Metaheuristics for bi-level optimization:
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin [u.a.]
Springer
2013
|
| Schriftenreihe: | Studies in computational intelligence
482 |
| Schlagworte: | |
| Online-Zugang: | Inhaltstext Inhaltsverzeichnis Klappentext |
| Beschreibung: | XVIII, 288 S. graph. Darst. |
| ISBN: | 9783642378379 |
Internformat
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Datensatz im Suchindex
| _version_ | 1806325494716563456 |
|---|---|
| adam_text |
Contents
1
A Taxonomy of Metaheuristics for Bi-level Optimization
. 1
El-Ghazali Talbi
1.1
Introduction
. 1
1.2
Bi-level Optimization Concepts
. 3
1.2.1
Bi-level Optimization Problems
. 6
1.2.2
Complexity and Optimality Conditions
. 9
1.3
Relationships with Other Problems
. 10
1.3.1
Bi-level versus Stackelberg Games
. 10
1.3.2
Bi-level versus Multi-objective Problems
. 11
1.3.3
Bi-level versus Set-Valued Optimization Problems
. 12
1.4
Applications of Bi-level Optimization
. 13
1.5
Metaheuristics
. 15
1.5.1
S-metaheuristics
. 17
1.5.2
P-metaheuristics
. 18
1.6
Metaheuristics for Bi-level Optimization
. 21
1.6.1
Metaheuristics Based on Nested Approach
. 22
1.6.2
Metaheuristics Based on Reformulation to Single-Level
Optimization Problems
. 25
1.6.3
Metaheuristics Based on Transformation to
Multi-objective Optimization Problems
. 27
1.6.4
Co-evolutionary Metaheuristics
. 28
1.7
Performance Assessment of Bi-level Metaheuristics
. 30
1.7.1
Performance Indicators
. 31
1.8
Conclusions and Perspectives
. 33
References
. 34
2
A Genetic Algorithm for Power System Vulnerability Analysis
under Multiple Contingencies
. 41
José M.
Arroyo, Francisco J. Fernandez
2.1
Introduction
. 41
2.2
Power System Vulnerability Analysis
. 43
2.3
Attacker-Defender Models
. 44
2.4
Genetic
Algorithm: An Evolutionary Metaheuristic
. 46
2.4.1
Structure of a Genetic Algorithm
. 47
2.4.2
Proposed Genetic Algorithm for Attacker-Defender
Models
. 49
2.5
Application: Maximum Vulnerability Model with Line
Switching
. 53
2.5.1
Problem Formulation
. 54
2.5.2
Particular Features of the Genetic Algorithm
Approach
. 55
2.6
Numerical Results
. 57
2.7
Conclusions
. 63
References
. 65
3
A Bilevel Particle Swarm Optimization Algorithm for Supply
Chain Management Problems
. 69
Yannis
Marinakis,
Magdalene
Marinaki.
3.1
Introduction
. 69
3.2
Bilevel Programming
. 71
3.3
Supply Chain Management Problems
. 72
3.3.1
Vehicle Routing Problem
. 72
3.3.2
Location Routing Problem
. 75
3.4
Bilevel Particle Swarm Optimization Algorithm
. 78
3.4.1
General Description of the Bilevel Particle Swarm
Optimization Algorithm (PSOBilevel)
. 78
3.4.2
Particle Swarm Optimization
. 79
3.4.3
Expanding Neighborhood Search
. 82
3.5
Results
. 83
3.6
Conclusions and Future Research
. 90
References
. 90
4
CoBRA: A Coevolutionary Metaheuristic for Bi-level
Optimization
. 95
François Legillon, Arnaud Liej
boghe, El-Ghazali
Talbi
4.1
Introduction
. 95
4.2
Bi-level Optimization
. 96
4.2.1
General Principles of Bi-level Optimization
. 97
4.2.2
Meta-heuristic Approaches for Bi-level Optimization
. 97
4.3
CoBRA, a Coevolutionary Meta-heuristic for Bi-level
Optimization
. 99
4.3.1
General Principles
. 99
4.3.2
CoBRA Components
. 99
4.3.3
General Algorithm
.
