I
n
t
e
r
n
at
ion
al
Jou
r
n
a
l
of
Robot
ics
an
d
Au
t
om
at
ion
(
I
JRA
)
Vo
l
.
9
,
No.
1
,
M
a
r
c
h
2020,
pp.
46~50
I
S
S
N:
2089
-
4856,
DO
I
:
10
.
11591/
i
j
r
a
.
v
9
i
1
.
pp
46
-
50
46
Jou
r
n
al
h
o
m
e
page
:
ht
tp:
//
ij
r
a.
iaes
c
or
e
.
c
om
A
d
v
an
c
e
d
t
e
ac
h
in
g
-
le
ar
n
in
g
-
b
ase
d
op
t
i
m
iz
at
io
n
al
gor
ith
m
f
or
ac
t
u
al
p
ow
e
r
l
oss
r
e
d
u
c
t
io
n
K
an
agas
ab
ai
L
e
n
in
D
e
p
art
men
t
o
f
E
E
E
,
Pras
ad
V
.
Po
t
l
u
ri
S
i
d
d
h
art
h
a
I
n
s
t
i
t
u
t
e
o
f
T
ec
h
n
o
l
o
g
y
,
I
n
d
i
a
Ar
t
ic
l
e
I
n
f
o
AB
S
T
RA
CT
A
r
ti
c
le
h
is
tor
y
:
R
e
c
e
i
ve
d
Ju
l
1
9
,
201
9
R
e
vi
s
e
d
Oc
t
6
,
201
9
A
c
c
e
pt
e
d
Oc
t
20
,
201
9
I
n
t
h
i
s
w
o
rk
A
d
v
a
n
ce
d
T
e
a
c
h
i
n
g
-
L
e
ar
n
i
n
g
-
Bas
e
d
O
p
t
i
mi
zat
i
o
n
al
g
o
r
i
t
h
m
(A
T
L
BO
)
i
s
p
ro
p
o
s
e
d
t
o
s
o
l
v
e
t
h
e
o
p
t
i
m
a
l
re
a
c
t
i
v
e
p
o
w
er
p
ro
b
l
em.
T
e
ach
i
n
g
-
L
e
arn
i
n
g
-
Bas
ed
O
p
t
i
mi
zat
i
o
n
(T
L
BO
)
o
p
t
i
m
i
zat
i
o
n
a
l
g
o
ri
t
h
m
h
as
b
e
en
framed
o
n
t
e
a
ch
i
n
g
l
e
ar
n
i
n
g
me
t
h
o
d
o
l
o
g
y
h
ap
p
e
n
i
n
g
i
n
c
l
as
s
ro
o
m.
A
l
g
o
ri
t
h
m
co
n
s
i
s
t
s
o
f
“
T
e
ac
h
e
r
P
h
as
e
”,
“
L
e
ar
n
e
r
Ph
a
s
e
”.
In
t
h
e
p
ro
p
o
s
e
d
A
d
v
a
n
ce
d
T
e
a
ch
i
n
g
-
L
e
arn
i
n
g
-
Bas
ed
O
p
t
i
m
i
zat
i
o
n
a
l
g
o
ri
t
h
m
n
o
n
-
l
i
n
e
ar
i
n
e
rt
i
a
w
ei
g
h
t
e
d
fa
c
t
o
r
i
s
i
n
t
ro
d
u
ce
d
i
n
t
o
t
h
e
f
u
n
d
a
me
n
t
al
T
L
BO
al
g
o
r
i
t
h
m
t
o
m
an
a
g
e
t
h
e
memo
r
y
rat
e
o
f
l
e
ar
n
e
rs
.
I
n
o
rd
e
r
t
o
c
o
n
t
ro
l
t
h
e
l
e
ar
n
e
r’s
mu
t
at
i
o
n
arb
i
t
rari
l
y
d
u
ri
n
g
t
h
e
l
e
ar
n
i
n
g
p
ro
ced
u
r
e
a
n
on
-
l
i
n
e
ar
m
u
t
at
i
o
n
fac
t
o
r
h
as
b
een
ap
p
l
i
e
d
.
Pr
o
p
o
s
ed
A
d
v
a
n
ce
d
T
e
a
ch
i
n
g
-
L
e
ar
n
i
n
g
-
Bas
e
d
O
p
t
i
m
i
zat
i
o
n
a
l
g
o
ri
t
h
m
(
A
T
L
BO
)
h
as
b
ee
n
t
e
s
t
e
d
i
n
s
t
an
d
ard
IE
E
E
1
4
,
3
0
b
u
s
t
e
s
t
s
y
s
t
e
m
s
a
n
d
s
i
m
u
l
at
i
o
n
r
e
s
u
l
t
s
s
h
o
w
t
h
e
p
ro
p
o
s
e
d
al
g
o
r
i
t
h
m
re
d
u
ce
d
t
h
e
r
e
al
p
o
w
e
r
l
o
s
s
e
f
fec
t
i
v
e
l
y
.
K
e
y
w
o
r
d
s
:
A
d
v
a
n
c
e
d
t
e
a
c
hi
ng
-
l
e
a
r
ni
ng
-
b
a
s
e
d
o
p
t
i
mi
z
a
t
i
o
n
a
l
go
r
i
t
hm
Opt
i
m
a
l
r
e
a
c
t
i
ve
po
we
r
T
r
a
n
s
mi
s
s
i
o
n
l
o
s
s
Th
i
s
i
s
a
n
o
p
en
a
c
ces
s
a
r
t
i
c
l
e
u
n
d
e
r
t
h
e
CC
B
Y
-
SA
l
i
cen
s
e.
C
or
r
e
s
pon
din
g
A
u
th
or
:
K
a
n
a
g
a
s
a
ba
i
L
e
ni
n
,
De
pa
r
t
m
e
n
t
o
f
E
E
E
,
P
r
a
s
a
d
V.
P
ot
l
ur
i
S
i
dd
h
a
r
t
h
a
I
ns
t
i
t
u
t
e
o
f
T
e
c
hn
o
l
o
g
y
,
K
a
n
ur
u,
V
i
j
a
y
a
w
a
da
,
An
d
h
r
a
P
r
a
de
s
h
520007,
I
n
d
i
a
.
E
m
a
i
l
:
gk
l
e
ni
n@g
m
a
il
.
c
o
m
1.
I
NT
RODU
C
T
I
ON
R
e
a
c
t
i
v
e
po
we
r
pr
o
bl
e
m
p
l
a
y
s
a
n
im
po
r
t
a
n
t
r
o
l
e
i
n
s
e
c
ur
e
a
n
d
e
c
o
n
o
m
i
c
o
pe
r
a
t
i
o
ns
o
f
po
we
r
s
y
s
t
e
m
.
