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规律的最佳交通问题的潜在功能Regularity of potential functions of the optimal transportation problem

规律的最佳交通问题的潜在功能Regularity of potential functions of the optimal transportation problem
规律的最佳交通问题的潜在功能Regularity of potential functions of the optimal transportation problem

ARMA manuscript No.

(will be inserted by the editor)

Regularity of potential functions

of the optimal transportation problem

Xi-Nan Ma,Neil S.Trudinger,Xu-Jia Wang

Abstract

The potential function to the optimal transportation problem satis?es a partial di?erential equation of Monge-Amp`e re type.In this paper we introduce the notion of generalized solution, and prove the existence and uniqueness of generalized solutions to the problem.We also prove the solution is smooth under certain structural conditions on the cost function.

1.Introduction

The optimal transportation problem,as proposed by Monge in1781[22],is to?nd an optimal mapping from one mass distribution to another such that a cost functional is minimized among all measure preserving mappings.The original cost function of Monge was proportional to the distance moved and surprisingly this problem was only recently completely solved[9,29],see also[2].When the cost function is strictly convex,it was proved[6,15]that a unique optimal mapping can be determined by the potential functions,which are maximizers of Kantorovich’s dual functional.

The potential function satis?es a fully nonlinear equation of Monge-Amp`e re type,subject to a natural boundary condition.When the cost function c is given by c(x,y)=|x?y|2,or equivalently c(x,y)=x·y,the equation can be reduced to the standard Monge-Amp`e re equation

det D2u=h(·,Du),(1.1) and the regularity of solutions was obtained in[7,8,30],and earlier in[12]in dimension2.See also §7.1below.In this paper we study the regularity of potential functions for general cost functions. We establish an a priori interior second order derivative estimate for solutions to the corresponding Monge-Amp`e re equation when the cost function satis?es an additional structural condition,namely the assumption(A3)in Section2.Although condition(A3)depends upon derivatives up to order four of the cost function,it is the natural condition for interior regularity of the associated Monge-Amp`e re type equation.Moreover we do not expect the interior regularity without this or a similar

2Xi-Nan Ma,Neil S.Trudinger,Xu-Jia Wang

condition.To apply the a priori estimate to the potential functions we introduce and develop the notion of generalized solution and prove that a potential function is indeed a generalized solution.The regularity of potential functions then follows by showing that a generalized solution can be approximated locally by smooth ones.

In Section 2we introduce Kantorovich’s dual functional and deduce the Monge-Amp`e re type equation satis?ed by the potential function.We then introduce the appropriate convexity notions relative to the cost function and state the main regularity result of the paper (Theorem 2.1).In Section 3we introduce the generalized solution and show that a generalized solution is a potential function to the optimal transportation problem,from which follows the existence and uniqueness of generalized solutions (Theorem 3.1).In Section 4we establish the a priori second order derivative estimates (Theorem 4.1)under assumption (A3).In Section 5we prove that a generalized solution can be approximated locally by smooth solutions and so complete the proof of Theorem 2.1.

In Section 6we verify the assumption (A3).We show that (A3)is satis?ed by the two important

cost functions [5],c (x,y )= 1?|x ?y |2and c (x,y )= 1+|x ?y |2;and more generally by the

cost function

c (x,y )=(ε+|x ?y |2)p/2

(1.2)

for 1≤p <2,where ε>0is a constant.We also consider the cost function

c (x,y )=|X ?Y |2,(1.3)which is a function of the distance between points on graphs,where X =(x,f (x ))an

d Y =(y,g (y ))ar

e points o

f the graphs of f and

g .We show that condition (A3)is satis?ed if f and g are uniformly convex or concave and their gradients are strictly less than one.The ?nal Section 7contains various remarks.First in §7.1we indicate a simpler proof for the existence and interior regularity of solutions to equation (1.1)subject to the second boundary condition.We then recall in §7.2the re?ector antenna design problem treated in [32,33],whic

h is an optimal transportation problem with cost function satisfying assumption (A3).In §7.3we show that a potential function may not be smooth if the target domain is not convex relative to the cost function,while in §7.4we provide conditions ensuring the convexity property for our examples in §6.We conclude in §7.5with further remarks pertaining to the scope of our conditions.

Our treatment of c -concavity builds upon that in [16]for strictly convex cost functions and in

[32]for the re?ector antenna problem.We are very grateful to Robert McCann for useful discussions about this and other aspects of this paper.

2.Potential functions

Let ?,??be two bounded domains in the Euclidean space R n ,and let f,g be two nonnegative functions de?ned on ?and ??,and satisfying

?f =

??g.(2.1)

Regularity of potential functions3 Let c be a C4smooth function de?ned on R n×R n.The optimal transportation problem concerns the existence of a measure preserving mapping s0:?→??which minimizes the cost functional

C(s)=

?

f(x)c(x,s(x))dx(2.2)

among all measure preserving mappings from?to??.A map s is called measure preserving if it is Borel measurable and for any Borel set E∈??,

s?1(E)f=

E

g.(2.3)

The above condition is equivalent to that for any continuous function h∈C(??),

?h(s(x))f(x)dx=

??

h(y)g(y)dy.

To study the existence of optimal mappings to the minimization problem,Kantorovich introduced the dual functional

I(?,ψ)=

?f(x)?(x)dx+

??

g(y)ψ(y)dy,(?,ψ)∈K,(2.4)

where

K={(?,ψ)|?(x)+ψ(y)≤c(x,y),x∈?,y∈??}.(2.5) A fundamental relation between the cost functional C and its dual functional I is the following

inf s∈S C(s)=sup

(?,ψ)∈K

I(?,ψ).(2.6)

It is readily shown(under appropriate conditions)that the maximizer to the right hand side always exists,and is unique up to a constant[6,15].Let(u,v)∈K be a maximizer.The component functions u and v are called the potential functions of the optimal transportation problem.In this paper we study their regularity.

We assume the following conditions:

(A1)For any x,z∈R n,there is a unique y∈R n,depending continuously on x,z,such that D x c(x,y)=z,and for any y,z∈R n,there is a unique x∈R n,depending continuously on y,z, such that D y c(x,y)=z.

(A2)For any x,y∈R n,

det D2xy c=0,

where D2xy c is the matrix whose element at the i th row and j th column is?2c(x,y)

?x i?y j

.

