Abstract
Consider a nonempty finite set of nonzero vectors \(S \subset \mathbb {R}^n\). The angle between a nonzero vector \(v \in \mathbb {R}^n\) and S is the smallest angle between v and an element of S. The cosine measure of S is the cosine of the largest possible angle between a nonzero vector \(v \in \mathbb {R}^n\) and S. The cosine measure provides a way of quantifying the positive spanning property of a set of vectors, which is important in the area of derivative-free optimization. This paper proves some of the properties of the cosine measure for a nonempty finite set of nonzero vectors. It also introduces the notion of the uniform angle subspace and some cones associated with it and proves some of their properties. Moreover, this paper proves some results that characterize the Karush–Kuhn–Tucker (KKT) points for the optimization problem of calculating the cosine measure. These characterizations of the KKT points involve the uniform angle subspace and its associated cones. Finally, this paper provides an outline for calculating the cosine measure of any nonempty finite set of nonzero vectors.
Similar content being viewed by others
References
Alberto, P., Nogueira, F., Rocha, H., Vicente, L.N.: Pattern search methods for user-provided points: application to molecular geometry problems. SIAM J. Optim. 14(4), 1216–1236 (2004)
Audet, C.: A short proof on the cardinality of maximal positive bases. Optim. Lett. 5(1), 191–194 (2011)
Audet, C., Hare, W.: Derivative-Free and Blackbox Optimization. Springer International Publishing AG, Cham (2017)
Audet, C., Ianni, A., Digabel, S.L., Tribes, C.: Reducing the number of function evaluations in mesh adaptive direct search algorithms. SIAM J. Optim. 24(2), 621–642 (2014)
Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press, Cambridge (2004)
Conn, A.R., Scheinberg, K., Vicente, L.N.: Introduction to Derivative-Free Optimization. MPS/SIAM Series on Optimization. Society for Industrial and Applied Mathematics (SIAM), Philadelphia (2009)
Davis, C.: Theory of positive linear dependence. Am. J. Math. 76(4), 733–746 (1954)
Dodangeh, M., Vicente, L.N., Zhang, Z.: On the optimal order of worst case complexity of direct search. Optim. Lett. 10, 699–708 (2016)
Hare, W., Jarry-Bolduc, G.: A deterministic algorithm to compute the cosine measure of a finite positive spanning set. Optim. Lett. 14, 1305–1316 (2020). https://doi.org/10.1007/s11590-020-01587-y
Horn, R.A., Johnson, C.R.: Matrix Analysis, 2nd edn. Cambridge University Press, Cambridge (2013)
Kolda, T.G., Lewis, R.M., Torczon, V.: Optimization by direct search: new perspectives on some classical and modern methods. SIAM Rev. 45(3), 385–482 (2003)
Larson, J., Menickelly, M., Wild, S.M.: Derivative-free optimization methods. Acta Numerica 28, 287–404 (2019)
Nævdal, G.: Positive bases with maximal cosine measure. Optim. Lett. 13(6), 1381–1388 (2019)
Nocedal, J., Wright, S.J.: Numer. Optim., 2nd edn. Springer, New York (2006)
Regis, R.G.: On the properties of positive spanning sets and positive bases. Optim. Eng. 17(1), 229–262 (2016)
Rockafellar, R.T.: Convex Analysis. Princeton University Press, Princeton (1970)
Acknowledgements
The author wishes to thank the reviewers for their thorough review of this paper and their excellent comments. Also, special thanks to Geir Nævdal for suggesting the result on the maximal cosine measure of a set in \(\mathbb {R}^n\) with at most n elements.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Regis, R.G. On the properties of the cosine measure and the uniform angle subspace. Comput Optim Appl 78, 915–952 (2021). https://doi.org/10.1007/s10589-020-00253-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10589-020-00253-4