Nu
m
e
r
o
us
t
y
p
e
s
o
f
m
e
t
h
o
ds
[
1
-
6]
h
a
v
e
be
e
n
ut
i
l
i
z
e
d
t
o
s
o
l
v
e
t
he
o
pt
i
m
a
l
r
e
a
c
t
i
v
e
po
we
r
pr
o
bl
e
m
.
Ho
we
v
e
r
m
a
ny
s
c
i
e
n
t
i
f
i
c
d
if
f
i
c
u
l
t
i
e
s
a
r
e
f
o
u
n
d
w
hil
e
s
o
l
vi
n
g
p
r
o
bl
e
m
du
e
t
o
a
n
a
s
s
o
r
t
m
e
n
t
o
f
c
o
ns
t
r
a
i
n
t
s
.
E
v
o
l
ut
i
o
n
a
r
y
t
e
c
hni
que
s
[
7
-
16]
a
r
e
a
pp
li
e
d
t
o
s
o
l
ve
t
h
e
r
e
a
c
t
i
ve
po
we
r
pr
o
bl
e
m
.
T
hi
s
p
a
pe
r
pr
o
p
o
s
e
s
A
d
v
a
n
c
e
d
T
e
a
c
hi
ng
-
L
e
a
r
ni
ng
-
B
a
s
e
d
Opt
i
m
i
z
a
t
i
o
n
a
l
go
r
i
t
hm
(
A
T
L
B
O)
to
s
o
l
v
e
o
pt
i
m
a
l
r
e
a
c
t
i
ve
po
we
r
pr
o
bl
e
m
.
T
e
a
c
hi
n
g
-
L
e
a
r
ni
ng
-
B
a
s
e
d
Opt
i
m
i
z
a
t
i
o
n
(
T
L
B
O)
o
p
t
i
mi
z
a
t
i
o
n
a
l
go
r
i
t
hm
h
a
s
b
e
e
n
f
r
a
m
e
d
o
n
t
e
a
c
hi
n
g
l
e
a
r
ni
ng
m
e
t
h
o
do
l
o
g
y
h
a
pp
e
ni
ng
i
n
c
l
a
s
s
r
oo
m
.
Al
go
r
i
t
hm
c
o
ns
i
s
t
s
o
f
“
T
e
a
c
h
e
r
P
ha
s
e
”
,
“
L
e
a
r
n
e
r
P
h
a
s
e
”
.
I
n
t
h
e
pr
o
po
s
e
d
A
d
v
a
n
c
e
d
T
e
a
c
hi
ng
-
L
e
a
r
ni
ng
-
B
a
s
e
d
Opt
i
mi
z
a
t
i
o
n
a
l
go
r
i
t
hm
(
A
T
L
B
O)
no
n
-
l
i
ne
a
r
i
ne
r
t
i
a
we
i
g
h
t
e
d
f
a
c
t
o
r
i
s
i
n
t
r
o
duc
e
d
i
n
to
t
h
e
f
u
nda
m
e
n
t
a
l
T
L
B
O
a
l
go
r
i
t
hm
t
o
m
a
n
a
g
e
t
h
e
m
e
m
o
r
y
r
a
t
e
o
f
l
e
a
r
n
e
r
s
.
I
n
o
r
de
r
to
c
o
n
t
r
o
l
t
h
e
l
e
a
r
n
e
r
’
s
m
ut
a
t
i
o
n
a
r
bi
t
r
a
r
i
l
y
dur
i
ng
t
h
e
l
e
a
r
ni
ng
pr
o
c
e
dur
e
a
n
o
n
-
l
i
ne
a
r
m
ut
a
t
i
o
n
f
a
c
t
or
h
a
s
b
e
e
n
a
pp
l
i
e
d.
P
r
e
c
e
d
i
n
g
i
nf
o
r
m
a
t
i
o
n
ga
t
h
e
r
i
ng
o
f
l
e
a
r
n
e
r
s
i
s
de
t
e
r
m
i
ne
d
by
t
h
e
we
i
g
h
t
f
a
c
t
o
r
a
n
d
t
h
r
o
ugh
t
h
a
t
n
e
w
-
f
a
n
g
l
e
d
v
a
l
u
e
s
a
r
e
c
a
l
c
u
l
a
t
e
d.
I
n
a
l
e
a
r
ni
ng
c
y
c
l
e
i
n
d
i
v
i
dua
l
s
w
i
ll
t
r
y
to
e
x
p
l
o
r
e
v
a
r
i
o
us
r
e
g
i
o
n
s
o
f
t
h
e
e
x
p
l
o
r
a
t
i
o
n
s
pa
c
e
in
i
n
i
t
i
a
l
p
ha
s
e
.
Af
t
e
r
wa
r
ds
i
nd
i
v
i
dua
l
s
pr
o
gr
e
s
s
i
n
a
li
t
t
l
e
r
a
n
ge
t
o
r
e
gul
a
t
e
t
h
e
t
r
i
a
l
s
o
l
ut
i
o
n
t
o
c
e
r
t
a
i
n
e
x
t
e
n
t
s
uc
h
t
h
a
t
i
t
c
a
n
i
nve
s
t
i
g
a
t
e
r
e
a
s
o
n
a
bly
li
t
t
l
e
l
o
c
a
l
s
pa
c
e
.
P
r
o
p
o
s
e
d
A
d
va
n
c
e
d
T
e
a
c
hi
ng
-
L
e
a
r
ni
ng
-
B
a
s
e
d
Op
t
i
mi
z
a
t
i
o
n
a
l
go
r
i
t
hm
(
A
T
L
B
O)
h
a
s
b
e
e
n
t
e
s
t
e
d
i
n
s
t
a
n
da
r
d
I
E
E
E
14,
30
,
b
us
t
e
s
t
s
y
s
t
e
m
s
a
n
d
s
im
u
l
a
t
i
o
n
r
e
s
u
l
t
s
s
h
o
w
t
h
e
pr
o
j
e
c
t
e
d
a
l
go
r
i
t
hm
r
e
duc
e
d
t
h
e
r
e
a
l
po
we
r
l
o
s
s
e
f
f
e
c
t
i
v
e
ly
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
R
o
b
&
A
ut
o
m
I
S
S
N:
2089
-
4856
A
dv
anc
e
d
teac
hing
-
lear
ni
ng
-
bas
e
d
opti
miz
ati
on
al
gor
it
hm.
.
.
(
K
anagas
abai
L
e
nin
)
47
2.
