It is very hard to report about the Combinatorial Optimization Workshop in Aussois. It was like an “informal” IPCO with *Super Heroes researchers* in the audience, leaded by *Captain Egon*, who appears at work in the following photo-tweet:

Egon talks intersection cuts at #aussois. Still the man. pic.twitter.com/7KMcNyJYV0

— Jeff Linderoth (@JeffLinderoth) January 8, 2014

The Captain gave an inspiring talk by questioning the recursive paradigm of cutting planes algorithms. With a very basic example, Balas has shown how a non basic vertex (solution) can produce a much deeper cut than a cut generated by an optimal basis. Around this intuition, Balas has presented a very nice generalization of Intersection Cuts… a new paper enters my “PAPERS-TO-BE-READ” folder.

To stay on the subject of cutting planes, the talk by Marco Molinaro in the first day of the workshop was really nice. He raises the fundamental question on how important are **sparse cuts** versus **dense cuts**. The importance of sparse cuts comes from linear algebra: when solving the simplex it is better to have small determinants in the coefficient matrix of the Linear Programming relaxation in order to avoid numerical issues; sparse cuts implicitly help in keeping small the determinants (intuitively, you have more zeros in the matrix). Dense cuts play the opposite role, but they can be really important to improve the bound of the LP relaxation.
In his talk, Molinaro has shown and proofed, for three particular cases, when sparse cuts are enough, and when they are not.
Another paper goes on the “PAPERS-TO-BE-READ” folder.

In the same day of Molinaro, it was really inspiring the talk by Sebastian Pokutta, who really gave a completely new (for me) perspective on **Extended Formulations** by using Information Theory. Sebastian is the author of a blog, and I hope he will post about his talk.

Andrea Lodi has discussed about an Optimization problem that arises in Supervised Learning. For this problem, the COIN-OR solver Couenne, developed by Pietro Belotti, significantly outperforms CPLEX. The issues seem to come from on a number of basic big-M (indicator) constraints. To make a long story short, if you have to solve a hard problem, it does pay off to try different solvers, since there is not a “win-all” solver.

Do you have an original new idea for developing solvers? Do not be intimidated by CPLEX or Gurobi and go for it!

The presentation by Marco Senatore was brilliant and his work looks very interesting. I have particularly enjoyed the application in Public Transport that he has mentioned at the end of his talk.

I recommend to have a look at the presentation of Stephan Held about the **Reach-aware Steiner Tree Problem**. He has an interesting Steiner tree-like problem with a very important application in chip design. The presentation has impressive pictures of what optimal solutions look like in chip design.

At the end of talk, Stephan announced the 11th DIMACS challenge on Steiner Tree Problems.

Eduardo Uchoa gave another impressive presentation on recent progresses on the classical **Capacitated Vehicle Routing Problem** (CVRP). He has a very sophisticated branch-and-price-and-cut algorithm, which comes with a very efficient implementation of every possible idea developed for CVRP, plus new ideas on solving efficiently the pricing sub problems (my understanding, but I might be wrong, is that they have a very efficient dominance rule for solving a shortest path sub problem).
+1 item in the “PAPERS-TO-BE-READ” folder.

The last day of the workshop, I have enjoyed the two talks by Simge Kucukyavuz and Jim Luedtke on **Stochastic Integer Programming**: for me is a completely new topic, but the two presentations were really inspiring.

To conclude, Domenico Salvagnin has shown how far it is possible to go by carefully using MIP technologies such as **cutting planes**, **symmetry handling**, and **problem decomposition**. Unfortunately, it does happen too often that when someone (typically a non OR expert) has a difficult application problem, he writes down a more or less complicated Integer Programming model, tries a solver, sees it takes too much time, and gives up with exact methods. Domenico, by solving the largest unsolved instance for the 3-dimensional assignment problem, has shown that

there are potentially no limits for MIP solvers!

In this post, I have only mentioned a few talks, which somehow overlap with my research interests. However, every talk was really interesting. Fortunately, Francois Margot has strongly encouraged all of the speakers to upload their slides and/or papers, so you can find (almost) all of them on the program web page of the workshop. Visit the website and have a nice reading!

To conclude, let me steal another nice picture from twitter:

Goodbye #aussois2014 pic.twitter.com/ODupKKmGTZ

— Matteo Fischetti (@MFischetti) January 10, 2014