A Simple, Quadratically Convergent Interior Point Algorithm for Linear Programming and Convex Quadratic Programming
نویسنده
چکیده
An algorithm for linear programming (LP) and convex quadratic programming (CQP) is proposed, based on an interior point iteration introduced more than ten years ago by J. Herskovits for the solution of nonlinear programming problems. Herskovits' iteration can be simpliied signiicantly in the LP/CQP case, and quadratic convergence from any initial point can be achieved. Interestingly the linear system solved at each iteration is identical to that of the primal-dual aane scaling scheme recently considered by Monteiro et al. independently of Herskovits' work. The proposed algorithm, however, uses an iteratively selected step length, diierent for each component of the dual variable.
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