Department of Computer Systems

Journal article

BIDLO Michal and DOBEŠ Michal. Evolutionary Development of Generic Sorting Networks by Means of Rewriting Systems. IEEE Transactions on Evolutionary Computation. 2019, vol. 99, no. 99, pp. 1-13. ISSN 1089-778X.
Publication language:english
Original title:Evolutionary Development of Generic Sorting Networks by Means of Rewriting Systems
Title (cs):Evoluční vývin obecných řadicích sítí pomocí přepisovacích systémů
Journal:IEEE Transactions on Evolutionary Computation, Vol. 99, No. 99, US
genetic algorithm, development, rewriting system, sorting network, scalability
This article presents an evolutionary developmental method for the design of arbitrarily growing sorting networks. The developmental model is based on a parallel rewriting system (a grammar) that is specified by an alphabet, an initial string (an axiom) and a set of rewriting rules. The rewriting process iteratively expands the axiom in order to develop more complex strings during a series of development steps (i.e. derivations in the grammar). A mapping function is introduced that allows for converting the strings onto comparator structures -- building blocks of sorting networks. The construction of the networks is performed in such a way that a given (initial) sorting network grows progressively by adding further building blocks within each development step.
For a given (fixed) alphabet, the axiom together with the rewriting rules themselves are the subjects of the evolutionary search. It will be shown that suitable grammars can be evolved for the construction of arbitrarily large sorting networks that grow with various given sizes of development steps. Moreover, the resulting networks exhibit significantly better properties (the number of comparators and delay) in comparison with those obtained by means of similar existing methods.

   author = {Michal Bidlo and Michal Dobe{\v{s}}},
   title = {Evolutionary Development of Generic Sorting
	Networks by Means of Rewriting Systems},
   pages = {1--13},
   journal = {IEEE Transactions on Evolutionary Computation},
   volume = 99,
 number = 99,
   year = 2019,
   ISSN = {1089-778X},
   doi = {10.1109/TEVC.2019.2918212},
   language = {english},
   url = {}

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