Ekeland's variational principle

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In mathematical analysis, Ekeland's variational principle, discovered by Ivar Ekeland,[1][2][3] is a theorem that asserts that there exist nearly optimal solutions to some optimization problems.

Ekeland's principle can be used when the lower level set of a minimization problems is not compact, so that the Bolzano–Weierstrass theorem cannot be applied. The principle relies on the completeness of the metric space.[4]

The principle has been shown to be equivalent to completeness of metric spaces.[5] In proof theory, it is equivalent to [[Reverse_mathematics#Π11_comprehension_Π11-CA0|ΠTemplate:SuCA0 over RCA0]], i.e. relatively strong.

It also leads to a quick proof of the Caristi fixed point theorem.[4][6]

History

Ekeland was associated with the Paris Dauphine University when he proposed this theorem.[1]

Ekeland's variational principle

Preliminary definitions

A function f:X{,+} valued in the extended real numbers {,+}=[,+] is said to be Template:Em if inff(X)=infxXf(x)> and it is called Template:Em if it has a non-empty Template:Em, which by definition is the set domf=def{xX:f(x)+}, and it is never equal to . In other words, a map is Template:Em if is valued in {+} and not identically +. The map f is proper and bounded below if and only if <inff(X)+, or equivalently, if and only if inff(X).

A function f:X[,+] is Template:Em at a given x0X if for every real y<f(x0) there exists a neighborhood U of x0 such that f(u)>y for all uU. A function is called Template:Em if it is lower semicontinuous at every point of X, which happens if and only if {xX:f(x)>y} is an open set for every y, or equivalently, if and only if all of its lower level sets {xX:f(x)y} are closed.

Statement of the theorem

Template:Math theorem

Template:Math proof

For example, if f and (X,d) are as in the theorem's statement and if x0X happens to be a global minimum point of f, then the vector v from the theorem's conclusion is v:=x0.

Corollaries

Template:Math theorem The principle could be thought of as follows: For any point x0 which nearly realizes the infimum, there exists another point v, which is at least as good as x0, it is close to x0 and the perturbed function, f(x)+ελd(v,x), has unique minimum at v. A good compromise is to take λ:=ε in the preceding result.Template:Sfn

See also

References

Template:Reflist Template:Reflist

Bibliography

Template:Convex analysis and variational analysis Template:Functional analysis