January 12-13, 2007
Demonstration of softwareJanuary 13, 2007 10:20 am - 11:10 am
Generating functions for integer optimization (part I)January 13, 2007 11:20 am - 12:10 pm
Barvinok's algorithm for counting
- Original approach
- Homogenized algorithm
- Integer linear programming in fixed dimension
Generating functions for integer optimization (part I)-continuedJanuary 13, 2007 1:30 pm - 2:20 pm
Generating functions for integer optimization (part II)January 13, 2007 3:00 pm - 3:50 pm
Barvinok's algorithm for counting
- Generating functions and non-linear integer optimization
- Other Rational Functions (Vergne, Lasserre,Nesterov)
Demo and introduction to LattEJanuary 13, 2007 4:00 pm - 5:00 pm
Optimization over polynomials with moment matrices and sums of squares
Remarks: (Due to visa problems Monique Laurent was not be able to attend the tutorial.
Jean Bernard Lasserre substituted for Monique Laurent.)
January 12, 2007 2:40 pm - 3:30 pm
We consider the problem (P) of minimizing a polynomial function
over a semialgebraic set defined by polynomial inequalities and equations.
This is a hard problem, which includes well known NP-hard instances such as
0/1 linear programming, the partition problem for integer sequences, or
matrix copositivity.
While it is hard to test whether a polynomial is nonnegative, one can test
efficiently whether it can be written as a sum of squares of polynomials
using semidefinite programming. Based on this paradigm, one can formulate
tractable semidefinite programming relaxations for (P) by replacing the
hard `nonnegativity' condition by the tractable 'sum of squares'
condition. The corresponding dual semidefinite programs involve positive
semidefinite moment matrices, which reflects the classical duality theory
between positive polynomials and moment sequences.
The objective of this tutorial is to present in detail the main properties
of these semidefinite programming relaxations: asymptotic/finite
convergence, optimality certificate, and extraction of global optimum
solutions for (P), and to review the underlying mathematical tools:
representation theorems for positive polynomials from real algebraic
geometry, results about the truncated moment problem, and the algebraic
eigenvalue method for solving systems of polynomial equations. These
characteristic features are implemented in GloptiPoly, a solver for
polynomial optimization developped by Henrion and Lasserre, and will be
demonstrated on examples. Additional topics that may be covered if time
allows include: various algebraic approaches to unconstrained polynomial
minimization, link to combinatorial methods for 0/1 polynomial
optimization, techniques for exploiting symmetry, sparsity, etc.
Optimization over polynomials with moment matrices and sums of squares(continued)January 13, 2007 9:00 am - 9:50 am
Gröebner basis methods in integer programming (Lecture Part I)
January 12, 2007 8:40 am - 9:30 am
Part I
- Linear programming and triangulations.
- The integer program and toric ideals.
- Test sets, Gröebner bases and initial ideals.
Hands on exercises assisted by Tristram Bogart (Tutorial Part I)January 12, 2007 10:00 am - 10:50 am
Gröebner basis methods in integer programming (Lecture Part II)January 12, 2007 11:00 am - 11:50 am
Part II
- The Gröebner fan.
- Total dual integrality.
- Group relaxations.
Hands on exercises assisted by Tristram Bogart (Tutorial Part II)January 12, 2007 1:30 pm - 2:20 pm