Service Network Design of Bike Sharing Systems (eBook)

Contents 6
Abbreviations 9
Symbols 9
1 Introduction 13
Part I Problem Description 17
2 Bike Sharing in the Context of Urban Mobility 18
2.1 Mobility, Urban Transportation Challenges, and Trends 19
2.1.1 Mobility Needs and Behavior 20
2.1.2 Basics of Urban Transportation 21
2.1.3 Urban Transportation Challenges 24
2.1.4 Trends in Urban Mobility and Transportation 25
2.2 Bike Sharing Systems as a Concept of Shared Mobility 26
2.2.1 Usage-Oriented Motives for Shared Mobility 26
2.2.2 Business Models of Shared Mobility Systems 29
2.2.3 Information Systems Support of Bike Sharing Systems 32
2.2.4 General Guidelines on the Planning, Implementation, and Operation of BSS 36
3 Service Network Design as a Logistical Challenge in the Reliable Provision of Service in Bike Sharing Systems 42
3.1 Classification of Logistical Planning Levels for SMS 43
3.2 Service Network Design for Tactical Planning of BSS 46
3.2.1 General Concept of Service Network Design in Freight Transportation 46
3.2.2 Special Requirements of Tactical Planning in BSS 48
3.3 Appreciation of Literature Related to Logistical Planning Levels for SMS 51
3.3.1 Operational and Strategic Planning 51
3.3.2 Tactical Planning 54
3.4 Intelligent Data Analysis and Optimization for Service Network Design of Bike Sharing Systems 56
Part II Intelligent Data Analysis 60
4 Determination of Typical Bike Flows 61
4.1 An Information Model for Generation of Typical Bike Flows 62
4.1.1 Combining Intelligent Data Analysis and Transportation Planning 62
4.1.2 Formalization of the Information Model 65
4.2 Intelligent Data Analysis for Parameterization of the Information Model 70
4.2.1 Preprocessing to Create the Target Data Set 74
4.2.2 Data Exploration to Understand Bike Imbalances and Determine the Temporal Scope of Tactical Planning 76
4.2.3 Determine Trip Purposes by Cluster Analysis 77
5 Case Study: Generation of Typical Bike Flows for Citybike Wien 91
5.1 Preprocessing to Create the Target Data Set 92
5.2 Spatial and Temporal Exploration of Trips 94
5.2.1 Spatial Exploration to Understand Trip Generation and Attraction 94
5.2.2 Temporal Exploration to Determine the Tactical Planning Scope 97
5.2.3 Spatiotemporal Exploration to Show the Flaw of Averages 102
5.3 Determination of Trip Purposes 104
5.3.1 Temporal Distribution of Trips 105
5.3.2 Spatial Distribution of Trips 109
5.4 Generation and Validation of Typical Bike Flows 111
5.5 Generating Artificial Instances of Bike Sharing Systems 114
Part III Optimization 120
6 Service Network Design of Bike Sharing Systems 121
6.1 Related Approaches of Dynamic Service Network Design 121
6.2 Mixed-integer Programming Formulation for SND of BSS 125
6.3 A Hybrid Metaheuristic to Solve the Service Network Design Model 130
6.3.1 Selecting a Suitable Hybrid Metaheuristic Concept 130
6.3.2 MIP-Based Large Neighborhood Search for Dynamic SND of BSS 133
6.3.3 Obtaining a Starting Solution by LP Relaxation 136
6.4 Investigating the Performance of Solution Methods Using Artificial Instances 137
6.4.1 Experimental Setup 137
6.4.2 Performance of Solution Methods 139
6.4.3 Effect of Neighborhood Operators 140
7 Case Study: Service Network Design of Citybike Wien 144
7.1 Experimental Setup 144
7.2 Performance of Solution Methods and Neighborhood Operators 145
7.2.1 Performance of Solution Methods 145
7.2.2 Effect of Neighborhood Operators 147
7.3 Service Network Design for Different Scenarios 148
7.3.1 The Current System Configuration with Low Demand 149
7.3.2 Comparison of Demand Scenarios 154
7.4 The Benefit and Usefulness of Service Network Design 160
Part IV Conclusion 162
8 Conclusions and Outlook 163
Bibliography 166