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E-raamat: City Logistics 2: Modeling and Planning Initiatives

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  • ISBN-13: 9781119495093
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City Logistics 2: Modeling and Planning InitiativesSuurem pilt
  • Formaat: PDF+DRM
  • Ilmumisaeg: 24-May-2018
  • Kirjastus: ISTE Ltd and John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781119495093
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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(22)
Daniele Patter
Florence Toilier
1.1 Introduction
1(3)
1.2 Literature review
1.3 ULS typology
4(14)
1.3.1 The Urban Logistics Zone (ULZ) or freight village
4(2)
1.3.2 The Urban Distribution Center (UDC)
6(3)
1.3.3 Vehicle Reception Points (VRP)
9(3)
1.3.4 Goods Reception Points (GRP)
12(1)
1.3.5 The Urban Logistics Box (ULB)
13(2)
1.3.6 Mobile Urban Logistics Spaces (mULS)
15(3)
1.4 Recommendations
18(1)
1.5 Conclusion
19(1)
1.6 Bibliography
20(3)
Chapter 2 Dynamic Management of Urban Last-Mile Deliveries 23(16)
Tomislav Letnik
Matej Mencinger
Stane Bozicnik
2.1 Introduction
23(2)
2.2 Review of urban freight loading bay problems and solutions
25(1)
2.3 Information system for dynamic management of urban last-mile deliveries
26(3)
2.4 Algorithm for dynamic management of urban freight deliveries
29(3)
2.5 Application of the model to a real case
32(1)
2.6 Conclusions
33(1)
2.7 Bibliography
34(5)
Chapter 3 Stakeholders' Roles for Business Modeling in a City Logistics Ecosystem: Towards a Conceptual Model 39(20)
Giovanni Zenezini
J.H.R. Van Duin
Lorant Tavasszy
Alberto De Marco
3.1 Introduction
39(2)
3.2 Research background
41(2)
3.2.1 Business model concept
41(1)
3.2.2 Business ecosystem
42(1)
3.2.3 Role-based networks and ecosystems
43(1)
3.3 The CL business model framework: roles, business entities and value exchanges
43(5)
3.4 City logistics concepts and role assignment
48(7)
3.4.1 Parcel lockers installation: My PUP
48(3)
3.4.2 Urban consolidation centers
51(3)
3.4.3 Business model implications
54(1)
3.5 Conclusions
55(1)
3.6 Bibliography
56(3)
Chapter 4 Establishing a Robust Urban Logistics Network at FEMSA through Stochastic Multi-Echelon Location Routing 59(20)
Andre Snoeck
Matthias Winkenbach
Esteban E. Mascarino
4.1 Introduction
59(3)
4.2 Strategic distribution network design
62(5)
4.2.1 Distribution network
63(1)
4.2.2 Network cost
63(1)
4.2.3 Distribution cost
64(1)
4.2.4 Optimization model
65(2)
4.3 Solution scheme
67(1)
4.3.1 Scenario generation and selection
67(1)
4.3.2 Design generation
68(1)
4.3.3 Design evaluation
68(1)
4.4 Case study
68(3)
4.4.1 Data and parameters
69(1)
4.4.2 Analysis results
70(1)
4.5 Results
71(4)
4.5.1 Design generation
71(1)
4.5.2 Design evaluation
72(1)
