PROFISIENSI Jurnal Program Studi Teknik Industri,
Journal Year:
2023,
Volume and Issue:
11(2), P. 144 - 151
Published: Dec. 31, 2023
CVRP
merupakan
masalah
paling
sederhana
dari
VRP.
Evolutionary
Algorithm
(EA)
sebuah
metaheuristic
yang
dapat
diaplikasikan
pada
berbagai
permasalahan
optimasi,
termasuk
CVRP.
Solver
Excel
Add-In
untuk
menyelesaikan
optimasi.
menggunakan
tiga
algoritma,
yaitu
LP
Simplex,
GRG
Nonlinear
dan
EA.
Dengan
adanya
kemampuan
EA
mampu
menjalankan
EA,
maka
disimpulkan
bahwa
penyelesaian
dilakukan
dengan
memanfaatkan
Solver.
Russia-20-Nodes-CVRP
Instance
salah
satu
terdapat
Russian
Instances.
&
Solver,
panjang
rute
terpendek
adalah
15.884
Km.
Cybernetics and Computer Technologies,
Journal Year:
2023,
Volume and Issue:
3, P. 44 - 58
Published: Sept. 29, 2023
Introduction.
In
the
context
of
modern
technologies
and
widespread
use
unmanned
aerial
vehicles
(UAVs)
in
various
fields
activity,
study
optimizing
their
mission
planning
becomes
increasingly
relevant.
This
is
particularly
true
for
hybrid
systems
where
UAVs
are
integrated
with
ground
transportation
("Drone+Vehicle").
The
article
deals
aspects
routes
a
drone
that
can
be
transported
by
specialized
vehicle,
performing
reconnaissance
or
maintenance
missions
presented
targets.
A
mathematical
model
has
been
developed
allows
integrating
stages,
including
determining
direction
vehicle
based
on
data
obtained
during
drone's
mission.
purpose
paper
development
application
software-algorithmic
tools,
particular,
ideas
swarm
intelligence,
operations
inspection
given
set
objects
using
"Drone+Vehicle".
Results.
problem
routing
"Drone+Vehicle"
type
formed.
Greedy
algorithms,
deterministic
local
search
ant
colony
optimization
(ACO)
to
solve
proposed,
implemented
analyzed.
computational
experiment
conducted
demonstrate
advantages
AMC
algorithm
terms
speed
efficiency,
even
problems
high
dimensionality.
Conclusions.
proposed
approach
cover
several
stages
system
an
aggregated
model.
also
covers
choosing
further
movement
located
certain
place,
depending
analysis
results
specified
targets
may
contain
maintenance.
To
formulated
combinatorial
problem,
greedy
type,
search,
OMC
algorithms
have
developed.
superiority
over
combined
"greedy
+
search"
algorithm.
An
important
future
research
models
take
into
account
obstacles
present
ground.
apparatus
move
consider
which
locations
vehicle's
base
route
not
but
determined
configuration
Keywords:
vehicles,
systems,
planning,
optimization,
mathematcal
modeling,
logistics.
Cybernetics and Computer Technologies,
Journal Year:
2023,
Volume and Issue:
2, P. 23 - 31
Published: July 28, 2023
Introduction.
The
hope
of
solving
the
problem
avalanche-like
growth
requirements
for
computing
power,
essential
complex
routing
problems
and
other
combinatorial
optimization,
relies
on
latest
quantum
computers,
in
development
which
governments
corporations
invest
multi-billion
investments.
article
examines
modern
algorithms
performs
their
analysis
verification,
if
authors
algorithm
provided
appropriate
test
programs.
purpose
is
to
review
current
state
field
hybrid
quantum-classical
clouds,
analyze
them
propose
a
classification
algorithms.
Results.
Modern
computers
(QCs)
make
it
possible
find
approximate
solutions
some
mathematical
faster
than
classical
computers.
inaccuracy
obtained
by
QC
consequence
physical
technological
limitations:
calculation
errors
are
caused
thermal
noise,
small
number
computational
elements
-
qubits
connections
between
them,
requires
decomposition
use
heuristic
approaches
solution
optimization
allows
us
single
out:
response
variational
search
eigenvalues
based
logic
gates
as
general
directions
vast
majority
problems.
considered
reduce
vehicle
quadratic
unconstrained
binary
problem,
isomorphic
Hamilton-Ising
model.
