Linearized Alternating Direction Method with Gaussian Back Substitution for Separable Convex Programming

Recently, we have proposed to combine the alternating direction method (ADM) with a Gaussian back substitution procedure for solving the convex minimization model with linear constraints and a general separable objective function, i.e., the objective function is the sum of many functions without coupled variables. In this paper, we further study this topic and show … Read more

Designing AC Power Grids using Integer Linear Programming

Recent developments have drawn focus towards the efficient calculation of flows in AC power grids, which are difficult to solve systems of nonlinear equations. The common linearization approach leads to the well known and often used DC formulation, which has some major drawbacks. To overcome these drawbacks we revisit an alternative linearization of the AC … Read more

Compact linearization for bilinear mixed-integer problems

We present a compact linearization for a broad class of bilinear 0-1 mixed-integer problems subject to assignment constraints. We apply the linearization to three classes of problems: quadratic assignment, multiprocessor scheduling with communication delays, and graph partitioning, and show that it yields faster solution times. CitationDEI, Politecnico di Milano, Working paper, April 2005.ArticleDownload View PDF