Mathematics,
Год журнала:
2024,
Номер
12(23), С. 3726 - 3726
Опубликована: Ноя. 27, 2024
In
this
paper,
an
improved
hybrid
genetic-hierarchical
algorithm
for
the
solution
of
quadratic
assignment
problem
(QAP)
is
presented.
The
based
on
genetic
search
combined
with
hierarchical
(hierarchicity-based
multi-level)
iterated
tabu
procedure.
following
are
two
main
scientific
contributions
paper:
(i)
enhanced
two-level
primary
(master)-secondary
(slave)
proposed;
(ii)
augmented
universalized
multi-strategy
perturbation
(mutation
process)—which
integrated
within
a
multi-level
algorithm—is
implemented.
proposed
scheme
enables
efficient
balance
between
intensification
and
diversification
in
process.
computational
experiments
have
been
conducted
using
QAP
instances
sizes
up
to
729.
results
from
demonstrate
outstanding
performance
new
approach.
This
especially
obvious
small-
medium-sized
instances.
Nearly
90%
runs
resulted
(pseudo-)optimal
solutions.
Three
best-known
solutions
achieved
very
hard,
challenging
Symmetry,
Год журнала:
2023,
Номер
15(7), С. 1430 - 1430
Опубликована: Июль 17, 2023
To
address
the
problems
of
single
evolutionary
approach,
decreasing
diversity,
inhomogeneity,
and
meaningfulness
in
destruction
process
when
teaching–learning-based
optimization
(TLBO)
algorithm
solves
no-wait
flow-shop-scheduling
problem,
multi-strategy
discrete
(MSDTLBO)
is
introduced.
Considering
differences
between
individuals,
redefined
from
student’s
point
view,
giving
basic
integer
sequence
encoding.
fact
that
prone
to
falling
into
local
optimum
leading
a
reduction
search
accuracy,
population
was
divided
three
groups
according
learning
ability
different
teaching
strategies
were
adopted
achieve
effect
their
needs.
improve
destruction-and-reconstruction
with
symmetry,
an
iterative
greedy
destruction–reconstruction
used
as
main
body,
knowledge
base
control
number
meaningless
artifacts
be
destroyed
dynamically
change
artifact-selection
method
process.
Finally,
applied
problem
(NWFSP)
test
its
practical
application
value.
After
comparing
twenty-one
benchmark
functions
six
algorithms,
experimental
results
showed
has
certain
effectiveness
solving
NWFSP.
Mathematics,
Год журнала:
2024,
Номер
12(23), С. 3726 - 3726
Опубликована: Ноя. 27, 2024
In
this
paper,
an
improved
hybrid
genetic-hierarchical
algorithm
for
the
solution
of
quadratic
assignment
problem
(QAP)
is
presented.
The
based
on
genetic
search
combined
with
hierarchical
(hierarchicity-based
multi-level)
iterated
tabu
procedure.
following
are
two
main
scientific
contributions
paper:
(i)
enhanced
two-level
primary
(master)-secondary
(slave)
proposed;
(ii)
augmented
universalized
multi-strategy
perturbation
(mutation
process)—which
integrated
within
a
multi-level
algorithm—is
implemented.
proposed
scheme
enables
efficient
balance
between
intensification
and
diversification
in
process.
computational
experiments
have
been
conducted
using
QAP
instances
sizes
up
to
729.
results
from
demonstrate
outstanding
performance
new
approach.
This
especially
obvious
small-
medium-sized
instances.
Nearly
90%
runs
resulted
(pseudo-)optimal
solutions.
Three
best-known
solutions
achieved
very
hard,
challenging
