H-Invex-Type Functions on Differentiable Manifolds

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H-Invex-Type Functions on Differentiable Manifolds

-invex-type functions on differentiable manifolds.

M.Ferrara1

Abstract. In this paper the Author introduces new properties about invex functions in the frame of mathematical programming on differentiable manifolds. Mathematics subject Classification(2000): Primary 90C30, Secondary 53B20. Journal of Economic Literature Classification: C00, C61. Key Words: Generalized invexity, Riemannian manifolds, Kuhn-Tucker conditions.

1. Introduction The aim of this paper is to make new remarks about results of invex programming obtained on Riemannian manifolds. In 1994 C. Udriste [see [11]] provides an exhaustive exposition of convex programming on Riemannian manifolds. Here, the Author proved the classic Kuhn-Tucker Theorem for the problem

min f x xA where f: MR is a geodesically convex function, (M,g) denotes a Riemannian manifold and

A  x  M : hi (x)  0;i  1,....,s

where hi: MR is a geodesically convex function for all i = 1,.....,s

Such a generalization is based on the fact that some properties of convex programs on Euclidean spaces can be used in the case of a Riemannian manifold. In 1994, R. Pini has introduced a definition of the invex function for functions defined on general differentiable manifolds. In fact in [7] Pini proved that the Kuhn-Tucker conditions are necessary and sufficient in order that a point is a solution for the problem

min f(x) xS

n n where f: R R is -invex and S  x  R : hi x  0; i  1,....s, with

1 Associate Professor, Faculty of Economics, University of Messina, Via dei Verdi, 75, 98122 Messina (ITALY). E-mail adress: [email protected]

1 n hi: R R -invex for all i = 1,...., s. The main result of the present paper is the proof of the validity of some theorems introduced in [1], with reference to differentiable manifolds.

2. Notation and definitions. This section, contains an outline of some important notions, concerning Riemannian geometry and which will be used in the sequel.

Definition 2.1 A differentiable manifold of dimension n is a set M and a family of injective n n mappings xα : Uα  R  M of open sets Uα of R into M such that:

(1) x (U )  M;  1 (2) for any pair ,  with xα (Uα )  xβ (Uβ )  W  . The set xα (W) and 1 n 1 -1 xβ (W) are open sets in R and the mappings xβ ° xα : xα (W)  xβ (W) are differentiable:

(3) the familyU, x is maximal relative to the conditions (1) e (2), each other family V, ysatisfying (1) and (2) is included in U, x.

The pair U, x with p  x (U) is called a parametrization (or system of coordinates) of M at p; x (U) is then called a coordinate neighbourhood at p. We know that each differentiable manifold can be made into a topological space using the family of finite intersection of coordinate neighbourhoods as a base of the topology. Usually, we can suppose that the manifold is an Hausdorff space with countable base.

Definition 2.2 Let M be a differentiable manifold. A differentiable function : (-, )  M is called a curve in M. Suppose that (0) = p and let  be the set of functions f: M  R differentiable at p. The tangent vector to the curve  at t = 0 is a function  (0):   R given by:

df ° α α' (0) f  f   dt t0

A tangent vector to M at p is the tangent vector at t = 0 of some curve : (-, )M with (0) = p. The set of all tangent vectors to M at p will be indicate by TpM and it will be called tangent space to M at p.

2 Let f: M  R a differentiable function. Its differential dfp at p is a linear mapping beetwen TpM and Tf(p) R  R. Therefore dfp is an element of the dual space of TpM.

After these notions, now, we consider only Riemannian manifold.

Definition 2.4 A Riemannian metric g on a differentiable manifolds M is a correspondence which associates to each point p of M an inner product gp on the tangent n space TpM such that, if x: U  R  M is a system of coordinates around p,     g  (q), (q)  g (x(q)) then p  ij  is a differentiable function for each  xi x j  q  U.

Definition 2.5 Let M be a differentiable manifold and g is a Riemannian metric on M. The pair (M, g) is called Riemannian manifold. As it happens in Rn, we can introduce some differential operators on a Riemannian manifolds. Let f be a function of class C1 (M), then grad f (or df) is defined by:

gp (grad fp, v) = dfp (v)  v  Tp M

It is clear that grad fp  Tp M.

