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( T o p )
1
D e f i n i t i o n
T o g g l e D e f i n i t i o n s u b s e c t i o n
1 . 1
D e f i n i t i o n 1 ( T h e o r i g i n a l d e f i n i t i o n )
1 . 2
D e f i n i t i o n 2 ( D e f i n i t i o n w i t h g e o m e t r i c i n t e r p r e t a t i o n )
1 . 3
P r o o f o f E q u i v a l e n c e
2
P r o p e r t i e s
T o g g l e P r o p e r t i e s s u b s e c t i o n
2 . 1
P r o p e r t y 1
2 . 2
P r o p e r t y 2
2 . 3
P r o p e r t y 3
2 . 4
P r o p e r t y 4
2 . 5
P r o p e r t y 5
3
R e f e r e n c e s
4
F u r t h e r r e a d i n g
T o g g l e t h e t a b l e o f c o n t e n t s
K - c o n v e x f u n c t i o n
A d d l a n g u a g e s
A d d l i n k s
● A r t i c l e
● T a l k
E n g l i s h
● R e a d
● E d i t
● V i e w h i s t o r y
T o o l s
T o o l s
A c t i o n s
● R e a d
● E d i t
● V i e w h i s t o r y
G e n e r a l
● W h a t l i n k s h e r e
● R e l a t e d c h a n g e s
● U p l o a d f i l e
● S p e c i a l p a g e s
● P e r m a n e n t l i n k
● P a g e i n f o r m a t i o n
● C i t e t h i s p a g e
● G e t s h o r t e n e d U R L
● D o w n l o a d Q R c o d e
● W i k i d a t a i t e m
P r i n t / e x p o r t
● D o w n l o a d a s P D F
● P r i n t a b l e v e r s i o n
A p p e a r a n c e
F r o m W i k i p e d i a , t h e f r e e e n c y c l o p e d i a
K -convex functions , first introduced by Scarf ,[1] are a special weakening of the concept of convex function which is crucial in the proof of the optimality of the
(
s
,
S
)
{\displaystyle (s,S)}
policy in inventory control theory . The policy is characterized by two numbers s and S ,
S
≥
s
{\displaystyle S\geq s}
, such that when the inventory level falls below level s , an order is issued for a quantity that brings the inventory up to level S , and nothing is ordered otherwise. Gallego and Sethi [2] have generalized the concept of K -convexity to higher dimensional Euclidean spaces.
Definition [ edit ]
Two equivalent definitions are as follows:
Definition 1 (The original definition) [ edit ]
Let K be a non-negative real number. A function
g
:
R
→
R
{\displaystyle g:\mathbb {R} \rightarrow \mathbb {R} }
is K -convex if
g
(
u
)
+
z
[
g
(
u
)
−
g
(
u
−
b
)
b
]
≤
g
(
u
+
z
)
+
K
{\displaystyle g(u )+z\left[{\frac {g(u )-g(u-b)}{b}}\right]\leq g(u+z)+K}
for any
u
,
z
≥
0
,
{\displaystyle u,z\geq 0,}
and
b
>
0
{\displaystyle b>0}
.
Definition 2 (Definition with geometric interpretation) [ edit ]
A function
g
:
R
→
R
{\displaystyle g:\mathbb {R} \rightarrow \mathbb {R} }
is K -convex if
g
(
λ
x
+
λ
¯
y
)
≤
λ
g
(
x
)
+
λ
¯
[
g
(
y
)
+
K
]
{\displaystyle g(\lambda x+{\bar {\lambda }}y)\leq \lambda g(x )+{\bar {\lambda }}[g(y )+K]}
for all
x
≤
y
,
λ
∈
[
0
,
1
]
{\displaystyle x\leq y,\lambda \in [0,1]}
, where
λ
¯
=
1
−
λ
{\displaystyle {\bar {\lambda }}=1-\lambda }
.
This definition admits a simple geometric interpretation related to the concept of visibility.[3] Let
a
≥
0
{\displaystyle a\geq 0}
. A point
(
x
,
f
(
x
)
)
{\displaystyle (x,f(x ))}
is said to be visible from
(
y
,
f
(
y
)
+
a
)
{\displaystyle (y,f(y )+a)}
if all intermediate points
(
λ
x
+
λ
¯
y
,
f
(
λ
x
+
λ
¯
y
)
)
,
0
≤
λ
≤
1
{\displaystyle (\lambda x+{\bar {\lambda }}y,f(\lambda x+{\bar {\lambda }}y)),0\leq \lambda \leq 1}
lie below the line segment joining these two points. Then the geometric characterization of K -convexity can be obtain as:
A function
g
{\displaystyle g}
is K -convex if and only if
(
x
,
g
(
x
)
)
{\displaystyle (x,g(x ))}
is visible from
(
y
,
g
(
y
)
+
K
)
{\displaystyle (y,g(y )+K)}
for all
y
≥
x
{\displaystyle y\geq x}
.
