Details

City Logistics 2


City Logistics 2

Modeling and Planning Initiatives
1. Aufl.

von: Eiichi Taniguchi, Russell G. Thompson

126,99 €

Verlag: Wiley-Iste
Format: EPUB
Veröffentl.: 24.05.2018
ISBN/EAN: 9781119495116
Sprache: englisch
Anzahl Seiten: 400

DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.

Beschreibungen

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.      
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, Stanis?aw IWAN, Kinga KIJEWSKA and Mariusz JEDLI?SKI 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

Diese Produkte könnten Sie auch interessieren: