PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation

@article{Negro2004PSFGAPP,
  title={PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation},
  author={F. de Toro Negro and Julio Ortega and Eduardo Ros Vidal and Sonia Mota and Ben Paechter and J. M. Mart{\'i}n},
  journal={Parallel Computing},
  year={2004},
  volume={30},
  pages={721-739}
}
This paper deals with the study of the cooperation between parallel processing and evolutionary computation to obtain efficient procedures for solving multiobjective optimisation problems. We propose a new algorithm called PSFGA (parallel single front genetic algorithm), an elitist evolutionary algorithm for multiobjective problems with a clearing procedure that uses a grid in the objective space for diversity maintaining purposes. Thus, PSFGA is a parallel genetic algorithm with a structured… CONTINUE READING

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