Optimality conditions, approximate stationarity, and applications – a story beyond lipschitzness
ESAIM: Control, Optimisation and Calculus of Variations, Tome 28 (2022), article no. 42

Approximate necessary optimality conditions in terms of Frechet subgradients and normals for a rather general optimization problem with a potentially non-Lipschitzian objective function are established with the aid of Ekeland’s variational principle, the fuzzy Frechet subdifferential sum rule, and a novel notion of lower semicontinuity relative to a set-valued mapping or set. Feasible points satisfying these optimality conditions are referred to as approximately stationary. As applications, we derive a new general version of the extremal principle. Furthermore, we study approximate stationarity conditions for an optimization problem with a composite objective function and geometric constraints, a qualification condition guaranteeing that approximately stationary points of such a problem are M-stationary, and a multiplier-penalty-method which naturally computes approximately stationary points of the underlying problem. Finally, necessary optimality conditions for an optimal control problem with a non-Lipschitzian sparsity-promoting term in the objective function are established.

DOI : 10.1051/cocv/2022024
Classification : 49J52, 49J53, 49K27, 90C30, 90C48
Keywords: Approximate stationarity, generalized separation, non-Lipschitzian programming, optimality conditions, Sparse control
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     title = {Optimality conditions, approximate stationarity, and applications {\textendash} a story beyond lipschitzness},
     journal = {ESAIM: Control, Optimisation and Calculus of Variations},
     year = {2022},
     publisher = {EDP-Sciences},
     volume = {28},
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     mrnumber = {4445585},
     zbl = {1494.49005},
     language = {en},
     url = {https://www.numdam.org/articles/10.1051/cocv/2022024/}
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Kruger, Alexander Y.; Mehlitz, Patrick. Optimality conditions, approximate stationarity, and applications – a story beyond lipschitzness. ESAIM: Control, Optimisation and Calculus of Variations, Tome 28 (2022), article no. 42. doi: 10.1051/cocv/2022024

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