P
ROB
L
E
M
F
ORM
UL
AT
I
ON
Obj
e
c
t
i
v
e
o
f
t
h
e
p
r
o
bl
e
m
i
s
to
r
e
duc
e
t
h
e
tr
u
e
p
o
we
r
l
o
s
s
:
∑
(
)
(
1)
Vo
l
t
a
ge
d
e
vi
a
t
i
o
n
gi
v
e
n
a
s
f
o
l
l
o
ws
:
(
2)
Vo
l
t
a
ge
d
e
vi
a
t
i
o
n
gi
v
e
n
by
:
∑
|
|
(
3)
C
o
n
s
t
r
a
i
n
t
(
e
qua
l
i
t
y
)
:
(
4)
C
o
n
s
t
r
a
i
n
t
s
(
i
n
e
qua
li
t
y
)
:
(
5)
(
6)
(7
)
(
8)
(
9)
3.
AD
VA
NC
E
D
T
E
A
CHI
NG
-
L
E
AR
NI
NG
-
B
ASE
D
OP
T
I
M
I
Z
AT
I
ON
AL
GO
RI
T
HM
T
e
a
c
hi
ng
-
L
e
a
r
ni
ng
-
B
a
s
e
d
Opt
i
mi
z
a
t
i
o
n
(
T
L
B
O)
o
p
t
i
mi
z
a
t
i
o
n
a
l
go
r
i
t
hm
ha
s
b
e
e
n
f
r
a
m
e
d
o
n
t
e
a
c
hi
n
g
l
e
a
r
ni
ng
m
e
t
h
o
do
l
o
g
y
h
a
pp
e
ni
ng
i
n
c
l
a
s
s
r
oo
m
.
Al
go
r
i
t
hm
c
o
ns
i
s
t
s
o
f
“
T
e
a
c
h
e
r
P
ha
s
e
”
,
“
L
e
a
r
n
e
r
P
h
a
s
e
”
[
17]
.
In
it
h
l
e
a
r
ne
r
t
h
e
jt
h
pa
r
a
m
e
t
e
r
i
s
a
s
s
i
g
n
e
d
va
l
ue
s
c
a
pr
i
c
i
o
us
ly
f
o
un
d
by
(
)
(
)
(
10)
F
o
r
t
h
e
pr
o
duc
t
i
o
n
“
g”
pa
r
a
m
e
t
e
r
s
o
f
t
h
e
ith
l
e
a
r
n
e
r
a
r
e
gi
v
e
n
by
,
(
)
0
(
)
(
)
(
)
(
)
(
)
1
(
11)
3.
1.
T
e
ac
h
e
r
P
h
as
e
C
r
e
a
t
i
o
n
o
f
“
g”
;
m
e
a
n
pa
r
a
m
e
t
e
r
E
g
o
f
e
a
c
h
s
u
bj
e
c
t
l
e
a
r
n
e
r
s
i
n
t
h
e
c
l
a
s
s
is
de
f
i
ne
d
by
,
[
]
(
12)
Ne
w
s
e
t
o
f
b
e
t
t
e
r
l
e
a
r
ne
r
s
a
r
e
f
o
un
d
by
(
)
(
)
(
)
(
13)
Va
l
ue
o
f
m
e
a
n
t
o
b
e
a
l
t
e
r
e
d
i
s
de
c
i
de
d
by
-
t
e
a
c
hi
ng
f
a
c
to
r
.
Va
l
ue
o
f
c
a
n
b
e
1
o
r
2.
,
(
)
*
+
-
(
14)
3.
2.
L
e
a
r
n
e
r
P
h
as
e
F
o
r
a
s
pe
c
i
f
i
e
d
l
e
a
r
n
e
r
(
)
a
di
f
f
e
r
e
n
t
l
e
a
r
n
e
r
(
)
i
s
c
a
pr
i
c
i
o
us
ly
c
h
o
s
e
n
(
)
.
I
n
t
h
e
l
e
a
r
n
e
r
s
t
a
ge
t
h
e
X
n
e
w
i
s
g
i
ve
n
a
s
:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2089
-
4856
I
n
t
J
R
o
b
&
A
ut
o
m
,
Vo
l
.
9
,
N
o
.
1
,
M
a
r
c
h
2020
:
4
6
–
50
48
(
)
{
(
)
(
(
)
(
)
)
(
(
)
)
(
(
)
)
(
)
(
(
)
(
)
)
(
15)
I
n
t
h
e
pr
o
p
o
s
e
d
A
d
v
a
n
c
e
d
T
e
a
c
hi
ng
-
L
e
a
r
ni
ng
-
B
a
s
e
d
Opt
i
mi
z
a
t
i
o
n
a
l
go
r
i
t
hm
(
A
T
L
B
O)
n
o
n
-
li
ne
a
r
i
ne
r
t
i
a
we
i
g
h
t
e
d
f
a
c
t
o
r
i
s
i
n
t
r
o
duc
e
d
i
n
to
t
h
e
f
u
nda
m
e
n
t
a
l
T
L
B
O
a
l
go
r
i
t
hm
t
o
m
a
n
a
g
e
t
h
e
m
e
m
o
r
y
r
a
t
e
o
f
l
e
a
r
n
e
r
s
.
I
n
o
r
de
r
to
c
o
n
t
r
o
l
t
h
e
l
e
a
r
n
e
r
’
s
m
ut
a
t
i
o
n
a
r
bi
t
r
a
r
i
l
y
dur
i
ng
t
h
e
l
e
a
r
ni
ng
pr
o
c
e
dur
e
a
n
o
n
-
l
i
ne
a
r
m
ut
a
t
i
o
n
f
a
c
t
o
r
h
a
s
be
e
n
a
pp
l
i
e
d.
P
r
e
c
e
d
i
n
g
i
n
f
o
r
m
a
t
i
o
n
ga
t
h
e
r
i
n
g
o
f
l
e
a
r
n
e
r
s
i
s
de
t
e
r
m
i
ne
d
by
t
he
we
i
g
h
t
f
a
c
t
o
r
a
n
d
t
h
r
o
ugh
t
h
a
t
n
e
w
-
f
a
n
g
l
e
d
v
a
l
ue
s
a
r
e
c
a
l
c
u
l
a
t
e
d.
T
i
s
n
u
m
be
r
o
f
i
t
e
r
a
t
i
o
n
i
n
s
i
ng
l
e
l
e
a
r
ni
ng
c
y
c
l
e
.
T
h
e
n
t
h
e
i
n
e
r
t
i
a
we
i
g
h
t
f
a
c
t
o
r
i
s
de
s
c
r
i
be
d
by
,
(
(
(
)
)
(
⁄
)
)
(
)
(
16)
I
n
a
l
e
a
r
ni
ng
c
y
c
l
e
i
n
d
i
v
i
dua
l
s
w
il
l
t
r
y
to
e
x
p
l
o
r
e
v
a
r
i
o
us
r
e
g
i
o
ns
o
f
t
h
e
e
x
p
l
o
r
a
t
i
o
n
s
pa
c
e
i
n
i
n
i
t
i
a
l
ph
a
s
e
.
