Features for Exploiting Black-Box Optimization Problem Structure

Abell T, Malitsky Y, Tierney K (2013)
In: Learning and Intelligent Optimization: 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers. Nicosia G, Pardalos P (Eds); Lecture Notes in Computer Science, 7997. Berlin, Heidelberg: Springer Berlin Heidelberg: 30-36.

Sammelwerksbeitrag | Veröffentlicht | Englisch
 
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Autor*in
Abell, Tinus; Malitsky, Yuri; Tierney, KevinUniBi
Herausgeber*in
Nicosia, Giuseppe; Pardalos, Panos
Abstract / Bemerkung
Black-box optimization (BBO) problems arise in numerous scientific and engineering applications and are characterized by computationally intensive objective functions, which severely limit the number of evaluations that can be performed. We present a robust set of features that analyze the fitness landscape of BBO problems and show how an algorithm portfolio approach can exploit these general, problem independent, features and outperform the utilization of any single minimization search strategy. We test our methodology on data from the GECCO Workshop on BBO Benchmarking 2012, which contains 21 state-of-the-art solvers run on 24 well-established functions.
Erscheinungsjahr
2013
Buchtitel
Learning and Intelligent Optimization: 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers
Serientitel
Lecture Notes in Computer Science
Band
7997
Seite(n)
30-36
Konferenz
7th International Conference on Learning and Intelligent Optimization (LION 7)
Konferenzort
Catania, Italy
Konferenzdatum
2013-01-07 – 2013-01-11
ISBN
978-3-642-44972-7
eISBN
978-3-642-44973-4
Page URI
https://pub.uni-bielefeld.de/record/2958252

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Abell T, Malitsky Y, Tierney K. Features for Exploiting Black-Box Optimization Problem Structure. In: Nicosia G, Pardalos P, eds. Learning and Intelligent Optimization: 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers. Lecture Notes in Computer Science. Vol 7997. Berlin, Heidelberg: Springer Berlin Heidelberg; 2013: 30-36.
Abell, T., Malitsky, Y., & Tierney, K. (2013). Features for Exploiting Black-Box Optimization Problem Structure. In G. Nicosia & P. Pardalos (Eds.), Lecture Notes in Computer Science: Vol. 7997. Learning and Intelligent Optimization: 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers (pp. 30-36). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-44973-4_4
Abell, T., Malitsky, Y., and Tierney, K. (2013). “Features for Exploiting Black-Box Optimization Problem Structure” in Learning and Intelligent Optimization: 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers, Nicosia, G., and Pardalos, P. eds. Lecture Notes in Computer Science, vol. 7997, (Berlin, Heidelberg: Springer Berlin Heidelberg), 30-36.
Abell, T., Malitsky, Y., & Tierney, K., 2013. Features for Exploiting Black-Box Optimization Problem Structure. In G. Nicosia & P. Pardalos, eds. Learning and Intelligent Optimization: 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers. Lecture Notes in Computer Science. no.7997 Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 30-36.
T. Abell, Y. Malitsky, and K. Tierney, “Features for Exploiting Black-Box Optimization Problem Structure”, Learning and Intelligent Optimization: 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers, G. Nicosia and P. Pardalos, eds., Lecture Notes in Computer Science, vol. 7997, Berlin, Heidelberg: Springer Berlin Heidelberg, 2013, pp.30-36.
Abell, T., Malitsky, Y., Tierney, K.: Features for Exploiting Black-Box Optimization Problem Structure. In: Nicosia, G. and Pardalos, P. (eds.) Learning and Intelligent Optimization: 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers. Lecture Notes in Computer Science. 7997, p. 30-36. Springer Berlin Heidelberg, Berlin, Heidelberg (2013).
Abell, Tinus, Malitsky, Yuri, and Tierney, Kevin. “Features for Exploiting Black-Box Optimization Problem Structure”. Learning and Intelligent Optimization: 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers. Ed. Giuseppe Nicosia and Panos Pardalos. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.Vol. 7997. Lecture Notes in Computer Science. 30-36.

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