SIMULATION APPLIED �TO URBAN LOGISTICS: �A STATE OF THE ART
Sarra JLASSI Simon TAMAYO
Arthur GAUDRON
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To cite this work: Jlassi , S. , Tamayo , S. and Gaudron , A. (2019). Simulation Applied to Urban Logistics: A State of the Art. . In City Logistics 3: Towards Sustainable and Liveable Cities. Doi:10.1002/9781119425472.ch4
• Modelling Vs Simulation • Research method • Findings
Synthetic view of the reviewed publications Simulation techniques (choices, advantages, drawbacks) Software solutions
• Synthesis of the research opportunities • Conclusions
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Modelling Vs Simulation Model » Representation of the system » Described with influence
diagram or using mathematics » A good model is a judicious
trade-off between realism and simplicity
Simulation » Operation of the model » Relates to techniques, methods
and tools to understand: ü how systems behave over
time ü estimate and evaluate
systems performances » What If Questions
WIVER Sonntag (1985) (Germany)
FRETURB Routhier &Toilier (2007) (France)
CityGoods Gentile &Vigo (2013)(Italy) 4
Research Method INITIAL KEYS SPECIFIC KEYS
Urban City Last mile
Logistics Distribution Delivery Planning Goods distribution Goods movements
Freight movements Freight transport Freight demand Transportation Routing Delivery spaces/areas/bays Loading/unloading bays
Demand Traffic Parking Commercial movements Decision support Supply chain
40 RESULTS
Year
Type of stakeholder
Output Criteria
Simulation techniques
Country
type of publication 6
Initial key AND Specific Key AND *Simulation*
CLASSIFICATION
Nb of publications in time
11
0
1
2
3
4
5
6
7
2005 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Types and sources 0 1 2 3 4 5 6
Social and behavioral sciences procedia Transportation research procedia
Transportation research board Proceedings of the winter simulation conference
International conference on computers & industrial engineering Computer Science On-line Conference - CSOC
Lecture Notes in Computer Science (LNCS) International conference on geographic information science
World electric vehicle journal Simulation modelling practice and theory
Journal of computational science Advances in engineering software journal
Euro journal on transportation and logistics IFAC papers on line
International Journal of Urban Sciences International journal of production economics
Journal of the transportation research board OMEGA international journal of management science
WIT Transactions on the Built Environment Journal of Industrial Engineering and Management
Tsinghua Science and Technology Dynamic fleet management concepts-systems, algorithms & case studies
Robotics, automation and control book
Conference proceedings
Book chapter Scientific journal
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Simulation Techniques Five main simulation techniques to address urban logistics problems » Instance Generation Simulation (IGS)�
tests on configurations of a problem » Monte Carlo Simulation (MCS)�
make use random sampling and statistical analysis
» Discrete Event Simulation (DES)�systems evolve in a discrete space where time is driven by events
» Agent Based Simulation (ABS)�several agents with independent behaviors are involved
» System Dynamics (SD)�real-world processes are represented in terms of stocks, flows and delays
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Types of problems Reviewed problems classified into 5 categories: 1. Transportation, network and infrastructure problems: 52.5% of the publications 2. Urban consolidation & mutualisation problems: 22.5% of the publications 3. Vehicle routing problems: 17.5% of the publications 4. Intermodality problems: 15% of the publications 5. Electromobility problems: 7.5% of the publications
The total of the percentages does not add up to 100%
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Types of problems �& simulation techniques
1 - Transportation, network and infrastructure problems: 52.5% of the publications
Planning of freight movements
Operations in urban environments
Traffic �management
Parking and facilities location
42%
11% 11% 11% 5% 5% 5% 5% 0%
20%
40%
60%
80%
100%
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2 - Urban consolidation & pooling problems: 22.5% of the publications
33% 50%
17%
0%
20%
40%
60%
80%
100%
Types of problems �& simulation techniques
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Urban �consolidation
Pooling of resources
Pooling of infrastructures
3 - Vehicle routing problems: 17.5% of the publications
14% 14% 14% 14%
43%
0%
20%
40%
60%
80%
100%
Types of problems �& simulation techniques
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Multi-path �TSP
UDCs and �VRP
VRPTW, VRPPD & VRPPDTW
4 - Intermodality problems: 15% of the publications
20%
80%
0%
20%
40%
60%
80%
100%
Types of problems �& simulation techniques
