Local search-based meta-heuristics combined with an improved K-Means++ clustering algorithm for unmanned surface vessel scheduling
International Journal of Production Research,
Год журнала:
2025,
Номер
unknown, С. 1 - 25
Опубликована: Фев. 26, 2025
Язык: Английский
A Self-Learning Discrete Artificial Bee Colony Algorithm for Energy-Efficient Distributed Heterogeneous L-R Fuzzy Welding Shop Scheduling Problem
IEEE Transactions on Fuzzy Systems,
Год журнала:
2024,
Номер
32(6), С. 3753 - 3764
Опубликована: Март 27, 2024
With
the
tendency
of
decentralization
into
factories,
production
scheduling
among
heterogeneous
factories
has
become
a
prominent
concern
in
industrial
demand
response,
spurring
research
on
distributed
welding
shop
problem
(DHWSP).
Moreover,
owing
to
inevitable
occurrence
uncontrollable
system
disturbance
practical
environment,
processing
time
jobs
is
uncertain
rather
than
deterministic.
Thus,
L-R
fuzzy
number
(LRFN)
introduced
tackle
uncertainty
time.
Furthermore,
pursuit
sustainable
development,
energy
efficiency
been
significant
emphasis
from
countries.
An
effective
can
optimize
both
and
efficiency,
but
no
related
reported.
address
this
gap,
paper
investigates
an
energy-efficient
(EDHFWSP)
with
objectives
minimizing
makespan
total
consumption
(TEC).
To
solve
issue,
self-learning
discrete
artificial
bee
colony
(SDABC)
algorithm
proposed.
First,
collaborative
initialization
presented
yield
excellent
initial
solutions.
Second,
selection
strategy
developed
help
solutions
select
superior
neighborhood
structure
employed
phase.
Third,
variable
search
(SVNS)
designed
adaptively
for
execution
onlooker
Fourth,
energysaving
devised
further
TEC
without
affecting
makespan.
Additionally,
verify
effectiveness
SDABC,
extensive
experiments
are
performed
compare
SDABC
other
5
optimization
algorithms.
Experimental
results
validate
that
outperforms
its
competitors.
Язык: Английский
An enhanced estimation of distribution algorithm with problem-specific knowledge for distributed no-wait flowshop group scheduling problems
Zi-Qi Zhang,
Yanxuan Xu,
Bin Qian
и другие.
Swarm and Evolutionary Computation,
Год журнала:
2024,
Номер
87, С. 101559 - 101559
Опубликована: Апрель 5, 2024
Язык: Английский
Novel MINLP model and Lamarckian learning-enhanced multi-objective optimization algorithm for smart household appliance scheduling
Swarm and Evolutionary Computation,
Год журнала:
2025,
Номер
94, С. 101886 - 101886
Опубликована: Фев. 18, 2025
Язык: Английский
Cooperation-based bi-level rescheduling method for multi-objective distributed hybrid flow shop with unrelated parallel machines under multi-type disturbances
International Journal of Computer Integrated Manufacturing,
Год журнала:
2025,
Номер
unknown, С. 1 - 23
Опубликована: Март 18, 2025
Язык: Английский
Integrating cumulative binomial probability into artificial bee colony algorithm for global optimization in mechanical engineering design
Engineering Applications of Artificial Intelligence,
Год журнала:
2025,
Номер
151, С. 110628 - 110628
Опубликована: Март 30, 2025
Язык: Английский
Fractional order swarming intelligence for multi-objective load dispatch with photovoltaic integration
Engineering Applications of Artificial Intelligence,
Год журнала:
2024,
Номер
137, С. 109073 - 109073
Опубликована: Авг. 8, 2024
Язык: Английский
Multi-robot multi-station welding flow shop closed-loop rescheduling with deep reinforcement learning and improved artificial bee colony algorithm
Computers & Industrial Engineering,
Год журнала:
2024,
Номер
193, С. 110295 - 110295
Опубликована: Июнь 14, 2024
Язык: Английский
Addressing the Single and Multi-Objective Energy-Aware Flowshop Scheduling Problem Through Diverse Variations of the Pso Algorithm
Опубликована: Янв. 1, 2024
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Язык: Английский
A Hybrid Multi-Threaded Parallel Iterated Greedy Algorithm for Distributed Flowshop Group Scheduling Problems with Preventive Maintenance
Xiaobin Sun,
Hongyan Sang,
Yasheng Zhao
и другие.
Опубликована: Март 1, 2024
The
distributed
flowshop
group
scheduling
abstracted
from
the
production
process
of
printed
circuit
boards
is
a
recent
active
research
topic.
flow
shop
problem
based
on
assumption
that
processing
machines
can
run
continuously.
However,
in
actual
production,
factories
not
only
pursue
productivity,
but
also
pay
attention
to
reliability
and
stability
process.
In
this
paper,
we
study
with
preventive
maintenance
(DFGSP/PM)
minimize
makespan.
Based
characteristics
DFGSP/PM,
proposed
hybrid
multi-threaded
parallel
iterated
greedy
algorithm
(HMPIG).
NEH
LPT
rule
used
initialization
phase
generate
initial
solution.
Different
destruction
reconstruction
rules
for
groups
jobs
are
designed
update
solution
phase.
local
search
phase,
multithreaded
strategy
introduced
improve
efficiency
IG
so
optimal
insertion
position
sequence
be
searched
more
quickly.
numerous
experimental
results
show
HMPIG
has
better
quality
as
well
stability.
Язык: Английский