Maximilian BROCK1, Tilman MATTEIS2, Cristina HAYDEN1, Li ZHANG2, Wendelin GROSS1 14flow AG, Germany, Federal Republic of; 2Institute for Economic Policy Research, Karlsruhe Institute of Technology, Germany, Federal Republic of;

1. A comparison of regular and disrupted operations for
route planning in freight transportation
WED 1.5. Critical Infrastructures II
Davos, August 29th, 2012

2. Agenda
1. Introduction
2. Methodology
a. Multi Agent Transport Simulation
b. Tour Planning Algorithm
3. The case study
a. A retail distribution network
b. Network disruption
c. Results and analysis
4. Added value to integrative risk management
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3. Multi-agent transport simulation model
 MATSim allows for setting the capacity and travel speed of each link or street
section, respectively.
 An agent (green dot) represents a given number of vehicles.
 A vehicle travels according to a tour plan.
 A genetic algorithm is used in order to simulate intelligence
 Each vehicle can change its departure time
and route with every iteration.
Traffic simulation in Baden-
Württemberg on European trunk
road network
 For each agent the travel distance and time-depended travel times are obtained.
 Per day the average travel times are calculated from the time-dependent travel times.
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4. Tour planning algorithm in 4flow vista
Sample tour schedules
 Products are delivered from regional depots
in small quantities and with a high delivery
frequency.
 Several stores are combined to one delivery
tour.
 Each store has an individual delivery pattern.
 For each day master tours are built with the
tour planning algorithm of the logistics
planning software 4flow vista.
 MATSim provides the basis for decision-
making for the final route planning process
considering traffic.
© 4flow vista
 Travel times, distances and master tours are interchanged between the models.
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5. A retail distribution network – case study I
Network locations in Germany Characteristics
 Ten regional depots
 702 stores
 The allocation of stores to depots is
not fixed.
 A store can be supplied by more
than one depot.
 The multiple-product demand of the
store is turned into a homogeneous
volume demand.
 The depots and trucks have
© 4flow vista
maximum capacities and trucks are
deployed between 6 and 20 h.
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6. Network disruptions – case study II
Snowfall scenario
 In order to model disturbances the link capacities
and free-speeds can be adjusted.
 In the snowfall scenario a decrease in free speed
of affected links is assumed around three regional
depots.
 A set of indicators will be used to evaluate the tour
performance before and after the disruption as well
as in a re-optimized state.
 The risk management strategies include the use of alternative roads or routes.
 Furthermore, a store might be supplied from different depot then before.
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7. Results and analysis – case study III
Undisturbed network
Disturbed network
Re-optimized network
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8. Added value to integrative risk management
More realistic investigation and assessment of the
I
perpetually changing traffic situation
Reducing the gap of uncertainty between the tour
II
planned and tours realized
The data interchange allows for the fast optimization
III and adaption of tour plans in case of traffic congestions
or even catastrophic events.
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9. Thank you for your attention
Maximilian Brock
4flow AG
M +49 (0) 173 629 27 77
m.brock@4flow.de
Zhang Li
KIT
li.zhang@kit.edu
 The results presented have been achieved in the research project RM-Log, which is
funded by the Federal Ministry of Education and Research within the framework of the
Federal Government's "Research for Civil Security" program.
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10. Back-up
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11. Results and analysis – case study III
Undisturbed network
Disturbed network (snowfall)
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12. Results and analysis – case study III
Disturbed network
Re-optimized network
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