- author = "Lukas Sekanina and Michal Bidlo",
- title = "Evolutionary Design of Arbitrarily Large Sorting Networks Using Development",
- journal = "Genetic Programming and Evolvable Machines",
- year = "2005",
- volume = "6",
- number = "3",
- pages = "319--347",
- month = sep,
- note = "Published online: 17 August 2005",
- keywords = "genetic algorithms, genetic programming, evolutionary algorithm, development, sorting network, scalability",
- ISSN = "1389-2576",
-
URL = "
http://www.genetic-programming.org/hc2005/genp05.pdf",
-
DOI = "
doi:10.1007/s10710-005-2987-8",
- abstract = "An evolutionary algorithm is combined with an application-specific developmental scheme in order to evolve efficient arbitrarily large sorting networks. First, a small sorting network (that we call the embryo) has to be prepared to solve the trivial instance of a problem. Then the evolved program (the constructor) is applied on the embryo to create a larger sorting network (solving a larger instance of the problem). Then the same constructor is used to create a new instance of the sorting network from the created larger sorting network and so on. The proposed approach allowed us to rediscover the conventional principle of insertion which is traditionally used for constructing large sorting networks. Furthermore, the principle was improved by means of the evolutionary technique. The evolved sorting networks exhibit a lower implementation cost and delay.",
-
notes = "Evolving 'general solutions', ie able to solve
problems of arbitary number of inputs. galib--M.Wall
",
