Abstract
Consider the minimization problem
in which \(f:\left[ {0,1} \right]x {\mathbb{R}}^n \to {\mathbb{R}} \cup \left\{ { + \infty } \right\}\)is a normal integrand. Define the convex function \(G:\mathbb{R}^n \to \mathbb{R} \cup \left\{ { + \infty } \right\}\) by \(G\left( p \right)\dot = \int_0^1 {f^* \left( {t,p} \right)dt.} \) It is known that, if the essential domain H of G is open, then problem (P) has a minimizer for any pair of endpoints (u 0, u 1). In this paper, the same result is proved under the condition that, for every point p in H, the subgradient set ∂G(p) is either bounded or empty (when H is open, this condition holds automatically).
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Crasta, G. Existence of Minimizers for Nonconvex Variational Problems with Slow Growth. Journal of Optimization Theory and Applications 99, 381–401 (1998). https://doi.org/10.1023/A:1021774227314
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DOI: https://doi.org/10.1023/A:1021774227314