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The GLOBAL Optimization Algorithm - Newly Updated with Java Implementation and Parallelization
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The GLOBAL Optimization Algorithm - Newly Updated with Java Implementation and Parallelization
von: Balázs Bánhelyi, Tibor Csendes, Balázs Lévai, László Pál, Dániel Zombori
Springer-Verlag, 2018
ISBN: 9783030023751
112 Seiten, Download: 3366 KB
 
Format:  PDF
geeignet für: Apple iPad, Android Tablet PC's Online-Lesen PC, MAC, Laptop

Typ: A (einfacher Zugriff)

 

 
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Inhaltsverzeichnis

  Acknowledgments 5  
  Contents 6  
  1 Introduction 9  
     1.1 Introduction 9  
     1.2 Problem Domain 10  
     1.3 The GLOBAL Algorithm 10  
  2 Local Search 14  
     2.1 Introduction 14  
     2.2 Local Search Algorithms 15  
        2.2.1 Derivative-Free Local Search 15  
        2.2.2 The Basic UNIRANDI Method 16  
        2.2.3 The New UNIRANDI Algorithm 16  
        2.2.4 Reference Algorithms 21  
     2.3 Computational Investigations 22  
        2.3.1 Experimental Settings 22  
        2.3.2 Comparison of the Two UNIRANDI Versions 23  
        2.3.3 Comparison with Other Algorithms 25  
        2.3.4 Error Analysis 26  
        2.3.5 Performance Profiles 29  
     2.4 Conclusions 32  
  3 The GLOBALJ Framework 33  
     3.1 Introduction 33  
     3.2 Switching from MATLAB to JAVA 34  
     3.3 Modularization 34  
     3.4 Algorithmic Improvements 37  
     3.5 Results 43  
     3.6 Conclusions 45  
  4 Parallelization 46  
     4.1 Introduction 46  
     4.2 Parallel Techniques 47  
        4.2.1 Principles of Parallel Computation 47  
     4.3 Design of PGLOBAL Based on GLOBAL 49  
     4.4 Implementation of the PGlobal Algorithm 53  
        4.4.1 SerializedGlobal 53  
        4.4.2 SerializedClusterizer 56  
     4.5 Parallelized Local Search 61  
     4.6 Losses Caused by Parallelization 61  
     4.7 Algorithm Parameters 61  
     4.8 Results 62  
        4.8.1 Environment 62  
        4.8.2 SerializedGlobal Parallelization Test 63  
        4.8.3 SerializedGlobalSingleLinkageClusterizer Parallelization Test 66  
        4.8.4 Comparison of Global and PGlobal Implementations 67  
     4.9 Conclusions 71  
  5 Example 73  
     5.1 Environment 73  
     5.2 Objective Function 73  
     5.3 Optimizer Setup 75  
     5.4 Run the Optimizer 76  
     5.5 Constraints 77  
     5.6 Custom Module Implementation 81  
  Appendix A User's Guide 84  
     A.1 Global Module 84  
        A.1.1 Parameters 84  
     A.2 SerializedGlobal Module 85  
        A.2.1 Parameters 85  
     A.3 GlobalSingleLinkageClusterizer Module 86  
        A.3.1 Parameters 86  
     A.4 SerializedGlobalSingleLinkageClusterizer Module 87  
        A.4.1 Parameters 87  
     A.5 UNIRANDI Module 87  
        A.5.1 Parameters 87  
     A.6 NUnirandi Module 88  
        A.6.1 Parameters 88  
     A.7 UnirandiCLS Module 88  
        A.7.1 Parameters 89  
     A.8 NUnirandiCLS Module 89  
        A.8.1 Parameters 89  
     A.9 Rosenbrock Module 90  
        A.9.1 Parameters 90  
     A.10 LineSearchImpl Module 90  
  Appendix B Test Functions 91  
  Appendix C DiscreteClimber Code 102  
  References 108  


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