Representations for genetic and evolutionary algorithms:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin [u.a.]
Springer
2002
|
| Ausgabe: | 1. ed., 2. print. |
| Schriftenreihe: | Studies in fuzziness and soft computing
104 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIV, 289 S. graph. Darst. |
| ISBN: | 3540006109 |
Internformat
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Datensatz im Suchindex
| _version_ | 1804129922486108160 |
|---|---|
| adam_text | Titel: Representations for genetic and evolutionary algorithms
Autor: Rothlauf, Franz
Jahr: 2002
Contents
1. Introduction............................................................................................1
1.1 Purpose..............................................................................................2
1.2 Organization......................................................................................4
2. Representations for Genetic and Evolutionary Algorithms 9
2.1 Genetic Representations..................................................................10
2.1.1 Genotypes and Phenotypes................................................10
2.1.2 Decomposition of the Fitness Function............................11
2.1.3 Types of Representations....................................13
2.2 Genetic and Evolutionary Algorithms..........................................15
2.2.1 Principles..............................................................................15
2.2.2 Functionality........................................................................16
2.2.3 Schema Theorem and Building Block Hypothesis..........19
2.3 Problem Difficulty............................................................................22
2.3.1 Reasons for Problem Difficulty..........................................22
2.3.2 Measurements of Problem Difficulty ................................25
2.4 Existing Recommendations for the Design of Efficient
Representations for Genetic and Evolutionary Algorithms ... 28
2.4.1 Goldberg s Meaningful Building Blocks and Minimal
Alphabets..............................................................................29
2.4.2 Palmer s Tree Encoding Issues..........................................29
2.4.3 Ronald s Representational Redundancy ..........................30
3. Three Elements of a Theory of Genetic and Evolutionary
Representations ....................................................................................31
3.1 Redundancy......................................................................................33
3.1.1 Definitions and Background ..............................................33
3.1.2 Decomposing Redundancy.........................................36
3.1.3 Population Sizing ................................................................37
3.1.4 Run Duration and Overall Problem Complexity............39
3.1.5 Empirical Results ................................................................40
3.1.6 Conclusions, Restrictions and Further Research............44
3.2 Building Block-Scaling....................................................................45
3.2.1 Background ..........................................................................46
3.2.2 Domino Model without Genetic Drift..............................47
XII
Contents
3.2.3 Population Sizing for Domino Model and Genetic Drift
3.2.4 Empirical Results................................
3.2.5 Conclusions......................................
3.3 Distance Distortion..........................;..........
3.3.1 Influence of Representations on Problem Difficulty
3.3.2 Locality and Distance Distortion...................
3.3.3 Modifying BB-Complexity for the One-Max Problem .
3.3.4 Empirical Results ................................
3.3.5 Conclusions......................................
3.4 Summary and Conclusions...............................
4. Time-Quality Framework for a Theory-Based Analysis
and Design of Representations............................
4.1 Solution Quality and Time to Convergence................
4.2 Elements of the Framework..............................
4.2.1 Redundancy.....................................
4.2.2 Scaling..........................................
4.2.3 Distance Distortion...............................
4.3 The Framework........................................
4.3.1 Uniformly Scaled Representations..................
4.3.2 Exponentially Scaled Representations...............
4.4 Implications for the Design of Representations .............
4.4.1 Uniformly Redundant Representations Are Robust ...
4.4.2 Exponentially Scaled Representations Are Fast, but
Inaccurate.......................................
4.4.3 BB-Modifying Representations Are Difficult to Predict
4.5 Summary and Conclusions...............................
5. Analysis of Binary Representations of Integers ...........
5.1 Two Integer Optimization Problems......................
5.2 Binary String Representations............................
5.3 A Theoretical Comparison...............................
5.3.1 Redundancy and the Unary Encoding...............
5.3.2 Scaling, Modification of Problem Difficulty, and the
Binary Encoding................................
