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.
A Norm Minimization-Based Convex Vector Optimization Algorithm,
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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.