This volume of three books presents recent advances in modelling, planning and evaluating city logistics for sustainable and liveable cities based on the application of ICT (Information and Communication Technology) and ITS (Intelligent Transport Systems). It highlights modelling the behaviour of stakeholders who are involved in city logistics as well as planning and managing policy measures of city logistics including cooperative freight transport systems in public-private partnerships. Case studies of implementing and evaluating city logistics measures in terms of economic, social and environmental benefits from major cities around the world are also given.
Table of Contents
Preface xv
Chapter 1. Urban Logistics Spaces: What Models, What Uses and What Role for Public Authorities? 1
Danièle PATIER and Florence TOILIER
1.1. Introduction 1
1.2. Literature review 2
1.3. ULS typology . 4
1.3.1. The Urban Logistics Zone (ULZ) or freight village 4
1.3.2. The Urban Distribution Center (UDC) 6
1.3.3. Vehicle Reception Points (VRP) 9
1.3.4. Goods Reception Points (GRP) 12
1.3.5. The Urban Logistics Box (ULB) 13
1.3.6. Mobile Urban Logistics Spaces (mULS) 15
1.4. Recommendations 18
1.5. Conclusion 19
1.6. Bibliography 20
Chapter 2. Dynamic Management of Urban Last-Mile Deliveries 23
Tomislav LETNIK, Matej MENCINGER and Stane BOZICNIK
2.1. Introduction 23
2.2. Review of urban freight loading bay problems and solutions 25
2.3. Information system for dynamic management of urban last-mile deliveries 26
2.4. Algorithm for dynamic management of urban freight deliveries 29
2.5. Application of the model to a real case 32
2.6. Conclusions 33
2.7. Bibliography 34
Chapter 3. Stakeholders’ Roles for Business Modeling in a City Logistics Ecosystem: Towards a Conceptual Model 39
Giovanni ZENEZINI, J.H.R. VAN DUIN, Lorant TAVASSZY and Alberto DE MARCO
3.1. Introduction 39
3.2. Research background 41
3.2.1. Business model concept 41
3.2.2. Business ecosystem 42
3.2.3. Role-based networks and ecosystems 43
3.3. The CL business model framework: roles, business entities and value exchanges 43
3.4. City logistics concepts and role assignment 48
3.4.1. Parcel lockers installation: MyPUP 48
3.4.2. Urban consolidation centers 51
3.4.3. Business model implications 54
3.5. Conclusions 55
3.6. Bibliography 56
Chapter 4. Establishing a Robust Urban Logistics Network at FEMSA through Stochastic Multi-Echelon Location Routing 59
André SNOECK, Matthias WINKENBACH and Esteban E. MASCARINO
4.1. Introduction 59
4.2. Strategic distribution network design 62
4.2.1. Distribution network 63
4.2.2. Network cost 63
4.2.3. Distribution cost 64
4.2.4. Optimization model 65
4.3. Solution scheme 67
4.3.1. Scenario generation and selection 67
4.3.2. Design generation 68
4.3.3. Design evaluation 68
4.4. Case study 68
4.4.1. Data and parameters 69
4.4.2. Analysis results 70
4.5. Results 71
4.5.1. Design generation 71
4.5.2. Design evaluation 72
4.5.3. Sensitivity to cost of lost sales 73
4.6. Conclusion 75
4.7. Bibliography 75
Chapter 5. An Evaluation Model of Operational and Cost Impacts of Off-Hours Deliveries in the City of São Paulo, Brazil 79
Cláudio B. CUNHA and Hugo T.Y. YOSHIZAKI
5.1. Introduction 79
5.2. Literature review 81
5.3. Proposed approach 84
5.4. Scenario generation 87
5.5. Results 90
5.6. Concluding remarks 94
5.7. Bibliography 94
Chapter 6. Application of the Bi-Level Location-Routing Problem for Post-Disaster Waste Collection 97
Cheng CHENG, Russell G. THOMPSON, Alysson M. COSTA and Xiang HUANG
6.1. Introduction 97
6.2. Model formulation 99
6.3. Solution algorithm 104
6.3.1. Genetic Algorithms 104
6.3.2. Greedy Algorithm 105
6.3.3. Simulated Annealing 106
6.4. Case study 106
6.4.1. Case study area 106
6.5. Result analysis 109
6.5.1. Models comparison 109
6.5.2. Sensitivity analysis 111
6.6. Conclusion 113
6.7. Bibliography 114
Chapter 7. Next-Generation Commodity Flow Survey: A Pilot in Singapore 117
Lynette CHEAH, Fang ZHAO, Monique STINSON, Fangping LU, Jing DING-MASTERA, Vittorio MARZANO, and Moshe BEN-AKIVA
7.1. Introduction 117
7.2. Integrated commodity flow survey 119
7.2.1. Overview 119
7.3. Key survey features 121
7.3.1. Sampling related supply network entities 121
7.3.2. Multiple survey instruments leveraging sensing technologies 121
7.3.3. A unified web-based survey platform 122
