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Publié par | profil-zyak-2012 |
Nombre de lectures | 11 |
Langue | English |
Extrait
O
P
T
to
eral
erturbations.
I
to
M
for
A
guaran
LIT
top
Y
the
CON
y
DITION
dimension.
S
,
F
o
O
S
R
The
S
[4
HAP
is
E
optimalit
AND
ativ
TOPOLO
GY
suitable
OPTIMI
treated
ZA
set
TION
existence
S
n
U
v
B
Q
JECT
Lagrange
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A
n
CONE
,
CONSTRAINT
top
S
A
,
M
e
U
the
E
w
L
ogy
AMS
k
TUT
ob
Z
ultaneous
A
appropriate
N
the
D
MA
y
R
m
C
t
C
y
ILI
erturbations
G
OT
a
TRA
ati
V
r
AIN
top
Ab
ological
s
analyze
t
functional
r
erturbations,
a
holes
6
.
2
T
nonnegativit
h
e
i
s
the
p
algorithms
ap
℄
e
the
r
y
pr
b
o
the
vi
In
des
estigate
rs
e
t
e
order
in
ne
t
y
opti
resp
ma
top
lit
w
y
problem
of
for
theory
sim
v
ultaneous
of
shap
alues
e
is
and
of
top
in
olo
ultipliers
gy
t
optimi
zation
out
su
of
b
at
to
ecial
a
This
mat
t
4
.
J05.
These
ases.
e
are
e,
e
of
xpressed
ativ
with
is
the
sensitivit
help
shap
of
resp
the
ology
shap
ypically
e
of
and
the
top
5,
ological
1
deriv
25
ativ
℄
es
situation,
of
of
the
deriv
ob
the
ob
e
it
and
h
of
t
ology
functionals.
,
Sev
,
eral
top
examples
of
applications
ted
are
giv
at
en.
,
1
anishing
.
e
I
[29
n
t
in
r
o
ultaneous
d
top
u
erturbations.
rst
ion
y
T
framew
h
a
e
of
l
that
a
e
ss
functionals
ical
expansions
the
to
o
e
r
ogy
y
e
o
through
f
ulation,
sha
b
p
the
e
adaptation
opti
nonlinear
mi
More
zatio
e
n
that
exit
in
tangen
analyzin
the
g
en
the
precited
b
t
eha
the
vior
ritz-
of
whic
a
yields
shap
Lagrange
e
a
f
e
-
erify
tional
ex-
with
it
resp
a
ect
b
to
ology
a
arbitrary
small
v
deformation
e
of
same
the
the
domain
of
,
where
000
h
h
p
b
oin
lassi
t
n
mo
K20
v
3
es
y
along
and
a
e
optimization,
represen
ativ
ted
deriv
b
y
y
ultiplier.
a
top
deriv
t
e.
eld
[
to
2
the
0
y
,
the
2
e
4
with
,
ect
30
top
℄
p
In
t
the
the
form
ucleation
ulation
small
of
in
[20
domain
,
,
℄
1
the
,
shap
7
e
19,
deriv
,
a-
8
tiv
In
e
is
the
dened
y
as
the
a
ological
F
ativ
r
in
?c
domain
het
an
deriv
vious
ativ
optimal-
e,
y
whic
whic
h
forms
allo
basis
ws
sev
to
top
optimization
at
[7
least
13
lo
19
26
,
This
shap
ological
e
y
optimization
inside
problems
domain
as
b
di
eren
b
tiable
the
optimization
optimalit
problems.
Therefore,
the
optimalit
oundary
y
namely
v
of
b
shap
e
deriv
deriv
e
ed
℄
straigh
this
tforw
tribution,
ardly
e
b
v
y
the
applying
situation
general
sim
results
shap
of
and
nonlinear
ol-
programming
p
in
W
establish
h
order
spaces.
optimalit
Unfor-
tunately
the
,
or
this
of
h
t
do
arbitrary
es
The
not
requiremen
apply
is
an
the
y
more
and
when
t
one
admit
w
asymptotic
an
with
ts
ect
to
sim
allo
shap
w
and
top
ol-
ology
p
v
W
ariations.
sho
In
that,
an
in
form
this
the
te
e
xt,
with
the
help
set
an
of
of
attainable
domains
programming
.
b
precisely
e
w
e
pro
quipp
e
ed
the
with
v
a
y
some
of
t
v
to
ector
v
space
tak
in
b
a
the
natural
functionals
and
sucien
to
v
tee
enien
existence
t
F
w
John
a
ultipliers
y
h,
.
turn,
In
the
order
of
to
m
b
under
ypass
Slater
this
yp
di
cult
y
T
and
v
still
this
v
top
it
ol-
assumption,
ogy
turns
optimization
that
algorithms,
nite
most
um
authors
er
use
top
relaxation
p
metho
at
ds
lo
[2,
ha
9
e
,
b
10
,
the
12,
time,
1
in
5
sp
℄
Ho
the
w
olume
ev
t.
er,
2
this
M
p
t
oin
e
t
i
of
s
view
u
je
hardly
C
lead
c
to
o
optimalit
.
y
9
,49
for
10,
the
5
non-relaxed
Ke
problem.
wo
Here,
ds
w
phr
e
shap
follo
optimization,
w
ology
another
shap
deriv
h
e,
whic
ological
h
ativ
relies
optimalit
on
the
m
notion
1E Y
K Y
E →R, E →Y,
J = G =
Ω →J(Ω), Ω →G(Ω).
P MinimizeJ(Ω) G(Ω)∈−K.
Ω∈E
Ω∈E Ω ξ : [0,τ ]→Eξ
τ > 0 ξ(0) = Ω ξ(t) = Ω t∈ [0,τ ] ξξ ξ
Per(Ω) Ω Per(Ω)
0 Ω Per(Ω) G(Ω)∈−K
∀ξ∈Per(Ω), ∃τ ∈ (0,τ ] ∀t∈ [0,τ], G(ξ(t))∈−K ⇒J(ξ(t))≥J(Ω).ξ
ξ Ω F :E → Z
Z Ω ξ F ◦ξ
F Ω ξ
′ ′F (Ω,ξ) = (F ◦ξ) (0).
F Ω ξ
′F(ξ(t)) =F(Ω)+tF (Ω,ξ)+o(t) ∀t∈ [0,τ ],ξ
o(t)
lim = 0 F Per(Ω) Ft→0 t
ξ∈Per(Ω)
third
example,
b
t
a
whic
also
h
of
in
e
v
expansion
olv
When
es
b
a
to
p
is
oin
these
t
resulting
wise
giv
state
e
t,
w
is
t
studied
of
in
the
as
6.
Let
In
.
this
zero
that
the
loads,
needed
additivit
sensitivit
resp
y
xpansion
form
Let
ulas
function
are
space,
kno
wn
in
[1
e
8
is
℄
of
2.
o
A
with
n
e
a
is
b
sa
s
p
t
[
ra
p
that
r
tains
es
h
u
W
l
t
if
As
and
said
y
in
pro
the
in
a
tro
t
dimensional,
the
deri
standard
a
theory
sa
of
[
mathematical
top
programming
entiable
do
es
tiable
not
deri
apply
dir
obtained
to
top
top
In
ological
the
shap
vior
e
requires
optimization
But
problems.<