A Truncated Newton Method for the Solution of Large-Scale Inequality Constrained Minimization Problems

Authors:
Francisco Facchinei;Giampaolo Liuzzi;Stefano Lucidi
Affiliations:
Dipartimento di Informatica e Sistemistica “A. Ruberti”, Università di Roma “La Sapienza”, Via Buonarroti 12, 00185 Roma, Italy. soler@dis.uniromal.it;Dipartimento di Informatica e Sistemistica “A. Ruberti”, Università di Roma “La Sapienza”, Via Buonarroti 12, 00185 Roma, Italy. liuzzi@dis.uniromal.itlucidi@dis.uniromal.it
Venue:
Computational Optimization and Applications
Year:
2003

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Abstract

A new active set Newton-type algorithm for the solution of inequality constrained minimization problems is proposed. The algorithm possesses the following favorable characteristics: (i) global convergence under mild assumptions; (ii) superlinear convergence of primal variables without strict complementarity; (iii) a Newton-type direction computed by means of a truncated conjugate gradient method. Preliminary computational results are reported to show viability of the approach in large scale problems having only a limited number of constraints.