Af
t
e
r
wa
r
ds
i
n
d
i
v
i
dua
l
s
pr
o
gr
e
s
s
i
n
a
li
t
t
l
e
r
a
n
ge
to
r
e
gul
a
t
e
t
h
e
t
r
i
a
l
s
o
l
ut
i
o
n
t
o
c
e
r
t
a
i
n
e
x
t
e
n
t
s
uc
h
t
h
a
t
i
t
c
a
n
i
nv
e
s
t
i
g
a
t
e
r
e
a
s
o
n
a
bly
li
t
t
l
e
l
o
c
a
l
s
pa
c
e
.
S
ubs
e
que
n
t
l
y
r
e
p
li
c
a
t
e
t
h
e
l
e
a
r
ni
ng
c
y
c
l
e
o
v
e
r
a
n
d
o
v
e
r
a
ga
i
n
.
T
h
e
r
a
n
do
m
n
u
m
be
r
“
r
”
i
s
m
o
d
i
f
i
e
d
by
(
)
(
17)
-
Dy
n
a
mi
c
i
n
e
r
t
i
a
we
i
g
h
t
.
T
h
e
m
e
a
n
va
l
ue
o
f
t
h
e
n
o
v
e
l
r
a
n
do
m
n
u
m
be
r
i
s
a
m
p
li
f
i
e
d
f
r
o
m
0.
5
to
0.
7
5,
a
n
d
t
h
e
n
t
h
e
s
t
o
c
h
a
s
t
i
c
v
a
r
i
a
t
i
o
n
s
a
r
e
a
ug
m
e
n
t
e
d.
M
a
i
nly
d
i
f
f
e
r
e
n
c
e
v
a
l
u
e
a
dde
d
t
o
t
h
e
c
ur
r
e
n
t
l
e
a
r
n
e
r
s
.
I
n
t
h
e
m
e
a
n
t
i
m
e
,
a
ug
m
e
n
t
f
r
o
m
l
i
t
t
l
e
t
o
bi
g
i
n
s
i
ng
le
l
e
a
r
ni
ng
c
y
c
l
e
.
Un
de
r
n
e
a
t
h
o
f
j
o
i
n
t
o
u
t
c
o
m
e
o
f
,
t
h
e
pr
o
j
e
c
t
e
d
a
l
go
r
i
t
hm
w
il
l
n
o
t
e
n
ge
n
de
r
pr
e
m
a
tur
e
c
o
n
v
e
r
ge
n
c
e
.
I
t
wi
l
l
pe
r
k
up
po
pul
a
t
i
o
n
d
i
ve
r
s
i
t
y
,
s
h
u
n
pr
e
m
a
t
ur
i
t
y
i
n
t
h
e
e
x
p
l
o
r
a
t
i
o
n
pr
o
c
e
dur
e
a
n
d
a
ug
m
e
n
t
t
h
e
c
a
pa
bi
li
t
y
o
f
t
h
e
f
u
n
d
a
m
e
n
t
a
l
T
L
B
O
t
o
f
l
e
e
f
r
o
m
l
o
c
a
l
o
pt
i
m
a.
I
n
t
e
a
c
hi
ng
ph
a
s
e
ne
w
-
f
a
n
g
l
e
d
s
e
t
o
f
e
nh
a
nc
e
d
l
e
a
r
n
e
r
s
a
r
e
de
f
i
ne
d
by
,
(
)
(
18)
I
n
l
e
a
r
n
e
r
s
t
a
ge
,
t
h
e
n
e
w
-
f
a
n
g
l
e
d
s
e
t
o
f
e
nh
a
n
c
e
d
l
e
a
r
n
e
r
s
i
s
de
f
i
ne
d
by
,
{
(
)
(
)
(
)
(
)
(
19)
M
ut
a
t
i
o
n
pr
o
c
e
dur
e
i
s
v
e
r
y
e
a
s
y
,
a
n
d
de
s
i
g
n
v
a
r
i
a
bl
e
s
a
r
e
i
ni
t
i
a
li
z
e
d
a
r
bi
t
r
a
r
i
ly
i
n
t
h
e
e
x
p
l
o
r
a
t
i
o
n
s
pa
c
e
:
.
(
⁄
)
/
(
20)
S
t
e
p
a
:
pa
r
a
m
e
t
e
r
s
a
r
e
i
ni
t
i
a
li
z
e
d
S
t
e
p
b
:
po
pul
a
t
i
o
n
ge
n
e
r
a
t
e
d
S
t
e
p
c
:
n
o
n
-
l
i
ne
a
r
i
n
e
r
t
i
a
we
i
g
h
t
f
a
c
t
or
,
dy
n
a
mi
c
i
n
e
r
t
i
a
we
i
g
h
t
c
o
m
put
e
d
by
(
(
(
)
)
(
⁄
)
)
(
)
;
(
)
S
t
e
p
d:
i
nd
i
v
i
dua
l
w
i
t
h
t
h
e
m
o
s
t
e
x
c
e
l
l
e
n
t
f
i
t
ne
s
s
i
s
c
h
o
s
e
n
a
n
d
a
ve
r
a
ge
v
a
l
ue
i
s
c
o
m
put
e
d
S
t
e
p
e
:
n
e
w
m
a
r
ks
o
f
t
h
e
l
e
a
r
ne
r
s
a
r
e
c
o
m
put
e
d
by
(
)
a
n
d
m
o
de
r
ni
z
e
t
h
e
o
l
d
va
l
ue
s
o
f
t
h
e
i
n
d
i
v
i
dua
l
s
by
(
)
(
)
(
)
S
t
e
p
f
:
c
o
m
put
e
t
h
e
n
e
w
-
f
a
n
g
l
e
d
v
a
l
u
e
s
o
f
t
h
e
s
tuden
t
s
;
{
(
)
(
)
(
)
(
)
a
n
d
m
o
de
r
ni
z
e
t
h
e
o
l
d
v
a
l
ue
s
o
f
t
h
e
i
n
d
i
v
i
dua
ls
b
y
(
)
(
)
(
)
S
t
e
p
g:
C
o
m
put
e
pr
o
b
a
bi
li
t
y
o
f
v
a
r
i
a
t
i
o
n
by
.