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Logistics networks integrating different transportation services, designed to move goods from origin to destination in a timely manner and using multiple modes of transportation (Dotoli et al. 2010)
5 - Electromobility problems: 7.5% of the publications
50% 50%
0%
20%
40%
60%
80%
100%
Types of problems �& simulation techniques
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Using zero emission vehicles to deal with pollution (emissions), �noise and other nuisances due to freight transportation in city centres
Simulation techniques advantages and drawbacks
The different choices of simulation techniques are detailed based on: • Arguments in reviewed publications • Email survey (amongst the authors)
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Simulation techniques advantages and drawbacks
ABS Useful to better understand real-world systems Allows interaction different urban entities: freight carriers, truck drivers,
retailers and local authorities Allows evaluating and improving the objectives of different stakeholders Useful when there is little knowledge about the global interdependencies
between coexisting stakeholders Agent based modelling is harder to develop
Works aiming to evaluate the performances of UDCs are usually tackled with ABS
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Simulation techniques advantages and drawbacks
Useful for problems containing networks of queues
à Simulate systems involving traffic and lead times
All the papers dealing with intermodal transportation systems (ITS) make use of DES
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DES
Simulation techniques advantages and drawbacks
Problems with significant uncertainties, whenever there is need of
estimations, forecasts and/or decisions Most of the reviewed publications use MCS to simulate the variability of urban
freight demand, behavior of actors, and duration of operations�à The main applications involve facility location decisions and scheduling
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MCS
Simulation techniques advantages and drawbacks
Publications dealing with vehicle routing problems and network design
Publications implementing IGS intend to model only �important scenarios of a system and in most cases �pay particular attention to travel times
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IGS
Simulation techniques advantages and drawbacks
Focuses more on the behavior of the system rather than the individuals
composing it
Rabelo, et al., (2005) SD is suitable for high level strategic modelling, because 1. it proposes a holistic approach of systems, integrating many subsystems 2. it focuses on policies and system structure 3. it make use of feedback loops to represent the effects of policy decisions. DES tends to look at the smaller detail of a system (microscopic), �
whereas SD tends to take a more overall perspective (macroscopic) (Maidstone (2012))
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SD
Simulation techniques advantages and drawbacks
Provide better representation of the reality
More efficient computing environment by capitalizing on advantages of both techniques
Ability of ABS to model different stakeholders that act as
independent decision-makers and/or behave as single entities.
Ability of DES to represent �complex queuing systems.
Good knowledge of this thechnique in the community.
DES + ABS
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Hybrid simulation
Software choices
Why ARENA? Surveys on simulation software shows the usability of Arena® is an attractive
feature (easy to use with available reference literature) (ORMS, 2015; Abu-Taieh, 2005) Capacity for dealing with large-scale and modular systems (Fanti el al. (2015) )
Our email survey amongst the authors that use Arena indicated that: • They were Arena® users beforehand. • Simul8, Simio, Witness and Anylogic are software solutions of equivalent
quality. • A default choice: software already available in their institution.
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Research opportunities what remains to be simulated?
» Lack of traffic micro-simulation » E-commerce » Regulations regarding vehicles (sizes, weights, load factors and/or
engine types) and restrictions of access (restricted areas and/or time windows)
» Alternative fuel vehicles (electric, hybrid, natural gas, and fuel cell vehicles): Study the needs and investments (infrastructure and/or fleets)
» Absence of statistical analysis in order to validate the reviewed simulations
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ACKNOWLEDGMENTS The authors would like to thank
Pr. A. Comi�Pr. P. Cortés�Pr. J. W. Joubert�Dr. M. Marinov�Dr. L. K. de Oliveira�Dr. G. Iacobellis Pr. J. Gonzalez-Feliu�Pr. G. Gentile�Dr. L. Delaître For their constructive feedback
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THANKS FOR �YOUR ATTENTION Any questions? You can find me at
• [email protected] • www.chairelogistiqueurbaine.fr
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