P. de. Jong
Simulating city distribution with eM-plant and Mappoint, an evaluation
Report 2005.TL.6966, Transport Engineering and Logistics.
City distribution is defined as the transportation of consumer goods from,
to and in urban regions. City distribution is dedicated on deliveries of
consumer goods to stores, department stores, hotel and catering industry,
offices and direct to the customers homes. Due to changing conditions, the
distribution of goods in urban regions must also change. The section Transport
Engineering and Logistics of Delft University of Technology has done research
on city distribution which resulted in the CiDiS model.
The CiDiS model (City Distribution) investigates the city-box concept which
represents a logistic chain. City boxes are transported by different vehicles
from distribution centres via transhipment locations to stores as shown in the
The model works as follows:
The model consists of different modules to control the simulation of
infrastructure, transportation and planning.
- Order data from the stores are read from a file
- These demands are translated into deliveries of city boxes
- The model uses heuristic for assigning these deliveries to distribution
vehicles. Driving- and transhipment times and congestion information play
a part in this planning method.
- Vehicles transport the boxes to and from the different locations
The eM-plant model is developed after the CiDiS model. This models works
globally the same as the CiDiS model. An important difference is the animation
of the distribution chain with help of Microsoft MapPoint. The eM-plant model
has three input modes for the simulation of more logistic distribution concepts
which is an extra possibility in comparison with the CiDiS model.
The eM-plant model also consists of different modules for controlling the
different objects (vehicles, locations, rides and orders) during the simulation.
Important modules are that for data input, route construction, animation and
Validation is necessary if the working of the eM-plant model must be compared
to working of the CiDiS model. Two cases (Amsterdam city centre, province
Groningen) are used for the validation test. The results show that travelling
times and driving distances differ because both models use different route data.
This difference in route information can be eliminated by correction of vehicle
speeds in Microsoft MapPoint which levels travelling time differences.
The validation shows that he eM-plant model has a slightly better order
planning. This is due to the possibility of the eM-plant model to deliver city
boxes to different stores in one ride. The CiDiS model has not this possibility.
An animation gives a clear overview and insight in the working of the model
and performance of the distribution concept. The simulation objects are
projected on a map in eM-plant. eM-plant uses Microsoft MapPoint to construct
routes and to receive maps as background layer for the animation. An interface
between MapPoint and eM-plant takes care that route information is send from
MapPoint to eM-plant and vice versa. Unfortunately, the routes used by the
vehicles are not realistic at all. They drive through cannels for example. This
is very unrealistic and not convincing. The interface returns only one point
per route part which is too inaccurate for a good and convincing animation.
Some visual programming tricks are proposed to improve the animation.
Simulation of congestion
To make the simulation more realistic, traffic congestion is taken into account.
In contrast with the CiDiS model, the eM-plant model cannot use congestion
information in the planning of rides. Congestion is simulated with help of
areas projected on the map used in the animation. Vehicles drive slower in
these areas during the simulation. The creation of congestion area creation is
time-consuming job. Only the areas shown by the map can get congestion
properties. This type of congestion simulation in combination with the earlier
mentioned bad animation makes the congestion simulation unreliable.
Order information from the stores is read from an Excel file. The eM-plant
simulation model uses heuristics to construct a ride planning with this data.
After the trips are constructed, they must be assigned to vehicles during the
simulation. A heuristic constructs the rides in the following steps:
During the simulation, rides are assigned to the vehicles on time basis. The
delivery with the shortest time to delivery is loaded first. This applies both
for distribution centres and for transhipment locations.
- Placing of orders
- Translation of these orders in deliveries
- Construction of a trip planning for trips between distribution centre and
Three differences can be distinguished between the eM-plant model and CiDiS
The eM-plant model is also compared to an improved CiDiS planning model made
by Van Rijswijk [H.J. van Rijswijk "CiDiS: City Distribution Simulation",
report 2002.LT.5680]. This model anticipates on time
window delivery and congestion information and can be described as the Vehicle
Routing and Scheduling Problem with Time Windows Forecasted model (VRP-TW-F).
Its improved heuristic gives a better efficiency than the eM-plant model. More
than two stores can be delivered in one ride and congestion information is
taken into account during the ride planning. Implementing this order planning
heuristic will improve the performance of the eM-plant model.
- City distribution vehicles combine deliveries of two stores in a trip in
the eM-plant model
- The eM-plant model can simulate more chains of shops in one simulation.
Each chain of shops can have its own distribution centre. This is positive
for investigation of the city-box concept on a larger scale. The CiDiS do
not have this possibility.
- The CiDiS model plans trips with help of congestion information
Reports on Transport Engineering and Logistics (in Dutch)
, TU Delft