Parameter prediction based on features of evolved instances for ant colony optimization and the traveling salesperson problem
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(Restricted Access)
Date
2014
Authors
Nallaperuma, S.
Wagner, M.
Neumann, F.
Editors
Bartz-Beielstein, T.
Branke, J.
Filipič, B.
Smith, J.
Branke, J.
Filipič, B.
Smith, J.
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
Citation
Lecture Notes in Artificial Intelligence, 2014 / Bartz-Beielstein, T., Branke, J., Filipič, B., Smith, J. (ed./s), vol.8672, pp.100-109
Statement of Responsibility
Samadhi Nallaperuma ,Markus Wagner, and Frank Neumann
Conference Name
13th International Conference on Parallel Problem Solving from Nature (PPSN XIII) (13 Sep 2014 - 17 Sep 2014 : Ljubljana, Slovenia)
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.
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Dissertation Note
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Description
LNCS, volume 8672
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Rights
© Springer International Publishing Switzerland 2014