As part of the Athens Week, the Urban Logistics Chair organized the course MP09 “Urban Logistics: Understanding, modeling and simulating urban freight” at Mines ParisTech, from Monday 19th to Friday23rd March 2017.
35 students took part in this course, coming from the following schools:
Germany: Technische Universität München (TU Munich)
Belgium: Katholieke Universiteit Leuven (KUL)
Spain: Universidad Politécnica of Madrid
France: Arts et Métiers ParisTech
France: ParisTech Mines
France: Institut d’Optique ParisTech
Italy: Politecnico di Milano (PM)
Norway: Norges teknisk-naturvitenskapelige universitet (NTNU)
Netherlands: Delft University of Technology (TU Delft)
Poland: Warsaw University of Technology (WUT)
Portugal: Instituto Superior Técnico (IST)
Czech Republic: Czech technical university in Prague (CVUT)
Sarra JLASSI, Simon TAMAYO, Arthur GAUDRON and Arnaud de LA FORTELLE presented this publication in the 6th IEEE International Conference on Advanced Logistics and Transport(the international conference “IEEE ICALT 2017“.
This paper proposes a “multi-agent and discrete event” simulation model to measure the impact of regulatory measures (vehicle size and access time) on the distribution of products in the catering sector.
For different regulation scenarios, the model allows to consider the total distances traveled, the number of vehicles used, the load rates and the emissions. The model was used to simulate the distribution of Parisian restaurants from the Rungis Market.
Abstract— Regulatory policies aim at reducing the negative effects of urban freight transportation, especially those related to traffic, emissions and noise. Nonetheless, the stakeholders in city logistics often have divergent objectives, which lead to difficulties upon defining the best possible choices regarding regulation, for it yields important economic impacts. This paper presents a multi-agent and discrete-event based simulation of urban deliveries that aims at evaluating the impacts of regulatory policies. Restrictions regarding vehicle weights and time windows are considered in order to measure the impacts on deliveries based on total distances, number of vehicles, loading rates and emissions. The simulation framework is applied to the delivery services for restaurants, in which 4 scenarios of regulation are evaluated in the city of Paris. One originality of the proposed approach is to use real data for the instantiation of agents and the GIS in the simulation.
Convinced of the stakes and aware of the need to prepare society and the economic actors for the revolutions in progress, the Government has conducted a national analysis in the context of the National Conference on Logistics.
Thus, at the end of the Council of Ministers on 24 March 2016, the Government agreed to undertake the challenges listed in the plan of action “France Logistique 2025”.
As part of the Athens Week, the Urban Logistics Chair organized the course MP09 “Urban Logistics: Understanding, modeling and simulating urban freight” at Mines ParisTech, from Monday 13th to Friday 17th March 2017.
The Urban Logistics Chair presented the stakes of logistics in the city, as well as a synthesis of its work during a hackathon open to the public on the 2nd of February 2017 at the Cité des Sciences.
In this event, a group of about about twenty students and professionals, discussed the possible usage of digital technologies in the cities of tomorrow and in particular their relationships with agriculture and logistical flows.
This model simulates the supply of restaurants located in the 5th arrondisement of Paris.
In the model restaurants are agents that place a given number of orders per day, this rate is represented by an updatable exponential timeout controlled by the user. The orders are processed by a supplier (in green) which will fulfil them by utilizing a fleet of vehicles.
PARAMETERS AND OUTPUTS
The user can modify the demand (orders per day), the capacity of vehicles (orders per vehicle) and the fleet size (number of vehicles); these parameters will define if the supplier delivers either by direct route or by delivery tour.
Three outputs are generated: the utilization of the fleet, the number of waiting restaurants and the distance driven each hour by the vehicles.