Definition 2.6 A Riemannian manifold M is geodesically complete when for all p  M, any geodesic  starting from p is defined for all values of the parameter t  R. In the case of complete Riemannian manifolds, one of the most important results is the Hopf-Rinow Theorem. This theorem states that the following assertions are equivalent: 1. M is geodesically complete; 2. M is complete metric space endowed with the metric d defined in this way: p,qM d(p,q)= inf l()   :a, bM piecewise differentiable curve; a = p, b = q 3. The closed and bounded sets of M are compact. In addition the Hopf-Rinow Theorem states that M is a geodesically complete manifold, so that for each p, q  M there exist a geodesic arc  joining p to q, moreover  is such that d(p, q) = l(), i. e. . minimizes the length of the curves passing through p and q. This important property of Hopf-Rinow Theorem explaines the reason why, when considering a geodesically convex function defined on a Riemannian manifolds (M,g), M must be a complete manifold.

3 3. Generalized invex functions on differentiable manifold. Considering the concept of geodesically convex function we assume that: a function f: M  R is geodesically convex when its restrictions to each geodesic arc of M are convex.

Definition 3.1 The function f : M  R is geodesically convex iff for each geodesic arc : a, b  M and for each 0, 1 we have:

f( ((1 ) a  b )  (1 ) f ( (a))   f ( (b))

We can have the usual notion of convexity when we consider the manifold (M, g) as the space Rn endowed with the Euclidean space. At this point, the concept of invexity, born in the Euclidean case, can be also extended to differentiable manifolds. As it has been shown by R.Pini see7, if we consider a complete Riemannian manifold (M,g) (definition 2.6) there exists a map  (see definition below) which has the same role played in classic definitions of invexity in Euclidean spaces. Hence the class of -invex functions are the geodesically convex functions on a Riemannian manifold.

Definition 3.2 Let (M, g) be a complete Riemannian manifolds of dimension n and A  M. Let f : M  R be a differentiable function and  a map such that:

(3.1) : M x M  TM

We know that a function  see 1 is said to be -invex at y  X  Rn iff:

(x) – (y)  ((x, y),  (y)) xX

Now, we consider a complete Riemannian manifolds (M,g).We have the following:

Definition 3.3 The function f : M  R is said to be -invex on M iff :

f(p) – f(q)  ( (p, q)) dfq for every p, q  M

where  is a map such that (p, q)  TqM  p, q  M, f is said to be -pseudoinvex at q  A if p  A, ( (p, q)) dfq  0  f(p) – f(q)  0 and f is said -quasiinvex at qA if pA, f(p) – f(q)  0  ((p, q)) dfq  0.

4 Starting from above definition, we can introduce the following:

Definition 3.4 f is -inf invex at qA0, with respect to A  M, iff:

inf f p f q inf ηp,q dfq pA0 pA0 f is -supinvex at qA0, with respect to A  M iff:

sup f p  f q  sup η p,q df         q pA0 pA0

f is -inf-pseudoinvex at q, with respect to A0 iff:

inf ηp,qdfq  0  inf f p f q 0 pA0 pA0

f is -sup-quasiinvex at qA0 iff:

sup f p  f q  0  sup η p,q df  0        q . pA0 pA0

We have the following general definitions:

Definition 3.5 f is -inf-invex (-sup invex, -inf pseudoinvex, -supquasiinvex) on

AM, with respect A0 iff it is -inf invex (-sup invex, -inf pseudoinvex, -supquasiinvex) at any point q  A  M. The previously properties introduced can be used in a classic framework of scalar optimization problem:

inf f p where A0  p A hjp  0, j  1,....,m  pA0

Definition 3.6 The problem (P) is -inf-sup invex at q  A, iff f:MR is -inf-invex at q, with respect to A0, and hj with j = 1,…m are -sup invex at q with respect to

A0. (P) is -inf-sup invex on A iff it is -inf-sup invex at every point q  A. Let consider us (D) a classical Wolfe dual in A  M of (P)  m  (D) sup  f p  v h p ,  p, V     j j    j 1 

5 m  m  where V  p,v MxR grad f p v j grad hj p  0  j1 

4. Sufficency of inf-sup invexity in Kuhn-Tucker conditions. 1 Let f : MR and hj :MR be two functions differentiable on M of class C . m A Kuhn-Tucker point (or K-T point) is a pair (p0, v)  M x R satisfying the following conditions: m (4.1) grad f p0  v jhj p0   0 j1 m (4.2) v jhj p0   0 j 1 for q  A0. Let J0 (q) the set of active constraints at q such that:

J0 q  j hj q0   0

Theorem 4.1 Let (p0, v) be any Kuhn-Tucker point of the problem (P). Iff there exists some , such that f is -inf pseudoinvex at p0 with respect to A0 and for every j  J0 (p0), hj is -sup.quasiinvex at q  A, with respect A0, then p0 is an optimum solution of (P).

