Proves that ℓ_p norm minimization yields p-independent Hausdorff convergence rate O(k^{2/(1-q)}) in convex vector optimization via Euclidean intermediary and norm equivalence.
L¨ ohne,Vector Optimization with Infimum and Supremum(Vector Optimization), en
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An adaptive metric framework for outer approximation in convex vector optimization extends convergence rates to inner-product norms, proves a dispersion theorem under strict convexity, and achieves 31-33% fewer iterations than fixed Euclidean norm on curved Pareto fronts.
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Convergence Rates for $\ell_p$ Norm Minimization in Convex Vector Optimization
Proves that ℓ_p norm minimization yields p-independent Hausdorff convergence rate O(k^{2/(1-q)}) in convex vector optimization via Euclidean intermediary and norm equivalence.
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Adaptive Metrics for Norm-Minimization-Based Outer Approximation in Convex Vector Optimization
An adaptive metric framework for outer approximation in convex vector optimization extends convergence rates to inner-product norms, proves a dispersion theorem under strict convexity, and achieves 31-33% fewer iterations than fixed Euclidean norm on curved Pareto fronts.