<s>
Online	B-Algorithm
optimization	I-Algorithm
is	O
a	O
field	O
of	O
optimization	O
theory	O
,	O
more	O
popular	O
in	O
computer	B-General_Concept
science	I-General_Concept
and	O
operations	O
research	O
,	O
that	O
deals	O
with	O
optimization	O
problems	O
having	O
no	O
or	O
incomplete	O
knowledge	O
of	O
the	O
future	O
(	O
online	O
)	O
.	O
</s>
<s>
The	O
research	O
on	O
online	B-Algorithm
optimization	I-Algorithm
can	O
be	O
distinguished	O
into	O
online	O
problems	O
where	O
multiple	O
decisions	O
are	O
made	O
sequentially	O
based	O
on	O
a	O
piece-by-piece	O
input	O
and	O
those	O
where	O
a	O
decision	O
is	O
made	O
only	O
once	O
.	O
</s>
<s>
A	O
famous	O
online	O
problem	O
where	O
a	O
decision	O
is	O
made	O
only	O
once	O
is	O
the	O
Ski	B-Algorithm
rental	I-Algorithm
problem	I-Algorithm
.	O
</s>
<s>
In	O
general	O
,	O
the	O
output	O
of	O
an	O
online	B-Algorithm
algorithm	I-Algorithm
is	O
compared	O
to	O
the	O
solution	O
of	O
a	O
corresponding	O
offline	B-Algorithm
algorithm	I-Algorithm
which	O
is	O
necessarily	O
always	O
optimal	O
and	O
knows	O
the	O
entire	O
input	O
in	O
advance	O
(	O
competitive	O
analysis	O
)	O
.	O
</s>
<s>
In	O
such	O
cases	O
,	O
online	B-Algorithm
optimization	I-Algorithm
can	O
be	O
used	O
,	O
which	O
is	O
different	O
from	O
other	O
approaches	O
such	O
as	O
robust	O
optimization	O
,	O
stochastic	B-Algorithm
optimization	I-Algorithm
and	O
Markov	O
decision	O
processes	O
.	O
</s>
<s>
A	O
problem	O
exemplifying	O
the	O
concepts	O
of	O
online	B-Algorithm
algorithms	I-Algorithm
is	O
the	O
Canadian	O
traveller	O
problem	O
.	O
</s>
<s>
For	O
this	O
method	O
of	O
analysis	O
,	O
the	O
offline	B-Algorithm
algorithm	I-Algorithm
knows	O
in	O
advance	O
which	O
edges	O
will	O
fail	O
and	O
the	O
goal	O
is	O
to	O
minimize	O
the	O
ratio	O
between	O
the	O
online	O
and	O
offline	B-Algorithm
algorithms	I-Algorithm
 '	O
performance	O
.	O
</s>
<s>
There	O
are	O
many	O
formal	O
problems	O
that	O
offer	O
more	O
than	O
one	O
online	B-Algorithm
algorithm	I-Algorithm
as	O
solution	O
:	O
</s>
