Please use this identifier to cite or link to this item: https://doi.org/10.1007/s10589-005-4565-7
DC FieldValue
dc.titleEfficient algorithms for the smallest enclosing ball problem
dc.contributor.authorZhou, G.
dc.contributor.authorTohemail, K.-C.
dc.contributor.authorSun, J.
dc.date.accessioned2014-12-02T06:52:43Z
dc.date.available2014-12-02T06:52:43Z
dc.date.issued2005-02
dc.identifier.citationZhou, G., Tohemail, K.-C., Sun, J. (2005-02). Efficient algorithms for the smallest enclosing ball problem. Computational Optimization and Applications 30 (2) : 147-160. ScholarBank@NUS Repository. https://doi.org/10.1007/s10589-005-4565-7
dc.identifier.issn09266003
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/114324
dc.description.abstractConsider the problem of computing the smallest enclosing ball of a set of m balls in ℛ n. Existing algorithms are known to be inefficient when n > 30. In this paper we develop two algorithms that are particularly suitable for problems where n is large. The first algorithm is based on log-exponential aggregation of the maximum function and reduces the problem into an unconstrained convex program. The second algorithm is based on a second-order cone programming formulation, with special structures taken into consideration. Our computational experiments show that both methods are efficient for large problems, with the product mn on the order of 10 7. Using the first algorithm, we are able to solve problems with n = 100 and m = 512,000 in about 1 hour.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/s10589-005-4565-7
dc.sourceScopus
dc.subjectComputational geometry
dc.subjectSecond order cone programming
dc.subjectSmoothing approximation
dc.typeArticle
dc.contributor.departmentDECISION SCIENCES
dc.contributor.departmentMATHEMATICS
dc.description.doi10.1007/s10589-005-4565-7
dc.description.sourcetitleComputational Optimization and Applications
dc.description.volume30
dc.description.issue2
dc.description.page147-160
dc.description.codenCPPPE
dc.identifier.isiut000227639100003
Appears in Collections:Staff Publications

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