Anticipatory optimization for dynamic decision making:
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
2011
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XI, 278 S. graph. Darst. |
Internformat
MARC
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| 264 | 1 | |c 2011 | |
| 300 | |a XI, 278 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
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| 502 | |a Braunschweig, Techn. Univ., Diss., 2010 | ||
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Datensatz im Suchindex
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|---|---|
| adam_text | Contents
Preface
ix
Acknowledgements
xi
1
Introduction
1
1.1
Recent economic developments
....................... 2
1.2
Examples of emerging problems
....................... 4
1.3
Problem similarities and implications
................... 8
1.4
Outline of the following chapters
...................... 10
2
Basic concepts and definitions
13
2.1
Dynamic decision making
.......................... 13
2.1.1
A basic dynamic decision process
.................. 14
2.1.2
Markov decision processes
...................... 17
2.2
Optimization
.................................. 19
2.2.1
Optimization problems
........................ 20
2.2.2
Optimization techniques
....................... 22
2.3
Anticipation
.................................. 24
2.3.1
Anticipatory decisions
........................ 24
2.3.2
Degrees of anticipation
........................ 26
iv CONTENTS
3
Perfect
anticipation
31
3.1 Dynamic Programming............................ 32
3.1.1
Value
Iteration............................. 32
3.1.2
Policy
Iteration ............................ 34
3.1.3
Modified Policy
Iteration....................... 36
3.1.4 Linear Programming......................... 37
3.2
Forward
Dynamic Programming ...................... 38
3.2.1
Asynchronous state sampling
.................... 38
3.2.2 Monte Carlo
updates
......................... 41
3.2.3
Stochastic approximation......................
45
3.2.4
The actor-critic framework
...................... 50
3.3
Model free Dynamic Programming
..................... 53
3.3.1
Q-Leaming
............................... 54
3.3.2
Post-decision states
.......................... 56
3.4
Limited effectiveness of perfect anticipation
................ 58
4
Synergies of optimization and data mining
63
4.1
Preliminaries
.................................. 63
4.1.1
Common foundations
........................ 64
4.1.2
Data mining
.............................. 68
4.1.3
Integration of optimization and data mining
........... 72
4.2
Efficient data mining
............................. 76
4.2.1
Optimized preprocessing
...................... 77
4.2.2
Optimized information extraction
................. 79
4.3
Effective optimization
............................ 83
4.3.1
Decision model substitution
..................... 84
4.3.2
Decision model approximation
................... 87
CONTENTS v
5
Approximate anticipation
93
5.1
Approximate value functions
........................ 96
5.1.1
State space aggregation
........................ 96
5.1.2
Predictive modeling
.......................... 98
5.2
Stochastic gradient updates
......................... 100
5.2.1
Steepest descent
........................... 101
5.2.2
Stepsize rules
............................. 102
5.3
The generalized actor-critic framework
................... 105
5.3.1
Regression models
.......................... 106
5.3.2
General information structures
................... 109
6
Dynamic vehicle routing
113
6.1
Foundations
.................................. 114
6.1.1
Vehicle routing background
..................... 114
6.1.2
Dynamic vehicle routing problems
................. 116
6.2
State of the art
................................. 119
6.2.1
Conventional non-reactive anticipation
.............. 121
6.2.2
Probabilisitic non-reactive anticipation
.............. 125
6.2.3
Implicit anticipation
......................... 127
6.2.4
Approximate anticipation
...................... 129
6.3
Dynamic routing of a service vehicle
.................... 132
6.3.1
Problem formulation
......................... 132
6.3.2
Casestudy
............................... 139
7
Anticipatory routing of a service vehicle
145
7.1
Perfect anticipation
.............................. 146
7.1.1
State sampling
............................. 146
7.1.2
Solution properties
.......................... 149
7.1.3
Limited
effectiveness
......................... 156
7.2
Approximate anticipation
.......................... 158
7.2.1
Value function approximation
.................... 159
7.2.2
Decision model identification
.................... 165
7.2.3
Decision model approximation
................... 169
7.2.4
The full scope of the approach
................... 172
7.3
Non-reactive anticipation
.......................... 174
7.3.1
Probabilistic approaches
....................... 174
7.3.2
Conventional approaches
...................... 176
8
Computational study
179
8.1
Experimental setup
.............................. 180
8.1.1
Problem instances
.......................... 180
8.1.2
Actor-critic configuration
...................... 184
8.2
Non-reactive anticipation
.......................... 186
8.2.1
Conventional approaches
...................... 186
8.2.2
Probabilistic approaches
....................... 194
8.3
Elementary value function approximation
................. 201
8.3.1
Solution properties
.......................... 202
8.3.2
Results
................................. 214
8.4
Fine-grained value function approximation
................ 222
8.4.1
Results and solution properties
................... 223
8.4.2
Variations
............................... 232
9
Managerial impact of anticipatory optimization
239
9.1
Technological preconditions
.........................240
9.2
Selecting a degree of anticipation
......................244
CONTENTS
vii
10
Conclusions
247
Bibliography
255
|
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| author | Meisel, Stephan 1979- |
| author_GND | (DE-588)143998013 |
| author_facet | Meisel, Stephan 1979- |
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| author_sort | Meisel, Stephan 1979- |
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| dewey-ones | 658 - General management |
| dewey-raw | 658.403 |
| dewey-search | 658.403 |
| dewey-sort | 3658.403 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Mathematik Wirtschaftswissenschaften |
| format | Thesis Book |
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| indexdate | 2024-07-09T23:22:29Z |
| institution | BVB |
| language | English |
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| physical | XI, 278 S. graph. Darst. |
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| spelling | Meisel, Stephan 1979- Verfasser (DE-588)143998013 aut Anticipatory optimization for dynamic decision making von Stephan Meisel 2011 XI, 278 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Braunschweig, Techn. Univ., Diss., 2010 Dynamisches Entscheidungsmodell (DE-588)4150931-6 gnd rswk-swf Tourenplanung (DE-588)4121783-4 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Dynamisches Entscheidungsmodell (DE-588)4150931-6 s Tourenplanung (DE-588)4121783-4 s b DE-604 Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=022496072&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Meisel, Stephan 1979- Anticipatory optimization for dynamic decision making Dynamisches Entscheidungsmodell (DE-588)4150931-6 gnd Tourenplanung (DE-588)4121783-4 gnd |
| subject_GND | (DE-588)4150931-6 (DE-588)4121783-4 (DE-588)4113937-9 |
| title | Anticipatory optimization for dynamic decision making |
| title_auth | Anticipatory optimization for dynamic decision making |
| title_exact_search | Anticipatory optimization for dynamic decision making |
| title_full | Anticipatory optimization for dynamic decision making von Stephan Meisel |
| title_fullStr | Anticipatory optimization for dynamic decision making von Stephan Meisel |
| title_full_unstemmed | Anticipatory optimization for dynamic decision making von Stephan Meisel |
| title_short | Anticipatory optimization for dynamic decision making |
| title_sort | anticipatory optimization for dynamic decision making |
| topic | Dynamisches Entscheidungsmodell (DE-588)4150931-6 gnd Tourenplanung (DE-588)4121783-4 gnd |
| topic_facet | Dynamisches Entscheidungsmodell Tourenplanung Hochschulschrift |
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