City Logistics 1

Eiichi Taniguchi, Kyoto University, Japan. Russell G. Thompson, The University of Melbourne, Australia.

• Preface xvChapter 1. Recent Developments and Prospects for Modeling City Logistics 1Eiichi TANIGUCHI, Russell G. THOMPSON and Ali Gul QURESHI1.1. Introduction 11.2. VRPTW with consideration of environment, energy efficiency and safetyh21.3. Multi-agent models 31.4. Big data analysis 41.5. Physical Internet 51.5.1. Movers 61.5.2. Nodes 61.5.3. Container loading 71.5.4. Cross-docking 71.6. Co-modality 81.7. Electric vehicles 121.8. Road network strengthening 131.9. Conclusions 151.10. Bibliography 16Chapter 2. Light Commercial Vehicles (LCVs) in Urban Areas, Revisited 29Johan VISSER, Julian ALLEN, Michael BROWNE, José HOLGUÍN-VERAS and Juvena NG2.1.Introduction 292.2. Terminology 302.3. Trends in the Netherlands 312.3.1. The number of LCVs is growing 312.3.2. Most LCVs are (not) used for logistics 322.3.3. LCVs are used mainly within urban areas 322.3.4. Due to Internet shopping, the number of LCVs in cities will increase but not with the same speed as the yearly growth of Internet shopping 332.3.5. Vans become bigger 332.3.6. Competition from the cargo bike 332.4. Trends in the United States 342.4.1. Historical estimates of LCV traffic (1960s) 342.4.2. Recent estimates of LCV traffic (2015) 352.5. Trends in the UK 372.5.1. LCVs journey purpose and fleet numbers by sector 382.5.2. Changes in size, weight and propulsion for LCVs in the UK 402.5.3. E-commerce and the rise in van numbers 402.6. Future 412.7. Conclusions 422.8. Bibliography 42Chapter 3. Importance and Potential Applications of Freight and Service Activity Models 45José HOLGUIN-VERAS, Shama CAMPBELL, Carlos A. GONZÁLEZ-CALDERÓN, Diana RAMÍREZ-RÍOS, Lokesh KALAHASTHI, Felipe AROS-VERA, Michael BROWNE and Ivan SANCHEZ-DIAZ3.1.Introduction 453.2. Urban economies and freight and service activity 473.3. Freight and service activity modeling 513.3.1. Survey data 523.3.2. Modeling approach 533.4. Practical uses of freight and service activity models 543.4.1. Identification of FTG patterns in metropolitan areas 553.4.2. FTG trends at the county level 573.4.3. FTG analyses to support development of freight model 583.4.4. Quantification of parking needs for a commercial center 583.5. Conclusions 593.6. Bibliography 60Chapter 4. Toward Sustainable Urban Distribution Using City Canals: The Case of Amsterdam 65J.H.R. VAN DUIN, L.J. KORTMANN and M. VAN DE KAMP4.1. Introduction 654.2. Literature review on waterborne urban freight transport 684.3. Conceptual model of distribution of the canal system 704.3.1. Freight 714.3.2. Freight vessels 714.3.3. Canals 724.3.4. Destinations (shops) and their final delivery 724.4. Specification of the model 724.4.1. Data collection and general modeling assumptions 734.4.2. Demand patterns 734.5. Verification and validation 744.5.1. Verification 754.5.2. Validation 754.6. Experiments 754.6.1. Overview and discussion of simulation experiments 764.6.2. Discussion of the main findings 784.7. Conclusions 794.8. Bibliography 80Chapter 5. Effects of Land Use Policies on Local Conditions for Truck Deliveries 85Kazuya KAWAMURA and Martin MENNINGER5.1. Introduction 855.2. Policy tools of land use and built environment 875.3. Research framework 895.3.1. Research hypothesis 895.3.2. Data 915.3.3. Truck Score 915.3.4. Analysis tools 945.4. Analysis results 965.4.1. Lane width 965.4.2. Access time to expressways 975.4.3. Truck parking citations 995.4.4. Truck Scores 1005.5. Summary and conclusion 1015.6. Bibliography 103Chapter 6. Investigating the Benefits of Shipper-driven Collaboration in Urban Freight Transport and the Effects of Various Gain-sharing Methods 105Milena JANJEVIC, Ahmed AL FARISI, Alexis NSAMZINSHUTI and Alassane NDIAYE6.1. Introduction 1056.2. Methodology 1076.3. Literature review 1086.3.1. Models for horizontal collaboration in urban freight transport 1086.3.2. Gain-sharing methodologies for horizontal collaboration 1116.3.3. Modeling horizontal collaboration schemes in urban freight transport 1136.4. Modeling horizontal collaboration in urban freight transport 1136.4.1. Simulating a horizontal collaboration between shippers 1136.4.2. Integrating different gain-sharing methods between shippers 1166.5. Application to Brussels-Capital Region 1176.5.1. Context 1176.5.2. Results with regard to the benefits of the co-loading scheme 1186.5.3. Analysis of different gain-sharing models 