Interior Point Methods for Linear Optimization is a comprehensive, thorough textbook on
interior point methods (IPMs). The era of IPMs was initiated by N. Karmarkar's 1984 paper …

When two protective apparatus installed in series have characteristics, which provide a
specified operating sequence, they are said to be coordinated or selective. The coordination …

Over the past half-century, Optimal Power Flow (OPF) has become one of the most important
and widely studied nonlinear optimization problems. In general, OPF seeks to optimize the …

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

Linear programming has been the dominant paradigm in optimization since Dantzig's
development of the simplex method in the 1940s. In 1984, the publication of a paper by …

The purpose of this work is to present the MOSEK optimizer intended for solution of large-
scale sparse linear programs. The optimizer is based on the homogeneous interior-point …

The modern era of interior-point methods dates to 1984, when Karmarkar proposed his
algorithm for linear programming. In the years since then, algorithms and software for linear …

Interior point methods for optimization have been around for more than 25 years now. Their
presence has shaken up the field of optimization. Interior point methods for linear and …

An n-dimensional vector x is an array of n scalars x1, x2,..., xn. The notation x represents the
array when its elements are arranged in a column, while the notation xT represents the array …

Based on the work of the Nesterov and Todd on self-scaled cones an implementation of a
primal-dual interior-point method for solving large-scale sparse conic quadratic optimization …