IDA - Intelligent Data Analysis Research Group

BibTeX Entry

@inproceedings{kubalik2009b,
  category = {ida-publications},
  author = {Kubal{\'i}k J.},
  title = {Solving the Sorting Network Problem Using Iterative Optimization with Evolved Hypermutations},
  booktitle = {Genetic and Evolutionary Computation Conference 2009},
  year = {2009},
  publisher = {New York: ACM},
  address = {Montreal, Qu{\'e}bec, Canada},
  pages = {301-308},
  url = {http://portal.acm.org/citation.cfm?id=1569944},
  abstract = {This paper presents an application of a prototype optimization with evolved improvement steps algorithm (POEMS) to the well-known problem of optimal sorting network design. The POEMS is an iterative algorithm that seeks the best variation of the current solution in each iteration. The variations, also called hypermutations, are evolved by means of an evolutionary algorithm. We compared the POEMS to two mutation-based optimizers, namely the (\mu+\lambda)- and (1+\lambda)-evolution strategies. For experimental evaluation 10-input, 12-input, 14-input and 16-input instances of the sorting network problem were used. Results show that the proposed POEMS approach clearly outperforms both compared algorithms. Moreover, POEMS was able to find several perfect networks that are equivalent w.r.t. the number of comparators to the best known solutions for the 10-input, 12-input, 14-input, and 16-input problems. Finally, we propose a modification to the POEMS approach that might further improve its performance.},
  vvvs = {0},
}


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