In
the
Information
Era,
integrating
technology
with
the
real-‐world
environment
is
a
trending
paradigm
that
attracts
researchers
in
many
fields.
For
example,
Smart
Cities’
applications
integrate
information
technology
with
existing
infrastructures
to
optimize
many
aspects,
such
as
time,
energy,
and
cost.
However,
many
difficulties
show
up,
including
a
time
constraint
in
some
of
the
applications
when
it
is
implemented
in
the
real
world.
One
of
these
applications
is
smart
transportation.
This
thesis
explores
Vehicle
Routing
Problem
(VRP)
and
introduces
a
variant
of
VRP
that
relates
to
time
constraints
called
VRP
with
Time
Window
(VRPTW).
Firstly,
the
problem
is
formulated
into
a
linear
mathematic
program
with
the
objective
of
minimizing
the
number
of
agents
used
in
routing
and
minimizing
the
time
spent
in
agents’
routing.
A
heuristic
approach
solves
this
problem
by
using
a
combined
of
A*
Search
and
Ruin
and
Recreate
algorithms
to
find
the
shortest
path
for
agents.
Additionally,
the
Local
Search
Algorithm
is
used
to
minimize
the
number
of
agents
used
in
routing.
Two
case
studies
test
this
heuristic
approach:
a
case
study
in
changing
number
of
nodes,
and
a
case
study
in
changing
nodes’
duration.
The
results
are
represented
in
numbers
to
show
the
reduced
number
of
agents
and
time
cost,
while
graph
plots
show
the
agents’
routings.Department of Computer ScienceBackground -- Methodologies and design -- Hueristic approach -- Simulation results.Thesis (M.S.
