Research on the Improvement of Bacterial Foraging Algorithm for Flexible Job shop Scheduling Problem
Abstract
Machine
workload
is
an
important
factor
to
be
considered
in
flexible
job
shop
scheduling,
and
the
existing
research
has
achieved
certain
results
optimizing
total
maximum
machine
workload,
but
balancing
among
machines
insufficiently
considered,
imbalance
will
lead
problems
such
as
underutilization
of
production
potential
overload
failure.
Therefore,
this
paper
first
proposes
a
scheduling
problem
that
considers
balancing,
optimization
model
was
established
with
goal
minimizing
completion
time(Makespan)
factor,
aiming
fully
unleash
while
avoiding
further
improve
efficiency.
In
order
effectively
solve
proposed
problem,
series
improvements
were
made
optimize
defects
bacterial
foraging
algorithm(BFOA),
easy
precocious
convergence
“escape”
elite
individuals,
improved
algorithm(IBFOA)
proposed.
The
algorithm
designs
introduces
Logistic-Circle
chaos
mapping
enhance
quality
initial
population;An
adaptive
dynamic
step
size
designed
ensure
efficiency
accuracy;
Improved
reproduction
operation
avoid
convergence;
An
migration
probability
"escape"
individuals.
case
testing
show
effectiveness
superiority
algorithm.
Research Square (Research Square), Год журнала: 2024, Номер unknown
Опубликована: Ноя. 29, 2024
Язык: Английский