(A3)There exists a constant c0>0such that for any x∈?,y∈??,andξ,η∈R n,ξ⊥η,

i,j,k,l,p,q,r,s

(c p,q c ij,p c q,rs?c ij,rs)c r,k c s,lξiξjηkηl≥c0|ξ|2|η|2,

where c i,j(x,y)=?2c(x,y)

i j

,and(c i,j)is the inverse matrix of(c i,j).

4Xi-Nan Ma,Neil S.Trudinger,Xu-Jia Wang

Assumption(A3)will be used in the proof of the regularity of u.For the regularity of v we assume instead

(c p,q c rs,p c q,ij?c rs,ij)c k,r c l,sξiξjηkηl≥c0|ξ|2|η|2.

In Section4we will show that assumption(A3)can be replaced by a slightly di?erent one,see (4.21).

From the proofs in[6,15],the existence and uniqueness,up to constants,of maximizers to (2.4)is readily inferred under conditions(A1)(A2),(although one should note that the stated hypotheses in these papers is stronger).Let(u,v)be the potential functions.It is easy to verify the relation[15],

{c(x,y)?v(y)},

u(x)=inf

y∈??

{c(x,y)?u(x)}.(2.7)

v(y)=inf

x∈?

It follows that u,v are Lipschitz continuous,and their Lipschitz constants are controlled by that of c.For any given x0∈?,let y0∈??such that

u(x0)=c(x0,y0)?v(y0),(2.8)

u(x)≤c(x,y0)?v(y0)?x∈?.(2.9) Then we have,provided Du and D2u exist at x0,

Du(x0)=D x c(x0,y0),(2.10)

D2u(x0)≤D2x c(x0,y0).(2.11)

By assumption(A1)and(2.10),we obtain a mapping T u,T u(x0)=y0,such that for almost all x∈?,

Du(x)=D x c(x,T u(x)).(2.12)

Similarly there is a mapping T v such that for almost all y∈??,

Dv(y)=D y c(T v(y),y).

From the proof in[6,15],the mapping T u is indeed measure preserving,and is optimal for the transportation problem(2.2).From(2.8)we have T u(x)=y if and only if T v(y)=x.Hence T v is the inverse of T u.From(2.11)we see that if u is C2smooth,then

D2u(x)≤D2x c(x,T u(x))?x∈?,(2.13)

where D2x c is the Hessian matrix of c with respect to the x-variable.Similarly if v is C2smooth, we have

D2v(y)≤D2y c(T v(y),y)?y∈??.

Next we introduce some convexity notions relative to the cost function c.These notions coincide with the classical ones when

c(x,y)=x·y.(2.14)

First we introduce the c-concavity of functions;see also[16].

Regularity of potential functions5

De?nition2.1.An upper semi-continuous functionφde?ned on?is c-concave if for any point x0∈?,there exists a c-support function at x0.Similarly,an upper semi-continuous functionψde?ned on??is c?-concave if for any point y0∈??,there exists a c?-support function at y0.

A c-support function of?at x0is a function of the form a+c(x,y0),where y0∈R n and a=a(x0,y0)is a constant,such that

?(x0)=c(x0,y0)+a,

?(x)≤c(x,y0)+a?x∈?.(2.15) Similarly one can de?ne c?-support functions by switching x and y,?and??.One can also introduce the notion of c-convex functions by changing the direction of the inequality in(2.15).

As the cost function c is smooth,any c-concave function?is semi-concave,namely there exists a constant C such that?(x)?C|x|2is concave.It follows that a c-concave function is locally Lipschitz continuous in?and twice di?erentiable almost everywhere.If?is twice di?erentiable at x0,then T?is well de?ned at x0and one has D2?(x)≤D2x c(x,T?(x))at x0.It is easy to show that if(?k)is a sequence of c-concave functions and?k→?,then?is c-concave.

In the special case when c(x,y)=x·y,the notion of c-concavity coincides with that of concavity, and the graph of a c-support function is a support hyperplane.

Obviously the potential function u is c-concave and v is c?-concave.Next we derive the equation satis?ed by(u,v).From(2.12)we have

D2u(x)=D2x c(x,T(x))+D2xy c·DT.(2.16) Hence

det(D2x c?D2u)=det(?D2xy c)det DT

=|det(D2xy c)|

f(x)

g(T(x))

x∈?.(2.17)

Note that det DT could be negative and by(2.13),the matrix(D2x c?D2u)is non-negative.Hence (2.17)is degenerate elliptic if u is c-concave.For the optimal transportation problem we have the natural boundary condition

T u(?)=??.(2.18) For the potential function v,we have,

D2v=D2y c+D2xy c·DT v.(2.19) Hence v satis?es the equation

det(D2y c?D2v)=|det D2xy c|·

g(y)

f(T v(y))

y∈??.(2.20)

The corresponding boundary condition is

T v(??)=?.(2.21)

6Xi-Nan Ma,Neil S.Trudinger,Xu-Jia Wang

We remark that equations(2.17)and(2.20)can also be found in[31],and the notion of c-concavity is already in the literature;see for example,[16].

Equations(2.17)and(2.20)are of Monge-Amp`e re type.If c(x,y)=x·y,then T u(x)=Du(x) and(2.17)is equivalent to the standard Monge-Amp`e re equation

det D2u=h,(2.22) with the boundary condition

Du(?)=??,(2.23) where h=g/f.As remarked earlier,the regularity for the second boundary problem(2.22)(2.23), as originally proposed in[20],was established in[7,8,12,30].

To study the regularity of equation(2.17),we not only need the c-convexity of functions,but also the convexity of domains,as in the case for the standard Monge-Amp`e re equation(2.22). First we introduce a notion of c-segments,which plays a similar role as line segments for the Monge-Amp`e re equation.

De?nition2.2.A c-segment in?with respect to a point y is a solution set{x}to D y c(x,y)=z for z on a line segment in R n.A c?-segment in??with respect to a point x is a solution set{y} to D x c(x,y)=z for z on a line segment in R n.

By assumptions(A1)and(A2),it is easy to check that a c-segment is a smooth curve,and for any two points x0,x1∈R n and any y∈R n,there is a unique c-segment connecting x0and x1 relative to y.

Let h(x)=c(x,y0)+a be a c-support function.Then T h(x)=y0for any x∈?,namely T h maps all points x∈?to the same point y0.Hence we may regard y0as the“focus”of h.Geometrically a c?-segment relative to x0is the set of foci of a family of c-support functions whose gradients at x0lie in a line segment.When c(x,y)=x·y,a c-support function is a hyperplane and the“focus”of a hyperplane is its slope.In this case a c-segment connecting x0and x1is the Euclidean line segment,and the c-convexity of domains introduced below is equivalent to convexity.

