Operational freight carrier planning: basic concepts, optimization models and advanced memetic algorithms ; with 24 tables
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin ; Heidelberg ; New York
Springer
2005
|
| Schriftenreihe: | GOR publications
|
| Schlagworte: | |
| Online-Zugang: | Inhaltstext Inhaltsverzeichnis |
| Beschreibung: | Literaturverz. S. 153 - 160 |
| Beschreibung: | IX, 164 S. graph. Darst. 24 cm |
| ISBN: | 3540253181 |
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Datensatz im Suchindex
| _version_ | 1804136524593233920 |
|---|---|
| adam_text | CONTENTS
1 TRANSPORT IN FREIGHT CARRIER NETWORKS 1
1.1 RECENT TRENDS IN FREIGHT TRANSPORTATION 1
1.2 CARRIER TRANSPORT NETWORKS 4
1.3 NETWORK DESIGN. CONFIGURATION AND DEPLOYMENT 9
1.4 DISTRIBUTION AND COLLECTION PLANNING 11
1.5 AIMS OF THIS BOOK AND USED METHODS 13
2 OPERATIONAL FREIGHT TRANSPORT PLANNING 15
2.1 DECISION PROBLEMS 16
2.1.1 REQUEST ACCEPTANCE 16
2.1.2 MODE SELECTION 17
2.1.3 ROUTING 19
2.1.4 FREIGHT OPTIMIZATION 20
2.2 HIERARCHICAL AND SIMULTANEOUS PLANNING 22
2.2.1 HIERARCHICAL APPROACH 22
2.2.2 SIMULTANEOUS ROUTING AND FREIGHT OPTIMIZATION 23
2.3 GENERIC MODELS FOR SIMULTANEOUS PROBLEMS 24
2.3.1 MAXIMAL-PROFIT SELECTION 25
2.3.2 BOTTLENECK SELECTION 25
2.3.3 SELECTION WITH COMPULSORY REQUESTS 26
2.3.4 SELECTION WITH POSTPONEMENT 27
2.4 CONCLUSIONS 29
3 PICKUP AND DELIVERY SELECTION PROBLEMS 31
3.1 PROBLEMS WITH PICKUP AND DELIVERY REQUESTS 31
3.1.1 PROBLEMS WITH DEPOT-CONNECTED REQUESTS 33
3.1.2 PROBLEMS WITH DIRECT DELIVERY REQUESTS 33
3.1.3 SIMULTANEOUS PROBLEMS 34
3.2 PICKUP AND DELIVERY PATHS AND SCHEDULES 34
3.3 OPTIMIZATION PROBLEM 36
3.4 PROBLEM VARIANTS 37
VIII CONTENTS
3.4.1 THE PDSP WITH LSP INCORPORATION 38
3.4.2 THE CAPACITATED PDSP 39
3.4.3 THE PDSP WITH COMPULSORY REQUESTS 39
3.4.4 THE PDSP WITH POSTPONEMENT 40
3.5 TEST CASE GENERATION 42
3.5.1 GENERATION OF PICKUP AND DELIVERY REQUESTS 42
3.5.2 FREIGHT TARIFF 45
3.5.3 BENCHMARK SUITES 46
3.6 CONCLUSIONS 48
4 MEMETIC ALGORITHMS 49
4.1 ALGORITHMIC SOLVING OF PROBLEMS WITH PD-REQUESTS 49
4.2 EVOLUTIONARY ALGORITHMS 52
4.3 GENETIC ALGORITHMS 55
4.3.1 TERMINUS TECHNICI 55
4.3.2 GENERAL FRAMEWORK 56
4.3.3 APPLICABILITY OF GENETIC SEARCH 57
4.3.4 LIMITS OF THE GENETIC SEARCH 58
4.4 REPAIRING AND IMPROVING THE GENETIC CODE 60
4.5 CONCLUSIONS 64
5 MEMETIC ALGORITHM VEHICLE ROUTING 65
5.1 GENETIC SEQUENCING 65
5.2 GENETIC CLUSTERING 68
5.3 COMBINED GENETIC SEQUENCING AND CLUSTERING 71
5.4 ADVANCED MA-APPROACHES: THE STATE-OF-THE-ART 71
5.4.1 MULTI-CHROMOSOME MEMETIC ALGORITHMS 72
5.4.2 CO-EVOLUTION WITH SPECIALIZATION 74
5.4.3 CO-EVOLUTION OF PARTIAL SOLUTIONS 75
5.5 CONCLUSIONS 76
6 MEMETIC SEARCH FOR OPTIMAL PD-SCHEDULES 77
6.1 PERMUTATION-CONTROLLED SCHEDULE CONSTRUCTION 78
6.1.1 CONSTRUCTION OF ROUTES FOR MORE THAN ONE VEHICLE 78
6.1.2 PARALLEL TIME-WINDOW-BASED ROUTING 78
6.1.3 ALGORITHM STEPS 79
6.1.4 DETERMINATION OF THE REQUEST INSTANTIATION ORDER 84
6.2 REPRESENTATION OF A PD-SCHEDULE 84
6.3 CONFIGURATION OF THE MEMETIC ALGORITHM 85