1196.6. Conclusion 1216.7. Bibliography 122Chapter 7. The Future of City Logistics – Trends and Developments Leading toward a Smart and Zero-Emission System 125Hans QUAK, Robert KOK and Eelco DEN BOER7.1.Introduction 1257.1.1. Zero-emission logistics in city centers 1267.1.2. Reducing city logistics’ carbon footprint to meet climate agreement 1267.1.3. Dealing with diversity and inertia in city logistics 1277.2. Research methodology and paper setup 1287.3. Trends and developments in city logistics 1307.3.1. More demanding customer 1307.3.2. Increasing pressure for reduction of GHG emissions 1307.3.3. Increased pressure for livability of cities 1317.3.4. Circular economy 1317.3.5. Connecting the physical world 1317.3.6. Physical Internet and universal labeling 1327.3.7. Robotization and automation 1327.3.8. Vehicle drivetrain technology 1337.4. Toward performance-based regulation 1347.5. City logistics unraveled: different segments 1357.5.1. General cargo 1367.5.2. Temperature controlled logistics 1377.5.3. Parcel and express mail 1387.5.4. Facility logistics 1387.5.5. Construction logistics 1387.5.6. Waste collection 1397.6. Developments’ impacts in city logistics segments 1397.7. Conclusion 1447.8. Acknowledgements 1447.9. Bibliography 145Chapter 8. A 2050 Vision for Energy-efficient and CO2-free Urban Logistics 147Martin RUESCH, Simon BOHNE, Thomas SCHMID, Philipp HEGI, Ueli HAEFELI, Tobias ARNOLD and Tobias FUMASOLI8.1. Introduction 1478.1.1. Starting point and challenges 1478.1.2. Research objectives 1488.1.3. Project phases and work packages 1498.1.4. Research focus and boundaries 1508.1.5. Research Framework 1508.1.6. Focus of the chapter 1518.2. Approach and methodology 1518.3. Scenario development and analysis 1548.3.1. Approach for scenario development 1548.3.2. Scenario A: protection of natural resources 1558.3.3. Scenario B: liberalization and technology orientation 1558.3.4. Main features of the scenarios 1568.3.5. Quantification of scenarios 1568.4. 2050 vision targets 1588.5. 2050 vision for energy-efficient and CO2-free urban logistics 1598.5.1. 2050 vision development process vision elements 1598.5.2. 2050 vision for energy-efficient and CO2-free urban logistics 1618.5.3. Vision impact 1638.6. Conclusions and outlook 1658.7. Acknowledgements 1668.8. Bibliography 166Chapter 9. Assessing the Impact of a Low Emission Zone on Freight Transport Emission 169Christophe RIZET9.1. Introduction 1699.1.1. Freight fleets and their changes 1719.2. Changes in emissions in the Paris area according to scenarios 1799.3. Conclusion 1839.4. Bibliography 185Chapter 10. Long-Term Effects of Innovative City Logistics Measures 189Tariq VAN ROOIJEN, Don GUIKINK and Hans QUAK10.1. Introduction 18910.2. Data and methodology 19210.3. General long-term effects of CIVITAS II city logistics measures 19310.4. Case studies of city logistics measures in CIVITAS PLUS 19510.4.1. Case study 1: Cargohopper 19510.4.2. Case study 2: Beer Boat 20010.5. Analysis 20510.6. Conclusion 20610.7. Acknowledgements 20710.8. Bibliography 207Chapter 11. Classification of Last-Mile Delivery Models for e-Commerce Distribution: A Global Perspective 209Matthias WINKENBACH and Milena JANJEVIC11.1. Introduction 20911.2. Scope of the study 21111.3. Literature review 21111.4. Characterizing the operational setups of delivery models 21211.4.1. Groups of variables defining last-mile e-commerce delivery models observed in case studies 21311.4.2. Relationships between characteristic variables 21411.5. Classification of last-mile delivery models in e-retail 21611.5.1. Delivery model archetype 1: direct non-priority home/near-home or workplace deliveries 21711.5.2. Delivery model archetype 2: deliveries towards automatic lockers 21911.5.3. Delivery model archetype 3: deliveries towards pick-up points 21911.5.4. Delivery model archetype 4: delivery through a (micro-) consolidation center or urban depot 22011.5.5. Delivery model archetype 5: delivery through mobile warehouse 22111.5.6. Delivery model archetype 6: home delivery using an intermediary transshipment point 22111.5.7. Delivery model archetype 7: local e-fulfillment and same-day delivery through local specialists 22211.5.8. Delivery model archetype 8: same-day delivery through hyperlocal inventory and process optimization 22211.5.9. Delivery model archetype 9: same-day customer pick-up at local e-fulfillment centers 22311.5.10. Delivery model archetype 10: delivery through local