String LEFT_LARGE_BRACKET_TAG = "{";
- public static final String RIGHT_LARGE_BRACKET_TAG = "}";
- public static final String LEFT_BRACKET_TAG = "[";
- public static final String RIGHT_BRACKET_TAG = "]";
- public static final String EQUAL_TAG = "=";
- public static final String SPACE_TAG = " ";
- public static final String SEMICOLON_TAG = ";";
- public static final String COLON_TAG = ":";
- public static final String COMMA_TAG = ",";
- public static final String DOT_TAG = ".";
- public static final String NULL_SEPARATE_TAG = " \t";
- public static final String SEPARATE_TAG = "|";
- public static final String UNDERLINE_TAG = "_";
- public static final String INC_TAG = "+";
- public static final String DEC_TAG = "-";
- public static final String ZERO_TAG = "0";
- public static final String EXP_TAG = "E";
- public static final String S_EXP_TAG = "e";
- public static final String FILE_SEP_TAG = System.getProperty("file.separator");
- public static final String RETURN_TAG = System.getProperty("line.separator");
-}
-
+/**
+ * Description: defines some static constant values.
+ *
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie Sep 22, 2000 xiaofengxie at tsinghua.org.cn
+ *
+ * @version 1.0
+ * @Since MAOS1.0
+ */
+
+package net.adaptivebox.global;
+
+
+public class BasicTag {
+ public static final String COMMAND_TAG = "%";
+ public static final String TAB_TAG = "\t";
+ public static final String LEFT_SMALL_BRACKET_TAG = "(";
+ public static final String RIGHT_SMALL_BRACKET_TAG = ")";
+ public static final String LEFT_LARGE_BRACKET_TAG = "{";
+ public static final String RIGHT_LARGE_BRACKET_TAG = "}";
+ public static final String LEFT_BRACKET_TAG = "[";
+ public static final String RIGHT_BRACKET_TAG = "]";
+ public static final String EQUAL_TAG = "=";
+ public static final String SPACE_TAG = " ";
+ public static final String SEMICOLON_TAG = ";";
+ public static final String COLON_TAG = ":";
+ public static final String COMMA_TAG = ",";
+ public static final String DOT_TAG = ".";
+ public static final String NULL_SEPARATE_TAG = " \t";
+ public static final String SEPARATE_TAG = "|";
+ public static final String UNDERLINE_TAG = "_";
+ public static final String INC_TAG = "+";
+ public static final String DEC_TAG = "-";
+ public static final String ZERO_TAG = "0";
+ public static final String EXP_TAG = "E";
+ public static final String S_EXP_TAG = "e";
+ public static final String FILE_SEP_TAG = System.getProperty("file.separator");
+ public static final String RETURN_TAG = System.getProperty("line.separator");
+}
+
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/CompareValue.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/CompareValue.java
index 1cd783f..7bfe6df 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/CompareValue.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/CompareValue.java
@@ -1,20 +1,20 @@
-/**
- * Description: Global value for comparison.
- *
- * @ Author Create/Modi Note
- * Xiaofeng Xie Jun 15, 2002
- * Xiaofeng Xie Feb 18, 2004
- *
- * @version 1.0
- * @Since MAOS1.0
- */
-
-
-package net.adaptivebox.global;
-
-public class CompareValue {
- public static final int LARGER_THAN = 2;
- public static final int EQUAL_TO = 1;
- public static final int LESS_THAN = 0;
- public static final int INVALID = -1;
-}
+/**
+ * Description: Global value for comparison.
+ *
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie Jun 15, 2002
+ * Xiaofeng Xie Feb 18, 2004
+ *
+ * @version 1.0
+ * @Since MAOS1.0
+ */
+
+
+package net.adaptivebox.global;
+
+public class CompareValue {
+ public static final int LARGER_THAN = 2;
+ public static final int EQUAL_TO = 1;
+ public static final int LESS_THAN = 0;
+ public static final int INVALID = -1;
+}
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/GlobalCompare.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/GlobalCompare.java
index 3f11dc5..1721b24 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/GlobalCompare.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/GlobalCompare.java
@@ -1,44 +1,44 @@
-/**
- * Description: Global package for comparison.
