convert EvolutionarySolver source to unix LF

so I dont keep getting problems when moving patches between Windows
and Linux

Change-Id: Ia2323ecb388bf5996279686e1bd2b1676c5ae213

15 files changed, 964 insertions, 964 deletions

diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/DEPSAgent.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/DEPSAgent.java
index 02043f5b89f2..3107fa8deff1 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 159ce7c73328..b4b9b4ca6a5e 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 50666ff4f8f5..7867fdb49db2 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 b4ae0017eb69..c1e8db0123ae 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 9ca77d32ca8f..637d9d016088 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 4071cf8c7540..98feb5639a53 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 f6e063ff08a6..383e9c2ed202 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 435577e46da5..8c21d8de3f1f 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@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@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 1cd783f54404..7bfe6df9511e 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 3f11dc59f98d..1721b240217c 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@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@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 18e9832e31bc..5dd4b7ef8719 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 a5deb6315954..2e91e65cde51 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 c06db87d83b7..03b621ec05d7 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 6a493f37ae74..48f4df46042a 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 fa5375b7608d..33737339a383 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();
+}