Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/4342

TitleA genetic and evolutionary programming environment with spatially structured populations and built-in parallelism
Author(s)Rocha, Miguel
Pereira, Filipe
Afonso, Sónia
Neves, José
Keywords(Parallel) genetic and evolutionary algorithms
Spatially structured populations
Issue date2001
PublisherSpringer
JournalLecture Notes in Computer Science (including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
CitationMONOSTORI, László; VÁNCZA, József; ALI, Moonis, ed. lit. – “Engineering of intelligent systems : proceedings of the International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, 14, Budapest, Hungary, 2001”. Berlin: Springer, 2001. p. 383-392.
Abstract(s)The recent development of the Genetic and Evolutionary Computation field lead to a kaleidoscope of approaches to problem solving, which are based on a common background. These shared principles are used in order to develop a programming environment that enhances modularity, in terms of software design and implementation. The system's core encapsulates the main features of the Genetic and Evolutionary Algorithms, by identifying the entities at stake and implementing them as hierarchies of software modules. This architecture is enriched with the parallelization of the algorithms, based on spatially structured populations, following coarse-grained (Island Model) and fine-grained (Neighborhood Model) strategies. A distributed physical implementation, under the PVM environment, running in a local network, is described.
TypeConference paper
URIhttp://hdl.handle.net/1822/4342
ISBN3540422196
ISSN0302-9743
Peer-Reviewedyes
AccessOpen access
Appears in Collections:DI/CCTC - Artigos (papers)

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