- *
- * @ Author Create/Modi Note
- * Xiaofeng Xie Jun 15, 2002 xiaofengxie at tsinghua.org.cn
- *
- *
- * @version 1.0
- * @Since MAOS1.0
- */
-
-
-package net.adaptivebox.global;
-
-public class GlobalCompare {
-
-/* compare the data1 and data2, if data1=data2, return 0
- * if data1 < data2, return LESS_THAN, else if data1 > data2, LARGER_THAN
- **/
- static public int compare(double data1, double data2) {
- if (data1 < data2)
- return CompareValue.LESS_THAN;
- else if (data1 > data2)
- return CompareValue.LARGER_THAN;
- else
- return CompareValue.EQUAL_TO;
- }
-
-/* check the magnitude of two array, the frontial is more important
- **/
- public static int compareArray(double[] fit1, double[] fit2) {
- if (fit1.length!=fit2.length) {
- return CompareValue.INVALID; //error
- }
- for (int i=0; i<fit1.length; i++) {
- if (fit1[i]>fit2[i]) {
- return CompareValue.LARGER_THAN; //Large than
- } else if (fit1[i]<fit2[i]){
- return CompareValue.LESS_THAN; //Less than
- }
- }
- return CompareValue.EQUAL_TO; //same
- }
-}
+/**
+ * Description: Global package for comparison.
+ *
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie Jun 15, 2002 xiaofengxie at tsinghua.org.cn
+ *
+ *
+ * @version 1.0
+ * @Since MAOS1.0
+ */
+
+
+package net.adaptivebox.global;
+
+public class GlobalCompare {
+
+/* compare the data1 and data2, if data1=data2, return 0
+ * if data1 < data2, return LESS_THAN, else if data1 > data2, LARGER_THAN
+ **/
+ static public int compare(double data1, double data2) {
+ if (data1 < data2)
+ return CompareValue.LESS_THAN;
+ else if (data1 > data2)
+ return CompareValue.LARGER_THAN;
+ else
+ return CompareValue.EQUAL_TO;
+ }
+
+/* check the magnitude of two array, the frontial is more important
+ **/
+ public static int compareArray(double[] fit1, double[] fit2) {
+ if (fit1.length!=fit2.length) {
+ return CompareValue.INVALID; //error
+ }
+ for (int i=0; i<fit1.length; i++) {
+ if (fit1[i]>fit2[i]) {
+ return CompareValue.LARGER_THAN; //Large than
+ } else if (fit1[i]<fit2[i]){
+ return CompareValue.LESS_THAN; //Less than
+ }
+ }
+ return CompareValue.EQUAL_TO; //same
+ }
+}
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/IUpdateCycleEngine.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/IUpdateCycleEngine.java
index 18e9832..5dd4b7e 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/IUpdateCycleEngine.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/global/IUpdateCycleEngine.java
@@ -1,24 +1,24 @@
-/**
- * Description: provide the inteface for updating according to the cycle number
- *
- * @ Author Create/Modi Note
- * Xiaofeng Xie Feb 18, 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.
- */
-
-package net.adaptivebox.global;
-
-public interface IUpdateCycleEngine {
- public void updateCycle(int t);
+/**
+ * Description: provide the inteface for updating according to the cycle number
+ *
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie Feb 18, 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.
+ */
+
+package net.adaptivebox.global;
+
+public interface IUpdateCycleEngine {
+ public void updateCycle(int t);
}
\ No newline at end of file
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/problem/ProblemEncoder.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/problem/ProblemEncoder.java
index a5deb63..2e91e65 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/problem/ProblemEncoder.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/problem/ProblemEncoder.java
@@ -1,123 +1,123 @@
-/**
- * Description: Encodes the specified problem into encoded information for
- * forming the goodness landscape.
- *
- * @ Author Create/Modi Note
- * Xiaofeng Xie May 31, 2000
- * Xiaofeng Xie Sep. 19, 2002
- * Xiaofeng Xie Mar. 01, 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.