6.3.1 INITIAL POPULATION 85
6.3.2 RECOMBINATION 86
6.3.3 MUTATION 90
6.3.4 POPULATION MODEL 92
6.4 COMPUTATIONAL EXPERIMENTS 93
6.4.1 PARAMETERIZATION OF THE MA 94
CONTENTS IX
6.4.2 IMPACTS OF SPATIAL DISTRIBUTION AND TIME WINDOW
TIGHTNESS 97
6.4.3 IDENTIFICATION OF PROFIT-MAXIMUM REQUEST SELECTIONS . .. 100
6.4.4 CONSIDERATION OF CAPACITY LIMITATIONS 102
6.4.5 IDENTIFICATION OF DEFERRABLE REQUESTS 109
6.5 CONCLUSIONS 113
7 COPING WITH COMPULSORY REQUESTS 115
7.1 LIMITS OF FITNESS PENALIZATION 116
7.1.1 STATIC PENALTIES 116
7.1.2 DYNAMICALLY DETERMINED PENALTIES 118
7.1.3 ADAPTIVE PENALIZATION 119
7.2 A DOUBLE-RANKING APPROACH 120
7.3 CONVERGING-CONSTRAINT APPROACH 121
7.3.1 ALTERNATING AND CONVERGING CONSTRAINTS 121
7.3.2 ACC-ALGORITHM CONTROL 124
7.4 ASSESSING QC-MA AND ACC-MA: NUMERICAL RESULTS 125
7.4.1 EXPERIMENTAL SETUP 125
7.4.2 NUMERICAL RESULTS 125
7.4.3 IMPACTS OF INTERMEDIATE COST REDUCTIONS: AN EXAMPLE . 130
7.5 CONCLUSIONS 133
8 REQUEST SELECTION AND COLLABORATIVE PLANNING 135
8.1 THE PORTFOLIO RE-COMPOSITION PROBLEM 136
8.1.1 LITERATURE REVIEW 136
8.1.2 FORMAL PROBLEM STATEMENT 137
8.2 CONFIGURATION OF THE GROUPAGE SYSTEM 139
8.2.1 BUNDLE SPECIFICATION BY THE CARRIERS 140
8.2.2 BUNDLE ASSIGNMENT BY THE MEDIATOR 140
8.3 COMPUTATIONAL EXPERIMENTS 141
8.3.1 TEST CASES 142
8.3.2 COLLABORATIVE PLANNING APPROACH 142
8.3.3 REFERENCE APPROACH 143
8.3.4 RESULTS 143
8.4 CONCLUSIONS 147
9 CONCLUSIONS 149
9.1 UNDERSTANDING FREIGHT CARRIER DECISION PROBLEMS 149
9.2 MODEL BUILDING 150
9.3 METHODOLOGICAL. ENHANCEMENTS 151
REFERENCES 153
INDEX 161
|
| adam_txt |
CONTENTS
1 TRANSPORT IN FREIGHT CARRIER NETWORKS 1
1.1 RECENT TRENDS IN FREIGHT TRANSPORTATION 1
1.2 CARRIER TRANSPORT NETWORKS 4
1.3 NETWORK DESIGN. CONFIGURATION AND DEPLOYMENT 9
1.4 DISTRIBUTION AND COLLECTION PLANNING 11
1.5 AIMS OF THIS BOOK AND USED METHODS 13
2 OPERATIONAL FREIGHT TRANSPORT PLANNING 15
2.1 DECISION PROBLEMS 16
2.1.1 REQUEST ACCEPTANCE 16
2.1.2 MODE SELECTION 17
2.1.3 ROUTING 19
2.1.4 FREIGHT OPTIMIZATION 20
2.2 HIERARCHICAL AND SIMULTANEOUS PLANNING 22
2.2.1 HIERARCHICAL APPROACH 22
2.2.2 SIMULTANEOUS ROUTING AND FREIGHT OPTIMIZATION 23
2.3 GENERIC MODELS FOR SIMULTANEOUS PROBLEMS 24
2.3.1 MAXIMAL-PROFIT SELECTION 25
2.3.2 BOTTLENECK SELECTION 25
2.3.3 SELECTION WITH COMPULSORY REQUESTS 26
2.3.4 SELECTION WITH POSTPONEMENT 27
2.4 CONCLUSIONS 29
3 PICKUP AND DELIVERY SELECTION PROBLEMS 31
3.1 PROBLEMS WITH PICKUP AND DELIVERY REQUESTS 31
3.1.1 PROBLEMS WITH DEPOT-CONNECTED REQUESTS 33
3.1.2 PROBLEMS WITH DIRECT DELIVERY REQUESTS 33
3.1.3 SIMULTANEOUS PROBLEMS 34
3.2 PICKUP AND DELIVERY PATHS AND SCHEDULES 34
3.3 OPTIMIZATION PROBLEM 36
3.4 PROBLEM VARIANTS 37
VIII CONTENTS
3.4.1 THE PDSP WITH LSP INCORPORATION 38
3.4.2 THE CAPACITATED PDSP 39
3.4.3 THE PDSP WITH COMPULSORY REQUESTS 39
3.4.4 THE PDSP WITH POSTPONEMENT 40
3.5 TEST CASE GENERATION 42
3.5.1 GENERATION OF PICKUP AND DELIVERY REQUESTS 42
3.5.2 FREIGHT TARIFF 45
3.5.3 BENCHMARK SUITES 46
3.6 CONCLUSIONS 48
4 MEMETIC ALGORITHMS 49
