Kudos for Livermore

The GO Competition would like to congratulate Cosmin G. Petra and his team,  Ignacio Andres Aravena Solis, Omar DeGuchy, and Juraj Kardos from Lawrence Livermore National Laboratory (LLNL), for achieving a very strong first place in Challenge 1. The team accounted for over half of the best scenario scores: 816 first places out of a possible 1408 or 58%! The team with the second most firsts had only 282 (20%).

Even when not getting the best objective value, the LLNL team was almost always very close. For Division 1, the difference between the LLNL score and the best score averaged only 0.15% larger, with a standard deviation of 0.48% and a worst case of 5.51%. For Division 2 the numbers are 0.21% (average), 0.74% (std. dev.) and 10.15% (worst case). 

For the 17 synthetic datasets, LLNL had the lowest network geometric mean score for 13 networks in Divisions  1 and 3 and 10 for Divisions 2 and 4. For the 3 industry datasets, their network geometric mean score placed first twice and second once in Divisions 1 and 3 and placed first once and second twice in Divisions 2 and 4.


GOLLNLP Team's core activities are performed at LLNL, while personnel at the University of California, Merced develop techniques for contingency screening.

  • Cosmin G. Petra (PI, petra1@llnl.gov) is a computational mathematician/computer scientist in the Center for Applied Scientific Computing (CASC) at LLNL. Cosmin's work focuses on algorithms and HPC solvers for the mathematical optimization of extreme-scale engineering systems with emphasis on complex energy systems.
  • Ignacio Aravena Solis (aravenasolis1@llnl.gov) is an operations research engineer at the Computational Engineering Division of LLNL. His work focuses on developing optimization models (mixed-integer, non-linear, stochastic) and scalable/parallel algorithms to improve power systems' resilience.
  • Omar DeGuchy, PhD student, University of California, Merced.
  • Juraj Kardos, PhD student, Università della Swizzera italiana (while at LLNL).

The team receives support and guidance from professors Roummel Marcia (University of California, Merced), Olaf Schenk (Università della Swizzera italiana), and Joey Huchette (Rice University).