{"editor":[{"first_name":"R","full_name":"Battiti, R","last_name":"Battiti"},{"first_name":"M","full_name":"Brunato, M","last_name":"Brunato"},{"first_name":"I","full_name":"Kotsireas, I","last_name":"Kotsireas"},{"full_name":"Pardalos, P","last_name":"Pardalos","first_name":"P"}],"title":"Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time","publication":"Learning and Intelligent Optimization","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."}],"series_title":"Lecture Notes in Computer Science","page":"215–219","intvolume":"     11353","language":[{"iso":"eng"}],"place":"Cham","date_updated":"2023-10-16T13:28:32Z","citation":{"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.","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.","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, J 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.","chicago":"Bossek, J, 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.","mla":"Bossek, J., 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.","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."},"volume":11353,"publisher":"Springer","type":"conference","department":[{"_id":"34"},{"_id":"819"}],"_id":"46337","status":"public","date_created":"2023-08-04T07:44:10Z","year":"2019","author":[{"full_name":"Bossek, J","last_name":"Bossek","first_name":"J"},{"last_name":"Trautmann","full_name":"Trautmann, Heike","id":"100740","first_name":"Heike","orcid":"0000-0002-9788-8282"}],"user_id":"15504","publication_identifier":{"isbn":["978-3-030-05347-5"]}}