Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem

Seiler, Moritz V; Pohl, Janina; Bossek, Jakob; Kerschke, Pascal; Trautmann, Heike

Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem

Seiler Moritz V, Pohl Janina, Bossek Jakob, Kerschke Pascal, Trautmann Heike

Schlüsselwörter

Automated algorithm selection; Traveling Salesperson Problem; Feature-based approaches; Deep learning

Zitieren als

Seiler, M. V., Pohl, J., Bossek, J., Kerschke, P., & Trautmann, H. (2020). Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. In Proceedings of the 16th International Conference on Parallel Problem Solving from Nature (PPSN XVI), Leiden, The Netherlands, 48–64.

Details

Publikationstyp

Forschungsartikel in Sammelband (Konferenz)

Begutachtet

Ja

Publikationsstatus

Veröffentlicht

Jahr

2020

Konferenz

Proceedings of the 16th International Conference on Parallel Problem Solving from Nature (PPSN XVI)

Konferenzort

Leiden, The Netherlands

Herausgeber

Bäck Thomas, Preuss Mike, Deutz André, Wang Hao, Doerr Carola, Emmerich Michael, Trautmann Heike

Erste Seite

48

Letzte Seite

64

Sprache

Englisch

DOI

https://doi.org/10.1007/978-3-030-58112-1_4

Gesamter Text

https://arxiv.org/