7.4. Pilot survey implementation 123
7.4.1. Sample design and recruitment 124
7.4.2. Shipment and vehicle tracking methods 125
7.4.3. Pilot survey experience and lessons learnt 126
7.4.4. Preliminary data analysis 127
7.5. Conclusion 129
7.6. Acknowledgements 129
7.7. Bibliography 130
Chapter 8. City Logistics and Clustering: Impacts of Using HDI and Taxes 131
Rodrigo Barros CASTRO, Daniel MERCH N, Orlando Fontes LIMA JR and Matthias WINKENBACH
8.1. Introduction 131
8.2. Methodology 133
8.2.1. Principal component analysis 135
8.2.2. K-means clustering 135
8.3. Results 135
8.4. Conclusion 140
8.5. Bibliography 140
Chapter 9. Developing a Multi-Dimensional Poly-Parametric Typology for City Logistics 143
Paulus ADITJANDRA and Thomas ZUNDER
9.1. Introduction 143
9.2. Literature review 144
9.3. Methodology 145
9.4. Evaluation and analysis 146
9.4.1. Inventory of all EU projects 146
9.4.2. Inventory of typologies 147
9.4.3. Land use typologies 148
9.4.4. Measure typologies 149
9.4.5. Urban freight markets 151
9.4.6. Traffic flow typology 152
9.4.7. Impacts 153
9.4.8. Gaps 153
9.5. Validation and enhancement of the inventory 154
9.6. Proposed typology 155
9.6.1. Approach 155
9.6.2. Dimension: Why? 157
9.6.3. Dimension: Where? 157
9.6.4. Dimension: Who? 158
9.6.5. Dimension: What? 158
9.6.6. Dimension: How? 159
9.7. Reflections 159
9.8. Conclusion 160
9.9. Acknowledgements 160
9.10. Bibliography 160
Chapter 10. Multi-agent Simulation with Reinforcement Learning for Evaluating a Combination of City Logistics Policy Measures 165
Eiichi TANIGUCHI, Ali Gul QURESHI and Kyosuke KONDA
10.1. Introduction 165
10.2. Literature review 166
10.3. Models 166
10.4. Case studies in Osaka and Motomachi 168
10.4.1. Settings 168
10.4.2. Results 170
10.5. Conclusion 175
10.6. Bibliography 176
Chapter 11. Decision Support System for an Urban Distribution Center Using Agent-based Modeling: A Case Study of Yogyakarta Special Region Province, Indonesia 179
Bertha Maya SOPHA, Anna Maria Sri ASIH, Hanif Arkan NURDIANSYAH and Rahma MAULIDA
11.1. Introduction 179
11.2. Theoretical background 182
11.2.1. Urban distribution center 182
11.2.2. Decision support system of city logistics 183
11.3. The proposed decision support system 184
11.3.1. System characterization 184
11.3.2. The logical architecture 185
11.3.3. Agent-based modeling (ABM) 187
11.3.4. Model verification and validation 190
11.4. Example of application: the case of Yogyakarta Special Region 191
11.5. Conclusion 192
11.6. Acknowledgements 193
11.7. Bibliography 194
Chapter 12. Evaluating the Relocation of an Urban Container Terminal 197
Johan W. JOUBERT
12.1. Introduction 197
12.2. Methodology 199
12.2.1. MATSim 199
12.2.2. Initial demand 200
12.2.3. Alternative scenarios 201
12.3. Results 201
12.3.1. Directly affected vehicles 202
12.3.2. Extended effects 205
12.4. Conclusion 208
12.5. Acknowledgements 209
12.6. Bibliography 209
Chapter 13. Multi-Agent Simulation Using Adaptive Dynamic Programing for Evaluating Urban Consolidation Centers 211
Nailah FIRDAUSIYAH, Eiichi TANIGUCHI and Ali Gul QURESHI
13.1. Introduction 211
13.2. Literature review 212
13.2.1. Evaluation models for city logistics measures 212
13.2.2. ADP for evaluating city logistics measures 213
13.3. Models 214
13.3.1. Freight carrier’s MAS-ADP model 215
13.3.2. Freight carrier’s MAS Q-learning model 217
13.3.3. Vehicle routing problem with soft time windows (VRPSSTW) 218
13.4. Case study 220
13.5. Results and discussions 221
13.5.1. Case 0 (base case) 222
13.5.2. Case 1 223
13.6. Conclusion and future work 226
13.7. Bibliography 226
Chapter 14. Use Patterns and Preferences for Charging Infrastructure for Battery Electric Vehicles in Commercial Fleets in the Hamburg Metropolitan Region 229
Christian BLUSCH, Heike FLÄMIG and Sören Christian TRÜMPER
14.1. Introduction 229
14.2. State of the art/context of study 230
14.3. Research goal and approach 231
14.4. Method of data collection 232
14.5. Results and discussion 232
14.6. Conclusions 237
14.7. Acknowledgements 238
14.8. Bibliography 238
Chapter 15. The Potential of Light Electric Vehicles for Specific Freight Flows: Insights from the Netherlands 241
Susanne BALM, Ewoud MOOLENBURGH, Nilesh ANAND and
Walther PLOOS VAN AMSTEL
15.1. Introduction 241
15.2. Definition of LEFV 243