10Q
4.4
Performance Assessment and Bi-level Optimization
. 101
4.4.1
Motivations
. 101
4.4.2
Rationality
. 103
4.4.3
Discussion
. 103
4.5
Application
to Bi-level
Transportation
.104
4.5.1
A Bi-level Multi-depot Vehicle
Routing
Problem
.105
4.5.2
A Multi-objective Bi-level Multi-depot Vehicle Routing
Problem
.107
4.6
Experimental Analysis
.108
4.6.1
Experimental Design
.108
4.6.2
CoBRA instantiation for BiMDVRP an M-BiMDVRP
. 108
4.6.3
Experimental Results
.110
4.7
Conclusions and Future Works
.112
References
.113
A Matheuristic for Leader-Follower Games Involving Facility
Location-Protection-Inter diction Decisions
. 115
Deniz
Aksen, Necati
Aras
5.1
Introduction and Background
.116
5.1.1
Man-Made Attacks as a Source of Disruption
.116
5.1.2
Preliminary Interdiction Models
.116
5.1.3
Recent Network and Power Grid Interdiction Models
. 117
5.1.4
Protection-Interdiction Models
.118
5.1.5
Location-Interdiction and Network Design-Interdiction
Models
.120
5.1.6
The Triple Problem of Facility
Location-Protection-Interdiction
.121
5.2
Two Service Network Design Models
.122
5.2.1
A Location-Protection-Interdiction Model for
Coverage-Type Networks
.122
5.2.2
A Location-Protection-Interdiction Model for
Median-Type Networks
.125
5.3
A Tabu Search Based Matheuristic for the BFCLP
.130
5.3.1
Background of Tabu Search
.132
5.3.2
Key Features of the Tabu Search Algorithm TSH
.132
5.3.3
Partial Validation of TSH Solutions with Exhaustive
Search
.137
5.4
Computational Results
.139
5.4.1
Random Generation of Test Instances
.139
5.4.2
Preliminary Analysis of the Neighborhood Structure
. 140
5.4.3
Test results of TSH
.140
5.4.4
Comparison of the Best TSH Solutions with the ESV-p
Results
.142
5.4.5
Sensitivity of the TSH Solutions to Problem
Parameters
. 145
5.4.6
Effect of the Protection Costs on the Best Facility
Configuration
. 146
5.5
Conclusions
. 147
References
. 148
A Metaheuristic Framework for Bi-Ievel Programming Problems
with Multi-disciplinary Applications
. 153
Andrew Koh
6.1
Introduction
.153
6.2
The Bi-level Programming Problem
.155
6.2.1
A General BLPP
.155
6.2.2
Mathematical Programs with Equilibrium Constraints
. 155
6.2.3
Solution Algorithms for the BLPP
.156
6.3
Differential Evolution for Bi-Level Programming (DEBLP)
.157
6.3.1
Differential Evolution
.158
6.3.2
Control Parameters of
DE
.161
6.3.3
Implicit Assumptions of DEBLP
.161
6.4
Applications to Transportation Systems Management
.162
6.4.1
The Lower Level Program in Transportation
.162
6.4.2
Continuous Optimal Toll Pricing Problem (COTP)
.164
6.4.3
Continuous Network Design Problem
.165
6.5
Applications to Parameter Estimation Problems
.168
6.5.1
Formulation of EIV Model
.168
6.5.2
Examples
.169
6.6
Handling Upper Level Constraints
.171
6.6.1
Overview of Constraint Handling Techniques with
Meta-Heuristics
.171
6.6.2
Stochastic Ranking
.172
6.6.3
Revised DEBLP with Stochastic Ranking
.173
6.7
Applications to Generalised Nash Equilibrium Problems
.173
6.7.1
The Generalised Nash Equilibrium Problem
.174
6.7.2
Nikaido Isoda Function
.175
6.7.3
Solution of the GNEP
.175
6.7.4
Examples
.176
6.7.5
Discussion
.177
6.8
Summary and Conclusions
.178
6.8.1
Summary
.178
6.8.2
Further Research
.179
References
.181
Matheuristics and Exact Methods for the Discrete (r|/?)-Centroid
Problem
. 189
Ekaterina Alekseeva, Yury Kochetov
7.1
Introduction
.189
7.2
The Problem Statement
.191
7.2.1
The Bi-level Mixed Integer Linear Formulation
.191
7.2.2
The
Min-Max
Formulation
.194
7.2.3
The Single-Level Mixed Integer Linear Formulation
. 195
7.2.4
The Brief Overview of Related Works
.196
7.3
Complexity Status
.198
7.4
Heuristics for the Discrete (r|/?)-Centroid Problem
.199
7.4.1
Median Heuristics
.200
7.4.2
Alternative Heuristics
.203
7.4.3
Hybrid Heuristics
.205
7.5
Exact Methods
.207
7.5.1
The Branch-and-Cut Method
.209
7.5.2
An Iterative Exact Method
.211
7.6
Computational Experiments
.213
7.7
Conclusions
.216
References
.217
8
Exact Solution Methodologies for Linear and (Mixed) Integer
Bilevel Programming
.221
Georgios K.D. Saharidis, Antonio J.