Proof. Starting from the conditions (4.1) and (4.2) one has:

inf ηp, p0  grad f p0   inf  v j ηp, p0 dhj p0  pA0 pA0 jJ 0  p0  Obviously,

inf  v j ηp, p0 grad h j p0    v j supηp, p0 grad h jp0  pA0 pA jJ 0  p0  jJ 0  p0 

suph p h p  0 We know that j j 0 whenever j J0(p0), it follows finally pA0 from:

 (v j ) supηp, p0 grad h jp0   0 pA jJ 0  p0  0

6 and hence, one has

inf  f p f p0  0  pA0

Corollary 1.

Let (p0, v) be a K-T point of the problem (P). Iff there exists some , such that f is -infinvex at p0 with respect A0, and for every j  J0 (p), hj is - supinvex at q  A with respect A0, then p0 is an optimum solution of (P).

Corollary 2. Assume that there exists some , such that (P) is -inf-supinvex on A. Then for every K-T point (p0, v), p0 is an optimum solution.

Remark We also assume that:

* j  J0 p0   supηp, p0 grad h j p0   0 (•) pA

Consequentely, one obtains:

Corollary 3.

Let (p0, v) be any point of the problem (P). Iff there exists some , such that the constraint function satisfy (•) and the objective function satisfies:

inf  p, p  grad f p   0  inf 0 0  f p f p0  0 (••) pA0 pA0

then p0 is an optimum solution.

5. Necessity of inf-sup invexity. We can call Kuhn-Tucker invex on A  M the problem (P) iff there exists a map :MxMTM such that:

 f p f q  ηp,q d fq  p,q, A0  ηp,qgrad hj q  0 whenever hj q  0   for j  1,2,...... ,m

7 Theorem 5.1 Every K-T point of problem (P) is a global minimizer iff (P) is K-T invex. We can exstend these results using the concepts introduced considering a Riemannian manifold (M,g) of dimension n.

One has the following:

Theorem 5.2 A K-T point (p0, v) is a global minimizer of the problem (P) iff there exists a map :MxMTM, such that (•) and (••) hold.

Proof. The sufficency follows from corollary 3 of theorem 4.1. For the necessity one observes that K-T invexity implies the conditions of the theorem.

It is also obvious the following:

Theorem 5.3 Every K-T point of problem (P) is a global minimizer iff there exists a map :MxMTM, such that f is -infpseudo invex (or -inf-invex) on

A0, and for every q  A0, hj is -sup quasiinvex (-sup-invex) at q, whenever j J0(q).

Acknowledgements. The author is grateful to Proff. F.Giannessi and M.I.Stoka for their attention, kindness and fruitful discussions.

References [1] Caristi G., Ferrara M., Stefanescu A. – New invexity – type conditions in constrained optimization. In Proceedings of the 6th International Symposium on Generalized Convexity/Monotonicity, Samos 1999 Ed.Springer-Verlag (to appear). [2] Caristi G., Ferrara M.,Generalized convexity for applications in decision theory. Quaderni dell’Istituto di Matematica, Facoltà di Economia, Università di Messina, 4; 1999. [3] Craven D. – Invex functions and constrained local minimaBull. Austral. Math. Soc. 24, 357 – 366; 1981. [4] do Carmo, M. P. – Riemannian geometry – Birkhausen, Boston 1992. [5] Hanson, M. A. – On sufficency of the Kuhn-Tucker conditions – Journal of Mathematical analysis and its applications, 80: 545-550. 1981.

8 [6] Miglierina, E. – Invex functions on differentiable manifolds, in Generalized convexity and optimization for economic and financial decision. Pitagora Editrice Bologna 1999. [7] Pini, R. – Convexity along curves and invexity – Optimization, 29: 301-309; 1994. [8] Rapcsák, T. – Smooth non linear optimization in Rn – Nonconvex optimization and its applications, 19. Kluwer 1997. [9] Rapcsák, T. – Minimum problems on differential manifolds. Optimization, 20 , 3-13; 1989. [10] Rapcsák, T. – Geodesic convexity in nonlinear optimization. JOTA, 69, 169-183; 1991. [11] Udriste C. – Convex functions and optimization methods on Riemannian manifolds – Mathematics and its applications, Kluwer 1994.

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