15.3. State of the art 244
15.4. Methodology 246
15.5. Potential of LEFV for different freight flows 247
15.5.1. Selection of freight flows 247
15.5.2. Description of freight flows 248
15.5.3. Receivers’ perspective 253
15.6. Multi-criteria evaluation 253
15.6.1. Setup 253
15.6.2. Outcome 254
15.7. Discussion 256
15.8. Conclusion 257
15.9. Acknowledgements 258
15.10. Bibliography 259
Chapter 16. Use of CNG for Urban Freight Transport: Comparisons Between France and Brazil 261
Leise Kelli DE OLIVEIRA and Diana DIZIAIN
16.1. Introduction 261
16.2. Brief literature review 263
16.3. Methodology 264
16.4. Brazilian case 264
16.5. French case 265
16.6. Comparison of Brazilian and French experience 267
16.7. Conclusion 268
16.8. Acknowledgements 268
16.9. Bibliography 268
Chapter 17. Using Cost–Benefit Analysis to Evaluate City Logistics Initiatives: An Application to Freight Consolidation in Small- and Mid-Sized Urban Areas 271
Johan HOLMGREN
17.1. Introduction 271
17.2. Characteristics of city logistics and some terminology 273
17.2.1. Efficiency in city logistics 274
17.2.2. Evaluation methods 275
17.3. Potential costs and benefits of implementing urban consolidation centers 279
17.4. Coordinated freight distribution in Linköping 280
17.5. Evaluating urban freight initiatives by cost–benefit analysis 281
17.6. The problem of cost allocation 286
17.7. Conclusion 286
17.8. Bibliography 287
Chapter 18. Assumptions of Social Cost–Benefit Analysis for Implementing Urban Freight Transport Measures 291
Izabela KOTOWSKA, Stanisław IWAN, Kinga KIJEWSKA and Mariusz JEDLIŃSKI
18.1. Introduction 291
18.2. The assumptions for utilization of SCBA in city logistics 295
18.2.1. External air pollution cost 296
18.2.2. Marginal climate change costs 299
18.2.3. Marginal accident costs 301
18.2.4. Congestion costs 302
18.2.5. Marginal external noise costs 304
18.2.6. Employment growth and development of local economy 305
18.2.7. Final calculations 308
18.3. Conclusions 310
18.4. Acknowledgements 310
18.5. Bibliography 310
Chapter 19. Barriers to the Adoption of an Urban Logistics Collaboration Process: A Case Study of the Saint-Etienne Urban Consolidation Centre 313
Kanyarat NIMTRAKOOL, Jesus GONZALEZ-FELIU and Claire CAPO
19.1. Introduction 313
19.2. Background and theoretical framework 315
19.2.1. The stakeholders in an urban logistics collaboration project 315
19.2.2. Urban Consolidation Centre (UCC) as an organizational innovation 316
19.2.3. Barriers in urban logistics projects 318
19.3. Research methodology 320
19.3.1. The research approach 320
19.3.2. Qualitative study: selection of respondents 320
19.3.3. Quantitative analysis: purpose and CBA methodology 321
19.4. Results 322
19.4.1. The UCC of Saint-Etienne: background and objectives 322
19.4.2. Operation aspects 323
19.4.3. The conditions of economic viability of Saint-Etienne’s UCC 324
19.4.4. Barriers identified by stakeholders 326
19.5. Conclusions 328
19.6. Bibliography 328
Chapter 20. Logistics Sprawl Assessment Applied to Locational Planning: A Case Study in Palmas (Brazil) 333
Lilian dos Santos Fontes Pereira BRACARENSE, Thiago Alvares ASSIS, Leise Kelli DE OLIVEIRA and Renata Lúcia Magalhães DE OLIVEIRA
20.1. Introduction 333
20.2. Logistics sprawl and the importance of logistics facilities’ location 334
20.3. Methodology 335
20.4. Area of study 339
20.4.1. Logistics sprawl assessment and scenario comparison 342
20.5. Conclusion 347
20.6. Acknowledgements 348
20.7. Bibliography 348
Chapter 21. Are Cities’ Delivery Spaces in the Right Places? Mapping Truck Load/Unload Locations 351
Anne GOODCHILD, Barb IVANOV, Ed MCCORMACK, Anne MOUDON, Jason SCULLY, José Machado LEON and Gabriela GIRON VALDERRAMA
21.1. Introduction 351
21.2. Moving more goods, more quickly 352
21.3. Establishment of a well-defined partnership 353
21.4. The Final 50 Feet project 354
21.5. Getting granular 356
21.6. Mapping the city’s freight delivery infrastructure 358
21.6.1. Step 1: collect existent data 358
21.6.2. Step 2: develop survey to collect freight bay and loading dock data 358
21.6.3. Preliminary site visits 359
21.6.4. Initial survey form and the pilot survey 360
21.6.5. Step 3: implement the survey 363
21.7. Research results 366
21.8. Conclusion 368
21.9. Bibliography 368
List of Authors 369
Index 375
