@inproceedings{48858,
  abstract     = {{The $$\textbackslash mathcal NP$$-hard multi-criteria shortest path problem (mcSPP) is of utmost practical relevance, e.~g., in navigation system design and logistics. We address the problem of approximating the Pareto-front of the mcSPP with sum objectives. We do so by proposing a new mutation operator for multi-objective evolutionary algorithms that solves single-objective versions of the shortest path problem on subgraphs. A rigorous empirical benchmark on a diverse set of problem instances shows the effectiveness of the approach in comparison to a well-known mutation operator in terms of convergence speed and approximation quality. In addition, we glance at the neighbourhood structure and similarity of obtained Pareto-optimal solutions and derive promising directions for future work.}},
  author       = {{Bossek, Jakob and Grimme, Christian}},
  booktitle    = {{Learning and Intelligent Optimization}},
  editor       = {{Battiti, Roberto and Brunato, Mauro and Kotsireas, Ilias and Pardalos, Panos M.}},
  isbn         = {{978-3-030-05348-2}},
  pages        = {{184–198}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Solving Scalarized Subproblems within Evolutionary Algorithms for Multi-criteria Shortest Path Problems}}},
  doi          = {{10.1007/978-3-030-05348-2_17}},
  year         = {{2019}},
}

@inproceedings{48875,
  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, Roberto and Brunato, Mauro and Kotsireas, Ilias and Pardalos, Panos M.}},
  isbn         = {{978-3-030-05348-2}},
  keywords     = {{Algorithm selection, Performance measurement}},
  pages        = {{215–219}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time}}},
  doi          = {{10.1007/978-3-030-05348-2_19}},
  year         = {{2019}},
}