courier or crowdshipping networks 22311.6. The importance of local context 22411.7. Conclusion 22511.8. Bibliography 225Chapter 12. City Logistics with Collaborative Centers 231Serban RAICU, Raluca RAICU, Dorinela COSTESCU and Mihaela POPA12.1.Introduction 23112.2. Problem presentation 23212.3. Transfer options between the collaborative centers 23512.4. Mathematical model 24012.5. Case study 24212.6. Conclusion 24712.7. Bibliography 248Chapter 13. Exploring Criteria for Tendering for Sustainable Urban Construction Logistics 251Susanne BALM and Walther PLOOS VAN AMSTEL13.1. Introduction 25113.2. Construction logistics 25213.2.1. Standardization 25413.2.2. Model development 25413.2.3. Traffic management and ITS 25513.3. Tendering construction projects 25613.4. Discussion and further research 25913.4.1. Current research 25913.5. Bibliography 260Chapter 14. Observing Interactions Between Urban Freight Transport Actors: Studying the Construction of Public Policies 265Mathieu GARDRAT14.1. Introduction 26514.2. A diversity of approaches 26614.3. Field of observation 26714.4. Analysis framework and data collection method 26714.5. Social interactions analysis: perceptions of urban freight 27414.6. Explaining the policy-making obstacles 27914.7. Conclusion 28114.8. Bibliography 283Chapter 15. Viewpoint of Industries, Retailers and Carriers about Urban Freight Transport: Solutions, Challenges and Practices in Brazil 287Leise Kelli DE OLIVEIRA, Paulo Renato DE SOUSA, Paulo Tarso Vilela DE RESENDE, Rafael Barroso DE OLIVEIRA and Renata Lúcia Magalhães DE OLIVEIRA15.1. Introduction 28715.2. Methodology 28915.3 Results 29015.3.1. City logistics solutions and stakeholders’ points of view 29115.3.2. Solutions, challenges and current practices 29515.4. Discussion of results 29715.5. Conclusion 29815.6. Acknowledgements 29815.7. Bibliography 298Chapter 16. Municipal Co-distribution of Goods: Business Models, Stakeholders and Driving Forces for Change 303Olof MOEN16.1. Introduction 30316.2. Business models 30516.3. Stakeholders 30816.4. Development 1999–2016 31016.5. The Skåne survey 31416.6. Driving forces for change 31516.7. Conclusion 31916.8. Bibliography 319Chapter 17. Optimizing Courier Routes in Central Business Districts 325Russell G. THOMPSON, Lele ZHANG and Michael STOKOE17.1. Introduction 32517.2. Model development 32617.3. Literature review 32817.3.1. Bi-level optimization 32817.3.2. Vehicle routing problem (traveling salesman problem) 32917.3.3. Multi-objective optimization 32917.4. Formulation 33017.4.1. Notation 33017.4.2. Assumptions 33017.4.3. Costs 33117.4.4. Bi-level programming formulation 33117.5. Software development 33217.5.1. Neighborhood generation procedures 33317.6. Test network 33317.7. Sydney central business district 33517.8. Conclusion 33817.9. Bibliography 339Chapter 18. A Vehicle Routing Model Considering the Environment and Safety in the Vicinity of Sensitive Urban Facilities 343Ali Gul QURESHI, Eiichi TANIGUCHI And Go IWASE18.1. Introduction 34318.2. Modeling 34518.3. Genetic algorithm 34818.4. Experiment setup 34918.5. Results and discussion 35018.6. Conclusion 35518.7. Bibliography 356Chapter 19. Remote Assessment Sensor Routing: An Application for Waste Management 359Mehdi NOURINEJAD, Nico MALFARA, Matthew J. ROORDA19.1. Introduction 35919.2. Literature review 36119.2.1. Vehicle routing 36119.2.2. Inventory routing problem 36319.2.3. State-of-practice in waste collection 36319.2.4. State-of-the-art in waste collection 36419.3. Remote assessment sensor routing problem (RASRP) 36419.3.1. Approximate dynamic programing model (ADPM) 36419.3.2. Benchmark models 36919.4. Model analysis and evaluation 37119.4.1. Analysis of the continuous approximation model 37119.4.2. Analysis of the approximate dynamic programing model 37419.5. Conclusions 37519.6. Bibliography 376Chapter 20. Can Routing Systems Surpass the Routing Knowledge of an Experienced Driver in Urban Deliveries? 381Jacques LEONARDI And Tadashi YAMADA20.1. Introduction: problem understanding and issues, research hypotheses, objectives and key questions 38120.2. Measures, approaches and method of the study and the trials 38520.3. Test design 38720.4. Results: Software A trial 39020.4.1. Combination of pedestrian and street routing optimization 39120.4.2. Grouping orders 39220.4.3. Software B trial 39420.5. Discussion and concluding remarks 39520.6. Acknowledgements 39820.7. Bibliography 398List of Authors 401Index 405