International Journal of Production Research,
Год журнала:
2024,
Номер
unknown, С. 1 - 26
Опубликована: Авг. 13, 2024
In
real-world
manufacturing
systems
for
processing
printed
circuit
boards
(PCBs),
the
workshops
integrating
various
flowline-based
cells
are
common
in
large-scale
enterprises.
The
scheduling
problem
within
is
modelled
as
distributed
heterogeneous
flowshop
group
(DHFGSP)
this
study.
Departing
from
practical
requirements
and
considering
grouping
characteristics
among
PCB
components,
we
account
carryover
sequence-dependent
setup
time
(CSDST).
Moreover,
recognising
critical
importance
of
just-in-time
production
semiconductor
manufacturing,
total
tardiness,
a
previously
unexplored
objective
DHFGSP
context,
addressed.
To
tackle
problem,
mixed-integer
linear
programming
(MILP)
model,
capable
obtaining
optimal
solutions
small-scale
instances,
proposed.
Due
to
NP-hard
nature
high-quality
reasonable
using
MILP
model
becomes
challenging
instances.
Therefore,
solution
algorithm,
comprising
construction
improvement
heuristics,
developed.
Capitalising
on
problem's
characteristics,
heuristic
efficiently
generates
feasible
very
short
time.
Built
primarily
around
artificial
bee
colony
(ABC)
optimisation,
can
significantly
further
enhance
by
collaborative
restart
operators.
Comprehensive
experiments
instances
varying
scales
demonstrate
effectiveness
proposed
algorithm
under
investigation.
Journal of Industrial Information Integration,
Год журнала:
2024,
Номер
39, С. 100598 - 100598
Опубликована: Март 12, 2024
Recent
advancements
in
production
scheduling
have
arisen
response
to
the
need
for
adaptation
dynamic
environments.
This
paper
addresses
challenge
of
real-time
within
context
sustainable
production.
We
redefine
distributed
permutation
flow-shop
problem
using
an
online
mixed-integer
programming
model.
The
proposed
model
prioritizes
minimizing
makespan
while
simultaneously
constraining
energy
consumption,
reducing
number
lost
working
days
and
increasing
job
opportunities
permissible
limits.
Our
approach
considers
machines
operating
different
modes,
ranging
from
manual
automatic,
employs
two
strategies:
predictive-reactive
proactive-reactive
scheduling.
evaluate
rescheduling
policies:
continuous
event-driven.
To
demonstrate
model's
applicability,
we
present
a
case
study
auto
workpiece
manage
complexity
through
various
reformulations
heuristics,
such
as
Lagrangian
relaxation
Benders
decomposition
initial
optimization
well
four
problem-specific
heuristics
considerations.
For
solving
large-scale
instances,
employ
simulated
annealing
tabu
search
metaheuristic
algorithms.
findings
underscore
benefits
strategy
efficiency
event-driven
policy.
By
addressing
challenges
integrating
sustainability
criteria,
this
contributes
valuable
insights
into
International Journal of Production Research,
Год журнала:
2024,
Номер
unknown, С. 1 - 18
Опубликована: Июнь 4, 2024
The
trend
of
reverse
globalisation
prompts
manufacturing
enterprises
to
adopt
distributed
structures
with
multiple
factories
for
improving
production
efficiency,
meeting
customer
requirements,
and
responding
disturbance
events.
This
study
focuses
on
scheduling
a
flexible
job
shop
random
processing
time
achieve
minimal
makespan
total
tardiness.
First,
stochastic
programming
model
is
established
formulate
the
concerned
problems.
Second,
in
accordance
natures
two
objectives
randomness,
an
evolutionary
algorithm
incorporating
evaluation
method
designed.
In
it,
population-based
external
archive-based
search
processes
are
developed
searching
candidate
solutions,
integrates
simulation
discrete
event
calculate
objective
values
acquired
solutions.
Finally,
mathematical
optimisation
solver,
CPLEX,
employed
validate
approach.
A
set
cases
solved
verify
performance
proposed
method.
comparisons
discussions
show
superiority
handling
problems
under
study.
