Abstract
AbstractThis article is concerned with the approximation of unbounded convex sets by polyhedra. While there is an abundance of literature investigating this task for compact sets, results on the unbounded case are scarce. We first point out the connections between existing results before introducing a new notion of polyhedral approximation called $$\left( \varepsilon , \delta \right) $$
ε
,
δ
-approximation that integrates the unbounded case in a meaningful way. Some basic results about $$\left( \varepsilon , \delta \right) $$
ε
,
δ
-approximations are proved for general convex sets. In the last section, an algorithm for the computation of $$\left( \varepsilon , \delta \right) $$
ε
,
δ
-approximations of spectrahedra is presented. Correctness and finiteness of the algorithm are proved.
Funder
Friedrich-Schiller-Universität Jena
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Management Science and Operations Research,Control and Optimization
Reference38 articles.
1. Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press, Cambridge (2004)
2. Bronshteĭn, E.M.: Approximation of convex sets by polyhedra. Sovrem. Mat. Fundam. Napravl. 22, 5–37 (2007)
3. Bronshteĭn, E.M., Ivanov, L.D.: The approximation of convex sets by polyhedra. Sibirsk. Mat. Ž. 16, 1110–1112 (1975). (1132)
4. Cheney, E.W., Goldstein, A.A.: Newton’s method for convex programming and Tchebycheff approximation. Numer. Math. 1, 254–268 (1959)
5. Ciripoi, D.: Approximation of Spectrahedral Shadows and Spectrahedral Calculus. Ph.D. thesis, Friedrich Schiller University Jena, (2019)
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献