The document describes a system dynamics approach to modeling the airplane boarding process. Key points: 1. A system dynamics model was developed to better understand the boarding system's behavior and provide strategic help to airlines in simulating different boarding policies. 2. The model considers passengers as stocks that flow through the boarding process. Interactions and delays caused by passengers are modeled to capture feedback loops. 3. Simulations tested different boarding strategies like random boarding and back-to-front boarding to analyze their effects on reducing boarding time. The model provided insights into optimizing the boarding process.

1. NiTiM graduate school is funded within the Marie Curie
Research & Innovation Actions by the European Union
Seventh
Framework
Program
FP7/2007-­‐2013
under
REA
grant
agreement
n°
?317382,
NITIMesr.
A
System
Dynamics
Approach
to
the
Airplane
Boarding
Process
System Dynamics
Prof.
Renato
De
Leone
Faculty
of
Science
and
Technology,
Mo8va8on,
Contribu8on
&
Research
Goals
Unicam.
Prof.
Stefan
Pickl
InsNtut
für
TheoreNsche
InformaNk,
MathemaNk
und
OperaNons
Research,
UniBW.
Elisa
Canzani
EU-­‐researcher
and
Ph.D
candidate
at
UniBW.
Master
degree
in
MathemaNcs
and
ApplicaNons,
Unicam.
Airplane Boarding Process
“System
Dynamics
is
the
study
of
informa8on-­‐feedback
characteris8cs
of
industrial
ac8vity
to
show
how
organiza8onal
structure,
amplifica8on
(in
policies),
and
8me
delays
(in
decisions
and
ac8ons)
interact
to
influence
the
success
of
the
enterprise.”
(Jay
W.
Forrester,
1950)
describes
the
system
behavior
as
a
number
of
interacNng
loops,
replacing
the
open-­‐loop
impression
of
the
abstract
from
single
events
and
enNNes,
and
takes
an
states
of
the
system
(e.g.
of
material,
knowledge,
people,
money),
acNons
which
cause
stocks
to
change
according
with
feedback
loops,
informaNon
that
determines
values
of
flows.
The
Boarding
Process
consists
of
these
simple
steps
[4]:
• Gate
A
Call-­‐Off
System
can
be
used
to
influence
the
sequence
of
passengers.
• Jetway.
passenger
registering
entries.
Then,
passengers
enter
the
airplane
via
jetway.
• Cabin.
assigned
seat,
put
his
carry-­‐on
luggage
in
the
overhead
compartment
and
sit
down.
It
seems
to
be
a
simple
process,
but
the
key
role
is
played
by
passengers.
Their
acNons
can
generate
several
delays.
1. Seat
interference:
The
flow
of
passengers
is
affected
by
interferences
but
is
obstructed
by
another
passenger
already
seated
near
the
aisle.
2. Aisle
interference:
aisle
(2B)
but
is
obstructed
by
other
passengers
trying
to
store
their
luggage.
Simulation Results
As
Benjamin
Franklin
said,
“Time
is
money".
In
our
context,
an
aircraZ
generates
revenue
only
when
it
is
flying,
so
airlines
aim
to
minimize
the
ground
Nme.
In
this
research
we
focused
our
aenNon
on
one
of
the
most
Nme
consuming
processes:
the
In
the
past,
some
authors
have
compared
some
exhausNve
lists
of
boarding
strategies
using
simulaNons
(e.g.[1]),
while
others
have
used
analyNcal
approaches
(e.g.
[2]).
We
believe
that
feedback
and
nonlineariNes
inherent
to
this
process
make
it
difficult
for
the
applicaNon
of
analyNcal
methods.
However,
coping
with
feedback
and
nonlineariNes
are
the
strengths
of
Different
to
other
simulaNon
approaches
used
by
previous
researchers
[3],
we
have
developed
a
System
Dynamics
model
in
order
to:
In
order
to
build
a
consistent
SD
model,
we
followed
the
Sterman’s
Five-­‐Step
System
Dynamics
Modeling
Process
2.
