Applied Sciences,
Journal Year:
2023,
Volume and Issue:
13(9), P. 5701 - 5701
Published: May 5, 2023
Production
scheduling
in
a
knitting
workshop
is
an
important
method
to
improve
production
efficiency,
reduce
costs
and
service.
In
order
achieve
reasonable
allocation
of
parallel
machines
as
well
cooperation
between
different
within
the
workshop,
thereby
ensuring
optimal
plans,
this
paper
proposes
using
improved
genetic
algorithm
(IGA)
based
on
tabu
search.
Firstly,
model
established.
Secondly,
IGA
minimum
processing
time
rule,
priority
idle
machine
rule
ranking
code
used
optimize
solution.
Finally,
experiment
platform
for
built
verify
proposed
method.
The
experimental
results
show
that
search
performs
terms
preconvergence
speed,
global
capability
local
capability.
converges
faster
than
traditional
by
about
25%,
reduces
redundancy
scheduling,
meets
requirements
intelligent
has
good
reference
value
promoting
development
production.
IEEE Transactions on Automation Science and Engineering,
Journal Year:
2023,
Volume and Issue:
21(2), P. 1323 - 1334
Published: Feb. 24, 2023
Robust
optimization
(RO)
has
been
recognized
as
an
effective
means
to
deal
with
unanticipated
events
in
highly
uncertain
and
risky
environments.
This
paper
systematically
reviews
two
types
of
emerging
RO
machine
scheduling
approaches—robust
(R-MS)
distributionally
R-MS
(DR-MS)
methods—which
usually
offer
tractable
formulations
analytical
results
for
problems
under
uncertainty.
First,
after
highlighting
the
advantages
methods
over
stochastic
approach
terms
tractability
robustness,
we
use
bibliometric
method
analyze
literature
related
R-MS/DR-MS
classify
them
from
following
aspects:
(1)
factors,
(2)
uncertainty
descriptions,
(3)
robustness
criteria,
(4)
environments
(5)
solution
methods.
Second,
discuss
robust
feasibility
optimality
criteria.
We
further
provide
a
state-of-the-art
review
models
different
performance
models.
Third,
existing
exact,
approximation,
online,
heuristic
solving
Finally,
present
future
research
opportunities
promising
areas:
green
learning-enabled
algorithms.
Note
Practitioners
—Machine
plays
essential
role
industrial
service
systems,
such
manufacturing,
power
generation,
transportation
medical
systems.
However,
practice,
systems
operate
due
noisy
measurements,
prediction
errors,
implementation
deviations.
To
ensure
optimality,
approaches
have
recently
proposed
hedge
against
uncertainties
processing
time,
release
date,
breakdown,
etc.
provides
comprehensive
algorithms
aspects
criteria
highlights
challenges
valuable
problem
algorithm
designs.
Applied Sciences,
Journal Year:
2023,
Volume and Issue:
13(9), P. 5701 - 5701
Published: May 5, 2023
Production
scheduling
in
a
knitting
workshop
is
an
important
method
to
improve
production
efficiency,
reduce
costs
and
service.
In
order
achieve
reasonable
allocation
of
parallel
machines
as
well
cooperation
between
different
within
the
workshop,
thereby
ensuring
optimal
plans,
this
paper
proposes
using
improved
genetic
algorithm
(IGA)
based
on
tabu
search.
Firstly,
model
established.
Secondly,
IGA
minimum
processing
time
rule,
priority
idle
machine
rule
ranking
code
used
optimize
solution.
Finally,
experiment
platform
for
built
verify
proposed
method.
The
experimental
results
show
that
search
performs
terms
preconvergence
speed,
global
capability
local
capability.
converges
faster
than
traditional
by
about
25%,
reduces
redundancy
scheduling,
meets
requirements
intelligent
has
good
reference
value
promoting
development
production.