De?nition2.3.A set E is c-convex relative to a set E?if for any two points x0,x1∈E and any y∈E?,the c-segment relative to y connecting x0and x1lies in E.Similarly we say E?is c?-convex relative to E if for any two points y0,y1∈E?and any x∈E,the c?-segment relative to x connecting y0and y1lies in E?.

The notion of c-convexity is not equivalent to convexity in the usual sense,rather it is stronger in general.For example,a ball may not be c-convex(relative to another given domain)at arbitrary location.On the other hand,a su?ciently small ball will be c-convex if c is C3smooth.Another way of expressing De?nition2.3is that E is c-convex with respect to E?if for each y∈E?,the image D y c(·,y)(E)is convex in R n and E?is c?-convex with respect to E if for each x∈E, D x c(x,·)(E?)is convex in R n.We will examine this notion further in§7.4in the light of our examples in Section6.

We can now state the main regularity result of the paper.

Regularity of potential functions 7

Theorem 2.1.Suppose f ∈C 2(?),g ∈C 2(??),f,g have positive upper and lower bounds,and (2.1)holds.Suppose the cost function c satis?es assumptions (A1)-(A3).Then if the domain ??is c ?-convex relative to ?,the potential function u is C 3smooth in ?.If ?is c -convex relative to ??,the potential function v is C 3smooth in ??.

We have not studied the regularity near the boundary.In the special case c (x,y )=x ·y ,it has been established in [8,12,30].We also point out that if ??is not c ?-convex (relative to ?),the regularity assertion of Theorem 2.1does not hold in general,see §7.3.

Remark 2.1.Instead of maximizers of Kantorovich’s functional,one can also consider minimizers,namely functions (u,v )satisfying

I (u,v )=

inf (?,ψ)∈K ?I (?,ψ),(2.24)

where K ?={(?,ψ)|?(x )+ψ(y )≥c (x,y ),x ∈?,y ∈??}.

The existence of minimizers to (2.24)can also be proved along the line of [6,15].In this paper we will study maximizers only,but the treatment in the paper also holds for minimizers.In particular Theorem 2.1holds for minimizers if assumption (A3)is replaced by (A3 )There exists a constant c 0>0such that for any x ∈?,y ∈??,and ξ,η∈R n ,ξ⊥η,

i,j,k,l,p,q,r,s

(c p,q c ij,p c q,rs ?c ij,rs )c r,k c s,l ξi ξj ηk ηl ≤?c 0|ξ|2|η|2,

Note that (A3)and (A3 )cannot hold simultaneously.

3.Generalized solutions

Let ?be a c -concave function in ?.We de?ne a set-valued mapping T ?:?→R n ,which is an extension of the normal mapping (super-gradient)for concave functions [24].For any x 0∈?,let T ?(x 0)denote the set of points y 0such that c (x,y 0)+a is a c -support function of ?at x 0for some constant a =a (x 0,y 0).For any subset E ??,we denote T ?(E )= x ∈E T ?(x ).

If ?is C 1smooth,then T ?is single valued,and is exactly the mapping given by (2.12).In general,T ?(x )is single valued for almost all x ∈?as ?is semi-concave and so twice di?erentiable almost everywhere.If c (x,y )=x ·y ,T ?is the normal mapping for concave functions.In this paper we call the mapping T ?the c -normal mapping of ?.Similarly one can de?ne the c ?-normal mapping for c ?-concave functions.

Remark 3.1.Since a c -concave function ?is semi-concave,its super-gradient

?+?(x 0)={p ∈R n |u (x )≤u (x 0)+p ·x +o (|x ?x 0|)}

is de?ned everywhere.By (2.12),we see that if y ∈T ?(x 0),then D x c (x 0,y )∈?+?(x 0).However if ?is not C 1at some point x 0,the relation

T ?(x 0)={y ∈R n |D x c (x 0,y )∈?+?(x 0)}

8Xi-Nan Ma,Neil S.Trudinger,Xu-Jia Wang

does not hold in general,where c(x,y)+a(for some constant a)is a c-support function of?at x0.Moreover,the set

E={x∈R n|?(x)=c(x,y)+a}

may be disconnected.See§7.5for further discussion.

By the c-normal mapping we can introduce a measureμ=μ?,g in?,where g∈L1(R n)is a nonnegative measurable function,such that for any Borel set E??,

μ(E)=

T?(E)

g(x)dx.(3.1)

To prove thatμis a Radon measure,we need to show thatμis countably additive.We will use the following generalized Legendre transform.

De?nition3.1.Let?be an upper semi-continuous function de?ned on?.The c-transform of?is a function??de?ned on R n,given by

??(y)=inf{c(x,y)??(x)|x∈?}.(3.2) Similarly for an upper semi-continuous functionψde?ned on??,the c?-transform ofψis the function

ψ?(x)=inf{c(x,y)?ψ(y)|y∈??}.

From the de?nition,??is obviously c?-concave andψ?is c-concave.If?is c-concave and c(x,y0)+a is a c-support function of?at x0,then??(y0)=?a and c(x0,y)??(x0)is a c?-support function of??at y0.Hence the c?-transform of??,when restricted to?,is?itself.In particular we see that y∈T?(x)if and only if x∈T??(y).

Lemma3.1.Let?be a c-concave function.Let

Y=Y?={y∈R n|?x1=x2∈?,such that y∈T?(x1)∩T?(x2)}.

Then Y has Lebesgue measure zero.

Proof.Letψbe the c-transform of?.Then?is the c?transform ofψ.Observe that if y∈T?(x1)∩T?(x2),we have x1,x2∈Tψ(y).Henceψis not twice di?erentiable at y.But sinceψis semi-concave,ψis twice di?erentiable almost everywhere.

It follows thatμis countably additive,see[3,10,24].

Lemma3.2.Let?i be a sequence of c-concave functions which converges to?locally uniformly in?.Then for any compact set K??and open set U???,we have

lim i→∞μ?

i ,g

(K)≤μ?,g(K),(3.3)

lim i→∞μ?

i ,g

(U)≥μ?,g(U).(3.4)

Regularity of potential functions9 Proof.To prove(3.3)it su?ces to prove

i→∞

j≥i

T?

j

(K)?T?(K).(3.5)

To prove(3.5),we suppose x i∈K and y i∈T?

i (x i)such that y i converges to y0.Let h i(x)=

a i+c(x,y i)be a c-support function of?i at x i.Obviously a i is uniformly bounded.Letting i→∞we obtain h i→h0and h0=a+c(x,y0)is a c-support function of?at x0.Hence y0∈T?(x0), and the inclusion(3.5)is proved.