(
⁄
)
/
S
t
e
p
h
:
I
f
t
h
e
e
n
d
c
o
n
d
i
t
i
o
n
i
s
r
e
a
c
h
e
d
t
h
e
n
s
t
o
p
or
e
l
s
e
go
to
S
t
e
p
c
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
R
o
b
&
A
ut
o
m
I
S
S
N:
2089
-
4856
A
dv
anc
e
d
teac
hing
-
lear
ni
ng
-
bas
e
d
opti
miz
ati
on
al
gor
it
hm.
.
.
(
K
anagas
abai
L
e
nin
)
49
4.
S
I
M
UL
AT
I
ON
RE
S
UL
T
S
A
t
f
i
r
s
t
i
n
s
t
a
n
da
r
d
I
E
E
E
14
b
us
s
y
s
t
e
m
[
18]
t
h
e
v
a
li
d
i
t
y
o
f
t
h
e
pr
o
p
o
s
e
d
A
dv
a
n
c
e
d
T
e
a
c
hi
ng
-
L
e
a
r
ni
ng
-
B
a
s
e
d
Opt
i
m
i
z
a
t
i
o
n
a
l
go
r
i
t
hm
(
A
T
L
B
O
)
h
a
s
b
e
e
n
t
e
s
t
e
d,
T
a
bl
e
1
s
h
o
ws
t
h
e
c
o
n
s
t
r
a
i
n
t
s
o
f
c
o
n
t
r
o
l
v
a
r
i
a
bl
e
s
T
a
bl
e
2
s
h
o
ws
t
h
e
l
im
i
t
s
o
f
r
e
a
c
t
i
v
e
po
we
r
ge
n
e
r
a
t
or
s
a
n
d
c
o
m
pa
r
i
s
o
n
r
e
s
u
l
t
s
a
r
e
pr
e
s
e
n
t
e
d
i
n
T
a
bl
e
3.
T
h
e
n
t
h
e
pr
o
p
o
s
e
d
A
T
L
B
O
h
a
s
be
e
n
t
e
s
t
e
d,
i
n
I
E
E
E
30
B
us
s
y
s
t
e
m
.
T
a
bl
e
4
s
h
o
ws
t
h
e
c
o
n
s
t
r
a
i
n
t
s
o
f
c
o
n
t
r
o
l
v
a
r
i
a
bl
e
s
,
T
a
bl
e
5
s
h
o
ws
t
h
e
l
im
i
t
s
o
f
r
e
a
c
t
i
v
e
po
we
r
ge
n
e
r
a
t
or
s
a
n
d
c
o
m
pa
r
i
s
o
n
r
e
s
u
l
t
s
a
r
e
pr
e
s
e
n
t
e
d
i
n
T
a
bl
e
6.
T
a
bl
e
1.
C
o
n
s
t
r
a
i
n
t
s
o
f
c
o
n
tr
o
l
v
a
r
i
a
bl
e
s
S
y
s
t
e
m
V
a
r
ia
bl
e
s
Mi
ni
m
um
(
P
U
)
M
a
x
im
um
(
P
U
)
I
E
E
E
14 B
us
G
e
ne
r
a
t
o
r
V
o
lt
a
g
e
0.95
1.1
T
r
a
ns
f
or
m
e
r
T
a
p
o
.9
1.1
V
A
R
S
o
ur
c
e
0
0.20
T
a
bl
e
2.
C
o
n
s
t
r
a
i
n
s
o
f
r
e
a
c
t
i
v
e
po
we
r
ge
n
e
r
a
to
r
s
S
y
s
t
e
m
V
a
r
ia
bl
e
s
Q
M
in
im
um
(
P
U
)
Q
M
a
x
im
um
(
P
U
)
I
E
E
E
14 B
us
1
0
10
2
-
40
50
3
0
40
6
-
6
24
8
-
6
24
T
a
bl
e
3
.
S
i
m
u
l
a
t
i
o
n
r
e
s
u
l
t
s
o
f
I
E
E
E
−
14
s
y
s
t
e
m
C
o
nt
r
o
l
v
a
r
ia
bl
e
s
B
a
s
e
c
a
s
e
M
P
S
O
[
19]
P
S
O
[
19]
E
P
[
19]
S
A
R
G
A
[
19]
A
T
L
B
O
−
1
1.060
1.100
1.100
N
R
*
N
R
*
1.0
17
−
2
1.045
1.085
1.086
1.029
1.060
1.010
−
3
1.010
1.055
1.056
1.016
1.036
1.0
16
−
6
1.070
1.069
1.067
1.097
1.099
1.0
09
−
8
1.090
1.074
1.060
1.053
1.078
1.0
20
8
0.978
1.018
1.019
1.04
0.95
0.9
19
9
0.969
0.975
0.988
0.94
0.95
0.9
17
10
0.932
1.024
1.008
1.03
0.96
0.9
20
−
9
0.19
14.64
0.185
0.18
0.06
0.123
272.39
271.32
271.32
N
R
*
N
R
*
271.
82
(
M
v
a
r
)
82.44
75.79
76.79
N
R
*
N
R
*
75.
83
R
e
duc
ti
o
n
in
P
L
o
s
s
(
%
)
0
9.2
9.1
1.5
2.5
26.18
T
ot
a
l
P
L
o
s
s
(
M
w
)
13.550
12.293
12.315
13.346
13.216
10.
002
NR
*
-
N
ot
r
e
p
o
r
t
e
d.
T
a
bl
e
4.
C
o
n
s
t
r
a
i
n
t
s
o
f
c
o
n
tr
o
l
v
a
r
i
a
bl
e
s
S
y
s
t
e
m
V
a
r
ia
bl
e
s
M
in
im
um
(
P
U
)
M
a
x
im
um
(
P
U
)
I
E
E
E
30 B
us
G
e
ne
r
a
t
o
r
V
o
lt
a
g
e
0.95
1.1
T
r
a
ns
f
or
m
e
r
t
ap
o
.9
1.1
V
A
R
s
o
ur
c
e
0
0.20
T
a
bl
e
5.
C
o
n
s
t
r
a
i
n
s
o
f
r
e
a
c
t
i
v
e
po
we
r
ge
n
e
r
a
to
r
s
S
y
s
t
e
m
V
a
r
ia
bl
e
s
Q
M
in
im
um
(
P
U
)
Q
M
a
x
im
um
(
P
U
)
I
E
E
E
30 B
us
1
0
10
2
-
40
50
5
-
40
40
8
-
10
40
11
-
6
24
13
-
6
24
T
a
bl
e
6.