- *
- * @version 1.0
- * @Since MAOS1.0
- */
-
-package net.adaptivebox.problem;
-
-import net.adaptivebox.global.*;
-import net.adaptivebox.space.*;
-import net.adaptivebox.encode.*;
-import net.adaptivebox.knowledge.*;
-
-public abstract class ProblemEncoder {
- //Store the calculated results for the responses
- double[] tempResponseSet; //temp values
- double[] tempLocation; //temp values
-
- //the search space (S)
- protected DesignSpace designSpace = null;
-
- // For evaluate the response vector into encoded vector double[2]
- protected EvalStruct evalStruct = null;
-
- protected ProblemEncoder(int paramNum, int targetNum) throws Exception {
- designSpace = new DesignSpace(paramNum);
- evalStruct = new EvalStruct(targetNum);
- tempLocation = new double[paramNum];
- tempResponseSet = new double[targetNum];
- }
-
- public DesignSpace getDesignSpace() {
- return designSpace;
- }
-
- public EvalStruct getEvalStruct() {
- return evalStruct;
- }
-
- //set the default information for each dimension of search space (S)
- protected void setDefaultXAt(int i, double min, double max, double grain) {
- DesignDim dd = new DesignDim();
- dd.grain = grain;
- dd.paramBound = new BasicBound(min, max);
- designSpace.setElemAt(dd, i);
- }
-
- protected void setDefaultXAt(int i, double min, double max) {
- DesignDim dd = new DesignDim();
- dd.paramBound = new BasicBound(min, max);
- designSpace.setElemAt(dd, i);
- }
-
- //set the default information for evaluation each response
- protected void setDefaultYAt(int i, double min, double max) {
- EvalElement ee = new EvalElement();
- ee.targetBound = new BasicBound(min, max);
- evalStruct.setElemAt(ee, i);
- }
-
- protected void setDefaultYAt(int i, double min, double max, double weight) {
- EvalElement ee = new EvalElement();
- ee.targetBound = new BasicBound(min, max);
- ee.weight = weight;
- evalStruct.setElemAt(ee, i);
- }
-
- //get a fresh point
- public SearchPoint getFreshSearchPoint() {
- return new SearchPoint(designSpace.getDimension());
- }
-
- //get an encoded point
- public SearchPoint getEncodedSearchPoint() {
- SearchPoint point = getFreshSearchPoint();
- designSpace.initializeGene(point.getLocation());
- evaluate(point);
- return point;
- }
-
- //evaluate the point into encoded information
- public void evaluate(SearchPoint point) {
- //copy to temp point
- System.arraycopy(point.getLocation(), 0, this.tempLocation, 0, tempLocation.length);
- //mapping the temp point to original search space S
- designSpace.getMappingPoint(tempLocation);
- //calculate based on the temp point
- calcTargets(tempResponseSet, tempLocation);
- evalStruct.evaluate(point.getEncodeInfo(), tempResponseSet);
- point.setObjectiveValue(tempResponseSet[0]);
- }
-
- //calcuate each response, must be implemented
- abstract protected double calcTargetAt(int index, double[] VX);
-
- // calculate all the responses VY[] based on given point VX[]
- private void calcTargets(double[] VY, double[] VX) {
- for(int i=0; i<VY.length; i++) {
- VY[i] = calcTargetAt(i, VX);
- }
- }
-}
-
+/**
+ * Description: Encodes the specified problem into encoded information for
+ * forming the goodness landscape.
+ *
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie May 31, 2000
+ * Xiaofeng Xie Sep. 19, 2002
+ * Xiaofeng Xie Mar. 01, 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.
