Combinatorial auctions and knapsack problems: an analysis of optimization methods
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Saarbrücken
VDM-Verl. Müller
2008
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| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | VII, 110 S. graph. Darst. |
| ISBN: | 9783836450065 |
Internformat
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Datensatz im Suchindex
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| adam_text | 4.4.1. DIRECT REPRESENTATION 40 CONTENTS LIST OF FIGURES III LIST OF
TABLES V ABBREVIATIONS VII 1. INTRODUCTION 1 2. COMBINATORIAL AUCTIONS 3
2.1. MOTIVATION 3 2.2. MECHANISM DESIGN 4 2.2.1. DEFINITION 4 2.2.2.
REVELATION PRINCIPLE AND GIBBARD-SATTERTHWAITE THEOREM 5 2.2.3.
VICKREY-CLARKE-GROOVES MECHANISM 7 2.3. AUCTIONS 8 2.3.1. AUCTION DESIGN
8 2.3.2. SINGLE-GOOD AUCTIONS 9 2.3.3. COMBINATORIAL AUCTIONS 10 2.4.
WINNER DETERMINATION PROBLEM (WDP) 11 2.4.1. COMPUTATIONAL ASPECTS 11
2.4.2. INTEGER PROGRAM FORMULATION 13 2.4.3. EQUIVALENCE TO THE
MULTI-DIMENSIONAL KNAPSACK PROBLEM (MDKP) . 15 3. OPTIMIZATION
ALGORITHMS FOR THE WDP AND THE MDKP 19 3.1. ALGORITHMS FOR THE WINNER
DETERMINATION PROBLEM 19 3.1.1. OPTIMAL ALGORITHMS 19 3.1.2. NON-OPTIMAL
ALGORITHMS 22 3.2. ALGORITHMS FOR THE MULTI-DIMENSIONAL KNAPSACK PROBLEM
23 3.2.1. OPTIMAL ALGORITHMS 23 3.2.2. NON-OPTIMAL ALGORITHMS 24 4.
GENETIC ALGORITHMS FOR THE WDP AND THE MDKP 27 4.1. FUNCTIONALITY OF
GENETIC ALGORITHMS 27 4.1.1. REPRESENTATION 29 4.1.2. OPERATORS 30
4.1.3. DESIGNING A GENETIC ALGORITHM 33 4.2. SEARCH SPACE OF THE WDP AND
THE MDKP 36 4.3. PROBLEM-SPECIFIC BIAS BY BID-SORTING HEURISTICS 37 4.4.
EXISTING GENETIC ALGORITHMS FOR THE MDKP 40 BIBLIOGRAFISCHE
INFORMATIONEN HTTP://D-NB.INFO/990098257 DIGITALISIERT DURCH CONTENTS
4.4.2. INDIRECT REPRESENTATION 43 4.4.3. COMPARISON 49 5. ANALYSIS 51
5.1. TEST INSTANCES 51 5.2. PERFORMANCE 59 5.2.1. CAMUS 59 5.2.2. CPLEX
61 5.2.3. PRIMAL GREEDY HEURISTICS 63 5.2.4. RAIDL S WEIGHT-CODED
APPROACH 70 5.3. PHENOTYPIC DISTANCE OF RAIDL S APPROACH 72 5.3.1.
EXPECTED DISTANCE OF TWO INDIVIDUALS 73 5.3.2. DISTANCE TO PRIMAL GREEDY
HEURISTICS AND CPLEX 76 5.3.3. DISTANCE DURING SEARCH PROCESS 78 5.4.
PHENOTYPIC DUPLICATES OF RAIDL S APPROACH 85 5.5. IMPROVING THE STATE OF
THE ART 89 6. SUMMARY, CONCLUSIONS, AND FURTHER WORK 93 6.1. SUMMARY 93
6.2. CONCLUSIONS 97 6.3. FURTHER WORK 99 A. APPENDIX 101
|
| adam_txt |
4.4.1. DIRECT REPRESENTATION 40 CONTENTS LIST OF FIGURES III LIST OF
TABLES V ABBREVIATIONS VII 1. INTRODUCTION 1 2. COMBINATORIAL AUCTIONS 3
2.1. MOTIVATION 3 2.2. MECHANISM DESIGN 4 2.2.1. DEFINITION 4 2.2.2.
REVELATION PRINCIPLE AND GIBBARD-SATTERTHWAITE THEOREM 5 2.2.3.