S
i
m
u
l
a
t
i
o
n
r
e
s
u
l
t
s
o
f
I
E
E
E
−
30
s
y
s
t
e
m
C
o
nt
r
o
l
v
a
r
ia
bl
e
s
B
a
s
e
c
a
s
e
M
P
S
O
[
19]
P
S
O
[
19]
E
P
[
19]
S
A
R
G
A
[
19]
A
T
L
B
O
−
1
1.060
1.101
1.100
N
R
*
N
R
*
1.0
10
−
2
1.045
1.086
1.072
1.097
1.094
1.0
19
−
5
1.010
1.047
1.038
1.049
1.053
1.0
12
−
8
1.010
1.057
1.048
1.033
1.059
1.0
20
−
12
1.082
1.048
1.058
1.092
1.099
1.0
26
VG
-
13
1.071
1.068
1.080
1.091
1.099
1.0
20
T
a
p11
0.978
0.983
0.987
1.01
0.99
0.9
29
T
a
p12
0.969
1.023
1.015
1.03
1.03
0.9
23
T
a
p15
0.932
1.020
1.020
1.07
0.98
0.9
20
T
a
p36
0.968
0.988
1.012
0.99
0.96
0.9
30
Q
C
10
0.19
0.077
0.077
0.19
0.19
0.09
0
Q
C
24
0.043
0.119
0.128
0.04
0.04
0.1
20
(
M
W
)
300.9
299.54
299.54
N
R
*
N
R
*
297.
54
(
M
v
a
r
)
133.9
130.83
130.94
N
R
*
N
R
*
131.
25
R
e
duc
ti
o
n
in
P
L
o
s
s
(
%
)
0
8.4
7.4
6.6
8.3
20.11
T
ot
a
l
P
L
o
s
s
(
M
w
)
17.55
16.07
16.25
16.38
16.09
14.
020
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2089
-
4856
I
n
t
J
R
o
b
&
A
ut
o
m
,
Vo
l
.
9
,
N
o
.
1
,
M
a
r
c
h
2020
:
4
6
–
50
50
5.
CONC
L
USI
ON
I
n
t
hi
s
pa
pe
r
A
d
v
a
n
c
e
d
T
e
a
c
hi
ng
-
L
e
a
r
ni
ng
-
B
a
s
e
d
Opt
i
m
i
z
a
t
i
o
n
a
l
go
r
i
t
hm
(
A
T
L
B
O)
s
uc
c
e
s
s
f
u
ll
y
s
o
l
ve
d
t
h
e
o
p
t
i
m
a
l
r
e
a
c
t
i
v
e
po
we
r
pr
o
bl
e
m
.
I
n
o
r
de
r
to
c
o
n
t
r
o
l
t
h
e
l
e
a
r
n
e
r
’
s
m
ut
a
t
i
o
n
a
r
bi
t
r
a
r
i
ly
dur
i
n
g
t
h
e
l
e
a
r
ni
ng
pr
o
c
e
dur
e
a
n
o
n
-
l
i
ne
a
r
m
ut
a
t
i
o
n
f
a
c
to
r
h
a
s
b
e
e
n
a
pp
li
e
d.
P
r
e
c
e
d
i
ng
i
n
f
o
r
m
a
t
i
o
n
ga
t
he
r
i
n
g
o
f
l
e
a
r
n
e
r
s
i
s
de
t
e
r
m
i
ne
d
by
t
h
e
we
i
g
h
t
f
a
c
t
or
a
nd
t
h
r
o
ugh
t
h
a
t
n
e
w
-
f
a
n
g
l
e
d
v
a
l
ue
s
a
r
e
c
a
l
c
u
l
a
t
e
d.
I
n
a
l
e
a
r
ni
ng
c
y
c
l
e
i
nd
i
vi
du
a
l
s
e
x
p
l
o
r
e
d
va
r
i
o
us
r
e
g
i
o
n
s
o
f
t
h
e
e
x
p
l
o
r
a
t
i
o
n
s
pa
c
e
i
n
i
n
i
t
i
a
l
p
h
a
s
e
.
P
r
o
p
o
s
e
d
A
d
v
a
n
c
e
d
T
e
a
c
hi
ng
-
L
e
a
r
ni
ng
-
B
a
s
e
d
Opt
i
mi
z
a
t
i
o
n
a
l
go
r
i
t
hm
(
A
T
L
B
O)
h
a
s
b
e
e
n
t
e
s
t
e
d
i
n
s
t
a
n
da
r
d
I
E
E
E
14
,
30
b
u
s
t
e
s
t
s
y
s
t
e
m
s
a
n
d
s
im
u
l
a
t
i
o
n
r
e
s
u
l
t
s
s
h
o
w
t
h
e
pr
o
j
e
c
t
e
d
a
l
go
r
i
t
hm
r
e
duc
e
d
t
h
e
r
e
a
l
po
we
r
l
o
s
s
.
P
e
r
c
e
n
t
a
ge
o
f
r
e
a
l
po
we
r
l
o
s
s
r
e
duc
t
i
o
n
ha
s
b
e
e
n
i
m
pr
o
v
e
d
whe
n
c
o
m
pa
r
e
d
t
o
ot
h
e
r
s
t
a
n
da
r
d
a
l
go
r
i
t
hm
s
.
RE
F
E
R
E
NC
E
S
[1
]
K
.
Y
.
L
ee
,
“
Fu
e
l
-
co
s
t
m
i
n
i
mi
s
at
i
o
n
fo
r
b
o
t
h
r
e
al
a
n
d
re
a
c
t
i
v
e
-
p
o
w
er
d
i
s
p
at
c
h
e
s
,
”
i
n
P
r
o
ceed
i
n
g
s
G
en
er
a
t
i
o
n
,
Tr
a
n
s
m
i
s
s
i
o
n
a
n
d
D
i
s
t
r
i
b
u
t
i
o
n
C
o
n
f
er
e
n
ce
,
v
o
l
.
1
3
1
,
n
o
.
3
,
p
p
.
8
5
-
93
,
1
9
8
4
.
[2
]
N.
I.
D
ee
b
.
“
A
n
e
ff
i
c
i
en
t
t
e
ch
n
i
q
u
e
fo
r
r
e
a
c
t
i
v
e
p
o
w
er
d
i
s
p
at
c
h
u
s
i
n
g
a
rev
i
s
e
d
l
i
n
e
ar
p
ro
g
ra
mm
i
n
g
ap
p
ro
ac
h
,
”
E
l
ect
r
i
c
P
o
w
er
S
ys
t
em
R
es
ea
r
c
h
,
v
o
l
.
15
,
n
o
.
2
,
p
p
.
1
2
1
–
1
3
4
,
1
9
9
8
.
[3
]
M.
R.
B
j
e
l
o
g
r
l
i
c
,
M.
S
.
Cal
o
v
i
c
,
a
n
d
B.
S
.
