<s>
In	O
evolutionary	O
computation	O
,	O
differential	B-Algorithm
evolution	I-Algorithm
(	O
DE	O
)	O
is	O
a	O
method	O
that	O
optimizes	O
a	O
problem	O
by	O
iteratively	B-Algorithm
trying	O
to	O
improve	O
a	O
candidate	O
solution	O
with	O
regard	O
to	O
a	O
given	O
measure	O
of	O
quality	O
.	O
</s>
<s>
Such	O
methods	O
are	O
commonly	O
known	O
as	O
metaheuristics	B-Algorithm
as	O
they	O
make	O
few	O
or	O
no	O
assumptions	O
about	O
the	O
problem	O
being	O
optimized	O
and	O
can	O
search	O
very	O
large	O
spaces	O
of	O
candidate	O
solutions	O
.	O
</s>
<s>
However	O
,	O
metaheuristics	B-Algorithm
such	O
as	O
DE	O
do	O
not	O
guarantee	O
an	O
optimal	O
solution	O
is	O
ever	O
found	O
.	O
</s>
<s>
DE	O
is	O
used	O
for	O
multidimensional	O
real-valued	O
functions	O
but	O
does	O
not	O
use	O
the	O
gradient	O
of	O
the	O
problem	O
being	O
optimized	O
,	O
which	O
means	O
DE	O
does	O
not	O
require	O
the	O
optimization	O
problem	O
to	O
be	O
differentiable	O
,	O
as	O
is	O
required	O
by	O
classic	O
optimization	O
methods	O
such	O
as	O
gradient	B-Algorithm
descent	I-Algorithm
and	O
quasi-newton	B-Algorithm
methods	I-Algorithm
.	O
</s>
<s>
Books	O
have	O
been	O
published	O
on	O
theoretical	O
and	O
practical	O
aspects	O
of	O
using	O
DE	O
in	O
parallel	B-Operating_System
computing	I-Operating_System
,	O
multiobjective	O
optimization	O
,	O
constrained	B-Application
optimization	I-Application
,	O
and	O
the	O
books	O
also	O
contain	O
surveys	O
of	O
application	O
areas	O
.	O
</s>
