Schorpp Dynamic Fleet Management for International Truck Transportation

Focusing on Occasional Transportation Tasks
1. Auflage 2011
ISBN: 978-3-8349-6675-9
Verlag: Betriebswirtschaftlicher Verlag Gabler
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 191 Seiten, eBook

Reihe: Produktion und Logistik

Two new dynamic planning approaches, incorporating all important real-life restrictions, such as regulations on driving and working hours, are developed and evaluated. Extensive numerical tests are carried out with a five-week real-life data set from an international freight forwarding company.

Dr. Steffen Schorpp wrote his dissertation under Prof. Dr. Bernhard Fleischmann's supervision at the Chair of Production and Logistics at the University of Augsburg.

Zielgruppe

Research

Autoren/Hrsg.

Schorpp, Steffen

Inhaltsverzeichnis

1;Foreword;6
2;Acknowledgements;8
3;Contents;9
4;Abbreviations;11
5;List of Figures;13
6;List of Tables;15
7;Chapter 1 Introduction ;17
7.1;1.1 Motivation;17
7.2;1.2 Goal of the Study and Problem Outline;19
7.3;1.3 Developments towards Dynamic Tour Planning;20
7.4;1.4 Market Analysis;23
7.5;1.5 Course of Action;25
8;Chapter 2 Dynamic Transportation Problems;27
8.1;2.1 Characteristics of Dynamic Problems;27
8.1.1;Measuring Dynamism;32
8.1.2;Configuration Framework for Dynamic Algorithms;34
8.1.2.1;1. Technique of Adjustment;34
8.1.2.2;2. Reaction of Adjustment;35
8.1.2.3;3. Frequency of Adjustment;35
8.1.2.4;4. Duration of Adjustment;35
8.1.2.5;5. Synchronization of Adjustment;36
8.1.2.6;6. Scope of Adjustment;36
8.1.2.7;Simulation Techniques for Dynamic Algorithms;36
8.1.2.8;Performance Analysis for dynamic algorithms;37
8.2;2.2 Relevance and Classification of Dynamic StandardProblems;39
8.3;2.3 Investigated Problem Settings;42
9;Chapter 3 Literature Review;46
9.1;3.1 Statistical Analysis of the Surveyed Publications;46
9.2;3.2 Practical Applications;48
9.3;3.3 Algorithmic Solution Concepts;51
9.3.1;3.3.1 Dynamic Approaches without Knowledge of the Future;52
9.3.1.1;3.3.1.1 Local Search Approaches;52
9.3.1.2;3.3.1.2 Metaheuristics;56
9.3.1.2.1;Tabu Search;56
9.3.1.2.2;Evolutionary Approaches;60
9.3.1.2.3;Variable Neighborhood Search;64
9.3.1.2.4;Ant Colony;66
9.3.1.2.5;Second Objective Function;67
9.3.1.3;3.3.1.3 Heuristic Application of Exact Procedures;68
9.3.1.3.1;Column Generation;68
9.3.1.3.2;Lagrange Relaxation;69
9.3.1.3.3;Application of CPLEX Solver;70
9.3.1.3.4;Linear Assignment Problems;71
9.3.1.4;3.3.1.4 Rule-Based Decision Making;72
9.3.1.4.1;Rule-Based Decision Making;72
9.3.1.4.2;Fuzzy Logic Approach;75
9.3.1.5;3.3.1.5 Multi-Agent Systems;75
9.3.1.6;3.3.2 Strategies Anticipating the Future without Knowledge ofthe Future;76
9.3.1.7;3.3.3 Dynamic Stochastic Approaches with Explicit Knowledgeof the Future;79
9.4;3.4 Dynamic Test Data;87
9.5;3.5 Acceptance of Dynamic Planning Applications inReal-Life;90
10;Chapter 4 Development and Evaluation of twoDynamic Planning Procedures ;92
10.1;4.1 Multiple Neighborhood Search;92
10.1.1;4.1.1 General Planning Process and Synchronization;92
10.1.2;4.1.2 Best Insertion;94
10.1.3;4.1.3 Improvement Neighborhoods;95
10.1.4;4.1.4 Simulation Framework;97
10.2;4.2 Assignment Based Procedure;102
10.2.1;4.2.1 Bipartite Assignment Problem;102
10.2.2;4.2.2 Assignment Matrix;103
10.2.2.1;Sector I;104
10.2.2.2;Sector II;105
10.2.2.3;Sector III;106
10.2.2.4;Sector IV;106
10.2.3;4.2.3 Events and Matrix Updates;109
10.2.4;4.2.4 Procedure Workflow and Simulation;110
10.3;4.3 A Comparison of Both Procedures;114
10.4;4.4 Test Data;116
10.4.1;4.4.1 Self-Generated Test Scenarios;116
10.4.1.1;Node Network;116
10.4.1.2;Static and dynamic orders;117
10.4.1.3;Vehicles;118
10.4.2;4.4.2 Benchmark Data from the Literature;118
10.5;4.5 Computational Results and Performance Analysis;123
10.5.1;4.5.1 Computational Results for Self-Generated Test Scenarios;123
10.5.2;4.5.2 Computational Results for Benchmark Data from the Literature;130
10.6;4.6 Selection of a Procedure for the Real-Life Application;134
11;Chapter 5 Real-Life Application at an Internationally Operating Freight Forwarding Company;137
11.1;5.1 General Requirements for Long-Haul Transportationin Europe;137
11.1.1;5.1.1 Social Regulation EC 561/2006;138
11.1.1.1;Single Driver Mode;139
11.1.1.2;Team Driver Mode;140
11.1.2;5.1.2 Social Regulation AETR;141
11.1.3;5.1.3 Directive EC 2002/15 on Working Hours;142
11.1.4;5.1.4 Traffic Bans;143
11.1.5;5.1.5 Inspection of Compliance;144
11.1.6;5.1.6 Some Recent Literature;145
11.2;5.2 Exemplary Real-Life Planning Situation at aFreight Forwarding Company;146
11.3;5.3 Adjustment of Multiple Neighborhood Search;149
11.3.1;5.3.1 Selected General Requirements;149
11.3.2;5.3.2 Selected Requirements based on the Real-Life PlanningSituation;150
11.3.3;5.3.3 Adjustment of Internal Data Structures;153
11.3.4;5.3.4 Adjustments to the MNS modules Best Insertion and Scheduling;154
11.4;5.4 Real-Life Test Data Set: Preprocessing and Analysis;158
11.4.1;Selection of appropriate data;158
11.4.2;Adjustment of notation inconsistencies;159
11.4.3;Plausibility checks;159
11.4.4;Determination of initial vehicle position and availability;160
11.4.5;Derivation of benchmark objective function values;161
11.5;5.5 Computational Results;162
11.5.1;5.5.1 Parameterization;162
11.5.2;5.5.2 Exemplary Real-Life Scheduling;171
11.5.3;5.5.3 Final Results;179
11.5.4;5.5.4 Discussion;181
12;Chapter 6 Conclusion and Outlook;184
12.1;6.1 Conclusion;184
12.2;6.2 Recommendations for Further Research;187
13;Bibliography;190
14;Appendix;200
15;A Pseudocode of MNS Improvement Neighborhoods;201
16;B Parameterization - Detailed Results;203

Über Autor(innen)

Dr. Steffen Schorpp wrote his dissertation under Prof. Dr. Bernhard Fleischmann’s supervision at the Chair of Production and Logistics at the University of Augsburg.