Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time Bossek, Jakob Trautmann, Heike Battiti, Roberto Brunato, Mauro Kotsireas, Ilias Pardalos, Panos M. Algorithm selection Performance measurement 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. Springer International Publishing 2019 info:eu-repo/semantics/conferenceObject doc-type:conferenceObject text http://purl.org/coar/resource_type/c_5794 https://ris.uni-paderborn.de/record/48875 Bossek J, Trautmann H. Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time. In: Battiti R, Brunato M, Kotsireas I, Pardalos PM, eds. <i>Learning and Intelligent Optimization</i>. Lecture Notes in Computer Science. Springer International Publishing; 2019:215–219. doi:<a href="https://doi.org/10.1007/978-3-030-05348-2_19">10.1007/978-3-030-05348-2_19</a> eng info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-030-05348-2_19 info:eu-repo/semantics/altIdentifier/isbn/978-3-030-05348-2 info:eu-repo/semantics/closedAccess