Workshop on Large Scale Nonlinear and Semidefinite Programming:

Theme

Interior point methods (IPMs) have changed the landscape for both linear and nonlinear programming in the last fifteen years. In conjunction with breakthroughs in computer hardware, tremendously large problems are being solved. However, the success in linear programming dwarfs that for general Nonlinear Programming and, in particular, for Semidefinite Programming (SDP). The main aim of this workshop is to bring together researchers who work on large scale nonlinear programming, and, in particular, on Cone Programming such as Semidefinite and Second Order Cone Programming.

A rich source of large-scale nonlinear problems arises from relaxations of NP-hard combinatorial optimization problems. The success to solve Semidefinite Programs (of moderate size) has resulted in increased interest in higher order relaxations of combinatorial optimization problems, which give tighter relaxations but which are computationally challenging.

Recent progress towards large-scale nonlinear programming is mostly based on algorithmic ideas which avoid using standard interior-point technology. These include first order methods, algorithms which focus on the sparsity structure as well as nonsmooth methods applied to some Lagrangian dual. In addition, several parallel implementations of IPM's as well as column generation-type techniques have been introduced and show promise.

It is the purpose of this workshop to provide a forum to exchange ideas on large sparse programming between researchers in general Nonlinear Programming and those in Cone Programming.

The workshop aims in particular at researchers from the following communities

The workshop will follow in spirit previous workshops such as:




Back to Workshop home page , by Henry Wolkowicz