[{"status":"public","type":"conference","publication":"Learning and Intelligent Optimization","language":[{"iso":"eng"}],"user_id":"40778","project":[{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"_id":"13250","citation":{"chicago":"Ansótegui, Carlos, Britta Heymann, Josep Pon, Meinolf Sellmann, and Kevin Tierney. “Hyper-Reactive Tabu Search for MaxSAT.” In <i>Learning and Intelligent Optimization</i>, 309–25. Cham: Springer International Publishing, 2019. <a href=\"https://doi.org/10.1007/978-3-030-05348-2_27\">https://doi.org/10.1007/978-3-030-05348-2_27</a>.","ieee":"C. Ansótegui, B. Heymann, J. Pon, M. Sellmann, and K. Tierney, “Hyper-Reactive Tabu Search for MaxSAT,” in <i>Learning and Intelligent Optimization</i>, 2019, pp. 309–325.","ama":"Ansótegui C, Heymann B, Pon J, Sellmann M, Tierney K. Hyper-Reactive Tabu Search for MaxSAT. In: <i>Learning and Intelligent Optimization</i>. Cham: Springer International Publishing; 2019:309-325. doi:<a href=\"https://doi.org/10.1007/978-3-030-05348-2_27\">10.1007/978-3-030-05348-2_27</a>","bibtex":"@inproceedings{Ansótegui_Heymann_Pon_Sellmann_Tierney_2019, place={Cham}, title={Hyper-Reactive Tabu Search for MaxSAT}, DOI={<a href=\"https://doi.org/10.1007/978-3-030-05348-2_27\">10.1007/978-3-030-05348-2_27</a>}, booktitle={Learning and Intelligent Optimization}, publisher={Springer International Publishing}, author={Ansótegui, Carlos and Heymann, Britta and Pon, Josep and Sellmann, Meinolf and Tierney, Kevin}, year={2019}, pages={309–325} }","short":"C. Ansótegui, B. Heymann, J. Pon, M. Sellmann, K. Tierney, in: Learning and Intelligent Optimization, Springer International Publishing, Cham, 2019, pp. 309–325.","mla":"Ansótegui, Carlos, et al. “Hyper-Reactive Tabu Search for MaxSAT.” <i>Learning and Intelligent Optimization</i>, Springer International Publishing, 2019, pp. 309–25, doi:<a href=\"https://doi.org/10.1007/978-3-030-05348-2_27\">10.1007/978-3-030-05348-2_27</a>.","apa":"Ansótegui, C., Heymann, B., Pon, J., Sellmann, M., &#38; Tierney, K. (2019). Hyper-Reactive Tabu Search for MaxSAT. In <i>Learning and Intelligent Optimization</i> (pp. 309–325). Cham: Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-030-05348-2_27\">https://doi.org/10.1007/978-3-030-05348-2_27</a>"},"page":"309-325","place":"Cham","year":"2019","publication_identifier":{"isbn":["978-3-030-05347-5"]},"doi":"10.1007/978-3-030-05348-2_27","conference":{"name":"International Conference on Learning and Intelligent Optimization"},"title":"Hyper-Reactive Tabu Search for MaxSAT","author":[{"full_name":"Ansótegui, Carlos","last_name":"Ansótegui","first_name":"Carlos"},{"first_name":"Britta","full_name":"Heymann, Britta","last_name":"Heymann"},{"first_name":"Josep","full_name":"Pon, Josep","last_name":"Pon"},{"last_name":"Sellmann","full_name":"Sellmann, Meinolf","first_name":"Meinolf"},{"last_name":"Tierney","full_name":"Tierney, Kevin","first_name":"Kevin"}],"date_created":"2019-09-17T13:39:32Z","publisher":"Springer International Publishing","date_updated":"2022-01-06T06:51:31Z"},{"publication_identifier":{"isbn":["978-3-030-05347-5"]},"year":"2019","place":"Cham","intvolume":"     11353","page":"215–219","citation":{"short":"J. Bossek, H. Trautmann, in: R. Battiti, M. Brunato, I. Kotsireas, P. Pardalos (Eds.), Learning and Intelligent Optimization, Springer, Cham, 2019, pp. 215–219.","mla":"Bossek, Jakob, and Heike Trautmann. “Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time.” <i>Learning and Intelligent Optimization</i>, edited by R Battiti et al., vol. 11353, Springer, 2019, pp. 215–219.","bibtex":"@inproceedings{Bossek_Trautmann_2019, place={Cham}, series={Lecture Notes in Computer Science}, title={Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time}, volume={11353}, booktitle={Learning and Intelligent Optimization}, publisher={Springer}, author={Bossek, Jakob and Trautmann, Heike}, editor={Battiti, R and Brunato, M and Kotsireas, I and Pardalos, P}, year={2019}, pages={215–219}, collection={Lecture Notes in Computer Science} }","ama":"Bossek J, Trautmann H. Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time. In: Battiti R, Brunato M, Kotsireas I, Pardalos P, eds. <i>Learning and Intelligent Optimization</i>. Vol 11353. Lecture Notes in Computer Science. Springer; 2019:215–219.","apa":"Bossek, J., &#38; Trautmann, H. (2019). Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time. In R. Battiti, M. Brunato, I. Kotsireas, &#38; P. Pardalos (Eds.), <i>Learning and Intelligent Optimization</i> (Vol. 11353, pp. 215–219). Springer.","chicago":"Bossek, Jakob, and Heike Trautmann. “Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time.” In <i>Learning and Intelligent Optimization</i>, edited by R Battiti, M Brunato, I Kotsireas, and P Pardalos, 11353:215–219. Lecture Notes in Computer Science. Cham: Springer, 2019.","ieee":"J. Bossek and H. Trautmann, “Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time,” in <i>Learning and Intelligent Optimization</i>, 2019, vol. 11353, pp. 215–219."},"publisher":"Springer","date_updated":"2024-06-10T12:00:23Z","volume":11353,"date_created":"2023-08-04T07:44:10Z","author":[{"first_name":"Jakob","id":"102979","full_name":"Bossek, Jakob","orcid":"0000-0002-4121-4668","last_name":"Bossek"},{"first_name":"Heike","orcid":"0000-0002-9788-8282","last_name":"Trautmann","id":"100740","full_name":"Trautmann, Heike"}],"title":"Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time","publication":"Learning and Intelligent Optimization","type":"conference","abstract":[{"lang":"eng","text":"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."}],"editor":[{"last_name":"Battiti","full_name":"Battiti, R","first_name":"R"},{"full_name":"Brunato, M","last_name":"Brunato","first_name":"M"},{"last_name":"Kotsireas","full_name":"Kotsireas, I","first_name":"I"},{"full_name":"Pardalos, P","last_name":"Pardalos","first_name":"P"}],"status":"public","_id":"46337","department":[{"_id":"34"},{"_id":"819"}],"series_title":"Lecture Notes in Computer Science","user_id":"15504","language":[{"iso":"eng"}]}]