To prove(3.4),we?x(as for example in[10])a compact set K?U.Then for su?ciently large i,we have

T?(K)?Y??T?

i

(U),

so that by Lemma3.1,

μ?,g(U)=sup K?Uμ?,g(K)

≤lim i→∞μ?

i ,g (U).

Corollary3.1.Let{?i}be a sequence of c-concave functions in?.If?i→?,thenμ?

i ,g

→μ?,g

weakly as measures in?.

Let P k={p1,···,p k}be arbitrary k points in?and?be a c-concave function.Let

ηk(x)=inf{c(x,y)+a},(3.6) where the in?mum is taken over all a∈R and y∈R n such that c(p i,y)+a≥?(p i)for i=1,···,k

and c(x,y)+a≥?(x)for x∈??.It is easy to see thatμη

k ,g

is a discrete measure,supported on

the set P k.Choosing a proper sequence of{P k}such thatηk→?,by Lemma3.2we see thatμ?,f is a Radon measure.

For the standard Monge-Amp`e re equation(2.22),which corresponds to the cost function c(x,y)=x·y,the above properties of the measureμ?,g can also be found in[10,24]for the case g=1,and in[3]for general positive function g.

De?nition3.2.A c-concave function?is called a generalized solution of(2.17)ifμ?,g=f dx in the sense of measures,that is for any Borel set E??,

E f=

T?(E)

g.(3.7)

If furthermore?satis?es

???T?(?),|{x∈?|f(x)>0and T?(x)???=?}|=0,(3.8) then?is a generalized solution of(2.17)(2.18).

10Xi-Nan Ma,Neil S.Trudinger,Xu-Jia Wang

For the standard Monge-Amp`e re equation(2.22),namely when c(x,y)=x·y,the above gener-alized solution was introduced by Aleksandrov with g=1and Bakelman for general nonnegative locally integrable function g,see[3].Note that for the boundary condition(3.8),we need to extend g to R n???by letting g=0so that the mass balance condition(2.1)is satis?ed.

Let u be a generalized solution of(2.17)and v its c-transform.Let E u and E v denote respectively the sets on which u and v are not twice di?erentiable.Then|E u|=|E v|=0,and for any x∈T v(E v), there is a point y∈E v such that y∈T u(x).Since T u(x)is a single point for all x∈??E u,we have

T v(E v)f=

E v

g=0.(3.9)

The above formula implies that T u is one to one almost everywhere on{x∈?|f(x)>0}.It follows that T u is a measure preserving mapping.Hence if u is a generalized solution of(2.17) (2.18),by condition(3.8)and the mass balance condition(2.1),we have T u(x)∈??for almost all x∈{f>0}.It follows that for any Borel set E????,

E?g=

T v(E?)

f,(3.10)

where v is the c-transform of u.Hence we have

Lemma3.3.Let u be a generalized solution of(2.17)(2.18).Let v be the c-transform of u.Then v is a generalized solution of(2.20)(2.21)

The next lemma shows that a c-concave function is a generalized solution if and only if it is a potential function.In particular,if c(x,y)=x·y,then a generalized solution of Aleksandrov-Bakelman(with g=0outside??)is equivalent to a generalized solution of Brenier[4].

Lemma3.4.Let(u,v)be a maximizer of the functional I over K.Then u is a generalized solution of(2.17)and(2.18).

Conversely,if u is a generalized solution of(2.17)and(2.18),then(u,v)is a maximizer of the functional I over K,where v is the c-transform of u.

Proof.Let(u,v)be a maximizer.Then by(2.7),u is c-concave and v is c?-concave,and v is the c-transform of u.By[6,15],the mapping T u,as determined by(2.12),is a measure preserving optimal mapping.Hence T u is a one to one mapping from{x∈?|f(x)>0}to{y∈??|g(y)>0} almost everywhere.Hence u is a generalized solution of(2.17).The assumption(2.1)implies that (3.8)holds.

Conversely,if u is a generalized solution of(2.17)and(2.18),then v is a generalized solution of (2.20)and(2.21).Hence T u is a one to one mapping from{x∈?|f(x)>0}to{y∈??|g(y)>0} almost everywhere.By(3.7)we have

??h(y)g(y)=

?

h(T u(x))f(x))

Regularity of potential functions11 for any continuous function h∈C(??).It follows that

u(x)f(x)dx+

v(y)g(y)dy=

(u(x)f(x)+v(T u(x))f(x))dx

=

c(x?T u(x))f(x)dx.(3.11)

Hence(u,v)is a maximizer by(2.6).

The existence and uniqueness of maximizers to the functional I can be found in[6,15],where the cost function is assumed to be of the form c(x,y)=?c(x?y)for some strictly convex or concave function?c.But the argument there applies to general smooth cost functions satisfying(A1).Note that the uniqueness of optimal mappings in[6,15]implies the uniqueness of potential functions (up to a constant).Namely if(u1,v1)and(u2,v2)are two maximizers,then Du1=Du2a.e.on {f>0}.By Lemma3.4we have accordingly the following existence and uniqueness of generalized solutions.

Theorem3.1.Let?and??be two bounded domains in R n.Suppose f and g are two positive, bounded,measurable functions de?ned respectively on?and??,satisfying condition(2.1).Suppose the cost function c(x,y)∈C2(R n×R n)and satis?es assumption(A1).Then there is a unique generalized solution to(2.17)(2.18).

Remark3.2.The existence and uniqueness of generalized solutions can also be proved by the Perron method;see[32]for the treatment of the re?ector antenna design problem,which is a special optimal transportation problem[33].See also Section7.1below.

4.Second derivative estimates

Consider the equation

det w ij=?in?(4.1) where w ij=c ij(x,T(x))?u ij,and?=|det(D2xy c)|f(x)

g(T(x))

.Suppose?>0and the matrix{w ij} is positive de?nite.Write(4.1)in the form

log det w ij=ψ,(4.2) whereψ=log?.Then we have,by di?erentiation,

w ij w ij,k=ψk

w ij w ij,kk=ψkk+w is w jt w ij,k w st,k≥ψkk,(4.3)

where(w ij)is the inverse of(w ij).We use the notation w ij,k=?

?x k w ij,c ijk=?

?x k

c ij(x,y),

c ij,k=?

?y k c ij(x,y),T s,k=?