Bab
i
c
,
“
A
p
p
l
i
c
at
i
o
n
o
f
N
ew
t
o
n
’s
o
p
t
i
m
al
p
o
w
e
r
fl
o
w
i
n
v
o
l
t
ag
e
/
r
e
a
c
t
i
v
e
p
o
w
e
r
c
o
n
t
ro
l
,
”
IE
E
E
Tr
a
n
s
P
o
w
er
S
ys
t
em
,
v
o
l
.
5
,
n
o
.
4
,
p
p
.
1
4
4
7
-
1
4
5
4
,
1
9
9
0
.
[4
]
S.
G
ran
v
i
l
l
e
.
“
O
p
t
i
m
al
r
e
a
c
t
i
v
e
d
i
s
p
at
c
h
t
h
r
o
u
g
h
i
n
t
e
r
i
o
r
p
o
i
n
t
me
t
h
o
d
s
,
”
IE
E
E
Tr
a
n
s
a
ct
i
o
n
s
o
n
P
o
w
er
S
ys
t
em
,
v
o
l
.
9
,
n
o
.
1
,
p
p
.
1
3
6
–
1
4
6
,
1
9
9
4
,
d
o
i
:
1
0
.
1
1
0
9
/
5
9
.
3
1
7
5
4
8
[5
]
N
.
G
ru
d
i
n
i
n
,
“
Re
a
c
t
i
v
e
p
o
w
e
r
o
p
t
i
m
i
zat
i
o
n
u
s
i
n
g
s
u
cces
s
i
v
e
q
u
a
d
rat
i
c
p
ro
g
ra
mmi
n
g
me
t
h
o
d
,
”
IE
E
E
Tr
a
n
s
a
c
t
i
o
n
s
o
n
P
o
w
er
S
ys
t
em
,
v
o
l
.
13
,
n
o
.
4
,
p
p
.
1
2
1
9
–
1
2
2
5
,
1
9
9
8
,
doi
:
1
0
.
1
1
0
9
/
5
9
.
7
3
6
2
3
2
.
[6
]
S.
M.
R
.
Ng
,
M
.
H
.
Su
l
ai
m
a
n
,
Z.
Mu
s
t
affa
,
an
d
H
.
D
an
i
y
a
l
,
“
O
p
t
i
m
al
r
e
a
c
t
i
v
e
p
o
w
er
d
i
s
p
at
c
h
s
o
l
u
t
i
o
n
b
y
l
o
s
s
mi
n
i
m
i
zat
i
o
n
u
s
i
n
g
m
o
t
h
-
f
l
a
me
o
p
t
i
mi
zat
i
o
n
t
ech
n
i
q
u
e
,
”
A
p
p
l
.
S
o
f
t
C
o
m
p
u
t
.
,
v
o
l
.
5
9
,
p
p
.
210
–
2
2
2
,
2
0
1
7
.
[7
]
G
.
Ch
en
,
L
.
L
i
u
,
Z
.
Z
h
an
g
,
a
n
d
S
.
H
u
an
g
,
“
O
p
t
i
m
al
r
e
a
c
t
i
v
e
p
o
w
e
r
d
i
s
p
at
c
h
b
y
i
m
p
ro
v
ed
G
SA
-
b
as
ed
al
g
o
r
i
t
h
m
w
i
t
h
t
h
e
n
o
v
e
l
s
t
rat
e
g
i
e
s
t
o
h
an
d
l
e
co
n
s
t
rai
n
ts
,
”
A
p
p
l
.
S
o
f
t
Co
m
p
u
t
.
,
v
o
l
.
5
0
,
p
p
.
58
–
70
,
2
0
1
7
.
[8
]
E
.
N
ad
e
ri
,
H
.
N
ari
m
an
i
,
M.
Fat
h
i
,
a
n
d
M
.
R.
N
ari
m
a
n
i
,
“
A
n
o
v
e
l
fu
zz
y
ad
ap
t
i
v
e
co
n
f
i
g
u
rat
i
o
n
o
f
p
art
i
cl
e
s
w
a
rm
o
p
t
i
mi
zat
i
o
n
t
o
s
o
l
v
e
l
arg
e
-
s
c
al
e
o
p
t
i
m
a
l
r
e
a
c
t
i
v
e
p
o
w
e
r
d
i
s
p
at
c
h
,
”
A
p
p
l
.
S
o
f
t
Co
m
p
u
t
.,
v
o
l
.
5
3
,
p
p
.
441
–
4
5
6
,
2
0
1
7
.
[9
]
A
.
A
.
H
e
i
d
ari
,
R.
A
l
i
A
b
b
as
p
o
u
r,
an
d
R
.
J
o
rd
eh
i
,
“
G
au
s
s
i
an
b
are
-
b
o
n
e
s
w
at
e
r
cy
cl
e
al
g
o
r
i
t
h
m
f
o
r
o
p
t
i
m
a
l
r
e
a
ct
i
v
e
p
o
w
e
r
d
i
s
p
at
c
h
i
n
el
ec
t
ri
c
al
p
o
w
er
s
y
s
t
em
s
,
”
A
p
p
l
.
S
o
f
t
Co
m
p
u
t
.
,
v
o
l
.
5
7
,
p
p
.
657
–
6
7
1
,
2
0
1
7
.
[1
0
]
M
.
Mo
rg
an
,
N
.
R
.
H
.
A
b
d
u
l
l
a
h
,
M
.
H
.
Su
l
a
i
m
an
,
M
.
Mu
s
t
afa,
an
d
R
.
Sam
ad
,
“
Be
n
c
h
m
ar
k
St
u
d
i
e
s
o
n
O
p
t
i
m
al
Re
a
c
t
i
v
e
P
o
w
e
r
D
i
s
p
at
c
h
(O
RPD
)
Bas
ed
Mu
l
t
i
-
o
b
j
ec
t
i
v
e
E
v
o
l
u
t
i
o
n
ar
y
Pro
g
ra
mm
i
n
g
(MO
E
P)
U
s
i
n
g
M
u
t
at
i
o
n
Bas
e
d
o
n
A
d
ap
t
i
v
e
M
u
t
at
i
o
n
A
d
ap
t
e
r
(A
MO
)
an
d
Po
l
y
n
o
m
i
al
M
u
t
at
i
o
n
O
p
e
rat
o
r
(PMO
)
,
”
Jo
u
r
n
a
l
o
f
E
l
ect
r
i
ca
l
S
ys
t
em
s
,
p
p
.
12
-
1
,
2
0
1
6
.
[1
1
]
S.
M.
R
.
N
g
,
M
.
H
.
S
u
l
a
i
m
an
,
a
n
d
Z
.
