Asia Pacific Journal of Marketing and Logistics,
Journal Year:
2024,
Volume and Issue:
36(8), P. 1918 - 1945
Published: Feb. 15, 2024
Purpose
Platform-based
enterprises,
as
micro-entities
in
the
platform
economy,
have
potential
to
effectively
promote
low-carbon
development
of
both
supply
and
demand
sides
chain.
Therefore,
this
paper
aims
provide
a
multi-criteria
decision-making
method
probabilistic
hesitant
fuzzy
environment
assist
platform-type
companies
selecting
cooperative
suppliers
for
carbon
reduction
green
chains.
Design/methodology/approach
This
combines
advantages
sets
(PHFS)
address
uncertainty
issues
proposes
an
improved
called
PHFS-DNMEREC-MABAC
aiding
platform-based
enterprises
emission
collaboration
Within
method,
we
enhance
standardization
process
DNMEREC
MABAC
methods
by
directly
standardizing
elements.
Additionally,
probability
splitting
algorithm
is
introduced
handle
elements
varying
lengths,
mitigating
information
bias
that
traditional
approaches
tend
introduce
when
adding
values
based
on
risk
preferences.
Findings
In
paper,
apply
proposed
case
study
involving
selection
Tmall
Mart
compare
it
with
latest
existing
methods.
The
results
demonstrate
applicability
effectiveness
avoiding
bias.
Originality/value
Firstly,
new
decision
making
Secondly,
provided
standard
information.
Finally,
was
avoid
dealing
inconsistent
lengths
Theoretical and Applied Computational Intelligence,
Journal Year:
2023,
Volume and Issue:
1(1), P. 58 - 81
Published: Oct. 18, 2023
Portfolio
optimization
is
a
critical
task
in
financial
management,
aiming
to
maximize
expected
returns
while
minimizing
risk.
This
study
compares
the
performance
of
Particle
Swarm
Optimization
(PSO),
Genetic
Algorithm
(GA),
Dynamic
Programming
(DP),
and
Differential
Evolutionary
(DEA)
optimizing
portfolios
NIFTY
50
market.
Using
daily
stock
data
from
March
2023
May
2023,
we
evaluate
algorithms
based
on
metrics
including
Sharpe
ratio,
return,
volatility
Sortino
ratio.
Then
an
integrated
multi-criteria
decision
making
(MCDM)
framework
Logarithmic
Percentage
Change-driven
Objective
Weighting
(LOPCOW)
Compromise
Ranking
Alternatives
Distance
Ideal
Solution
(CRADIS)
methods
has
been
used
compare
evolutionary
for
portfolio
optimization.
The
results
show
that
PSO
outperforms
other
terms
Ratio
Expected
Return,
DEA
exhibits
lowest
Furthermore,
efficient
frontier
analysis
confirms
PSO's
ability
generate
with
higher
at
same
risk
level.
research
highlights
effectiveness
management
provides
valuable
insights
investors
managers
maximizing
managing
risks.
Discrete Dynamics in Nature and Society,
Journal Year:
2023,
Volume and Issue:
2023, P. 1 - 17
Published: Oct. 31, 2023
This
research
focuses
on
the
use
of
electric
vehicles
(EVs)
to
transport
visitors
and
cargo
within
Bosnia
Herzegovina’s
Kozara
National
Park.
Reduced
air
pollution
preservation
natural
resources
are
required
help
protect
this
aerial
spa.
Together
with
expert
employees
NP,
EV
that
would
best
suit
their
needs
was
chosen.
The
process
decision-making
combines
subjective
objective
methods.
Employees
first
chose
criteria
alternatives
then
weighed
importance.
On
occasion,
Z-numbers
were
used
include
uncertainty
in
decision,
because
it
is
not
always
possible
make
decisions
complete
certainty.
Furthermore,
weight
these
determined
using
fuzzy
PIPRECIA
(PIvot
Pairwise
Relative
Criteria
Importance
Assessment)
method.
Range
(C1)
became
most
important
criterion,
followed
by
vehicle
cost
(C2),
technical
specifications
EVs
compare
them.
Because
vary,
a
rough
set
which
minimum
maximum
characteristics
taken
based
specific
criteria.
To
rank
alternatives,
R-CRADIS
(Rough
Compromise
Ranking
Alternatives
Distance
Ideal
Solution)
method
used.
According
results,
Mercedes
eVito
Tourer
90
kWh
highest
ranked
validation
results
confirmed
findings.
sensitivity
analysis
revealed
if
criterion
C1
as
important,
other
higher.
research`s
methodology
has
demonstrated
flexibility,
therefore
recommended
for
similar
research.
The
production
of
electric
vehicles
is
highly
increasing
in
recent
days
to
meet
the
demands
alternatives
fuel-based
vehicles.
automobile
industries
are
manufacturing
new
variants
which
both
economical
and
environmentally
friendly.
As
number
many
market
it
quite
challenging
for
customers
make
decisions
on
selecting
also
retailers
E-vehicles
confronted
with
same
challenges
decision
making.
This
paper
proposes
a
decision-making
model
by
using
machine-learning
technique
Decision
Trees.
selection
based
significant
parameters.
data
different
respect
core
parameters
subjected
treatment
supervised
learning
Trees
R
environment.
In
this
case,
trees
used
classify
into
two
categories
feasible
infeasible
five
On
comparing
accuracy
results
classification
other
machine
techniques,
found
be
more
optimal.
Asia Pacific Journal of Marketing and Logistics,
Journal Year:
2024,
Volume and Issue:
36(8), P. 1918 - 1945
Published: Feb. 15, 2024
Purpose
Platform-based
enterprises,
as
micro-entities
in
the
platform
economy,
have
potential
to
effectively
promote
low-carbon
development
of
both
supply
and
demand
sides
chain.
Therefore,
this
paper
aims
provide
a
multi-criteria
decision-making
method
probabilistic
hesitant
fuzzy
environment
assist
platform-type
companies
selecting
cooperative
suppliers
for
carbon
reduction
green
chains.
Design/methodology/approach
This
combines
advantages
sets
(PHFS)
address
uncertainty
issues
proposes
an
improved
called
PHFS-DNMEREC-MABAC
aiding
platform-based
enterprises
emission
collaboration
Within
method,
we
enhance
standardization
process
DNMEREC
MABAC
methods
by
directly
standardizing
elements.
Additionally,
probability
splitting
algorithm
is
introduced
handle
elements
varying
lengths,
mitigating
information
bias
that
traditional
approaches
tend
introduce
when
adding
values
based
on
risk
preferences.
Findings
In
paper,
apply
proposed
case
study
involving
selection
Tmall
Mart
compare
it
with
latest
existing
methods.
The
results
demonstrate
applicability
effectiveness
avoiding
bias.
Originality/value
Firstly,
new
decision
making
Secondly,
provided
standard
information.
Finally,
was
avoid
dealing
inconsistent
lengths
