Abstract
This paper addresses the numerical computation of critical angles between two convex cones in Euclidean spaces. We present a novel approach to computing these critical angles by reducing the problem to finding stationary points of a fractional programming problem. To efficiently compute these stationary points, we introduce a partial linearization-like algorithm that offers significant computational advantages. Solving a sequence of strictly convex subproblems with straightforward solutions in several settings gives the proposed algorithm high computational efficiency while delivering reliable results: our theoretical analysis demonstrates that the proposed algorithm asymptotically computes critical angles. Numerical experiments validate the efficiency of our approach, even when dealing with problems of relatively large dimensions: only a few seconds are necessary to compute critical angles between different types of cones in spaces of dimension 1000.
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Acknowledgements
The authors acknowledge the support of MATH-AMSUD 23-MATH-09 MORA-DataS project. The research of V. Sessa and W. de Oliveira benefited from the support of the Gaspard-Monge Program for Optimization and Operations Research (PGMO) project “SOLEM - Scalable Optimization for Learning and Energy Management”. D. Sossa is partially supported by FONDECYT (Chile) through grant 11220268.
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Communicated by Radu Ioan Bot.
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de Oliveira, W., Sessa, V. & Sossa, D. Computing Critical Angles Between Two Convex Cones. J Optim Theory Appl 201, 866–898 (2024). https://doi.org/10.1007/s10957-024-02424-3
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DOI: https://doi.org/10.1007/s10957-024-02424-3