5.3.3 Modification of Problem Difficulty and the Gray
Encoding............................
5.4 Empirical Results ............................
5.5 Conclusions..........................
6. Analysis of Tree Representations.................
6.1 The Tree Design Problem ................
6.1.1 Definition...................
6.1.2 Metrics and Distances .................
6.1.3 Tree Structures ........
50
53
56
57
59
61
63
67
71
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119
120
120
122
123
Contents XIII
6.1.4 Schema Analysis for Graphs.......................124
6.1.5 Scalable Test Problems for Graphs .................125
6.1.6 Tree Encoding Issues .............................128
6.2 Priifer Numbers........................................130
6.2.1 Historical Review.................................130
6.2.2 Construction.....................................132
6.2.3 Properties.......................................134
6.2.4 The Low Locality of the Priifer Number Encoding .... 136
6.2.5 Summary and Conclusions.........................148
6.3 The Link and Node Biased Encoding......................149
6.3.1 Introduction.....................................150
6.3.2 Motivation and Functionality......................151
6.3.3 Biased Initial Populations and Non-Uniformly
Redundant Encodings.............................153
6.3.4 The Node-Biased Encoding........................155
6.3.5 The Link-and-Node-Biased Encoding...............159
6.3.6 Empirical Results ................................162
6.3.7 Conclusions......................................165
6.4 The Characteristic Vector Encoding......................166
6.4.1 Encoding Trees with the Characteristic Vector.......167
6.4.2 Repairing Invalid Solutions........................168
6.4.3 Bias and Stealth Mutation.........................169
6.4.4 Summary........................................173
6.5 Conclusions............................................174
7. Design of Tree Representations...........................177
7.1 Network Random Keys (NetKeys)........................178
7.1.1 Motivation......................................178
7.1.2 Functionality....................................179
7.1.3 Advantages......................................183
7.1.4 Bias............................................185
7.1.5 Population Sizing and Run Duration for the One-Max
Tree Problem....................................187
7.1.6 Conclusions......................................189
7.2 A Direct Tree Representation (NetDir)....................190
7.2.1 Historical Review.................................191
7.2.2 Properties of Direct Representations................191
7.2.3 Operators for NetDir .............................193
7.2.4 Summary........................................196
8. Performance of Genetic and Evolutionary Algorithms on
Tree Problems............................................199
8.1 GEA Performance on Scalable Test Tree Problems..........200
8.1.1 Analysis of Representations........................200
8.1.2 One-Max Tree Problem...........................202
XIV Contents
8.1.3 Deceptive Tree Problem...........................210
8.2 GEA Performance on the Optimal Communication Spanning
Tree Problem..........................................215
8.2.1 Problem Definition...............................216
8.2.2 Theoretical Predictions............................216
8.2.3 Palmer s Test Instances...........................217
8.2.4 Raidl s Test Instances.............................221
8.2.5 Test Instances from Berry, Murtagh, and McMahon
(1995) .......................................... 225
8.2.6 Selected Real-World Test Instances.................229
8.3 Summary..............................................235
9. Summary, Conclusions and Future Work..................237
9.1 Summary..............................................237
9.2 Conclusions............................................239
9.3 Future Work...........................................242
A. Optimal Communication Spanning Tree Test Instances ... 245
A.l Palmer s Test Instances.................................245
A.2 Raidl s Test Instances...................................250
A.3 Berry s Test Instances...................................254
