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Exact relaxations of non-convex variational problems
Authors:René Meziat  Diego Patiño
Affiliation:(1) Departamento de Matemáticas, Universidad de los Andes, Carrera 1 No. 18A-10, Bogotá, Colombia
Abstract:Here, we solve non-convex, variational problems given in the form
$$min_{u} I(u) = intlimits_{0}^{1} f(u'(x))dx quad {rm s.t.} quad u(0) = 0, u(1) = a, quad(1)$$
where u ∈ (W 1,∞(0, 1)) k and $$f : {mathbb{R}}^k rightarrow {mathbb{R}}$$ is a non-convex, coercive polynomial. To solve (1) we analyse the convex hull of the integrand at the point a, so that we can find vectors $$a^1,ldots,a^N in {mathbb{R}}^k$$ and positive values λ1, . . . , λ N satisfying the non-linear equation
$$(1, a, f_c(a)) = sumlimits_{i=1}^{N}lambda_i(1, a^i, f(a^i)). quad (2)$$
Thus, we can calculate minimizers of (1) by following a proposal of Dacorogna in (Direct Methods in the Calculus of Variations. Springer, Heidelberg, 1989). Indeed, we can solve (2) by using a semidefinite program based on multidimensional moments. We dedicate this work to our colleague Jesús Bermejo.
Keywords:Calculus of variations  Convex analysis  Semidefinite programming  Multidimensional moment problem
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