Proof of Equivalence [ edit ]
It is sufficient to prove that the above definitions can be transformed to each other. This can be seen by using the transformation
λ
=
z
/
(
b
+
z
)
,
x
=
u
−
b
,
y
=
u
+
z
.
{\displaystyle \lambda =z/(b+z),\quad x=u-b,\quad y=u+z.}
Properties [ edit ]
[4]
Property 1 [ edit ]
If
g
:
R
→
R
{\displaystyle g:\mathbb {R} \rightarrow \mathbb {R} }
is K -convex, then it is L -convex for any
L
≥
K
{\displaystyle L\geq K}
. In particular, if
g
{\displaystyle g}
is convex, then it is also K -convex for any
K
≥
0
{\displaystyle K\geq 0}
.
Property 2 [ edit ]
If
g
1
{\displaystyle g_{1}}
is K -convex and
g
2
{\displaystyle g_{2}}
is L -convex, then for
α
≥
0
,
β
≥
0
,
g
=
α
g
1
+
β
g
2
{\displaystyle \alpha \geq 0,\beta \geq 0,\;g=\alpha g_{1}+\beta g_{2}}
is
(
α
K
+
β
L
)
{\displaystyle (\alpha K+\beta L)}
-convex.
Property 3 [ edit ]
If
g
{\displaystyle g}
is K -convex and
ξ
{\displaystyle \xi }
is a random variable such that
E
|
g
(
x
−
ξ
)
|
<
∞
{\displaystyle E|g(x-\xi )|<\infty }
for all
x
{\displaystyle x}
, then
E
g
(
x
−
ξ
)
{\displaystyle Eg(x-\xi )}
is also K -convex.
Property 4 [ edit ]
If
g
:
R
→
R
{\displaystyle g:\mathbb {R} \rightarrow \mathbb {R} }
is K -convex, restriction of
g
{\displaystyle g}
on any convex set
D
⊂
R
{\displaystyle \mathbb {D} \subset \mathbb {R} }
is K -convex.
Property 5 [ edit ]
If
g
:
R
→
R
{\displaystyle g:\mathbb {R} \rightarrow \mathbb {R} }
is a continuous K -convex function and
g
(
y
)
→
∞
{\displaystyle g(y )\rightarrow \infty }
as
|
y
|
→
∞
{\displaystyle |y|\rightarrow \infty }
, then there exit scalars
s
{\displaystyle s}
and
S
{\displaystyle S}
with
s
≤
S
{\displaystyle s\leq S}
such that
g
(
S
)
≤
g
(
y
)
{\displaystyle g(S )\leq g(y )}
, for all
y
∈
R
{\displaystyle y\in \mathbb {R} }
;
g
(
S
)
+
K
=
g
(
s
)
<
g
(
y
)
{\displaystyle g(S )+K=g(s )<g(y )}
, for all
y
<
s
{\displaystyle y<s}
;
g
(
y
)
{\displaystyle g(y )}
is a decreasing function on
(
−
∞
,
s
)
{\displaystyle (-\infty ,s)}
;
g
(
y
)
≤
g
(
z
)
+
K
{\displaystyle g(y )\leq g(z )+K}
for all
y
,
z
{\displaystyle y,z}
with
s
≤
y
≤
z
{\displaystyle s\leq y\leq z}
.
References [ edit ]
^ Scarf, H. (1960). The Optimality of (S, s) Policies in the Dynamic Inventory Problem . Stanford, CA: Stanford University Press. p. Chapter 13.
^ Gallego, G. and Sethi, S. P. (2005). K -convexity in ℜn . Journal of Optimization Theory & Applications, 127(1 ):71-88.
^ Kolmogorov, A. N.; Fomin, S. V. (1970). Introduction to Real Analysis . New York: Dover Publications Inc.
^ Sethi S P, Cheng F. Optimality of (s, S) Policies in Inventory Models with Markovian Demand. INFORMS, 1997.
Further reading [ edit ]
R e t r i e v e d f r o m " https://en.wikipedia.org/w/index.php?title=K-convex_function&oldid=1219183676 "
C a t e g o r i e s :
● C o n v e x a n a l y s i s
● T y p e s o f f u n c t i o n s
● T h i s p a g e w a s l a s t e d i t e d o n 1 6 A p r i l 2 0 2 4 , a t 0 6 : 4 5 ( U T C ) .
● T e x t i s a v a i l a b l e u n d e r t h e C r e a t i v e C o m m o n s A t t r i b u t i o n - S h a r e A l i k e L i c e n s e 4 . 0 ;
a d d i t i o n a l t e r m s m a y a p p l y . B y u s i n g t h i s s i t e , y o u a g r e e t o t h e T e r m s o f U s e a n d P r i v a c y P o l i c y . W i k i p e d i a ® i s a r e g i s t e r e d t r a d e m a r k o f t h e W i k i m e d i a F o u n d a t i o n , I n c . , a n o n - p r o f i t o r g a n i z a t i o n .
● P r i v a c y p o l i c y
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● C o d e o f C o n d u c t
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● C o o k i e s t a t e m e n t
● M o b i l e v i e w