A.4 Real World Problems...................................256
References..........................................................................................263
List of Symbols............................281
List of Acronyms............................................................235
|
| any_adam_object | 1 |
| author | Rothlauf, Franz 1971- |
| author_GND | (DE-588)123759978 |
| author_facet | Rothlauf, Franz 1971- |
| author_role | aut |
| author_sort | Rothlauf, Franz 1971- |
| author_variant | f r fr |
| building | Verbundindex |
| bvnumber | BV017018998 |
| classification_rvk | ST 285 |
| ctrlnum | (OCoLC)488958200 (DE-599)BVBBV017018998 |
| discipline | Informatik |
| edition | 1. ed., 2. print. |
| format | Book |
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| institution | BVB |
| isbn | 3540006109 |
| language | English |
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| series | Studies in fuzziness and soft computing |
| series2 | Studies in fuzziness and soft computing |
| spelling | Rothlauf, Franz 1971- Verfasser (DE-588)123759978 aut Representations for genetic and evolutionary algorithms Franz Rothlauf 1. ed., 2. print. Berlin [u.a.] Springer 2002 XIV, 289 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Studies in fuzziness and soft computing 104 Baum <Mathematik> Binärdarstellung Darstellung <Mathematik> Evolutionärer Algorithmus Genetischer Algorithmus Leistungsbewertung Leistungsbewertung (DE-588)4167271-9 gnd rswk-swf Genetischer Algorithmus (DE-588)4265092-6 gnd rswk-swf Darstellung Mathematik (DE-588)4128289-9 gnd rswk-swf Baum Mathematik (DE-588)4004849-4 gnd rswk-swf Evolutionärer Algorithmus (DE-588)4366912-8 gnd rswk-swf Binärdarstellung (DE-588)4370795-6 gnd rswk-swf 1\p (DE-588)4113937-9 Hochschulschrift gnd-content Evolutionärer Algorithmus (DE-588)4366912-8 s Binärdarstellung (DE-588)4370795-6 s Baum Mathematik (DE-588)4004849-4 s Darstellung Mathematik (DE-588)4128289-9 s Leistungsbewertung (DE-588)4167271-9 s DE-604 Genetischer Algorithmus (DE-588)4265092-6 s Studies in fuzziness and soft computing 104 (DE-604)BV021858135 104 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010272035&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Rothlauf, Franz 1971- Representations for genetic and evolutionary algorithms Studies in fuzziness and soft computing Baum <Mathematik> Binärdarstellung Darstellung <Mathematik> Evolutionärer Algorithmus Genetischer Algorithmus Leistungsbewertung Leistungsbewertung (DE-588)4167271-9 gnd Genetischer Algorithmus (DE-588)4265092-6 gnd Darstellung Mathematik (DE-588)4128289-9 gnd Baum Mathematik (DE-588)4004849-4 gnd Evolutionärer Algorithmus (DE-588)4366912-8 gnd Binärdarstellung (DE-588)4370795-6 gnd |
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| title | Representations for genetic and evolutionary algorithms |
| title_auth | Representations for genetic and evolutionary algorithms |
| title_exact_search | Representations for genetic and evolutionary algorithms |
| title_full | Representations for genetic and evolutionary algorithms Franz Rothlauf |
| title_fullStr | Representations for genetic and evolutionary algorithms Franz Rothlauf |
| title_full_unstemmed | Representations for genetic and evolutionary algorithms Franz Rothlauf |
| title_short | Representations for genetic and evolutionary algorithms |
| title_sort | representations for genetic and evolutionary algorithms |
| topic | Baum <Mathematik> Binärdarstellung Darstellung <Mathematik> Evolutionärer Algorithmus Genetischer Algorithmus Leistungsbewertung Leistungsbewertung (DE-588)4167271-9 gnd Genetischer Algorithmus (DE-588)4265092-6 gnd Darstellung Mathematik (DE-588)4128289-9 gnd Baum Mathematik (DE-588)4004849-4 gnd Evolutionärer Algorithmus (DE-588)4366912-8 gnd Binärdarstellung (DE-588)4370795-6 gnd |
| topic_facet | Baum <Mathematik> Binärdarstellung Darstellung <Mathematik> Evolutionärer Algorithmus Genetischer Algorithmus Leistungsbewertung Darstellung Mathematik Baum Mathematik Hochschulschrift |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010272035&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV021858135 |
| work_keys_str_mv | AT rothlauffranz representationsforgeneticandevolutionaryalgorithms |