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Generalized Polyhedral DC Optimization Problems

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abstract

The problem of minimizing the difference of two lower semicontinuous, proper, convex functions (a DC function) on a nonempty closed convex set in a locally convex Hausdorff topological vector space is studied in this paper. The focus is made on the situations where either the second component of the objective function is a generalized polyhedral convex function or the first component of the objective function is a generalized polyhedral convex function and the constraint set is generalized polyhedral convex. Various results on optimality conditions, the local solution set, the global solution set, and solution algorithms via duality are obtained. Useful illustrative examples are considered.

fields

math.OC 1

years

2025 1

verdicts

CONDITIONAL 1

representative citing papers

Scalable DC Optimization via Adaptive Frank-Wolfe Algorithms

math.OC · 2025-07-23 · conditional · novelty 5.0

DCA-BPCG-WS-ES, a Frank-Wolfe variant with warm-starting and adaptive early stopping, solves constrained DC problems with orders of magnitude fewer linear oracle calls than prior FW-based DCA variants.

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  • Scalable DC Optimization via Adaptive Frank-Wolfe Algorithms math.OC · 2025-07-23 · conditional · none · ref 38 · internal anchor

    DCA-BPCG-WS-ES, a Frank-Wolfe variant with warm-starting and adaptive early stopping, solves constrained DC problems with orders of magnitude fewer linear oracle calls than prior FW-based DCA variants.