+ *
+ * @version 1.0
+ * @Since MAOS1.0
+ */
+
+package net.adaptivebox.problem;
+
+import net.adaptivebox.global.*;
+import net.adaptivebox.space.*;
+import net.adaptivebox.encode.*;
+import net.adaptivebox.knowledge.*;
+
+public abstract class ProblemEncoder {
+ //Store the calculated results for the responses
+ double[] tempResponseSet; //temp values
+ double[] tempLocation; //temp values
+
+ //the search space (S)
+ protected DesignSpace designSpace = null;
+
+ // For evaluate the response vector into encoded vector double[2]
+ protected EvalStruct evalStruct = null;
+
+ protected ProblemEncoder(int paramNum, int targetNum) throws Exception {
+ designSpace = new DesignSpace(paramNum);
+ evalStruct = new EvalStruct(targetNum);
+ tempLocation = new double[paramNum];
+ tempResponseSet = new double[targetNum];
+ }
+
+ public DesignSpace getDesignSpace() {
+ return designSpace;
+ }
+
+ public EvalStruct getEvalStruct() {
+ return evalStruct;
+ }
+
+ //set the default information for each dimension of search space (S)
+ protected void setDefaultXAt(int i, double min, double max, double grain) {
+ DesignDim dd = new DesignDim();
+ dd.grain = grain;
+ dd.paramBound = new BasicBound(min, max);
+ designSpace.setElemAt(dd, i);
+ }
+
+ protected void setDefaultXAt(int i, double min, double max) {
+ DesignDim dd = new DesignDim();
+ dd.paramBound = new BasicBound(min, max);
+ designSpace.setElemAt(dd, i);
+ }
+
+ //set the default information for evaluation each response
+ protected void setDefaultYAt(int i, double min, double max) {
+ EvalElement ee = new EvalElement();
+ ee.targetBound = new BasicBound(min, max);
+ evalStruct.setElemAt(ee, i);
+ }
+
+ protected void setDefaultYAt(int i, double min, double max, double weight) {
+ EvalElement ee = new EvalElement();
+ ee.targetBound = new BasicBound(min, max);
+ ee.weight = weight;
+ evalStruct.setElemAt(ee, i);
+ }
+
+ //get a fresh point
+ public SearchPoint getFreshSearchPoint() {
+ return new SearchPoint(designSpace.getDimension());
+ }
+
+ //get an encoded point
+ public SearchPoint getEncodedSearchPoint() {
+ SearchPoint point = getFreshSearchPoint();
+ designSpace.initializeGene(point.getLocation());
+ evaluate(point);
+ return point;
+ }
+
+ //evaluate the point into encoded information
+ public void evaluate(SearchPoint point) {
+ //copy to temp point
+ System.arraycopy(point.getLocation(), 0, this.tempLocation, 0, tempLocation.length);
+ //mapping the temp point to original search space S
+ designSpace.getMappingPoint(tempLocation);
+ //calculate based on the temp point
+ calcTargets(tempResponseSet, tempLocation);
+ evalStruct.evaluate(point.getEncodeInfo(), tempResponseSet);
+ point.setObjectiveValue(tempResponseSet[0]);
+ }
+
+ //calcuate each response, must be implemented
+ abstract protected double calcTargetAt(int index, double[] VX);
+
+ // calculate all the responses VY[] based on given point VX[]
+ private void calcTargets(double[] VY, double[] VX) {
+ for(int i=0; i<VY.length; i++) {
+ VY[i] = calcTargetAt(i, VX);
+ }
+ }
+}
+
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/problem/UnconstrainedProblemEncoder.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/problem/UnconstrainedProblemEncoder.java
index c06db87d..03b621e 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/problem/UnconstrainedProblemEncoder.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/problem/UnconstrainedProblemEncoder.java
@@ -1,39 +1,39 @@
-/**
- * Description: For unconstrained function
- *
- * @ Author Create/Modi Note
- * Xiaofeng Xie Dec 28, 2001
- * Xiaofeng Xie Mar 02, 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.
- *
- * @version 1.0
- * @Since MAOS1.0
- */
-
-package net.adaptivebox.problem;
-
-import net.adaptivebox.global.*;
-
-public abstract class UnconstrainedProblemEncoder extends ProblemEncoder {
- protected UnconstrainedProblemEncoder(int NX) throws Exception {
- super(NX, 1);
- setDefaultYAt(0, BasicBound.MINDOUBLE, BasicBound.MINDOUBLE);
- }
-
- protected double calcTargetAt(int index, double[] VX) {
- return calcTarget(VX);
- }
- abstract public double calcTarget(double[] VX);
-}
+/**
+ * Description: For unconstrained function
+ *
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie Dec 28, 2001
+ * Xiaofeng Xie Mar 02, 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.