Mu
s
t
affa
,
“
A
n
t
L
i
o
n
O
p
t
i
m
i
z
e
r
fo
r
O
p
t
i
m
a
l
R
e
a
c
t
i
v
e
Po
w
er
D
i
s
p
at
c
h
So
l
u
t
i
o
n
,
”
Jo
u
r
n
a
l
o
f
E
l
ect
r
i
c
a
l
S
y
s
t
em
s
,
n
o
.
Sp
eci
al
I
s
s
u
e
A
MP
E
2
0
1
5
,
p
p
.
6
8
-
74
,
2
0
1
6
.
[1
2
]
P.
A
n
b
aras
an
an
d
T
.
J
a
y
ab
arat
h
i
,
“
O
p
t
i
m
al
r
e
a
c
t
i
v
e
p
o
w
e
r
d
i
s
p
at
c
h
p
ro
b
l
em
s
o
l
v
ed
b
y
s
y
m
b
i
o
t
i
c
o
rg
a
n
i
s
m
s
earc
h
al
g
o
r
i
t
h
m
,
”
In
n
o
va
t
i
o
n
s
i
n
P
o
w
er
a
n
d
A
d
va
n
ce
d
Co
m
p
u
t
i
n
g
Tech
n
o
l
o
g
i
e
s
,
2
0
1
7
,
d
o
i
:
1
0
.
1
1
0
9
/
I
PA
CT
.
2
0
1
7
.
8
2
4
4
9
7
0
[1
3
]
A
.
G
ag
l
i
a
n
o
an
d
F.
N
o
ce
ra,
“
A
n
a
l
y
s
i
s
o
f
t
h
e
p
e
rfo
r
m
a
n
ce
s
o
f
el
ec
t
ri
c
en
e
rg
y
s
t
o
rag
e
i
n
r
e
s
i
d
en
t
i
al
ap
p
l
i
c
at
i
o
n
s
,
”
In
t
e
r
n
a
t
i
o
n
a
l
Jo
u
r
n
a
l
o
f
H
ea
t
a
n
d
Tech
n
o
l
o
g
y
,
v
o
l
.
3
5
,
n
o
.
Sp
eci
al
I
s
s
u
e
1
,
p
p
.
S4
1
-
S4
8
,
2
0
1
7
,
doi
:
1
0
.
1
8
2
8
0
/
i
j
h
t
.
3
5
Sp
0
1
0
6
.
[1
4
]
M.
Cal
d
e
ra
,
P.
U
n
g
aro
,
G.
Ca
mm
arat
a,
an
d
G.
Pu
g
l
i
s
i
,
“
Su
rv
ey
-
b
as
ed
a
n
al
y
s
i
s
o
f
t
h
e
el
ec
t
ri
c
a
l
en
e
rg
y
d
em
an
d
i
n
I
t
al
i
a
n
h
o
u
s
eh
o
l
d
s
,
”
M
a
t
h
em
a
t
i
ca
l
M
o
d
el
l
i
n
g
o
f
E
n
g
i
n
eer
i
n
g
P
r
o
b
l
em
s
,
v
o
l
.
5
,
n
o
.
3
,
p
p
.
2
1
7
-
2
2
4
,
2
0
1
8
,
d
o
i
:
1
0
.
1
8
2
8
0
/
m
me
p
.
0
5
0
3
1
3
[1
5
]
M.
Bas
u
,
“
Q
u
as
i
-
o
p
p
o
s
i
t
i
o
n
al
d
i
ff
e
r
en
t
i
al
ev
o
l
u
t
i
o
n
f
o
r
o
p
t
i
m
a
l
r
e
a
c
t
i
v
e
p
o
w
er
d
i
s
p
at
c
h
,
”
E
l
ect
r
i
ca
l
P
o
w
er
a
n
d
E
n
er
g
y
S
y
s
t
em
s
,
v
o
l
.
7
8
,
p
p
.
2
9
-
4
0
,
2
0
1
6
.
[1
6
]
G
.
G
.
W
an
g
,
“
Mo
t
h
s
e
arch
al
g
o
r
i
t
h
m
:
a
b
i
o
-
i
n
s
p
i
r
e
d
me
t
ah
e
u
r
i
s
t
i
c
a
l
g
o
ri
t
h
m
fo
r
g
l
o
b
al
o
p
t
i
m
i
zat
i
o
n
p
ro
b
l
em
s
,
”
M
em
et
i
c
Co
m
p
.
,
2
0
1
6
,
doi
:
1
0
.
1
0
0
7
/
s
1
2
2
9
3
-
0
1
6
-
0
2
1
2
-
3.
[1
7
]
X
.
Ch
en
,
B.
Xu
,
C.
M
ei
,
Y.
D
i
n
g
,
a
n
d
K
.
L
i
,
“
T
e
ach
i
n
g
–
l
e
arn
i
n
g
–
b
as
e
d
art
i
fi
ci
al
b
ee
co
l
o
n
y
fo
r
s
o
l
ar
p
h
o
t
o
v
o
l
t
ai
c
p
aram
e
t
e
r
e
s
t
i
m
at
i
o
n
,”
A
p
p
l
.
E
n
er
g
y
,
v
o
l
.
2
1
2
,
p
p
.
1
5
7
8
–
1
5
8
8
,
2
0
1
8
,
doi
:
1
0
.
1
0
1
6
/
j
.
ap
e
n
e
r
g
y
.
2
0
1
7
.
1
2
.
1
1
5
[1
8
]
I
E
E
E
,
“
T
h
e
IE
E
E
-
t
e
s
t
s
y
s
t
em
s
,”
h
t
t
p
:
/
/
w
w
w
.
e
e.
w
as
h
i
n
g
t
o
n
.
ed
u
/
t
rs
e
ar
c
h
/
p
s
t
c
a/
,
1
9
9
3
.
[1
9
]
A
.
N
.
H
u
s
s
ai
n
,
A
.
A
.
A
b
d
u
l
l
a
h
,
a
n
d
O
.
M
.
N
ed
a,
“
Mo
d
i
fi
e
d
Part
i
c
l
e
S
w
ar
m
O
p
t
i
mi
zat
i
o
n
fo
r
S
o
l
u
t
i
o
n
o
f
R
e
a
c
t
i
v
e
Po
w
e
r
D
i
s
p
at
c
h
,
”
R
es
ea
r
ch
Jo
u
r
n
a
l
o
f
A
p
p
l
i
ed
S
c
i
en
ce
s
,
E
n
g
i
n
e
er
i
n
g
a
n
d
Tec
h
n
o
l
o
g
y
,
v
o
l
.
15
,
n
o
.
8
,
p
p
.
3
1
6
-
3
2
7
,
20
18
,
doi
:
1
0
.
1
9
0
2
6
/
rj
as
e
t
.
1
5
.
5
9
1
7
.
Evaluation Warning : The document was created with Spire.PDF for Python.