<s>
A	O
memetic	B-Algorithm
algorithm	I-Algorithm
(	O
MA	O
)	O
in	O
computer	B-General_Concept
science	I-General_Concept
and	O
operations	O
research	O
,	O
is	O
an	O
extension	O
of	O
the	O
traditional	O
genetic	B-Algorithm
algorithm	I-Algorithm
(	O
GA	O
)	O
or	O
more	O
general	O
evolutionary	B-Algorithm
algorithm	I-Algorithm
(	O
EA	O
)	O
.	O
</s>
<s>
It	O
uses	O
a	O
suitable	O
heuristic	B-Algorithm
or	O
local	B-Algorithm
search	I-Algorithm
technique	O
to	O
improve	O
the	O
quality	O
of	O
solutions	O
generated	O
by	O
the	O
EA	O
and	O
to	O
reduce	O
the	O
likelihood	O
of	O
premature	O
convergence	O
.	O
</s>
<s>
Memetic	B-Algorithm
algorithms	I-Algorithm
represent	O
one	O
of	O
the	O
recent	O
growing	O
areas	O
of	O
research	O
in	O
evolutionary	O
computation	O
.	O
</s>
<s>
Quite	O
often	O
,	O
MAs	O
are	O
also	O
referred	O
to	O
in	O
the	O
literature	O
as	O
Baldwinian	O
evolutionary	B-Algorithm
algorithms	I-Algorithm
(	O
EAs	O
)	O
,	O
Lamarckian	O
EAs	O
,	O
cultural	O
algorithms	O
,	O
or	O
genetic	O
local	B-Algorithm
search	I-Algorithm
.	O
</s>
<s>
Inspired	O
by	O
both	O
Darwinian	O
principles	O
of	O
natural	O
evolution	O
and	O
Dawkins	O
 '	O
notion	O
of	O
a	O
meme	O
,	O
the	O
term	O
memetic	B-Algorithm
algorithm	I-Algorithm
(	O
MA	O
)	O
was	O
introduced	O
by	O
Pablo	O
Moscato	O
in	O
his	O
technical	O
report	O
in	O
1989	O
where	O
he	O
viewed	O
MA	O
as	O
being	O
close	O
to	O
a	O
form	O
of	O
population-based	O
hybrid	B-Algorithm
genetic	I-Algorithm
algorithm	I-Algorithm
(	O
GA	O
)	O
coupled	O
with	O
an	O
individual	O
learning	O
procedure	O
capable	O
of	O
performing	O
local	O
refinements	O
.	O
</s>
<s>
The	O
metaphorical	O
parallels	O
,	O
on	O
the	O
one	O
hand	O
,	O
to	O
Darwinian	O
evolution	O
and	O
,	O
on	O
the	O
other	O
hand	O
,	O
between	O
memes	O
and	O
domain	O
specific	O
(	O
local	B-Algorithm
search	I-Algorithm
)	O
heuristics	B-Algorithm
are	O
captured	O
within	O
memetic	B-Algorithm
algorithms	I-Algorithm
thus	O
rendering	O
a	O
methodology	O
that	O
balances	O
well	O
between	O
generality	O
and	O
problem	O
specificity	O
.	O
</s>
<s>
This	O
two-stage	O
nature	O
makes	O
them	O
a	O
special	O
case	O
of	O
dual-phase	B-Algorithm
evolution	I-Algorithm
.	O
</s>
<s>
In	O
the	O
context	O
of	O
complex	O
optimization	O
,	O
many	O
different	O
instantiations	O
of	O
memetic	B-Algorithm
algorithms	I-Algorithm
have	O
been	O
reported	O
across	O
a	O
wide	O
range	O
of	O
application	O
domains	O
,	O
in	O
general	O
,	O
converging	O
to	O
high-quality	O
solutions	O
more	O
efficiently	O
than	O
their	O
conventional	O
evolutionary	O
counterparts	O
.	O
</s>
<s>
In	O
general	O
,	O
using	O
the	O
ideas	O
of	O
memetics	O
within	O
a	O
computational	O
framework	O
is	O
called	O
memetic	B-Algorithm
computing	I-Algorithm
or	O
memetic	O
computation	O
(	O
MC	O
)	O
.	O
</s>
<s>
More	O
specifically	O
,	O
MA	O
covers	O
one	O
area	O
of	O
MC	O
,	O
in	O
particular	O