4.1 ALGORITHMIC SOLVING OF PROBLEMS WITH PD-REQUESTS 49
4.2 EVOLUTIONARY ALGORITHMS 52
4.3 GENETIC ALGORITHMS 55
4.3.1 TERMINUS TECHNICI 55
4.3.2 GENERAL FRAMEWORK 56
4.3.3 APPLICABILITY OF GENETIC SEARCH 57
4.3.4 LIMITS OF THE GENETIC SEARCH 58
4.4 REPAIRING AND IMPROVING THE GENETIC CODE 60
4.5 CONCLUSIONS 64
5 MEMETIC ALGORITHM VEHICLE ROUTING 65
5.1 GENETIC SEQUENCING 65
5.2 GENETIC CLUSTERING 68
5.3 COMBINED GENETIC SEQUENCING AND CLUSTERING 71
5.4 ADVANCED MA-APPROACHES: THE STATE-OF-THE-ART 71
5.4.1 MULTI-CHROMOSOME MEMETIC ALGORITHMS 72
5.4.2 CO-EVOLUTION WITH SPECIALIZATION 74
5.4.3 CO-EVOLUTION OF PARTIAL SOLUTIONS 75
5.5 CONCLUSIONS 76
6 MEMETIC SEARCH FOR OPTIMAL PD-SCHEDULES 77
6.1 PERMUTATION-CONTROLLED SCHEDULE CONSTRUCTION 78
6.1.1 CONSTRUCTION OF ROUTES FOR MORE THAN ONE VEHICLE 78
6.1.2 PARALLEL TIME-WINDOW-BASED ROUTING 78
6.1.3 ALGORITHM STEPS 79
6.1.4 DETERMINATION OF THE REQUEST INSTANTIATION ORDER 84
6.2 REPRESENTATION OF A PD-SCHEDULE 84
6.3 CONFIGURATION OF THE MEMETIC ALGORITHM 85
6.3.1 INITIAL POPULATION 85
6.3.2 RECOMBINATION 86
6.3.3 MUTATION 90
6.3.4 POPULATION MODEL 92
6.4 COMPUTATIONAL EXPERIMENTS 93
6.4.1 PARAMETERIZATION OF THE MA 94
CONTENTS IX
6.4.2 IMPACTS OF SPATIAL DISTRIBUTION AND TIME WINDOW
TIGHTNESS 97
6.4.3 IDENTIFICATION OF PROFIT-MAXIMUM REQUEST SELECTIONS . . 100
6.4.4 CONSIDERATION OF CAPACITY LIMITATIONS 102
6.4.5 IDENTIFICATION OF DEFERRABLE REQUESTS 109
6.5 CONCLUSIONS 113
7 COPING WITH COMPULSORY REQUESTS 115
7.1 LIMITS OF FITNESS PENALIZATION 116
7.1.1 STATIC PENALTIES 116
7.1.2 DYNAMICALLY DETERMINED PENALTIES 118
7.1.3 ADAPTIVE PENALIZATION 119
7.2 A DOUBLE-RANKING APPROACH 120
7.3 CONVERGING-CONSTRAINT APPROACH 121
7.3.1 ALTERNATING AND CONVERGING CONSTRAINTS 121
7.3.2 ACC-ALGORITHM CONTROL 124
7.4 ASSESSING QC-MA AND ACC-MA: NUMERICAL RESULTS 125
7.4.1 EXPERIMENTAL SETUP 125
7.4.2 NUMERICAL RESULTS 125
7.4.3 IMPACTS OF INTERMEDIATE COST REDUCTIONS: AN EXAMPLE . 130
7.5 CONCLUSIONS 133
8 REQUEST SELECTION AND COLLABORATIVE PLANNING 135
8.1 THE PORTFOLIO RE-COMPOSITION PROBLEM 136
8.1.1 LITERATURE REVIEW 136
8.1.2 FORMAL PROBLEM STATEMENT 137
8.2 CONFIGURATION OF THE GROUPAGE SYSTEM 139
8.2.1 BUNDLE SPECIFICATION BY THE CARRIERS 140
8.2.2 BUNDLE ASSIGNMENT BY THE MEDIATOR 140
8.3 COMPUTATIONAL EXPERIMENTS 141
8.3.1 TEST CASES 142
8.3.2 COLLABORATIVE PLANNING APPROACH 142
8.3.3 REFERENCE APPROACH 143
8.3.4 RESULTS 143
8.4 CONCLUSIONS 147
9 CONCLUSIONS 149
9.1 UNDERSTANDING FREIGHT CARRIER DECISION PROBLEMS 149
9.2 MODEL BUILDING 150
9.3 METHODOLOGICAL. ENHANCEMENTS 151
REFERENCES 153
INDEX 161 |
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| author | Schönberger, Jörn 1973- |
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| ctrlnum | (OCoLC)633978116 (DE-599)BVBBV022446598 |
| discipline | Mathematik Wirtschaftswissenschaften |
| discipline_str_mv | Mathematik Wirtschaftswissenschaften |
| format | Book |