4.5.3 Sensitivity to cost of lost sales
73(2)
4.6 Conclusion
75(1)
4.7 Bibliography
75(4)
Chapter 5 An Evaluation Model of Operational and Cost Impacts of Off-Hours Deliveries in the City of Sao Paulo, Brazil 79(18)
Claudio B. Cunha
Hugo T.Y. Yoshizaki
5.1 Introduction
79(2)
5.2 Literature review
81(3)
5.3 Proposed approach
84(3)
5.4 Scenario generation
87(3)
5.5 Results
90(4)
5.6 Concluding remarks
94(1)
5.7 Bibliography
94(3)
Chapter 6 Application of the Bi-Level Location-Routing Problem for Post-Disaster Waste Collection 97(20)
Cheng Cheng
Russell G. Thompson
Alysson M. Costa
Xiang Huang
6.1 Introduction
97(2)
6.2 Model formulation
99(5)
6.3 Solution algorithm
104(2)
6.3.1 Genetic Algorithms
104(1)
6.3.2 Greedy Algorithm
105(1)
6.3.3 Simulated Annealing
106(1)
6.4 Case study
106(3)
6.4.1 Case study area
106(3)
6.5 Result analysis
109(4)
6.5.1 Models comparison
109(2)
6.5.2 Sensitivity analysis
111(2)
6.6 Conclusion
113(1)
6.7 Bibliography
114(3)
Chapter 7 Next-Generation Commodity Flow Survey: A Pilot in Singapore 117(14)
Lynette Cheah
Fang Zhao
Monique Stinson
Fangping Lu
Jing Ding-Mastera
Vittorio Marzano
Moshe Ben-Akiva
7.1 Introduction
117(2)
7.2 Integrated commodity flow survey
119(2)
7.2.1 Overview
119(2)
7.3 Key survey features
121(2)
7.3.1 Sampling related supply network entities
121(1)
7.3.2 Multiple survey instruments leveraging sensing technologies
121(1)
7.3.3 A unified web-based survey platform
122(1)
7.4 Pilot survey implementation
123(6)
7.4.1 Sample design and recruitment
124(1)
7.4.2 Shipment and vehicle tracking methods
125(1)
7.4.3 Pilot survey experience and lessons learnt
126(1)
7.4.4 Preliminary data analysis
127(2)
7.5 Conclusion
129(1)
7.6 Acknowledgements
129(1)
7.7 Bibliography
130(1)
Chapter 8 City Logistics and Clustering: Impacts of Using HDI and Taxes 131(12)
Rodrigo Barros Castro
Daniel Merchan
Orlando Fontes Lima Jr
Matthias Winkenbach
8.1 Introduction
131(2)
8.2 Methodology
133(2)
8.2.1 Principal component analysis
135(1)
8.2.2 K-means clustering
135(1)
8.3 Results
135(5)
8.4 Conclusion
140(1)
8.5 Bibliography
140(3)
Chapter 9 Developing a Multi-Dimensional Poly-Parametric Typology for City Logistics 143(22)
Paulus Aditjandra
Thomas Zunder
9.1 Introduction
143(1)
9.2 Literature review
144(1)
9.3 Methodology
145(1)
9.4 Evaluation and analysis
146(8)
9.4.1 Inventory of all EU projects
146(1)
9.4.2 Inventory of typologies
147(1)
9.4.3 Land use typologies
148(1)
9.4.4 Measure typologies
149(2)
9.4.5 Urban freight markets
151(1)
9.4.6 Traffic flow typology
152(1)
9.4.7 Impacts
153(1)
9.4.8 Gaps
153(1)
9.5 Validation and enhancement of the inventory
154(1)
9.6 Proposed typology
155(4)
9.6.1 Approach
155(2)
9.6.2 Dimension: Why?
157(1)
9.6.3 Dimension: Where?
157(1)
9.6.4 Dimension: Who?
158(1)
9.6.5 Dimension: What?
158(1)