dealing	O
with	O
areas	O
of	O
evolutionary	B-Algorithm
algorithms	I-Algorithm
that	O
marry	O
other	O
deterministic	O
refinement	O
techniques	O
for	O
solving	O
optimization	O
problems	O
.	O
</s>
<s>
This	O
insight	O
leads	O
directly	O
to	O
the	O
recommendation	O
to	O
complement	O
generally	O
applicable	O
metaheuristics	O
with	O
application-specific	O
methods	O
or	O
heuristics	B-Algorithm
,	O
which	O
fits	O
well	O
with	O
the	O
concept	O
of	O
MAs	O
.	O
</s>
<s>
Pablo	O
Moscato	O
characterized	O
an	O
MA	O
as	O
follows	O
:	O
"	O
Memetic	B-Algorithm
algorithms	I-Algorithm
are	O
a	O
marriage	O
between	O
a	O
population-based	O
global	O
search	O
and	O
the	O
heuristic	B-Algorithm
local	B-Algorithm
search	I-Algorithm
made	O
by	O
each	O
of	O
the	O
individuals	O
.	O
</s>
<s>
The	O
mechanisms	O
to	O
do	O
local	B-Algorithm
search	I-Algorithm
can	O
be	O
to	O
reach	O
a	O
local	O
optimum	O
or	O
to	O
improve	O
(	O
regarding	O
the	O
objective	O
cost	O
function	O
)	O
up	O
to	O
a	O
predetermined	O
level.	O
"	O
</s>
<s>
Multi-meme	O
,	O
hyper-heuristic	B-Algorithm
and	O
meta-Lamarckian	O
MA	O
are	O
referred	O
to	O
as	O
second	O
generation	O
MA	O
exhibiting	O
the	O
principles	O
of	O
memetic	O
transmission	O
and	O
selection	O
in	O
their	O
design	O
.	O
</s>
<s>
In	O
contrast	O
to	O
2nd	O
generation	O
MA	O
which	O
assumes	O
that	O
the	O
memes	O
to	O
be	O
used	O
are	O
known	O
a	O
priori	O
,	O
3rd	O
generation	O
MA	O
utilizes	O
a	O
rule-based	O
local	B-Algorithm
search	I-Algorithm
to	O
supplement	O
candidate	O
solutions	O
within	O
the	O
evolutionary	O
system	O
,	O
thus	O
capturing	O
regularly	O
repeated	O
features	O
or	O
patterns	O
in	O
the	O
problem	O
space	O
.	O
</s>
<s>
In	O
the	O
context	O
of	O
continuous	O
optimization	O
,	O
individual	O
learning	O
exists	O
in	O
the	O
form	O
of	O
local	O
heuristics	B-Algorithm
or	O
conventional	O
exact	O
enumerative	O
methods	O
.	O
</s>
<s>
Examples	O
of	O
individual	O
learning	O
strategies	O
include	O
the	O
hill	B-Algorithm
climbing	I-Algorithm
,	O
Simplex	O
method	O
,	O
Newton/Quasi	O
-Newton	O
method	O
,	O
interior	B-Algorithm
point	I-Algorithm
methods	I-Algorithm
,	O
conjugate	B-Algorithm
gradient	I-Algorithm
method	I-Algorithm
,	O
line	O
search	O
,	O
and	O
other	O
local	O
heuristics	B-Algorithm
.	O
</s>
<s>
In	O
combinatorial	O
optimization	O
,	O
on	O
the	O
other	O
hand	O
,	O
individual	O
learning	O
methods	O
commonly	O
exist	O
in	O
the	O
form	O
of	O
heuristics	B-Algorithm
(	O
which	O
can	O
be	O
deterministic	O
or	O
stochastic	O
)	O
that	O
are	O
tailored	O
to	O
a	O
specific	O
problem	O
of	O
interest	O
.	O
</s>
<s>
Typical	O
heuristic	B-Algorithm
procedures	O
and	O
schemes	O
include	O
the	O
k-gene	O
exchange	O
,	O
edge	O
exchange	O
,	O
first-improvement	O
,	O
and	O
many	O
others	O
.	O
</s>
<s>
One	O
of	O
the	O
first	O
issues	O
pertinent	O
to	O
memetic	B-Algorithm
algorithm	I-Algorithm
design	O