?x k

T s etc.That is

?w ij[u ijk?c ijk?c ij,s T s,k]=ψk,

?w ij[u ijkk?c ijkk?2c ijk,s T s,k?c ij,s T s,kk?c ij,st T s,k T t,k]≥ψkk.(4.4)

12Xi-Nan Ma,Neil S.Trudinger,Xu-Jia Wang

Let

G(x,ξ)=η2(x)wξξ,(4.5)

whereηis a cut-o?function,and for a vectorξ∈R n we denote wξξ=

ξiξj w ij.Suppose G

attains a maximum at x0andξ0∈S n?1.By a rotation of the coordinate system we assume ξ0=e1.At x0we have

(log G)i=w11,i

w11

+2

ηi

η

=0,

(log G)ij=w11,ij

w11

?

w11,i w11,j

w211

+2

ηij

η

?2

ηiηj

η

=w11,ij

w11

+2

ηij

η

?6

ηiηj

η2

.(4.6)

Hence

0≥w11

w ij(log G)ij=w ij w11,ij+2

w11

η

w ijηij?6w11w ij

ηiηj

η

.

We have

w11,ij=c11ij+c11i,s T s,j+c11j,s T s,i+c11,s T s,ij+c11,st T s,i T t,j?u11ij. It follows that

0≥w ij[c11,s T s,ij+c11,st T s,i T t,j?u11ij]?K,

where we use K to denote a positive constant satisfying

K≤C(1+w211+w11

η2

w ii).

By(4.4),

?w ij u ij11≥?w ij[c ij,s T s,11+c ij,st T s,1T t,1]?K.

Hence we obtain

0≥?w ij[c ij,s T s,11+c ij,st T s,1T t,1]

+w ij[c11,s T s,ij+c11,st T s,i T t,j]?K.(4.7) Recall that

w ij=c ij?u ij=?c i,k T k,j.(4.8) From the?rst relation,

w ki,j=c kij+c ki,p T p,j?u kij

=w ij,k+c ki,p T p,j?c ij,p T p,k.(4.9) From the second one we have

?w ki,j=c kj,p T p,i+c k,pq T p,i T q,j+c k,p T p,ij.(4.10) Hence

T p,ij=?c p,k w ki,j?c p,k[c kj,s T s,i+c k,st T s,i T t,j]

=?c p,k w ij,k?c p,k[c ki,s T s,j?c ij,s T s,k+c kj,s T s,i+c k,st T s,i T t,j].(4.11)

Regularity of potential functions13 Note that by(4.8),

T k,j=?c k,i w ij.(4.12) We have|T|≤Cw11.Hence

w ij T p,ij=?c p,k w ij w ij,k?c p,k w ij[2c ki,s T s,j?c ij,s T s,k+c k,st T s,i T t,j]

=?c p,k w ij c k,st T s,i T t,j+O(K).(4.13) By(4.12),

w ij T p,i T q,j=c p,s c q,t w ij w si w tj=O(w11).(4.14) Inserting(4.13)(4.14)into(4.7)we obtain

0≥?w ij[c ij,s T s,11+c ij,st T s,1T t,1]?K.(4.15) We have from(4.11)

T s,11=?c s,k w11,k?c s,k[2c k1,p T p,1?c11,p T p,k+c k,pq T p,1T q,1]

=?c s,k c k,pq T p,1T q,1+O(K).

Hence we obtain,by(4.12)

0≥?w ij c ij,st T s,1T t,1+c l,k c k,st c ij,l w ij T s,1T t,1?K

=w ij[c k,l c ij,k c l,st?c ij,st]c s,p c t,q w p1w q1?K,(4.16) where the summation runs over all parameters from1to n.

Let us assume by a rotation of coordinates that the matrix{w ij}is diagonal at x0.Then we obtain

w ii[c k,l c ii,k c l,st?c ii,st]c s,1c t,1w211≤K.

By assumption(A3),we obtain

w211

w ii≤K.

Observing that

n

i=1w ii≥

n

i=2

w ii≥

n

i=2

w ii

1

n?1≥Cw

1

n?1

11

,

we obtainη2w11≤C,namely G≤C.We have thus proved

Theorem4.1.Let u∈C4(?)be a c-concave solution of(4.1).Suppose assumptions(A1)-(A3) are satis?ed.Then we have the a priori second order derivative estimate

|D2u(x)|≤C,(4.17) where C depends on n,dist(x,??),sup?|u|,ψup to its second derivatives,the cost function c up to its fourth order derivatives,the constant c0in(A3),and a positive lower bound of|det D2xy c|.

14Xi-Nan Ma,Neil S.Trudinger,Xu-Jia Wang

With the estimate (4.17),equation (4.1)becomes a uniformly elliptic equation,and so higher order derivative estimates follows from the elliptic regularity theory [17].

Instead of the auxiliary function G given in (4.5),we can choose the auxiliary function G =η2

w kk =?w .Then by the same computation as above,we have w ij [c k,l c ij,k c l,st ?c ij,st ]c s,p c t,q w pm w qm ≤K.

(4.18)Hence we also need to assume condition (A3).

Remark 4.1.From our preceding argument or by direct calculation we have the formula

A ij,kl

=:?2A ij ?z k ?z l =(c ij,rs ?c p,q c ij,p c q,rs )c r,k c s,l ,(4.19)where

A ij (x,z )=c ij (x,T (x,z )),(4.20)

and T (x,z )is the mapping determined by (2.12),namely D x c (x,T (x,z ))=z .Consequently con-dition (A3)may be written in the form

A ij,kl ξi ξj ηk ηl ≤?c 0|ξ|2|η|2

(4.21)

for all ξ⊥η∈R n .

Moreover our proof of Theorem 4.1extends to Monge-Amp`e re equations of the form

det[A (x,u,Du )?D 2u ]=B (x,u,Du ),(4.22)where A and B are respectively C 2matrix and scalar valued functions on ?×R ×R n with

A ij,kl (x,u,z )=?2A ij ?z k ?z l

(x,u,z )satisfying (4.21)with respect to the gradient variables and B >0.Any elliptic solution u ∈C 4(?)of (4.22)will satisfy an interior estimate of the form (4.17),with constant C depending on n ,dist (x,??),sup ?(|u |+|Du |),A and B .The Heinz-Lewy example [26]shows that there is no C 1regularity for equation (4.22)without some restriction on A .

