• Corpus ID: 7129189

Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization

@inproceedings{Fonseca1993GeneticAF,
  title={Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization},
  author={Carlos M. Fonseca and Peter John Fleming},
  booktitle={ICGA},
  year={1993}
}
The paper describes a rank-based fitness assignment method for Multiple Objective Genetic Algorithms (MOGAs. [] Key Method The fitness assignment method is then modified to allow direct intervention of an external decision maker (DM). Finally, the MOGA is generalised further: the genetic algorithm is seen as the optimizing element of a multiobjective optimization loop, which also comprises the DM. It is the interaction between the two that leads to the determination of a satisfactory solution to the problem…

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