Conejo,
George Kozanidis
8.1
Introduction
.222
8.2
Description of the Bilevel Problem
.223
8.3
Solution Approaches for the Linear Bilevel Problem
.226
8.4
Solution Approaches for the Mixed Integer Bilevel Problem
.234
8.5
Bilevel Programming Applications
.236
8.6
Summary
.241
References
.241
9
Bilevel
Multi-
Objective Optimization and Decision Making
.247
Ankar
Sinha, Kalyanmoy Deb
9.1
Introduction
.248
9.2
Multi-objective Bilevel Optimization Problems
.249
9.2.1
Real World Problems
.251
9.3
Existing Classical and Evolutionary Methodologies
.253
9.3.1
Theoretical Developments
.253
9.3.2
Algorithmic Developments
.254
9.3.3
Evolutionary Methods
.255
9.3.4
Development of Tunable Test Problems
.256
9.4
Hybrid Bilevel Evolutionary Multi-Objective Optimization
(H-BLEMO) Algorithm
.259
9.4.1
Update of Population Sizes
.261
9.4.2
Termination Criteria
.262
9.4.3
Step-by-Step Procedure
.263
9.4.4
Algorithmic Complexity
.265
9.5
Results on Test Problems
.266
9.6
Scalability Study
.268
9.7
Comparison with a Nested Algorithm
.269
9.8
Incorporating Decision Maker Preferences in H-BLEMO
.271
9.9
Progressively Interactive Hybrid Bilevel Evolutionary
Multi-Objective Optimization Algorithm (PI-HBLEMO)
.272
9.9.1
Step
3:
Preference Elicitation and Construction of a
Value Function
.273
XVI Contents
9.9.2
Termination Criterion
.275
9.9.3
Modified Domination Principle
.275
9.10
Results
.276
9.11
Accuracy and DM Calls
.278
9.12
Conclusions
.280
References
.281
Index
.285
The series Studies in Computational Intelligence (SCI) publishes new developments
and advances in the various areas of computational intelligence
-
quickly and with
high quality. The intent is to cover the theory, applications, and design methods
of computational intelligence, as embedded in the fields of engineering, computer
science, physics and life sciences, as well as the methodologies behind them.
The series contains monographs, lecture notes and edited volumes in computational
intelligence spanning the areas of neural networks, connectionist systems, genetic
algorithms, evolutionary computation, artificial intelligence, cellular automata,
self-organizing systems, soft computing, fuzzy systems, hybrid intelligent, and
virtual reality systems. Of particular value to both the contributors and the
readership are the short publication
timeframe
and the world-wide distribution,
which enable both wide and rapid dissemination of research output.
This book provides a complete background on metaheuristics to solve complex
bi-level optimization problems (continuous/discrete, mono-objective/multiobjective)
in a diverse range of application domains.
Readers learn to solve large scale bi-level optimization problems by efficiently
combining metaheuristics with complementary metaheuristics and mathematical
programming approaches. Numerous real-world examples of problems demonstrate
how metaheuristics are applied in such fields as networks, logistics and
transportation, engineering design, finance and security. |
| any_adam_object | 1 |
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| dewey-full | 620 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 620 - Engineering and allied operations |
| dewey-raw | 620 |
| dewey-search | 620 |
| dewey-sort | 3620 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Informatik |
| format | Book |
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| id | DE-604.BV041197245 |
| illustrated | Illustrated |
| indexdate | 2024-08-03T00:50:30Z |
| institution | BVB |
| isbn | 9783642378379 |
| language | English |
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| physical | XVIII, 288 S. graph. Darst. |
| publishDate | 2013 |
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| publisher | Springer |
| record_format | marc |
| series | Studies in computational intelligence |
| series2 | Studies in computational intelligence |
| spelling | Metaheuristics for bi-level optimization El-Ghazali Talbi (ed.) Berlin [u.a.] Springer 2013 XVIII, 288 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Studies in computational intelligence 482 Metaheuristik (DE-588)4820176-5 gnd rswk-swf Zwei-Ebenen-Optimierung (DE-588)4715689-2 gnd rswk-swf Zwei-Ebenen-Optimierung (DE-588)4715689-2 s Metaheuristik (DE-588)4820176-5 s DE-604 Talbi, El-Ghazali 1965- (DE-588)131576542 edt Erscheint auch als Online-Ausgabe 978-3-642-37838-6 Studies in computational intelligence 482 (DE-604)BV020822171 482 X:MVB text/html http://deposit.dnb.de/cgi-bin/dokserv?id=4283847&prov=M&dok_var=1&dok_ext=htm Inhaltstext Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026172200&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026172200&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Metaheuristics for bi-level optimization Studies in computational intelligence Metaheuristik (DE-588)4820176-5 gnd Zwei-Ebenen-Optimierung (DE-588)4715689-2 gnd |
| subject_GND | (DE-588)4820176-5 (DE-588)4715689-2 |
| title | Metaheuristics for bi-level optimization |
| title_auth | Metaheuristics for bi-level optimization |
| title_exact_search | Metaheuristics for bi-level optimization |
| title_full | Metaheuristics for bi-level optimization El-Ghazali Talbi (ed.) |
| title_fullStr | Metaheuristics for bi-level optimization El-Ghazali Talbi (ed.) |
| title_full_unstemmed | Metaheuristics for bi-level optimization El-Ghazali Talbi (ed.) |
| title_short | Metaheuristics for bi-level optimization |
| title_sort | metaheuristics for bi level optimization |
| topic | Metaheuristik (DE-588)4820176-5 gnd Zwei-Ebenen-Optimierung (DE-588)4715689-2 gnd |
| topic_facet | Metaheuristik Zwei-Ebenen-Optimierung |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=4283847&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026172200&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026172200&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV020822171 |
| work_keys_str_mv | AT talbielghazali metaheuristicsforbileveloptimization |