VICKREY-CLARKE-GROOVES MECHANISM 7 2.3. AUCTIONS 8 2.3.1. AUCTION DESIGN
8 2.3.2. SINGLE-GOOD AUCTIONS 9 2.3.3. COMBINATORIAL AUCTIONS 10 2.4.
WINNER DETERMINATION PROBLEM (WDP) 11 2.4.1. COMPUTATIONAL ASPECTS 11
2.4.2. INTEGER PROGRAM FORMULATION 13 2.4.3. EQUIVALENCE TO THE
MULTI-DIMENSIONAL KNAPSACK PROBLEM (MDKP) . 15 3. OPTIMIZATION
ALGORITHMS FOR THE WDP AND THE MDKP 19 3.1. ALGORITHMS FOR THE WINNER
DETERMINATION PROBLEM 19 3.1.1. OPTIMAL ALGORITHMS 19 3.1.2. NON-OPTIMAL
ALGORITHMS 22 3.2. ALGORITHMS FOR THE MULTI-DIMENSIONAL KNAPSACK PROBLEM
23 3.2.1. OPTIMAL ALGORITHMS 23 3.2.2. NON-OPTIMAL ALGORITHMS 24 4.
GENETIC ALGORITHMS FOR THE WDP AND THE MDKP 27 4.1. FUNCTIONALITY OF
GENETIC ALGORITHMS 27 4.1.1. REPRESENTATION 29 4.1.2. OPERATORS 30
4.1.3. DESIGNING A GENETIC ALGORITHM 33 4.2. SEARCH SPACE OF THE WDP AND
THE MDKP 36 4.3. PROBLEM-SPECIFIC BIAS BY BID-SORTING HEURISTICS 37 4.4.
EXISTING GENETIC ALGORITHMS FOR THE MDKP 40 BIBLIOGRAFISCHE
INFORMATIONEN HTTP://D-NB.INFO/990098257 DIGITALISIERT DURCH CONTENTS
4.4.2. INDIRECT REPRESENTATION 43 4.4.3. COMPARISON 49 5. ANALYSIS 51
5.1. TEST INSTANCES 51 5.2. PERFORMANCE 59 5.2.1. CAMUS 59 5.2.2. CPLEX
61 5.2.3. PRIMAL GREEDY HEURISTICS 63 5.2.4. RAIDL'S WEIGHT-CODED
APPROACH 70 5.3. PHENOTYPIC DISTANCE OF RAIDL'S APPROACH 72 5.3.1.
EXPECTED DISTANCE OF TWO INDIVIDUALS 73 5.3.2. DISTANCE TO PRIMAL GREEDY
HEURISTICS AND CPLEX 76 5.3.3. DISTANCE DURING SEARCH PROCESS 78 5.4.
PHENOTYPIC DUPLICATES OF RAIDL'S APPROACH 85 5.5. IMPROVING THE STATE OF
THE ART 89 6. SUMMARY, CONCLUSIONS, AND FURTHER WORK 93 6.1. SUMMARY 93
6.2. CONCLUSIONS 97 6.3. FURTHER WORK 99 A. APPENDIX 101 |
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| index_date | 2024-07-02T20:28:46Z |
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| isbn | 9783836450065 |
| language | English |
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| spelling | Pfeiffer, Jella Verfasser aut Combinatorial auctions and knapsack problems an analysis of optimization methods Jella Pfeiffer Saarbrücken VDM-Verl. Müller 2008 VII, 110 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016438516&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Pfeiffer, Jella Combinatorial auctions and knapsack problems an analysis of optimization methods |
| title | Combinatorial auctions and knapsack problems an analysis of optimization methods |
| title_auth | Combinatorial auctions and knapsack problems an analysis of optimization methods |
| title_exact_search | Combinatorial auctions and knapsack problems an analysis of optimization methods |
| title_exact_search_txtP | Combinatorial auctions and knapsack problems an analysis of optimization methods |
| title_full | Combinatorial auctions and knapsack problems an analysis of optimization methods Jella Pfeiffer |
| title_fullStr | Combinatorial auctions and knapsack problems an analysis of optimization methods Jella Pfeiffer |
| title_full_unstemmed | Combinatorial auctions and knapsack problems an analysis of optimization methods Jella Pfeiffer |
| title_short | Combinatorial auctions and knapsack problems |
| title_sort | combinatorial auctions and knapsack problems an analysis of optimization methods |
| title_sub | an analysis of optimization methods |
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