FormulaNon
of
Dynamic
Hypothesis
Funding
Passengers
Boarding
Process.
System
Dynamics
(SD).
Main
characteris7cs:
• SD
feedback
world
with
its
realisNc
nonlinear
percepNon.
• SD
aggregated
view
concentraNng
on
policies.
• SD
represents
real-­‐world
processes
in
terms
of
ü Stocks:
ü Flows:
ü Auxilary
Variables:
Fig.
1
Basic
SD
elements
to
idenNfy
feedback
structures
within
which
all
change
occur
and
decision
are
made.
Desk.
The
gate
agent
controls
the
boarding
pass
of
each
Once
inside
the
cabin,
each
passenger
has
to
reach
his
Overview Research Methodology of the SD Model
• get
a
beer
understanding
of
the
boarding
system's
behavior,
• provide
a
strategical
help
to
airlines
managers
which
can
use
our
SD
model
to
simulate
different
boarding
policies
and
to
opNmize
the
boarding
process.
References
This
research
was
funded
by
the
[5].
Qualita7ve
Modeling
University
of
Camerino
through
a
6-­‐months
scholarship
“Stage
di
perfezionamento
all’estero
per
neolaurea8
magistrali”
A
gate
agent
announces
the
start
of
the
boarding.
Passenger
(1A)
tries
to
get
to
a
seat
near
the
window
(1B)
A
passenger
(2A)
tries
to
reach
his
seat
further
down
the
(i.e.
Internship
specializaNon
abroad
for
postgraduate
students).
Elisa
Canzani
performed
this
research
acNvity
at
the
Universität
der
Bundeswher
München
in
joint
collaboraNon
with
Prof.
Pickl
(UniBW)
and
Prof.
De
Leone
(Unicam).
which
they
create
for
each
other.
1.
Problem
ArNculaNon
What
is
the
Boarding
Problem?
Why
is
it
a
problem?
IdenNficaNon
of
key
variables.
3.
FormulaNon
of
SimulaNon
Model
4.
TesNng
5.
Policy
Design
and
EvaluaNon
A
SD
Causal
Loop
Diagram
makes
explicit
the
mental
model
hypothesizing
feedback
structures
of
the
Boarding
System.
QuanNficaNon
of
variables
and
development
of
decision
rules
(i.e.
equaNons)
by
creaNng
a
computer
model
through
the
SD
Stock
and
Flow
Diagram.
Use
of
Reference
Modes
for
model
calibraNon
and
validaNon
by
comparing
simulaNon
results
with
real
system
behavior.
Boarding
Strategies
Analysis.
ImplementaNon
and
evaluaNon
of
different
scenarios
to
examine
their
effects
on
the
boarding
Nme.
Quan7ta7ve
Modeling
and
Simula7on
using
Building
the
SD
model
We
considered
an
interior
configura8on
of
airplane
for
Short
Haul
flight
(capacity
of
180
passengers,
1
front
door,
1
aisle
and
rows
of
3
seats
in
each
side
of
the
aisle).
We
used
a
Top-­‐Down
Approach
to
build
our
SD
model.
DisaggregaNng
stocks
and
splirng
passengers
flows
inside
the
cabin
(Fig.
3)
make
possible
to:
• get
a
deeper
understanding
of
the
real
system’s
behavior
(interferences
model),
• build
a
very
flexible
model
(strategies
implementa8on).
However,
SD
copes
with
Aggregated
Data
[5].
The
Stock
and
Flow
Diagram
(Fig.
4)
shows
that
our
SD
model
does
not
take
into
account
2
different
sides
of
the
aisle,
as
there
is
no
difference
regarding
interferences
which
can
occur.
Fig.
4
This
simplified
SD
model
shows
only
the
stock
of
passengers
at
the
Gate
Desk,
their
flow
in
the
Jetway
and
feedback
structures
of
the
front
cabin
block.
It
helps
to
understand
how
we
faced
the
problem
of
boarding
using
SD
in
this
research.
