期刊
MATHEMATICAL PROGRAMMING
卷 100, 期 2, 页码 379-410出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s10107-003-0477-4
关键词
interior-point methods; primal-dual; filter; global convergence
In this paper, the filter technique of Fletcher and Leyffer (1997) is used to globalize the primal-dual interior-point algorithm for nonlinear programming, avoiding the use of merit functions and the updating of penalty parameters. The new algorithm decomposes the primal-dual step obtained from the perturbed first-order necessary conditions into a normal and a tangential step, whose sizes are controlled by a trust-region type parameter. Each entry in the filter is a pair of coordinates: one resulting from feasibility and centrality, and associated with the normal step; the other resulting from optimality (complementarity and duality), and related with the tangential step. Global convergence to first-order critical points is proved for the new primal-dual interior-point filter algorithm.
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