Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/108009
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Type: Conference paper
Title: Parameter prediction based on features of evolved instances for ant colony optimization and the traveling salesperson problem
Author: Nallaperuma, S.
Wagner, M.
Neumann, F.
Citation: Proceedings of the 13th International Conference on Parallel Problem Solving from Nature, 2014 / Bartz-Beielstein, T., Branke, J., Filipič, B., Smith, J. (ed./s), vol.8672, pp.100-109
Publisher: Springer Verlag
Issue Date: 2014
Series/Report no.: Lecture Notes in Computer Science
ISBN: 9783319107615
ISSN: 0302-9743
1611-3349
Conference Name: 13th International Conference on Parallel Problem Solving from Nature (PPSN XIII) (13 Sep 2014 - 17 Sep 2014 : Ljubljana, Slovenia)
Statement of
Responsibility: 
Samadhi Nallaperuma ,Markus Wagner, and Frank Neumann
Abstract: Ant 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.
Description: LNCS, volume 8672
Rights: © Springer International Publishing Switzerland 2014
RMID: 0030024054
DOI: 10.1007/978-3-319-10762-2
Grant ID: http://purl.org/au-research/grants/arc/DP140103400
Published version: https://doi.org/10.1007/978-3-319-10762-2
Appears in Collections:Computer Science publications

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