25.7. MAXIMAL MONOTONE OPERATORS 871

lim infn→∞

tnH (g(y+ tn (z− y)) ,z)

≤ lim infn→∞

((1− tn)H (g(y+ tn (z− y)) ,y)+tnH (g(y+ tn (z− y)) ,z)

)≤ lim sup

n→∞

H (x,y+ tn (z− y))≤ H (x,y)

This shows that x̂ = g(y) because this holds for every x. Since tn → 0 was arbitrary, thisshows that in fact

limt→0+

g(y+ t (z− y)) = g(y)

Now with this preparation, here is the min-max theorem. A norm is called strictly convexif whenever x ̸= y,

∥∥ x+y2

∥∥< ∥x∥2 + ∥y∥2 .

Theorem 25.7.6 Let E,F be Banach spaces with E having a strictly convex norm. Alsosuppose that A ⊆ E,B ⊆ F are compact and convex sets and that H : A×B→ R is suchthat

x→ H (x,y) is convex

y→ H (x,y) is concave

Thus H is continuous in each variable in the case of finite dimensional spaces. Hereassume that x→H (x,y) is lower semicontinuous and y→H (x,y) is upper semicontinuous.Then

minx∈A

maxy∈B

H (x,y) = maxy∈B

minx∈A

H (x,y)

This condition is equivalent to the existence of (x0,y0) ∈ A×B such that

H (x0,y)≤ H (x0,y0)≤ H (x,y0) for all x,y (25.7.41)

Proof: One part of the main equality is obvious.

maxy∈B

H (x,y)≥ H (x,y)≥minx∈A

H (x,y)

and so for each x,maxy∈B

H (x,y)≥maxy∈B

minx∈A

H (x,y)

and sominx∈A

maxy∈B

H (x,y)≥maxy∈B

minx∈A

H (x,y) (25.7.42)

Next consider the other direction.Define Hε (x,y)≡ H (x,y)+ ε ∥x∥2 where ε > 0. Then Hε is strictly convex in the first

variable. This results from the observation that∥∥∥∥x+ y2

∥∥∥∥2

<

(∥x∥+∥y∥

2

)2

≤ 12

(∥x∥2 +∥y∥2

),

25.7. MAXIMAL MONOTONE OPERATORS 871lim inf tH (8 (y+tm (z—y)).z)ar (1—t)H (g(yt+t(z—y)),y)Stim ( 4th (g (y +tn(2—y)) »2) )< lim sup H (x,y +t (z—y)) < A (x,y)n—y0oThis shows that £ = g(y) because this holds for every x. Since t, — 0 was arbitrary, thisshows that in factjim svt+t—y)) =a) FlNow with this preparation, here is the min-max theorem. A norm is called strictly convexif whenever x F y, ||| < Ie + IpTheorem 25.7.6 Let E,F be Banach spaces with E having a strictly convex norm. Alsosuppose that A C E,B C F are compact and convex sets and that H : A x B > R is suchthatx — H (x,y) is convexy > H (x,y) is concaveThus H is continuous in each variable in the case of finite dimensional spaces. Hereassume that x —> H (x,y) is lower semicontinuous and y — H (x,y) is upper semicontinuous.Then‘amaxH (x.y) <maxmin ttTER eR TT Coo) = mag ray Oo)This condition is equivalent to the existence of (x0, yo) € A X B such thatH (x0,y) < H (x0, ¥0) SH (x,y) for all x,y (25.7.41)Proof: One part of the main equality is obvious.H >H > minmax H (x,y) 2 H (x,y) 2 min# (x,y)and so for each x,max H (x,y) > max mind (x,y)yeB yEB xcAand sominmax H > max minH 25.7.42mipmay H (x,y) 2 maymin H (2,9) (25.742)Next consider the other direction.Define He (x,y) =H (x,y) +€ ||x||? where € > 0. Then H, is strictly convex in the firstvariable. This results from the observation that2 2x+y Ill] + Ill 1 ( 2 ”)—_ < a <- ;| < (et) <5 (rt