One of the most effective methods for nonlinearly constrained optimization generates steps
by solving quadratic subproblems. This sequential quadratic programming (SQP) approach …

This is a book for people interested in solving optimization problems. Because of the wide
(and growing) use of optimization in science, engineering, economics, and industry, it is …

A practical monthly optimization model, called SISOPT, is developed for the management
and operations of the Brazilian hydropower system. The system, one of the largest in the …

The object-oriented software package OOQP for solving convex quadratic programming
problems (QP) is described. The primal-dual interior point algorithms supplied by OOQP are …

A new class of preconditioners for the iterative solution of the linear systems arising from
interior point methods is proposed. For many of these methods, the linear systems are …

The relative solvent accessibility (RSA) of an amino acid residue in a protein structure is a
real number that represents the solvent exposed surface area of this residue in relative …

We implement several warm-start strategies in interior-point methods for linear programming
(LP). We study the situation in which both the original LP instance and the perturbed one …

In this paper we discuss the polynomiality of a feasible version of Mehrotra's predictor-
corrector algorithm whose variants have been widely used in several interior point method …

We devise a hybrid approach for solving linear systems arising from interior point methods
applied to linear programming problems. These systems are solved by preconditioned …

Interior-point methods feature prominently among numerical methods for inequality-
constrained optimization problems, and involve the need to solve a sequence of linear …