If D 2x

c is positive de?nite,we can also choose the auxiliary function G =η2 c ij w ij ,(4.23)

where {c ij }is the inverse matrix of {c ij }.The advantage of this function is that it is invariant under linear transformation.Denote H = c ij w ij .Suppose G attains a maximum at x 0.Then we have,at x 0,

0≥H w ij (log G )ij ≥ w ij H ij ?K =w ij c kl w kl,ij ?2c ks c lt (?x i c st )w kl,j ?c ks c lt (?2x i x j c st

)w kl +2c kp c sq c lt (?x i c st )(?x j c pq )w kl ?K.

Regularity of potential functions 15

To control the terms A =w ij ?2c ks c lt (?x i c st )w kl,j +2c kp c sq c lt (?x i c st )(?x j c pq )w kl ,

one observes that G is invariant under linear transformations.Hence one may assume by a linear transformation that {c ij }is the unit matrix and w ij is diagonal.Then

A =2w ii ?(?x i c kl )w kl,j +(?x i c kl )2w kk

≥?12w ii w kk w 2kl,i .Hence A can be controlled by the term w is w jt w ij,k w st,k in (4.3)(note that w ii (?x i c kl )2w kk ≤K by (4.12)-(4.14)).It follows that

w ij c kl w kl,ij ?c ks c lt w kl w ij (?2x i x j c st )≤K.(4.24)

The ?rst term can be estimated in the same way as (4.16)or (4.18).For the second one,we have by (4.12)-(4.14)that

?c ks c lt w kl w ij (?2x i x j c st

)=c ks c lt c st,p c ij,q c p,a c q,b w kl w ab w ij ?K.Hence by (4.18),we obtain

c ab w ij [c k,l c ij,k c l,st ?c ij,st ]c s,p c t,q w pa w qb

+c ks c lt c st,p c ij,q c p,a c q,b w kl w ab w ij ≤K.

(4.25)If the matrix {c ij }is negative,we replace the auxiliary function G in (4.23)by G =η2

(?c ij )w ij

and obtain ?c ab w ij [c k,l c ij,k c l,st ?c ij,st ]c s,p c t,q w pa w qb ?c ks c lt c st,p c ij,q c p,a c q,b w kl w ab w ij ≤K.

If {c ij }is not de?nite,we can replace G by G =η2 c ki c jk w ij and obtain similar su?cient

condition.

To verify (4.25),one may choose a proper coordinate system such that {c ij }=I is the unit matrix and {c i,j }=?I at x 0,and {w ij }is diagonal,as we will do in Section 6.Then (4.25)can be rewritten as

(?c ii,k c k,jj ?c ii,jj )w 2jj w ii +c kk,l c ii,l w kk w ll w ii

5.Proof of Theorem 2.1

With the a priori estimates established in Section 4,we need only to show that a generalized solution of (2.17)(2.18)can locally be approximated by smooth ones.

We will use the notion of extreme points of convex sets.For a bounded convex set E ?R n ,we say x 0is an extreme point of E if there is a hyperplane P such that P ∩E ={x 0}.It is well known that any point x ∈E can be represented as a linear combination of extreme points of E ,namely there exists extreme points x 1,···,x k and nonnegative constants α1,···,αk with

αi =1such that x = αi x i .

We also need an obvious property of concave functions.That is for any x 0∈?and any extreme point y ∈?+u (x 0),there is a sequence of points {x i }???{x 0}such that u is twice di?erentiable at x i and Du (x i )→y .

16Xi-Nan Ma,Neil S.Trudinger,Xu-Jia Wang

Lemma5.1.Let u be a generalized solution of(2.17).Suppose f>0in?,and??is c?-convex relative to?.Then T u(?)???.

Proof.Let G denote the set of points where u is twice di?erentiable.Then for any x∈G,T u(x) is a single point.Moreover,for any x0∈?and any sequence(x i)?G such that x i→x0and T u(x i)→y0for some y0∈R n,we have y0∈T u(x0).It follows that if there is a point x0∈G such that T u(x0)∈??,then for almost all x∈?,close to x0,we have T u(x)∈??.The mass balance condition implies this is impossible.

Observe that if x i→x0and T u(x i)→y0,then y0∈T u(x0).Hence for any point x0∈??G, if T u(x0)is a single point,then it falls in??.If T u(x0)contains more than one point,then the super-gradient?+u(x0)is a convex set.For every extreme point y∈?+u(x0),let z be the unique solution of y=D x c(x0,z).Then z∈??since there is a sequence(x i)∈G such that T u(x i)→z. Hence T u(x0)???as??is c?-convex and any point z∈?+u(x0)can be represented as a linear combination of extreme points of?+u(x0).

Lemma5.2.(Monotonicity)Let?be a bounded domain in R n and u,v∈C0(?),c-concave functions satisfying u≤v in?and u=v on??.Then T u(?)?T v(?).

Proof.This result follows,as in the Monge-Amp`e re case,by vertical translation upwards of c-support functions for u.

From Lemma5.2follows a simple comparison principle,namely if u,v∈C0(?)are c-concave, u≤v on??,μu,g<μv,g in?,then u≤v in?.For a more general result,based on the Aleksandrov argument[1],see[16].

Proof of Theorem2.1.It su?ces to show that u is smooth in any su?ciently small ball B r???.For this purpose we consider the approximating Dirichlet problems

det(D2x c?D2w)=|det(D2xy c)|

f

g?T

in B r,(5.1)

w=u m on?B r,

where{u m}is a sequence of smooth functions converging uniformly to u.We want to prove that (5.1)has a C3smooth solution w=w m such that the matrix{D2x c?D2w}is positive de?nite.

First we show that if w is a C2solution of(5.1),the cost function c(x,y)satis?es assumption (A3)at any points x∈B r and y∈T w(B r),so that the a priori estimate in§4applies.Indeed we may assume that(A3)holds in??×???,where??and???are respectively c-convex neighborhoods of?and c?-convex neighborhoods of??.By the semi-concavity of u,there exists a constant C such that the function?u=u?C|x|2is concave and|Du|0su?ciently small,we let

?u h(x)=

ρ(

x?y

h

)u(y),(5.2)

denote the molli?cation of?u,with respect to a symmetric molli?erρ≥0,∈C∞0(R n),

ρ=1,

suppρ?B1(0).Setting

u m=?u h

m

+C|x|2,(5.3)

Regularity of potential functions17 where h m→0,we then have u m→u uniformly and

D2u m≤C,|Du m|≤C.(5.4) Moreover for su?ciently large k and small r,the functions

v=v m=u m+k(r2?|x|2)(5.5) will be upper barriers for(5.1),that is,writing(5.1)in the form(4.22),we have A(x,Dv)>D2v and

det(A(x,Dv)?D2v)≥B(x,Dv)in B r,(5.6)

v=u m on?B r.