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| spelling | Schönberger, Jörn 1973- Verfasser (DE-588)1020884118 aut Operational freight carrier planning basic concepts, optimization models and advanced memetic algorithms ; with 24 tables Jörn Schönberger Berlin ; Heidelberg ; New York Springer 2005 IX, 164 S. graph. Darst. 24 cm txt rdacontent n rdamedia nc rdacarrier GOR publications Literaturverz. S. 153 - 160 Memetischer Algorithmus (DE-588)4625421-3 gnd rswk-swf Güterverkehr (DE-588)4022492-2 gnd rswk-swf Tourenplanung (DE-588)4121783-4 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Güterverkehr (DE-588)4022492-2 s Tourenplanung (DE-588)4121783-4 s Memetischer Algorithmus (DE-588)4625421-3 s DE-604 text/html http://deposit.dnb.de/cgi-bin/dokserv?id=2601858&prov=M&dok_var=1&dok_ext=htm Inhaltstext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015654550&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Schönberger, Jörn 1973- Operational freight carrier planning basic concepts, optimization models and advanced memetic algorithms ; with 24 tables Memetischer Algorithmus (DE-588)4625421-3 gnd Güterverkehr (DE-588)4022492-2 gnd Tourenplanung (DE-588)4121783-4 gnd |
| subject_GND | (DE-588)4625421-3 (DE-588)4022492-2 (DE-588)4121783-4 (DE-588)4113937-9 |
| title | Operational freight carrier planning basic concepts, optimization models and advanced memetic algorithms ; with 24 tables |
| title_auth | Operational freight carrier planning basic concepts, optimization models and advanced memetic algorithms ; with 24 tables |
| title_exact_search | Operational freight carrier planning basic concepts, optimization models and advanced memetic algorithms ; with 24 tables |
| title_exact_search_txtP | Operational freight carrier planning basic concepts, optimization models and advanced memetic algorithms ; with 24 tables |
| title_full | Operational freight carrier planning basic concepts, optimization models and advanced memetic algorithms ; with 24 tables Jörn Schönberger |
| title_fullStr | Operational freight carrier planning basic concepts, optimization models and advanced memetic algorithms ; with 24 tables Jörn Schönberger |
| title_full_unstemmed | Operational freight carrier planning basic concepts, optimization models and advanced memetic algorithms ; with 24 tables Jörn Schönberger |
| title_short | Operational freight carrier planning |
| title_sort | operational freight carrier planning basic concepts optimization models and advanced memetic algorithms with 24 tables |
| title_sub | basic concepts, optimization models and advanced memetic algorithms ; with 24 tables |
| topic | Memetischer Algorithmus (DE-588)4625421-3 gnd Güterverkehr (DE-588)4022492-2 gnd Tourenplanung (DE-588)4121783-4 gnd |
| topic_facet | Memetischer Algorithmus Güterverkehr Tourenplanung Hochschulschrift |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=2601858&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=015654550&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT schonbergerjorn operationalfreightcarrierplanningbasicconceptsoptimizationmodelsandadvancedmemeticalgorithmswith24tables |