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On the Behavior of the Homogeneous Self-Dual Model for Conic Convex Optimization

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dc.creator Freund, Robert M.
dc.date 2004-10-15T14:45:20Z
dc.date 2004-10-15T14:45:20Z
dc.date 2004-10
dc.date.accessioned 2013-10-09T02:46:45Z
dc.date.available 2013-10-09T02:46:45Z
dc.date.issued 2013-10-09
dc.identifier http://hdl.handle.net/1721.1/6752
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description There is a natural norm associated with a starting point of the homogeneous self-dual (HSD) embedding model for conic convex optimization. In this norm two measures of the HSD model’s behavior are precisely controlled independent of the problem instance: (i) the sizes of ε-optimal solutions, and (ii) the maximum distance of ε-optimal solutions to the boundary of the cone of the HSD variables. This norm is also useful in developing a stopping-rule theory for HSD-based interior-point methods such as SeDuMi. Under mild assumptions, we show that a standard stopping rule implicitly involves the sum of the sizes of the ε-optimal primal and dual solutions, as well as the size of the initial primal and dual infeasibility residuals. This theory suggests possible criteria for developing starting points for the homogeneous self-dual model that might improve the resulting solution time in practice
dc.format 194788 bytes
dc.format application/pdf
dc.language en_US
dc.publisher Massachusetts Institute of Technology, Operations Research Center
dc.relation Operations Research Center Working Paper Series;OR 372-04
dc.title On the Behavior of the Homogeneous Self-Dual Model for Conic Convex Optimization
dc.type Working Paper


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