is	O
to	O
consider	O
how	O
often	O
the	O
individual	O
learning	O
should	O
be	O
applied	O
;	O
i.e.	O
,	O
individual	O
learning	O
frequency	O
.	O
</s>
<s>
introduced	O
a	O
simulated	O
heating	O
technique	O
for	O
systematically	O
integrating	O
parameterized	O
individual	O
learning	O
into	O
evolutionary	B-Algorithm
algorithms	I-Algorithm
to	O
achieve	O
maximum	O
solution	O
quality	O
.	O
</s>
<s>
Memetic	B-Algorithm
algorithms	I-Algorithm
have	O
been	O
successfully	O
applied	O
to	O
a	O
multitude	O
of	O
real-world	O
problems	O
.	O
</s>
<s>
Although	O
many	O
people	O
employ	O
techniques	O
closely	O
related	O
to	O
memetic	B-Algorithm
algorithms	I-Algorithm
,	O
alternative	O
names	O
such	O
as	O
hybrid	B-Algorithm
genetic	I-Algorithm
algorithms	I-Algorithm
are	O
also	O
employed	O
.	O
</s>
<s>
Researchers	O
have	O
used	O
memetic	B-Algorithm
algorithms	I-Algorithm
to	O
tackle	O
many	O
classical	O
NP	O
problems	O
.	O
</s>
<s>
To	O
cite	O
some	O
of	O
them	O
:	O
graph	O
partitioning	O
,	O
multidimensional	B-Algorithm
knapsack	I-Algorithm
,	O
travelling	B-Algorithm
salesman	I-Algorithm
problem	I-Algorithm
,	O
quadratic	B-Algorithm
assignment	I-Algorithm
problem	I-Algorithm
,	O
set	B-Algorithm
cover	I-Algorithm
problem	I-Algorithm
,	O
minimal	O
graph	O
coloring	O
,	O
max	O
independent	O
set	O
problem	O
,	O
bin	O
packing	O
problem	O
,	O
and	O
generalized	B-Algorithm
assignment	I-Algorithm
problem	I-Algorithm
.	O
</s>
<s>
More	O
recent	O
applications	O
include	O
(	O
but	O
are	O
not	O
limited	O
to	O
)	O
business	B-Algorithm
analytics	I-Algorithm
and	O
data	O
science	O
,	O
training	O
of	O
artificial	B-Architecture
neural	I-Architecture
networks	I-Architecture
,	O
pattern	O
recognition	O
,	O
robotic	O
motion	O
planning	O
,	O
beam	O
orientation	O
,	O
circuit	O
design	O
,	O
electric	O
service	O
restoration	O
,	O
medical	O
expert	B-Application
systems	I-Application
,	O
single	B-Algorithm
machine	I-Algorithm
scheduling	I-Algorithm
,	O
automatic	O
timetabling	O
(	O
notably	O
,	O
the	O
timetable	O
for	O
the	O
NHL	O
)	O
,	O
manpower	O
scheduling	B-Application
,	O
nurse	B-Application
rostering	I-Application
optimisation	I-Application
,	O
processor	O
allocation	O
,	O
maintenance	O
scheduling	B-Application
(	O
for	O
example	O
,	O
of	O
an	O
electric	O
distribution	O
network	O
)	O
,	O
scheduling	B-Application
of	O
multiple	O
workflows	B-Operating_System
to	O
constrained	O
heterogeneous	O
resorces	O
,	O
multidimensional	B-Algorithm
knapsack	I-Algorithm
problem	O
,	O
VLSI	O
design	O
,	O
clustering	B-Algorithm
of	O
gene	O
expression	O
profiles	O
,	O
feature/gene	O
selection	O
,	O
parameter	O
determination	O
for	O
hardware	O
fault	O
injection	O
,	O
and	O
multi-class	O
,	O
multi-objective	O
feature	B-General_Concept
selection	I-General_Concept
.	O
</s>
<s>
IEEE	O
Workshop	O
on	O
Memetic	B-Algorithm
Algorithms	I-Algorithm
(	O
WOMA	O
2009	O
)	O
.	O
</s>