9.6.6 Dimension: How?
159(1)
9.7 Reflections
159(1)
9.8 Conclusion
160(1)
9.9 Acknowledgements
160(1)
9.10 Bibliography
160(5)
Chapter 10 Multi-agent Simulation with Reinforcement Learning for Evaluating a Combination of City Logistics Policy Measures 165(14)
Eiichi Taniguchi
Ali Gul Qureshi
Kyosuke Konda
10.1 Introduction
165(1)
10.2 Literature review
166(1)
10.3 Models
166(2)
10.4 Case studies in Osaka and Motomachi
168(7)
10.4.1 Settings
168(2)
10.4.2 Results
170(5)
10.5 Conclusion
175(1)
10.6 Bibliography
176(3)
Chapter 11 Decision Support System for an Urban Distribution Center Using Agent-based Modeling: A Case Study of Yogyakarta Special Region Province, Indonesia 179(18)
Bertha Maya Sopha
Anna Maria Sri Asih
Hanif Arkan Nurdiansyah
Rahma Maulida
11.1 Introduction
179(3)
11.2 Theoretical background
182(2)
11.2.1 Urban distribution center
182(1)
11.2.2 Decision support system of city logistics
183(1)
11.3 The proposed decision support system
184(7)
11.3.1 Sy stem characterization
184(1)
11.3.2 The logical architecture
185(2)
11.3.3 Agent-based modeling (ABM)
187(3)
11.3.4 Model verification and validation
190(1)
11.4 Example of application: the case of Yogyakarta Special Region
191(1)
11.5 Conclusion
192(1)
11.6 Acknowledgements
193(1)
11.7 Bibliography
194(3)
Chapter 12 Evaluating the Relocation of an Urban Container Terminal 197(14)
Johan W. Joubert
12.1 Introduction
197(2)
12.2 Methodology
199(2)
12.2.1 MATSim
199(1)
12.2.2 Initial demand
200(1)
12.2.3 Alternative scenarios
201(1)
12.3 Results
201(7)
12.3.1 Directly affected vehicles
202(3)
12.3.2 Extended effects
205(3)
12.4 Conclusion
208(1)
12.5 Acknowledgements
209(1)
12.6 Bibliography
209(2)
Chapter 13 Multi-Agent Simulation Using Adaptive Dynamic Programing for Evaluating Urban Consolidation Centers 211(18)
Nailah Firdausiyah
Eiichi Taniguchi
Ali Gul Qureshi
13.1 Introduction
211(1)
13.2 Literature review
212(2)
13.2.1 Evaluation models for city logistics measures
212(1)
13.2.2 ADP for evaluating city logistics measures
213(1)
13.3 Models
214(6)
13.3.1 Freight carrier's MAS-ADP model
215(2)
13.3.2 Freight carrier's MAS Q-learning model
217(1)
13.3.3 Vehicle routing problem with soft time windows (VRPSSTW)
218(2)
13.4 Case study
220(1)
13.5 Results and discussions
221(5)
13.5.1 Case 0 (base case)
222(1)
13.5.2 Case 1
223(3)
13.6 Conclusion and future work
226(1)
13.7 Bibliography
226(3)
Chapter 14 Use Patterns and Preferences for Charging Infrastructure for Battery Electric Vehicles in Commercial Fleets in the Hamburg Metropolitan Region 229(12)
Christian Blusch
Heike Flamig
Soren Christian Trumper
14.1 Introduction
229(1)
14.2 State of the art/context of study
230(1)
14.3 Research goal and approach
231(1)
14.4 Method of data collection
232(1)
14.5 Results and discussion
232(5)
14.6 Conclusions
237(1)
14.7 Acknowledgements
238(1)
14.8 Bibliography
238(3)
Chapter 15 The Potential of Light Electric Vehicles for Specific Freight Flows: Insights from the Netherlands 241(20)
Susanne Balm
Ewoud Moolenburgh
Nilesh Anand
Walther Ploos Van Amstel
15.1 Introduction
241(2)
15.2 Definition of LEFV
243(1)
15.3 State of the art
244(2)
15.4 Methodology
246(1)
15.5 Potential of LEFV for different freight flows
247(6)
15.5.1 Selection of freight flows
247(1)
15.5.2 Description of freight flows
248(5)
15.5.3 Receivers' perspective
253(1)
15.6 Multi-criteria evaluation
253(3)
15.6.1 Setup
253(1)
15.6.2 Outcome
254(2)
15.7 Discussion
256(1)
15.8 Conclusion
257(1)
15.9 Acknowledgements
258(1)
15.10 Bibliography
259(2)
Chapter 16 Use of CNG for Urban Freight Transport: Comparisons Between France and Brazil 261(10)
Leise Kelli De Oliveira
Diana Diziain
16.1 Introduction
261(2)
16.2 Brief literature review
263(1)
16.3 Methodology
264(1)
16.4 Brazilian case
264(1)
16.5 French case
265(2)
16.6 Comparison of Brazilian and French experience
267(1)
16.7 Conclusion