+ *
+ * @version 1.0
+ * @Since MAOS1.0
+ */
+
+package net.adaptivebox.problem;
+
+import net.adaptivebox.global.*;
+
+public abstract class UnconstrainedProblemEncoder extends ProblemEncoder {
+ protected UnconstrainedProblemEncoder(int NX) throws Exception {
+ super(NX, 1);
+ setDefaultYAt(0, BasicBound.MINDOUBLE, BasicBound.MINDOUBLE);
+ }
+
+ protected double calcTargetAt(int index, double[] VX) {
+ return calcTarget(VX);
+ }
+ abstract public double calcTarget(double[] VX);
+}
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/DesignSpace.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/DesignSpace.java
index 6a493f3..48f4df4 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/DesignSpace.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/DesignSpace.java
@@ -1,141 +1,141 @@
-/**
- * Description: provide the information for the search space (S)
- *
- * @ Author Create/Modi Note
- * Xiaofeng Xie Mar 2, 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] Zhang W J, Xie X F, Bi D C. Handling boundary constraints for numerical
- * optimization by particle swarm flying in periodic search space. Congress
- * on Evolutionary Computation, Oregon, USA, 2004
- * @ especially for particle swarm agent
- */
-
-package net.adaptivebox.space;
-import net.adaptivebox.global.*;
-
-public class DesignSpace {
- //The information of all the dimension
- private DesignDim[] dimProps;
-
- public DesignSpace(int dim) {
- dimProps = new DesignDim[dim];
- }
-
- public DesignDim getDimAt(int index) {
- return dimProps[index];
- }
-
- public void setElemAt(DesignDim elem, int index) {
- dimProps[index] = elem;
- }
-
- public int getDimension() {
- if (dimProps==null) {
- return -1;
- }
- return dimProps.length;
- }
-
- public double boundAdjustAt(double val, int dim){
- return dimProps[dim].paramBound.boundAdjust(val);
- }
-
- public void annulusAdjust (double[] location){
- for (int i=0; i<getDimension(); i++) {
- location[i] = dimProps[i].paramBound.annulusAdjust(location[i]);
- }
- }
-
- public void randomAdjust (double[] location){
- for (int i=0; i<getDimension(); i++) {
- location[i] = dimProps[i].paramBound.randomAdjust(location[i]);
- }
- }
-
- public boolean satisfyCondition(double[] location){
- for (int i=0; i<getDimension(); i++) {
- if (!dimProps[i].paramBound.isSatisfyCondition(location[i])) {
- return false;
- }
- }
- /*If the limits are not violated, return TRUE*/
- return(true);
- }
-
- public void mutationAt(double[] location, int i){
- location[i] = dimProps[i].paramBound.getRandomValue();
- }
-
- public double mutationUniformAtPointAsCenter (double pointX, int i){
- double length = this.getMagnitudeIn(i)/2;
- pointX += RandomGenerator.doubleRangeRandom(-1*length, length);
-
- return pointX;
- }
-
- public double getUpValueAt(int dimensionIndex) {
- return dimProps[dimensionIndex].paramBound.maxValue;
- }
-
- public double getLowValueAt(int dimensionIndex) {
- return dimProps[dimensionIndex].paramBound.minValue;
- }
-
- public double getMagnitudeIn(int dimensionIndex) {
- return dimProps[dimensionIndex].paramBound.getLength();
- }
-
-
- public boolean initilizeGeneAtPointAsCenter(double[] tempX){
- if (tempX.length!=this.getDimension()) {
- return false;
- }
- for(int i=0;i<tempX.length;i++) {
- double length = this.getMagnitudeIn(i)/2;
- tempX[i]+=RandomGenerator.doubleRangeRandom(-1*length, length);
- }
- return true;
- }
-
- public void initializeGene(double[] tempX){
- for(int i=0;i<tempX.length;i++) tempX[i] = dimProps[i].paramBound.getRandomValue(); //Global.RandomGenerator.doubleRangeRandom(9.8, 10);
- }
-
- public double[] getFreshGene() {
- double[] tempX = new double[this.getDimension()];
- initializeGene(tempX);
- return tempX;
- }
- public void getMappingPoint(double[] point) {
- for(int i=0; i<getDimension(); i++) {
- point[i] = dimProps[i].paramBound.annulusAdjust(point[i]);
- if(dimProps[i].isDiscrete()) {
- point[i] = dimProps[i].getGrainedValue(point[i]);
- }
- }
- }
-
- public double[] getRealLoc(double[] imageLoc) {
- double[] realLoc = new double[imageLoc.length];
- for (int i=0; i<imageLoc.length; i++) {
- realLoc[i] = imageLoc[i];
- }
- annulusAdjust(realLoc);
- return realLoc;
- }
-}
-
+/**
+ * Description: provide the information for the search space (S)
+ *
