Framework para execução distribuída de GAvaPS

Autores

  • Nataniel Pereira Borges Junior Universidade Federal de Santa Catarina (UFSC) Departamento de Informática e Estatística (INE) Caixa Postal 476 88.037-000 Florianópolis – Santa Catarina
  • Ricardo Pereira e Silva Universidade Federal de Santa Catarina (UFSC) Departamento de Informática e Estatística (INE) Caixa Postal 476 88.037-000 Florianópolis – Santa Catarina

DOI:

https://doi.org/10.14210/cotb.v0n0.pp.395-397

Resumo

Genetic algorithms (GAs) are non-speciï¬c optimization methods that posses a well-deï¬ned architecture and execution flow and are widely used into areas like machine learning and design optimization. Object-oriented frame- work is a known approach for the reuse of application architecture and execu- tion flow aimed to increase speed and quality on software development. Multi- computer environments, such as clusters and grids, are now widespread and available at low cost. The focus of this document is to introduce a framework under development to allow the execution of genetic algorithms with variable population size (GAvaPS) into multi-computer environments.

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