A Portfolio-Based Analysis Method for Competition Results

EasyChair Preprint 8627

Abstract

Competitions such as the MiniZinc Challenges or the SAT competitions have been very useful sources for comparing performance of different solving approaches and for advancing the state-of-the-arts of the fields. Traditional competition setting often focuses on producing a ranking between solvers based on their average performance across a wide range of benchmark problems and instances. While this is a sensible way to assess the relative performance of solvers, such ranking does not necessarily reflect the full potential of a solver, especially when we want to utilise a portfolio of solvers instead of a single one for solving a new problem. In this paper, I will describe a portfolio-based analysis method which can give complementary insights into the performance of participating solvers in a competition. The method is demonstrated on the results of the MiniZinc Challenges and new insights gained from the portfolio viewpoint are presented.

Keyphrases: Algorithm Portfolio, Constraint Programming, algorithm selection, competitions

@booklet{EasyChair:8627,
  author    = {Nguyen Dang},
  title     = {A Portfolio-Based Analysis Method for Competition Results},
  howpublished = {EasyChair Preprint 8627},
  year      = {EasyChair, 2022}}