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Abstract:
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Dissertation
title
:
Metaheuristic
approach
for
solving
one
class
of
optimization
problems
in
transp ort
Abstract
:
Berth
Allo cation
Problem
incorp orates
some
of
the
most
imp ortant
de-
cisions
that
have
to
b e
made
in
order
to
achieve
maximum
e ciency
in
a
p ort.
Terminal
manager
of
a
p ort
has
to
assign
incoming
vessels
to
the
available
b erths,
where
they
will
b e
loaded/unloaded
in
such
a
way
that
some
ob jective
function
is
optimized.
It
is
well
known
that
even
the
simpler
variants
of
Berth
Allo cation
Problem
are
NP-hard,
and
thus,
metaheuristic
approaches
are
more
convenient
than
exact
metho ds,
b ecause
they
provide
high
quality
solutions
in
reasonable
compu-
tational
time.
This
study
considers
two
variants
of
the
Berth
Allo cation
Problem:
Minimum
Cost
Hybrid
Berth
Allo cationProblem
(MCHBAP)
and
Dynamic
Mini-
mum
Cost
Hybrid
Berth
Allo cationProblem
(DMCHBAP),
b oth
with
xed
handling
times
of
vessels.
Ob jective
function
to
b e
minimized
consists
of
the
following
com-
p onents:
costs
of
p ositioning,
sp eeding
up
or
waiting
of
vessels,
and
tardiness
of
completion
for
all
vessels.
Having
in
mind
that
the
sp eed
of
nding
high-quality
solutions
is
of
crucial
imp ortance
for
designing
an
e cient
and
reliable
decision
supp ort
system
in
container
terminal,
metaheuristic
metho ds
represent
the
natural
choice
when
dealing
with
MCHBAP
and
DMCHBAP.
This
study
examines
the
fol-
lowing
metaheuristic
approaches
for
b oth
typ es
of
a
given
problem:
two
variants
of
the
Bee
Colony
Optimization
(BCO),
two
variants
of
the
Evolutionary
Algorithm
(EA),
and
four
variants
of
Variable
Neighb orho o d
Search
(VNS).
All
metaheuristics
are
evaluated
and
compared
against
each
other
and
against
exact
metho ds
inte-
grated
in
commercial
CPLEX
solver
on
real-life
instances
from
the
literature
and
randomly
generated
instances
of
higher
dimensions.
The
analysis
of
the
obtained
results
shows
that
on
real-life
instances
all
metaheuristics
were
able
to
nd
optimal
solutions
in
short
execution
times.
Randomly
generated
instances
were
out
of
reach
for
exact
solver
due
to
time
or
memory
limits,
while
metaheuristics
easily
provided
high-quality
solutions
in
short
CPU
time
in
each
run.
The
conducted
computational
analysis
indicates
that
metaheuristics
represent
a
promising
approach
for
MCHBAP
and
similar
problems
in
maritime
transp ortation.
The
results
presented
in
this
pap er
represent
a
contribution
to
the
elds
of
combinatorial
optimization,
op erational
research,
metaheuristic
metho ds,
and
b erth
allo cation
problem
in
the
container
terminals. |