Primal-dual nonlinear rescaling method with dynamic scaling parameter update. (English) Zbl 1134.90494

Summary: In this paper we developed a general primal-dual nonlinear rescaling method with dynamic scaling parameter update (PDNRD) for convex optimization. We proved the global convergence, established 1.5-Q-superlinear rate of convergence under the standard second order optimality conditions. The PDNRD was numerically implemented and tested on a number of nonlinear problems from COPS and CUTE sets. We present numerical results, which strongly corroborate the theory.


90C30 Nonlinear programming
90C46 Optimality conditions and duality in mathematical programming


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