A Convergence Analysis for a Convex Version
of Dikin's Algorithm
Jie Sun
A version of Dikin's algorithm is studied in which a
quadratic merit function is minimized at each iteration
together with an affine transformation of the variables.
It is shown that the sequence generated by the algorithm
globally converges to a point at a local linear rate.
The result is of theoretical nature in the sense that
in order to ensure that the limit point is an epsilon-
optimal solution, one may have to restrict the
steplength to the order of O(epsilon). The analysis
does not depend on the non-degeneracy assumptions.
To appear in Annals of Operations Research.
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