268(1)
16.8 Acknowledgements
268(1)
16.9 Bibliography
268(3)
Chapter 17 Using Cost-Benefit Analysis to Evaluate City Logistics Initiatives: An Application to Freight Consolidation in Small- and Mid-Sized Urban Areas 271(20)
Johan Holmgren
17.1 Introduction
271(2)
17.2 Characteristics of city logistics and some terminology
273(6)
17.2.1 Efficiency in city logistics
274(1)
17.2.2 Evaluation methods
275(4)
17.3 Potential costs and benefits of implementing urban consolidation centers
279(1)
17.4 Coordinated freight distribution in Linkoping
280(1)
17.5 Evaluating urban freight initiatives by cost-benefit analysis
281(5)
17.6 The problem of cost allocation
286(1)
17.7 Conclusion
286(1)
17.8 Bibliography
287(4)
Chapter 18 Assumptions of Social Cost-Benefit Analysis for Implementing Urban Freight Transport Measures 291(22)
Izabela Kotowska
Stanislaw Iwan
Kinga Kuewska
Mariusz Jedlinski
18.1 Introduction
291(4)
18.2 The assumptions for utilization of SCBA in city logistics
295(15)
18.2.1 External air pollution cost
296(3)
18.2.2 Marginal climate change costs
299(2)
18.2.3 Marginal accident costs
301(1)
18.2.4 Congestion costs
302(2)
18.2.5 Marginal external noise costs
304(1)
18.2.6 Employment growth and development of local economy
305(3)
18.2.7 Final calculations
308(2)
18.3 Conclusions
310(1)
18.4 Acknowledgements
310(1)
18.5 Bibliography
310(3)
Chapter 19 Barriers to the Adoption of an Urban Logistics Collaboration Process: A Case Study of the Saint-Etienne Urban Consolidation Centre 313(20)
Kanyarat Nimtrakool
Jesus Gonzalez-Feliu
Claire Capo
19.1 Introduction
313(2)
19.2 Background and theoretical framework
315(5)
19.2.1 The stakeholders in an urban logistics collaboration project
315(1)
19.2.2 Urban Consolidation Centre (UCC) as an organizational innovation
316(2)
19.2.3 Barriers in urban logistics projects
318(2)
19.3 Research methodology
320(2)
19.3.1 The research approach
320(1)
19.3.2 Qualitative study: selection of respondents
320(1)
19.3.3 Quantitative analysis: purpose and CBA methodology
321(1)
19.4 Results
322(6)
19.4.1 The UCC of Saint-Etienne: background and objectives
322(1)
19.4.2 Operation aspects
323(1)
19.4.3 The conditions of economic viability of Saint-Etienne's UCC
324(2)
19.4.4 Barriers identified by stakeholders
326(2)
19.5 Conclusions
328(1)
19.6 Bibliography
328(5)
Chapter 20 Logistics Sprawl Assessment Applied to Locational Planning: A Case Study in Palmas (Brazil) 333(18)
Lilian Dos Santos Fontes Pereira Bracarense
Thiago Alvares Assis
Leise Kelli De Oliveira
Renata Lucia Magalhaes De Oliveira
20.1 Introduction
333(1)
20.2 Logistics sprawl and the importance of logistics facilities' location
334(1)
20.3 Methodology
335(4)
20.4 Area of study
339(8)
20.4.1 Logistics sprawl assessment and scenario comparison
342(5)
20.5 Conclusion
347(1)
20.6 Acknowledgements
348(1)
20.7 Bibliography
348(3)
Chapter 21 Are Cities' Delivery Spaces in the Right Places? Mapping Truck Load/Unload Locations 351(18)
Anne Goodchild
Barb Ivaistov
Ed McCormacx
Anne Moudon
Jason Scully
Jose Machado Leon
Gabriela Giron Valderrama
21.1 Introduction
351(1)
21.2 Moving more goods, more quickly
352(1)
21.3 Establishment of a well-defined partnership
353(1)
21.4 The Final 50 Feet project
354(2)
21.5 Getting granular
356(2)
21.6 Mapping the city's freight delivery infrastructure
358(8)
21.6.1 Step 1: collect existent data
358(1)
21.6.2 Step 2: develop survey to collect freight bay and loading dock data
358(1)
21.6.3 Preliminary site visits
359(1)
21.6.4 Initial survey form and the pilot survey
360(3)
21.6.5 Step 3: implement the survey
363(3)
21.7 Research results
366(2)
21.8 Conclusion
368(1)
21.9 Bibliography
368(1)
List of Authors 369(6)
Index 375
Eiichi Taniguchi, Kyoto University, Japan. Russell G. Thompson, The University of Melbourne, Australia.
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