@article{48848,
  abstract     = {{We build upon a recently proposed multi-objective view onto performance measurement of single-objective stochastic solvers. The trade-off between the fraction of failed runs and the mean runtime of successful runs \textendash both to be minimized \textendash is directly analyzed based on a study on algorithm selection of inexact state-of-the-art solvers for the famous Traveling Salesperson Problem (TSP). Moreover, we adopt the hypervolume indicator (HV) commonly used in multi-objective optimization for simultaneously assessing both conflicting objectives and investigate relations to commonly used performance indicators, both theoretically and empirically. Next to Penalized Average Runtime (PAR) and Penalized Quantile Runtime (PQR), the HV measure is used as a core concept within the construction of per-instance algorithm selection models offering interesting insights into complementary behavior of inexact TSP solvers. \textbullet The multi-objective perspective is naturally generalizable to multiple objectives. \textbullet Proof of relationship between HV and the PAR in the considered bi-objective space. \textbullet New insights into complementary behavior of stochastic optimization algorithms.}},
  author       = {{Bossek, Jakob and Kerschke, Pascal and Trautmann, Heike}},
  issn         = {{1568-4946}},
  journal      = {{Applied Soft Computing}},
  keywords     = {{Algorithm selection, Combinatorial optimization, Multi-objective optimization, Performance measurement, Traveling Salesperson Problem}},
  number       = {{C}},
  title        = {{{A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms}}},
  doi          = {{10.1016/j.asoc.2019.105901}},
  volume       = {{88}},
  year         = {{2020}},
}

@article{46334,
  abstract     = {{We build upon a recently proposed multi-objective view onto performance measurement of single-objective stochastic solvers. The trade-off between the fraction of failed runs and the mean runtime of successful runs – both to be minimized – is directly analyzed based on a study on algorithm selection of inexact state-of-the-art solvers for the famous Traveling Salesperson Problem (TSP). Moreover, we adopt the hypervolume indicator (HV) commonly used in multi-objective optimization for simultaneously assessing both conflicting objectives and investigate relations to commonly used performance indicators, both theoretically and empirically. Next to Penalized Average Runtime (PAR) and Penalized Quantile Runtime (PQR), the HV measure is used as a core concept within the construction of per-instance algorithm selection models offering interesting insights into complementary behavior of inexact TSP solvers.}},
  author       = {{Bossek, Jakob and Kerschke, Pascal and Trautmann, Heike}},
  issn         = {{1568-4946}},
  journal      = {{Applied Soft Computing}},
  keywords     = {{Algorithm selection, Multi-objective optimization, Performance measurement, Combinatorial optimization, Traveling Salesperson Problem}},
  pages        = {{105901}},
  title        = {{{A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms}}},
  doi          = {{https://doi.org/10.1016/j.asoc.2019.105901}},
  volume       = {{88}},
  year         = {{2020}},
}

@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}},
}

@inproceedings{10677,
  author       = {{Ho, Nam and Kaufmann, Paul and Platzner, Marco}},
  booktitle    = {{2014 {IEEE} Intl. Conf. on Evolvable Systems (ICES)}},
  keywords     = {{Linux, cache storage, embedded systems, granular computing, multiprocessing systems, reconfigurable architectures, Leon3 SPARe processor, custom logic events, evolvable-self-adaptable processor cache, fine granular profiling, integer unit events, measurement infrastructure, microarchitectural events, multicore embedded system, perf_event standard Linux performance measurement interface, processor properties, run-time reconfigurable memory-to-cache address mapping engine, run-time reconfigurable multicore infrastructure, split-level caching, Field programmable gate arrays, Frequency locked loops, Irrigation, Phasor measurement units, Registers, Weaving}},
  pages        = {{31--37}},
  title        = {{{Towards self-adaptive caches: A run-time reconfigurable multi-core infrastructure}}},
  doi          = {{10.1109/ICES.2014.7008719}},
  year         = {{2014}},
}