Consequently by the classical comparison principle[17],we have

w m≤v m in B r,

whence

T w

m (?B r)?T v

m

(B r).

It follows that T w

m

(B r)???if kr is small.Hence c is well de?ned on B r×T w(B r).

The preceding arguments yield a priori bounds for solutions and their gradients of the Dirichlet problem(5.1).To conclude the existence of globally smooth solutions,we need global second derivative bounds.The argument of the previous section,withη=1,clearly implies a priori bounds for second derivatives in terms of their boundary estimates.The latter can be established similarly to[32],(see also[17,19]),or by directly using the method introduced in[27,28]for the Monge-Amp`e re equation.The key observation again is that functions of the form k(r2?|x|2) provide appropriate barriers for large k and small r.From the interior estimates in Theorem4.1, we?nally infer the existence of locally smooth elliptic solutions w of the Dirichlet problem(5.1) with w=u on?B r.Finally it remains to show that w=u in B r.By perturbation of w,we may suppose that the setωε={x∈B r|w(x)>u(x)+ε}has su?ciently small diameter,with w c-concave a strict supersolution of equation(5.1)inωε,that isμw,g<μu,g inωε.From Lemma 5.2,we thus conclude w≤u in B r and similarly w≥u follows.

Our argument above may also be used to prove interior regularity for the generalized Dirichlet problem,the solvability of which depends upon the existence of barriers.Note that the condition of c-convexity is not directly relevant to the Dirichlet problem.

6.Veri?cation of assumption(A3)

In this section we give some cost functions which satisfy assumption(A3).First we consider cost functions of the form

c(x,y)=?(1

2

|x?y|2).(6.1)

In general a function of the form(6.1)does not satis?es(A3),see for example§7.5.

18Xi-Nan Ma,Neil S.Trudinger,Xu-Jia Wang

For the cost function(6.1),we have?y

i c=??x

i

c.We can write c(x,y)as c(x?y).Then(A3)

is equivalent to

k,l,s,t

(c kl c iik c stl?c iist)c sj c tj≥c0(6.2) for any?xed1≤i,j≤n,i=j,where(c ij)is the inverse matrix of(c ij).

It is hard to verify(6.2)directly,as it involves fourth order derivatives.To verify(6.2),we recall the estimate(4.16),which can be written as

w ij[c kl c ijk c lst?c ijst]c sp c tq w pξw qξ≤K,(4.16) whereξis the unit vector in which the auxiliary function G=η(x)wξξattains its maximum at some point x0.Let y0=T u(x0)and assume by a rotation of coordinates that x0?y0=(r,0,...,0). We?rst make a linear transformation(dilation)such that{c ij}=? I at x0?y0,then make a rotation of coordinates such that{w ij}is diagonal.Then the unit vectorξ=αk e k for some constantsαk,and(4.16) becomes

w ii[c iik c kst?c iist]αsαt w ss w tt≤K,(4.16) where{e k}are the axial directions.After the coordinate transformations,it su?ces to verify

Σk c iik c kjj?c iijj≥c0>0(6.3) for any i=https://www.doczj.com/doc/864492911.html,ly(6.3)implies(A3).

We compute

c i=? r i,

c ij=? δij+? r i r j

where r i=x i?y i.At the point(r,0,...,0),we have

{c ij}=diag(? +r2? ,? ,...,? ).

Suppose that?

? +r2?

>0.Let

x1=β?x1,

x i=?x i,i>1,

whereβ=

?

? +r2?

.Then

c(?x)=?(

1

2

(β2?x21+?x22+...+?x2n))

with

{c ij}=? I at?x0=(r

β

,0,...,0)(6.4)

in the coordinates?x,where I is the unit matrix.

Regularity of potential functions19 We make a rotation?x=Ay,where A is an orthogonal matrix.Then

c(y)=?(1

2

y By),

where

B=A ?BA,?B=diag(β2,1...,1).

Denote z=By.We have,at the point y0=A ?x0,

|z|2=z ·z=y A ?B2Ay

=?x ?B2?x=β2r2=

? r2

? +r2?

.(6.5)

In the y-coordinates,we have

c i=? z i,

c ij=? b ij+? z i z j,

c ijk=? (b ij z k+b ik z j+b jk z i)+? z i z j z k,

c ijkl=? (b ij b kl+b ik b jl+b il b jk)

+? (b ij z k z l+b ik z j z l+b il z j z k+b jk z i z l+b jl z i z k+b kl z i z j)

+? z i z j z k z l.

By(6.4)and since A is orthogonal,we have{c ij}=? I in the y-coordinates.From the above formula for c ij,we obtain

b ij=δij??

?

z i z j.

Hence

c ijk=? (δij z k+δik z j+δjk z i)+(? ?3(? )2

?

)z i z j z k,

c ijkl=? (δijδkl+δikδjl+δilδjk)

+(? ?(? )2

?

)(δij z k z l+δik z j z l+δil z j z k+δjk z i z l+δjl z i z k+δkl z i z j)

+[? ?6? ?

?

+3

(? )3

(? )2

]z i z j z k z l.

Denote F=:Σk c kk c iik c jjk?c iijj.From the above formulae and noting that i=j,we obtain

F=z2

k

?

? (1+2δik)+(? ?3

(? )2

?

)z2i

? (1+2δjk)+(? ?3

(? )2

?

)z2j

?[? +(? ?

(? )2

?

)(z2i+z2j)+(? ?6

? ?

?

+3

(? )3

(?)

)z2i z2j].(6.6)

First let us check the cost function

c(x,y)=

1+|x?y|2.(6.7)

20Xi-Nan Ma,Neil S.Trudinger,Xu-Jia Wang

The corresponding Monge-Amp`e re equation is

det(?D 2u +(1?|Du |2)1/2(δij ?u i u j ))=(1?|Du |2)(n +2)/2f (x )/g (T (x )).(6.8)

The negative sign on the left hand side is due to the c -concavity of u .For the cost function (6.7),we have φ(t )=√1+2t ,and by direct computation,

? ?3(? )2

?

=0,? ?6? ? ? +3(? )3(? )2=0.(6.9)

Hence

F =?? +(? )2?