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie Mar 2, 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] Zhang W J, Xie X F, Bi D C. Handling boundary constraints for numerical
+ * optimization by particle swarm flying in periodic search space. Congress
+ * on Evolutionary Computation, Oregon, USA, 2004
+ * @ especially for particle swarm agent
+ */
+
+package net.adaptivebox.space;
+import net.adaptivebox.global.*;
+
+public class DesignSpace {
+ //The information of all the dimension
+ private DesignDim[] dimProps;
+
+ public DesignSpace(int dim) {
+ dimProps = new DesignDim[dim];
+ }
+
+ public DesignDim getDimAt(int index) {
+ return dimProps[index];
+ }
+
+ public void setElemAt(DesignDim elem, int index) {
+ dimProps[index] = elem;
+ }
+
+ public int getDimension() {
+ if (dimProps==null) {
+ return -1;
+ }
+ return dimProps.length;
+ }
+
+ public double boundAdjustAt(double val, int dim){
+ return dimProps[dim].paramBound.boundAdjust(val);
+ }
+
+ public void annulusAdjust (double[] location){
+ for (int i=0; i<getDimension(); i++) {
+ location[i] = dimProps[i].paramBound.annulusAdjust(location[i]);
+ }
+ }
+
+ public void randomAdjust (double[] location){
+ for (int i=0; i<getDimension(); i++) {
+ location[i] = dimProps[i].paramBound.randomAdjust(location[i]);
+ }
+ }
+
+ public boolean satisfyCondition(double[] location){
+ for (int i=0; i<getDimension(); i++) {
+ if (!dimProps[i].paramBound.isSatisfyCondition(location[i])) {
+ return false;
+ }
+ }
+ /*If the limits are not violated, return TRUE*/
+ return(true);
+ }
+
+ public void mutationAt(double[] location, int i){
+ location[i] = dimProps[i].paramBound.getRandomValue();
+ }
+
+ public double mutationUniformAtPointAsCenter (double pointX, int i){
+ double length = this.getMagnitudeIn(i)/2;
+ pointX += RandomGenerator.doubleRangeRandom(-1*length, length);
+
+ return pointX;
+ }
+
+ public double getUpValueAt(int dimensionIndex) {
+ return dimProps[dimensionIndex].paramBound.maxValue;
+ }
+
+ public double getLowValueAt(int dimensionIndex) {
+ return dimProps[dimensionIndex].paramBound.minValue;
+ }
+
+ public double getMagnitudeIn(int dimensionIndex) {
+ return dimProps[dimensionIndex].paramBound.getLength();
+ }
+
+
+ public boolean initilizeGeneAtPointAsCenter(double[] tempX){
+ if (tempX.length!=this.getDimension()) {
+ return false;
+ }
+ for(int i=0;i<tempX.length;i++) {
+ double length = this.getMagnitudeIn(i)/2;
+ tempX[i]+=RandomGenerator.doubleRangeRandom(-1*length, length);
+ }
+ return true;
+ }
+
+ public void initializeGene(double[] tempX){
+ for(int i=0;i<tempX.length;i++) tempX[i] = dimProps[i].paramBound.getRandomValue(); //Global.RandomGenerator.doubleRangeRandom(9.8, 10);
+ }
+
+ public double[] getFreshGene() {
+ double[] tempX = new double[this.getDimension()];
+ initializeGene(tempX);
+ return tempX;
+ }
+ public void getMappingPoint(double[] point) {
+ for(int i=0; i<getDimension(); i++) {
+ point[i] = dimProps[i].paramBound.annulusAdjust(point[i]);
+ if(dimProps[i].isDiscrete()) {
+ point[i] = dimProps[i].getGrainedValue(point[i]);
+ }
+ }
+ }
+
+ public double[] getRealLoc(double[] imageLoc) {
+ double[] realLoc = new double[imageLoc.length];
+ for (int i=0; i<imageLoc.length; i++) {
+ realLoc[i] = imageLoc[i];
+ }
+ annulusAdjust(realLoc);
+ return realLoc;
+ }
+}
+
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/ILocationEngine.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/ILocationEngine.java
index fa5375b..3373733 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/ILocationEngine.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/ILocationEngine.java
@@ -1,25 +1,25 @@
-/**
- * Description: provide the information for location
- *
- * @ Author Create/Modi Note
- * Xiaofeng Xie May 3, 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.
- */
-
-package net.adaptivebox.space;
-
-public interface ILocationEngine{
- abstract public double[] getLocation();
-}
+/**
+ * Description: provide the information for location
+ *
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie May 3, 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.
+ */
+
+package net.adaptivebox.space;
+
+public interface ILocationEngine{
+ abstract public double[] getLocation();
+}
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