Parameter prediction based on features of evolved instances for ant colony optimization and the traveling salesperson problem

Simple item page
dc.contributor.authorNallaperuma, S.
dc.contributor.authorWagner, M.
dc.contributor.authorNeumann, F.
dc.contributor.conference13th International Conference on Parallel Problem Solving from Nature (PPSN XIII) (13 Sep 2014 - 17 Sep 2014 : Ljubljana, Slovenia)
dc.contributor.editorBartz-Beielstein, T.
dc.contributor.editorBranke, J.
dc.contributor.editorFilipič, B.
dc.contributor.editorSmith, J.
dc.date.issued2014
dc.descriptionLNCS, volume 8672
dc.description.abstractAnt colony optimization performs verywell onmany hard optimization problems, even though no good worst case guarantee can be given. Understanding the reasons for the performance and the influence of its different parameter settings has become an interesting problem. In this paper, we build a parameter prediction model for the Traveling Salesperson problem based on features of evolved instances. The two considered parameters are the importance of the pheromone values and of the heuristic information. Based on the features of the evolved instances, we successfully predict the best parameter setting for a wide range of instances taken from TSPLIB.
dc.description.statementofresponsibilitySamadhi Nallaperuma ,Markus Wagner, and Frank Neumann
dc.identifier.citationLecture Notes in Artificial Intelligence, 2014 / Bartz-Beielstein, T., Branke, J., Filipič, B., Smith, J. (ed./s), vol.8672, pp.100-109
dc.identifier.doi10.1007/978-3-319-10762-2
dc.identifier.isbn9783319107615
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.orcidWagner, M. [0000-0002-3124-0061]
dc.identifier.orcidNeumann, F. [0000-0002-2721-3618]
dc.identifier.urihttp://hdl.handle.net/2440/108009
dc.language.isoen
dc.publisherSpringer Verlag
dc.relation.granthttp://purl.org/au-research/grants/arc/DP140103400
dc.relation.ispartofseriesLecture Notes in Computer Science
dc.rights© Springer International Publishing Switzerland 2014
dc.source.urihttps://doi.org/10.1007/978-3-319-10762-2
dc.titleParameter prediction based on features of evolved instances for ant colony optimization and the traveling salesperson problem
dc.typeConference paper
pubs.publication-statusPublished

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
RA_hdl_108009.pdf
Size:
560.38 KB
Format:
Adobe Portable Document Format
Description:
Restricted Access
Download

Collections

Computer Science publications