Multivalued Maps And Differential Inclusions: Elements Of Theory And Applications. Valeri Obukhovskii

Multivalued Maps And Differential Inclusions: Elements Of Theory And Applications - Valeri Obukhovskii


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× F : XP(
× Y) is l.s.c. by Theorem 1.3.15. The map φ :
× YY,

figure

      is continuous. Then the multimap

figure

      is l.s.c. by Theorem 1.3.11.

figure

      The following statement can be proved by a similar application of Theorems 1.3.17 and 1.3.11.

      Theorem 1.3.24. If a multimap F : XK(Y) is upper semicontinuous and a function f : X

is continuous then the product f · F : XK(Y) is upper semicontinuous.

      Definition 1.3.25. Let Y be a linear topological space, F : XP(Y) a multimap. The multimap figure,

figure

      is called the convex closure of the multimap F.

      Theorem 1.3.26. Let Y be a Banach space. If a multimap F : XK(Y) is u.s.c. (l.s.c.) then the convex closure figure is u.s.c. (l.s.c.)

      Proof. First, we note that the multimap figure has compact values by Mazur’s theorem (see Chapter 0). Let the multimap F be u.s.c. Consider a point xX and let ε > 0. Then for every ε1, 0 < ε1 < ε there exists a neighborhood U(x) of x such that F(x′) ⊂ Fε1(x) for all x′ ∈ U(x) (Theorem 1.2.39). But Fε1(x) ⊂ Uε1(figure(x)), hence coF(x′) ⊂ Uε1(figure(x)) since the set Uε1(figure(x)) is convex. Then

figure

      for each x′ ∈ U(x) proving, by Theorem 1.2.39, the upper semicontinuity of the multimap figure.

      The lower semicontinuity of the multimap figure can be proved in a similar way by applying Theorem 1.2.40.

figure

      Remark 1.3.27. The property of closedness of a multimap can be lost under the operation of convex closure, as the following example shows.

      Example 1.3.28. The multimap F :

C(
),

figure

      is closed, but its convex closure

Cv(
),

figure

      is not closed.

      Theorem of maximum, which is called sometimes the principle of continuity of optimal solutions plays an important role in the applications of multivalued maps in the theory of games and mathematical economics (see Chapter 4).

a continuous function. Then the function φ : X
,

figure

      is continuous and the multimap F : XP(Y)

figure

      has compact values and is upper semicontinuous.

      Remark 1.3.30. The function φ and the multimap F are often called marginal.

      The proof of Theorem 1.3.29 will be based on the following two assertions.

lower semicontinuous (in the single-valued sense). Then the function figure,

figure

      is lower semicontinuous.

      Proof. Choose a point xX and assume at first that φ(x) < +∞. Fix ε > 0; then there exists a point y ∈ Φ(x) such that f(x, y) ≥ φ(x) − ε. By the lower semicontinuity of f there exist neighborhoods U0(x) of x and V(Y) of y such that, for each x′ ∈ U0(x), y′ ∈ V(Y) we have

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