Designing Evolutionary Algorithms for Dynamic Environments

Preface......Page 3
Contents......Page 4
Overview and Background......Page 8
Previous Research......Page 13
Open Research Issues......Page 16
Book Structure......Page 18
Non-stationary Problems......Page 20
Algorithm Attributes......Page 22
Biological Systems......Page 25
Engineering Control Systems......Page 27
Summary......Page 29
Efficient  Diversity Measurement......Page 30
Improved Diversity Measurement for  Dynamic  Problems......Page 47
Summary......Page 57
New EA Design Goals......Page 58
Sentinel Placement......Page 62
Summary......Page 73
Problem Generator Background......Page 74
Generator Requirements......Page 75
Problem Generator Description and Features......Page 77
Test Problem Description......Page 83
Summary......Page 89
Issues in Performance Measurement......Page 90
Performance Measurement: Collective Mean Fitness......Page 92
Summary......Page 97
Introduction......Page 98
Overview of Comparison to Other Techniques......Page 106
Comparison Analysis and Combined Techniques......Page 109
Relationship Between Collective Fitness and  Collective Dispersion......Page 117
Important Dispersion Levels for  Different Movement  Periods......Page 125
Background......Page 128
Experiment......Page 129
Experimental Results......Page 130
Research Results......Page 137
Open Issues and Suggested Areas for  Future  Research......Page 139
Conclusion......Page 141
Notation......Page 142
Refs......Page 144
Index......Page 149