In
this
form,
suitable
embedding
QC,
finds
an
that
has
best
statistical
reliability
or
corresponds
with
lowest
energy.
As
separate
class,
accelerate
can
be
distinguished.
For
example,
neural
networks
calculate
weighting
factors
using
ant
calculates
pheromone
trail
cloud.
It
should
mentioned
quantum-inspired
algorithms,
software
tools
simulation
corresponding
libraries
allow
creating
effective
class
routing.
Conclusions.
Combining
hardware
annealing
calculating
cloud
service
obtain
advantages
speed
accuracy
types
commercial
scale,
particular,
vehicles,
already
bringing
substantial
profits
corporations.
Keywords:
computer,
annealing,
traveling
salesman
clustering,
qubit.
Sainteks Jurnal Sains dan Teknik,
Journal Year:
2024,
Volume and Issue:
6(1), P. 89 - 99
Published: March 28, 2024
Travelling
Salesman
Problem
(TSP)
is
the
problem
for
finding
shortest
route
starting
from
start
node
then
visiting
number
of
exactly
once
and
finally
go
back
to
node.
Savings
Algorithm
(SA)
a
heuristic
solving
TSP.
In
Algorithm,
first
step
that
must
be
taken
calculate
each
pair
nodes.
Then
values
have
been
obtained
are
sorted
largest
smallest
Savings.
Route
made
by
inserting
into
nodes
who
has
highest
value.
Sometimes
there
many
pairs
same
value,
so
it
will
become
SA
choose
one
them.
Random
can
solution
this
problem.
Using
on
SA,
makes
(RSA).
Performance
RSA
TSP
tested
Instance.
Two
important
criterias
test
CPU
Time.
Russian
Instances
contain
ten
Instances,
which
tested.
The
result
shows
improve
length
existing
rapidly.
This
work
addresses
the
programming
of
offshore
oil
well
construction,
using
drilling
rigs.Drilling
costs
constitute
a
substantial
portion
total
development
an
field,
therefore,
planning
efficient
use
platforms
is
crucial
to
ensure
economic
viability
and
gas
exploration
production
(E&P)
projects.The
objective
problem
minimize
completion
time
all
operations
involved
in
subsea
wells,
considering
availability
rigs,
which
have
different
characteristics
periods.These
activities
include
drilling,
completion,
maintenance
activities.Technical
constraints,
vessels,
release
dates,
activity
precedence
constraints
are
considered.Furthermore,
vessel
eligibility
respected.Five
models
mixed-integer
linear
programming,
constructive
heuristics,
local
search
were
developed,
above
objectives
constraints.Numerical
experiments,
instances
based
on
situations
from
real
company,
exhibit
appropriate
behavior,
demonstrating
that
faithfully
represent
depicted
situation
can
be
combined
with
metaheuristics
more
advanced
optimization
techniques
achieve
better
results.
Applied Sciences,
Journal Year:
2024,
Volume and Issue:
14(19), P. 8642 - 8642
Published: Sept. 25, 2024
Intermodal
freight
transport
(IFT)
requires
a
large
number
of
optimisation
measures
to
ensure
its
attractiveness.
This
involves
numerous
control
decisions
on
different
time
scales,
making
integrated
with
traditional
methods
almost
unfeasible.
Recently,
new
trend
in
science
has
emerged:
the
application
Deep
Learning
(DL)
combinatorial
problems.
Neural
(NCO)
enables
real-time
decision-making
under
uncertainties
by
considering
rich
context
information—a
crucial
factor
for
seamless
synchronisation,
optimisation,
and,
consequently,
competitiveness
IFT.
The
objective
this
study
is
twofold.
First,
we
systematically
analyse
and
identify
key
actors,
operations,
problems
IFT
categorise
them
into
six
major
classes.
Second,
collect
structure
methodological
components
NCO
framework,
including
DL
models,
training
algorithms,
design
strategies,
review
current
State
Art
focus
hybrid
models.
Through
synthesis,
integrate
latest
research
efforts
from
three
closely
related
fields:
planning,
NCO.
Finally,
critically
discuss
outline
patterns
derive
potential
opportunities
obstacles
learning-based
frameworks
Together,
these
aim
enable
better
integration
advanced
techniques
logistics.
We
hope
that
will
help
researchers
practitioners
fields
expand
their
intuition
foster
development
intelligent
systems
algorithms
tomorrow’s
systems.
