@inproceedings{13250,
  author       = {{Ansótegui, Carlos and Heymann, Britta and Pon, Josep and Sellmann, Meinolf and Tierney, Kevin}},
  booktitle    = {{Learning and Intelligent Optimization}},
  isbn         = {{978-3-030-05347-5}},
  pages        = {{309--325}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Hyper-Reactive Tabu Search for MaxSAT}}},
  doi          = {{10.1007/978-3-030-05348-2_27}},
  year         = {{2019}},
}

@inproceedings{46337,
  abstract     = {{A multiobjective perspective onto common performance measures such as the PAR10 score or the expected runtime of single-objective stochastic solvers is presented by directly investigating the tradeoff between the fraction of failed runs and the average runtime. Multi-objective indicators operating in the bi-objective space allow for an overall performance comparison on a set of instances paving the way for instance-based automated algorithm selection techniques.}},
  author       = {{Bossek, Jakob and Trautmann, Heike}},
  booktitle    = {{Learning and Intelligent Optimization}},
  editor       = {{Battiti, R and Brunato, M and Kotsireas, I and Pardalos, P}},
  isbn         = {{978-3-030-05347-5}},
  pages        = {{215–219}},
  publisher    = {{Springer}},
  title        = {{{Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time}}},
  volume       = {{11353}},
  year         = {{2019}},
}