Modeling
interferences
Once
understood
causal
relaNonships
between
variables
and
feedback
structures,
we
modeled
interferences
by
serng
equaNons
and
parameters.
First,
we
found
in
the
literature
reasonable
average
values.
Then,
we
regulated
flows
over
Nme
considering
that
the
Nme
passengers
need
to
sit
down
depends
on
the
number
of
interferring
passengers
that
are
already
seated
(or
standing
in
the
aisle
for
aisle
interference).
Example
(Fig.3)
Fig.
2
Fig.
3
IdenNficaNon
of
passengers
stocks
and
flows
flow
to
aisle
Aisle
seats
flow
in
the
jetway
number
of
aisle
seats
flow
to
middle
seats
flow
to
window
seats
=
INTEG(
-­‐
flow
to
aisle
seats
=
average
flow
to
aisle
seats
*
(
1
-­‐
Aisle
seats
Aisle
*
occupancy
)
=
INTEG(
-­‐
-­‐
0
)
Aisle
seats
occupancy
=
Aisle
Seats
Aisle
Seats
,
flow
to
aisle
seats
,
0
)
By
defining
several
control
variables
in
the
SD
model,
we
implemented
the
most
common
boarding
policies
nowdays
applied
by
airline
[6].
• Random
Boarding.
This
method
does
not
specify
any
boarding
condiNon.
Passengers
enter
the
airplane
randomly,
without
waiNng
for
any
call-­‐off
system.
• Back-­‐to-­‐Front
Strategy.
It
implies
that
groups
of
passengers
board
the
aircraZ
from
the
back
and
conNnue
up
to
the
front,
by
calling
off
different
blocks
of
full
rows.
For
the
simulaNon
we
considered
3
groups
of
passengers
which
board
in
different
Nmes.
We
run
simulaNons
for
an
average
occupancy
level
of
the
plane
of
62.5
%
(i.e.
the
average
uNlizaNon
of
the
reference
period
with
the
airline
used
by
Van
der
Landeghem
and
Beuselinck
[1]).
[1]
Van
der
Landeghem,
H.,
Beuselinck,
A.,
Reducing
passenger
boarding
Nme
in
airplanes:
A
simulaNon
based
approach.
European
Journal
of
Opera8onal
Research
,
2002,
142(2),
pp.
294-­‐308.
[2]
Bazargan,
M.,
A
Linear
Programming
Approach
for
AircraZ
Boarding.
Strategy
Journal
of
Opera8onal
Research,
2007,
183
(1),
pp.
394-­‐411.
[3]
Marelli,
S.,
Maocks,
G.,
Merry,
R.,
The
role
of
computer
simulaNon
in
reducing
airplane
turn
Nme.
Aero
Magazine
1,
1998.
[4]
Sterman.
J.
D.,Business
Dynamics
.
McGraw-­‐Hill,
2000.
[5]
Borshchev,
A.,
Filippov,
A.,
From
System
Dynamics
and
Discrete
Event
to
PracNcal
Agent
Based
Modeling:
Reasons,
Techniques,
Tools.
The
22nd
Interna8onal
Conference
of
the
System
Dynamics
Society,
Oxford,
2004.
[6]
Seatguru.
Guide
to
Airline
Boarding
Procedure.
From
hp://www.seatguru.com/arNcles/boarding_procedures.php
[7]
Van
de
Briel,
M.H.L.,
Villalobos,
J.R.,
Hogg,
G.L.,
Lindemann,
T.,
Mul,
A.V.,
America
West
airlines
develops
efficient
boarding
strategies.
Inter-­‐
faces,
35,
pp.
191-­‐201,
2005.
[8]
P.
Ferrari,
P.,
Nagel,
K.,
Robustness
of
Efficient
Passenger
Boarding
in
Airplanes.
TransportaNon
Research
Record,
1915,
pp.
44-­‐54,
2005.
[9]
Steiner,
A.,
Philipp,
M.,
Speeding
up
the
airplane
boarding
process
by
using
pre-­‐
boarding
areas.
The
9th
Swiss
Transport
Research
Conference,
2009.
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