Σk (1+2δik )(1+2δjk )z 2k ?2(z 2i +z 2j ) =?? +|z |2(? )2? ≥?? >0.(6.10)

The matrix A in (6.8)is given by

A (x,z )=A (z )=(1?|z |2)1/2(δij ?z i z j )

(6.11)

and our calculations above show that

A ij,kl ξi ξj ηk ηl >0(6.12)for all ξ,η∈R n ,ξ⊥η,|z |<1.The condition (6.12)may also be veri?ed directly from (6.11).We remark that (6.10)and (6.12)are not true for all |z |<1if i =j in (6.3)or ξ=ηin (6.12).

Note also for (6.7)that (A1)only holds for |z |<1.However this does not a?ect our proof on Theorems 2.1and 3.1.

By a linear transformation,(A3)is also satis?ed for

c (x,y )=[1+a ij (x i ?y i )(x j ?y j )]1/2,

where {a ij }is a positive matrix.Note that the graph of the function [1+a ij x i x j ]1/2is a hyperboloid .

Next we verify (A3)for the cost function

c (x,y )= 1?|x ?y |(6.13)

For this cost function,equation (2.17)takes the form

det(?D 2u ?(1+|Du |2)1/2(δij +u i u j ))=(1+|Du |2)(n +2)/2f (x )/g (T (x )).(6.14)

For the cost function (6.13),we have ?(t )=√1?2t .Hence (6.9)holds and similarly to (6.10)we

have F =?? +|z |2(? )2?.

[城市轨道,交通,系统分析,其他论文文档]城市轨道交通系统分析

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生态人居示范区度假别墅区,养生别墅区,老年公寓区,将旅游、度假、休闲、养生、疗养、康乐等旅游地产开发一体化打造。

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但通常都市圈和城市群概念区分不大。 专业 城市轨道交通系统 相关设施 市郊铁路:是由电气或燃机车牵引,轮轨导向,车辆编组运行在城市中心与市郊,市郊与市郊、市郊与新建城镇间,以地面专用线路为主的大运量快速轨道交通系统。通常其所属权不属于所在的城市政 府,而由铁路部门经营。 课外:卫星城:是指在大城市外围建立的既有就业岗位,又有较完善的住宅和公共设施的城镇,是在大城市郊区或其以外附近地区,为分散中心城市的人口和工业而新建或扩建的具有相对独立性的城镇。因其围绕中心城市像气象卫星一样,故名。旨在控制大城市的过度扩展,疏散过分集中的人口和工业。卫星城虽有一定的独立性,但是在行政管理﹑经济﹑文化以及生活上同它所依托的大城市十分密切的

城市道路支路系统的交通组织

少年易学老难成,一寸光阴不可轻- 百度文库 目录 摘要 (1) Abstract (2) 城市道路支路系统的交通组织············· - 1 -第一章绪论··················· - 3 -第二章城市道路支路系统的规划设计········· - 7 -第四章应用实例··················- 16 -第五章结束语···················- 20 -

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The traffic organization of the system of city road branch Absract: Local roads play an important role in utban street systems,just like capillaries do in human bodies. However,local roads have not gained sufficient attention thus far in the planning and design process of urban street systems in China .This paper discusses issues on road functional classifications, road network density, and cross-sectional design in local road development, and provides a detailed analysis of local road functionalities. According to road functional classifications typically adopted abroad,the paper classifies local roads into three functionalities, namely, through-traffic,neighbor-hood-specific, and special use, and specifies their typical funcions and application scopes. Finally, the paper fur-ther analyzes local road density,right-of-way,lane-width, separation facilities,and road-side parking issues. In order to rationally organize the traffic in the area of urban arterial road intersected by multi-inferior roads at T-intersection,a traffic organization method with channelized traffic design and signal coordinated control was presented,based on the investigation and analysis of the characteristics of the above. Keywords:local road planning、local road design、local road functionalities、coordination control

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2020年(发展战略)我国三大都市圈的发展及功能定位分析

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交通系统分析---功能

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(2)应急功能 (3)促进功能(经济、科技) (4)引导功能 (5)其他功能 四、交通系统各功能之间的关系以及子系统之间的关系: 1、系统各功能之间的联系 2、子系统各功能之间的联系 3、系统各功能的相互影响 4、子系统各功能的相互影响 五、交通系统功能特性(优势、劣势、其它) 1、交通系统功能的积极方面 2、交通系统功能的消极方面 3、交通系统功能的整体特性 六、交通系统功能需求(智能、未来需求) 1、智能化需求(智能公交、智能交通、智能汽车) 2、物联网技术需求(物联网技术融入交通系统) 3、文化建设需求(长久性、发展性) 4、“绿色交通”需求

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项目定位分析

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?商场: 11750平方米 ?写字楼: 21290 平方米 ?其余为公寓: ?地下建筑面积: 25775平方米 ?地下车位: 333辆 ?地上车位: 63辆 ?自行车: 466辆 2、整体功能布局 建议项目规划为: 一栋写字楼,一栋商业,两栋公寓。 ●整个社区采用围合式建筑方案 ●公寓采用板式高层 ●围合社区中央空间 ●用地西侧从北至南依次摆放商业配套、写字楼的一部 分;用地南侧从西至东依次坐落另一部分写字楼和公寓 1号楼;用地北侧设计为公寓2号楼;社区西侧与东侧 保持完整外立面。 ●社区设计两个出入口,实现人车分流。

商业配套地下可设计为地下停车场,主要满足写字楼的需求;公寓停车场可设计在1号楼和2号楼地下;商业配套北侧小片空地可设计为商业用停车位。围合出的空间可聘请具有实力的景观设计事务所进行布置,达到环境优美、视野明亮、集绿化休闲为一体的场所。从外观上,在西侧与南侧保持完整连接,成为: 劲松商圈地标性建筑。 (具体规划情况见附图)

三、目标客户群体描述 1、写字楼目标客户群体 ●中小型外资企业 ●以CBD内大公司为服务对象的各类公司 ●留学归国人员创办企业 ●投资型买家 2、公寓目标客户群体: ●投资型买家 ●首次置业的白领阶层 ●单身贵族 ●知名企业高层管理人员的工作居所 ●外企置业 ●留学归国人员 注: 21世纪不动产认为项目在推广入市过程中,应赋予产品一个包装概念,但这一包装概念应是在产品已具有鲜明特点之后,才在项目具备一系列竞争点的基础上,通过富有创意概念进行推广包装,而不是在塑造产品之前,毫无理由,且无产品支撑的一种空谈。这一点如有机会,21世纪不动产将会在今后一个阶段协同发展商及广告公司共同

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